bioRxiv Subject Collection: Neuroscience's Journal

Detection of Region-specific Fiber Damage within Injured Spinal Cord Using Advanced Diffusion MRI
This study aimed to evaluate diffusion parameters derived from diffusion tensor imaging (DTI) and spherical mean technique (SMT) for detecting region-specific, fine-grained tissue damage and white matter (WM) tract disruptions following spinal cord injury (SCI). Diffusion MRI data were acquired from the cervical spinal cord of monkeys before and after a unilateral dorsal column lesion at the C5 level, using a 9.4T scanner. Parametric maps derived from DTI and SMT effectively detected regional fiber damage around 16 weeks post-injury. Post-mortem silver staining served as the ground truth for assessing region-specific fiber damage. Diffusion MRI maps aligned well with histological measures and captured the severity of WM damage at the lesioned segment (in an order of dorsal > ventral > lateral WM tracts) and along the dorsal column tract across segments (in an order of lesion center > rostral > caudal). Among the diffusion parameters, fractional anisotropy (FA), axonal volume fraction (Vax), radial diffusivity (RD), and extra-axonal transverse diffusivity (Dex) showed most significant changes at and around the lesion site where severe tissue damage occurred. FA, Vax, and axial diffusivity (AD) exhibited marked changes in dorsal column proximal to the lesion center, where moderate axonal damage occurred. Additionally, AD and FA showed the greatest sensitivity (true positive rate) and specificity (true negative rate) to mild fiber disruption and demyelination in regions distal to the lesion. Overall, FA provided the highest sensitivity and specificity for detecting fiber degeneration and demyelination, while Vax demonstrated the strongest spatial correlation with histologic markers of regional fiber damage. The combination of DTI and SMT thus offers reliable biomarkers for assessing SCI.

Task demands and visual context naturalness modulate gravitational expectation during ocular tracking of temporarily occluded ballistic trajectories
During ocular tracking of a target, contextual information provides useful cues to account for motion features the visual system is poorly sensitive to, like its acceleration. For example, the brain can rely on an internal model of gravity to intercept and track accelerated targets under gravity, and cues about the visual environment naturalness can facilitate its recruitment. Notably, in real life, these two tasks are often associated. Experimental evidence suggests that predictive information may be shared between the two tasks, albeit their concurrent execution can, in turn, affect the oculomotor performance. To gain further insight on how task demands and the naturalness of the visual context affect the weighting of sensory feedback and predictive feedforward information in ocular tracking, subjects tracked targets either congruent with gravity or perturbed during the trajectory with altered gravity. Targets were projected on either pictorial or neutral background, and, to enforce prediction, were occluded for variable intervals 550 ms after the perturbation. Sixty-nine participants were divided into two groups: one group performed only ocular tracking, the other also intercepted the targets. In general, subjects ocular tracking performance depended on the target acceleration level and the visual context, with effects of gravitational expectations being more evident with the pictorial naturalistic environment. This result reinforced the idea that gravity a priori information can be weighted based on the naturalness of the visual context. Another striking finding was that participants who only tracked the target showed systematic changes of the oculomotor performance with the acceleration level right after the perturbation, compatible with a strong reliance on gravitational expectation; instead, participants that also intercepted the target showed such systematic changes primarily after the targets occlusion, perhaps weighting more sensory information until then. Thus, concurrence of ocular tracking and manual interception seemingly influenced the temporal recruitment of internalized gravity information.

The GPCR Smoothened on Cholinergic Interneurons Modulates Dopamine-associated Acetylcholine Dynamics
The striatum is a hub for associative learning where fluctuations in dopamine (DA) and acetylcholine (ACh) dynamically regulate behavior. ACh is released by cholinergic interneurons (CIN), which integrate diverse inputs to contextualize DA signals and shape adaptive responses. Among these inputs, we previously observed that the GPCR Smoothened (Smo) on CIN suppresses L-DOPA-induced dyskinesias, a motor side-effect resulting from artificially elevated DA levels in the Parkinsonian brain. Here, we examine whether Smo signaling modulates ACh dynamics, its coordination with DA, and motor learning in the healthy brain. We find that CIN-specific Smo activity bidirectionally modulates ACh inhibition in response to both optogenetically evoked and endogenous DA. Smo relieves DA-associated ACh inhibition and permits its progressive modification with repeated DA release. These effects alter the temporal organization of ACh in the dorsolateral striatum and its coupling to DA, without affecting DA release itself. Behaviorally, Smo ablation from cholinergic neurons promotes initial motor learning at the expense of future behavioral flexibility. Together, these findings identify Smo as a bidirectional modulator of striatal DA-ACh coordination and striatal learning.

Features fade, pointers persist: dissociable parietal mechanisms in visual working memory formation and maintenance
An emerging body of work has adopted the theoretical construct of pointers: an object is mentally represented by a content-free pointer binding the corresponding features together. Indeed, fMRI studies have highlighted dissociable parietal regions sensitive to pointer and feature load respectively. Specifically, while the superior IPS (intraparietal sulcus) is sensitive to feature load, inferior IPS is only sensitive to the number of pointers - i.e., the number of objects. However, the spatiotemporal dynamics remain unclear, and therefore it is unknown whether these effects reflect visual working memory (VWM) formation, maintenance, or both, especially given limited temporal resolution of fMRI. In our current MEG (magnetoencephalography) study, participants memorized visual arrays with different numbers of objects (object/pointer load: two, four), as well as different features and feature-per-object (color, orientation, bifeatural) in a VWM task. We observed a dissociation between inferior and superior IPS in the temporal dynamics of feature-sensitive and pointer-sensitive responses. While pointer-sensitive signals persisted across VWM formation and maintenance in inferior IPS, feature-sensitivity was only transiently manifested during VWM formation in superior IPS. This spatiotemporal dissociation may reflect a representational architecture optimized for efficiency, reducing the need for sustained neural activity to maintain features once they are bound to pointers. In revealing the spatiotemporal profile of pointer and feature representations, our results provide novel evidence on how pointers underlie energy-efficient neural representations in VWM.

White adipose tissue undergoes pathological dysfunction in the TDP-43A315T mouse model of amyotrophic lateral sclerosis (ALS)
White adipose tissue (WAT) has a crucial role in maintaining systemic energy homeostasis. Numerous biological pathway studies have highlighted the importance of adipokines in regulating metabolic pathways and contributing to metabolic dysfunction in animal models and patients with ALS. Despite these associations, the specific molecular mechanisms remain poorly understood. Moreover, the direct contribution of WAT to the energy metabolism abnormalities observed in ALS has yet to be clearly defined. The current study sought to identify perturbances in WAT, main source of leptin, during the clinical course of the disease in TDP-43A315T mice using histological, proteomic, and molecular biological techniques. We present the first evidence of a significant histological alteration in WAT prior to the symptomatic stage of the disease in TDP-43A315T mice, providing novel insights into pathological features earlier in the onset of symptoms, and showing WAT as a target organ for ALS. In human ALS cases, we found that circulating leptin levels at the time of diagnosis were lower in the plasma of men with ALS who were overweight or obese and had rapidly progressive ALS, emphasizing the importance of considering sex-specific approaches when analysing adipokines essential for body weight control.

Wakeful targeted memory reactivation during short rest periods modulates motor learning via the lateral orbitofrontal cortex network
This study investigated whether wakeful targeted memory reactivation (TMR) during short rest intervals improves motor learning. Participants were randomly assigned to the following four groups and performed a sequential key-press task under each condition: (1) TMRno group: no auditory stimuli, (2) TMRregular group: auditory cues played at the same speed as the previous task, (3) TMRfast group: auditory cues played 1.3 times faster, and (4) TMRrandom group: auditory cues randomized in pitch. The TMRregular group suppressed early learning gains compared with the TMRno and TMRfast groups. Electroencephalogram revealed reduced functional connectivity centered on the lateral orbitofrontal cortex (lOFC) in the TMRregular group. In contrast, the TMRfast group preserved early learning and exhibited improved lOFC-centered functional connectivity compared with the TMRregular group. Therefore, wakeful TMR might either hinder or support motor learning, depending on cue timing and structure, emphasizing the need to optimize sensory parameters for effective learning improvement.

Cortex-Wide, Cellular-Resolution Volumetric Imaging with a Modular Two-Photon Imaging Platform
Mapping cortex-wide neuronal activity at single-cell resolution has been limited by the physical trade-off between numerical aperture and field-of-view (FOV) in two-photon microscopes. We present Meso2P, a modular two-photon platform that decouples excitation and detection by introducing a lateral paraboloid fluorescence collector. The design sustains an effective NA 0.87 over a contiguous 6 * 6 mm^2 FOV at high speed (2,048 * 2,048 pixels at 7.67 Hz). The modular platform can be upgraded with optional modules for simultaneous multi-plane imaging (1-4 planes at full resolution and speed), volumetric imaging (6 * 6 * 0.5mm^3, 2,048 * 2,048 * 28 voxels at 1Hz capturing > 210,000 neurons), and holographic two-photon optogenetic stimulation for targeted perturbations. To handle the resulting large-scale data, we provide an open-source deep-learning pipeline that automates motion correction, segmentation, and spike inference. We demonstrate cortex-wide sensory responses, layer-specific network synchrony during anaesthesia, and in-vivo tracking of micro- and nanoplastic distribution. Meso2P therefore provides a reproducible route to high-throughput volumetric imaging across almost the entire cortex with high detection efficiency.

A causal role for the posterior corpus callosum in bimanual coordination
Inter-areal communication is crucial for brain function. Given the largely contralateral organization of the brain, bimanual coordination likely involves interactions across the two cerebral hemispheres for motor planning and execution. The parietal reach region (PRR) is an early node in the sensorimotor transformation stream. Here we examine the contributions of direct callosal connections between left and right PRR to bimanual coordination. Using manganese-enhanced magnetic resonance imaging, we traced callosal pathways crossing the midline and found that PRR-PRR connections are restricted to the splenium. We then temporarily blocked these fibers with lidocaine while measuring behavioral performance and interhemispheric coherence. Blockade reduced task-specific PRR-PRR coherence during bimanual movements. Behaviorally, blockade sped movement initiation across tasks, consistent with an inhibitory role of interhemispheric communication, reduced the temporal synchrony of bimanual movements to a common target and reduced errors for bimanual movements to separate targets. These findings provide causal evidence that posterior callosal communication supports spatial coordination of bimanual actions but may also constrain independent limb control.

Choosing safety or success: Fall-avoidance preference limits goal achievement during whole-body movements
Human bipedal posture is inherently unstable, making even daily activities potentially lead to falls and serious injuries. Although prior studies have shown that appropriate postural control supports both task success and postural balance during quiet standing or under modest postural demands, it remains unclear how the central nervous system controls whole-body posture under high-demand, near-fall conditions. Here, we investigated how varying postural demands influence postural strategies using a whole-body task in which participants leaned their body mediolaterally to reach a target. We manipulated the required leaning angles and velocities by varying target positions and time constraints to reach a target, thereby introducing different levels of postural demand. The results demonstrated that target position, time constraint, and movement distance significantly affected task performance, defined as reaching accuracy. Specifically, participants could accurately reach targets requiring upright or moderately leaning postures. However, when targets required greater leaning postures, participants failed to reach them. Furthermore, the detrimental effects of shorter time constraints and longer movement distances on task performance became more pronounced when target positions required greater leaning postures. These findings suggest that the central nervous system tolerates low to moderate postural demands to achieve task goals. In contrast, when postural demands exceed a certain threshold, the central nervous system begins to prioritize postural safety over task success. This study highlights the nonlinear effect of postural demands on motor planning during whole-body movements.

Accurate and Interpretable Prediction of Antidepressant Treatment Response from Receptor-informed Neuroimaging
Conventional antidepressants show moderate efficacy in treating major depressive disorder. Psychedelic-assisted therapy holds promise, yet individual responses vary, underscoring the need for predictive tools to guide treatment selection. Here, we present graphTRIP (graph-based Treatment Response Interpretability and Prediction) - a geometric deep learning architecture that enables three advances: 1) accurate prediction of post-treatment depression severity using only pretreatment clinical and neuroimaging data; 2) identification of robust, patient-specific biomarkers; and 3) causal analysis of treatment effects and underlying mechanisms. Trained on data from a clinical trial comparing psilocybin and escitalopram (NCT03429075), graphTRIP achieves strong predictive accuracy (r = 0.75, p < 10e-8), and generalises both to an independent dataset and across brain atlases. The model links better outcomes to reduced functional coupling within serotonin systems, and broader serotonergic integration with sensory-motor networks. Finally, causal analysis reveals a group-level advantage of psilocybin over escitalopram, but also identifies individuals with specific stress-related neuromodulatory profiles who may benefit more from escitalopram. Overall, this work advances precision medicine and biomarker discovery in depression.

Inferior Reinnervation of Reverse End-to-Side Nerve Transfer in a Delayed Nerve Repair Rat Model
Objective Reverse end-to-side (RETS) nerve transfer is a recent surgical technique to augment injured nerve function by supplying a dispensable donor motor nerve to the side of the distal injured nerve. Although clinical studies have suggested advantages of RETS transfer for upper extremity repairs, uncertainties remain regarding its underlying mechanism. Furthermore, our recent clinical studies using electrophysiological examinations revealed no contribution from the donor nerve. Given that most experimental studies were conducted on acutely injured nerves, our objective is to reassess the effectiveness of reverse end-to-side nerve transfer in a model of chronic nerve injury and repair. Methods Obturator and femoral nerve were used as donor and recipient nerves, respectively. Electromyogram (EMG), retrograde labeling of regenerated motoneurons and neuromuscular junction (NMJ) formation were used to compare regenerative ability of donor nerve in acute and delayed RETS transfer where the femoral nerve in the latter group was injured 8 weeks prior. Nerve- babysitting effect on injured nerve was investigated by 1) no intervention; 2) perineurial window creation; and 3) RETS transfer to femoral nerve in delayed repair model. The effects of availability of regeneration tracks, i.e. bands of bungner, were investigated by severing proximal femoral nerve with subsequent acute and delayed repairs. Results EMG and motoneuron quantification confirmed inferiority of donor nerve regeneration into recipient nerve in delayed RETS transfer compared to acute repair, yet donor axons reached target muscle and formed NMJs in both conditions. Same functional assessments revealed nerve baby-sitting effects did not significantly contribute to repair success but availability of regeneration tracks in the recipient nerve may influence the final outcomes. Conclusions Our study offered insights into the effectiveness of RETS nerve transfer in clinically relevant settings, underscoring the compounded impact of delayed intervention and native nerve regeneration which both negatively affect the efficacy of RETS nerve transfer.

Comparison of AAV9-driven motor neuron transduction following different CNS-directed delivery methods in mice
Background: Gene therapies are promising for diseases previously considered incurable. Adeno-associated virus serotype 9 (AAV9) demonstrates remarkable tropism for motor neurons (MNs) and represents an exciting candidate to target genetic causes of motor neuron diseases like amyotrophic lateral sclerosis (ALS). However, systemic delivery risks immunogenicity and off-target effects, therefore localised delivery to the CNS is advantageous. New method: We assessed MN transduction in wild-type mice using AAV9-controlled, cytomegalovirus-promoter driven, enhanced GFP expression. Intra-cisterna magna (ICM) and intra-cerebroventricular (ICV) methods were compared. Four weeks post-delivery, GFP positivity in MN and astrocytes were quantified via immunohistochemical approaches and viral genome copy number determined by qPCR. Results: All delivery methods achieved high MN transduction in lumbar spinal cord (>68%). Unilateral ICV delivery provided the highest and most consistent levels (89 {+/-} 3%), and minimal peripheral viral copies. ICV delivery resulted in higher astrocytic transduction, most notably in the cortex. Brainstem MN transduction was high with all methods (>55%). We failed to find evidence of neuronal transduction in motor cortex. Viral genome copies trended higher in spinal cord and brainstem with ICV approaches, however further work is required to understand how bilateral delivery leads to such profound increases. Comparison to existing methods: Whilst several routes of administration into cerebrospinal fluid exist, direct comparisons for targeting MNs in vivo remain limited. Conclusions: Overall, consideration of gene therapy delivery methods is critical to ensure that the most appropriate administration route is chosen to reach MNs effectively, selectively, and at high levels to exact biological effects.

The Contribution of Audition and Proprioception in Unisensory and Multisensory Target Reaching
Everyday actions often involve reaching for targets sensed by auditory and proprioceptive senses (reaching a ringing smartphone in the dark or tapping on it while holding it with the other hand). However, it is still unclear whether reaching performance toward auditory and proprioceptive targets is modality-specific and whether performance improves under multisensory compared to unisensory conditions. Here, we addressed these questions by measuring reaching performance toward auditory, proprioceptive, and combined audio-proprioceptive targets. Accuracy was generally similar across conditions, but precision was lower for auditory targets compared to proprioceptive and audio-proprioceptive targets. A second experiment investigated whether providing additional proprioceptive information while reaching for an auditory target could improve precision in subsequent auditory-only trials. A slight improvement was observed, indicating that proprioceptive cues may help reduce spatial variability in auditory-guided actions, though not to the level seen in the multisensory condition. Overall, the results suggest that while the target modality slightly impacts movement accuracy, it has a significant impact on movement precision, with proprioceptive input playing a crucial role in enhancing precision. The concurrent availability of auditory and proprioceptive target information does not enhance precision beyond that achieved with proprioceptive information alone, whereas proprioception can modestly improve subsequent auditory-guided reaching.

Tonotopically distinct OFF responses arise in the mouse auditory midbrain following sideband suppression
The parsing of sensory information into discrete topographic domains is a fundamental principle of sensory processing. In the auditory cortex, these domains evolve during a stimulus, with the onset and offset of tones evoking distinct spatial patterns of neural activity. However, it is not known where in the auditory system this spatial segregation occurs or how these dynamics are affected by hearing loss. Using widefield single photon neuronal Ca2+ imaging in the inferior colliculus (IC) of awake mice, we found that pure tone stimuli elicited both spatially constrained neural activity within isofrequency bands and simultaneous sideband suppression. At cessation of the stimulus, offset responses emerged within the region of sideband suppression, demonstrating that simple stimuli elicit spatiotemporally distinct neural activity patterns to represent the presence of sound and sound termination. Because sound frequency is spatially encoded in the IC, this spatial shift creates a tonotopically distinct offset (tdOFF) response relative to sound onset. Two-photon Ca2+ imaging confirmed that tdOFF neuron activity in the sideband region was suppressed during sound and elevated above baseline after stimulus termination, raising the possibility that rebound excitation could contribute to this post-stimulus activation. Loud noise exposure, a common model of hearing loss, abolished both sideband suppression and tdOFF responses. These results show that hearing loss profoundly reshapes the spatiotemporal pattern of sound processing by altering sideband activity. This preferential loss of sideband suppression and tdOFF activation after sound-induced injury in the auditory midbrain may contribute to hyperacusis and tinnitus by promoting neuronal hyperactivity.

Parkinsons disease microglia induce endogenous alpha-Synuclein pathology in patient-specific midbrain organoids.
The accumulation of misfolded alpha-synuclein and the loss of dopaminergic neurons are hallmarks of Parkinsons disease (PD), contributing to the development of synucleinopathies. Although considerable progress has been made in understanding -synuclein's role in PD pathology, the precise mechanisms involved remain unclear. Human midbrain organoids (hMOs) have emerged as valuable models for studying PD, yet the lack of microglia limits the ability to investigate neuroimmune interactions. Recent studies show that integrating microglia into hMOs enhances neuronal maturation and functionality. Here, we generated a human midbrain assembloid model by incorporating iPSC-derived microglia into midbrain organoids from healthy control individuals and a PD patient carrying the SNCA triplication (3xSNCA) mutation. Our results show that 3xSNCA microglia alone are sufficient to induce early, endogenous formation of phosphorylated alpha-synuclein (pS129) pathology in the absence of exogenous fibril seeding. This PD-pathology emerged as early as day 50 of culture and was not observed in models lacking microglia. These findings highlight a critical role for patient-derived microglia in driving -synuclein pathology and provide a physiologically relevant platform for studying early neuroimmune mechanisms in PD and testing potential therapeutic strategies.

Boundary homogenization and numerical modeling of solute transport across the blood-brain barrier
Effective clearance of amyloid-{beta} (A{beta}) from the brain is essential for preventing neurodegenerative diseases such as Alzheimer's. A significant portion of this clearance occurs through the blood-brain barrier (BBB) via receptor-mediated transport. However, current models fail to capture the complex kinetics and spatial heterogeneity of receptors at the BBB. In this study, we derive a novel boundary condition that accounts for finite receptor kinetics, receptor density, and bidirectional transport across the BBB. Specifically, we develop a nonlinear homogenized boundary condition that ensures mass conservation and incorporates receptor-mediated Michaelis-Menten kinetics. We then implement this boundary condition in a cylindrical geometry representing a capillary surrounded by brain tissue. After verifying that the model matches an analytical steady state solution that we derive and that it yields realistic blood A{beta} concentrations, we explore how realistic variations in parameter values drive changes in both steady state A{beta} concentration and transient dynamics. Simulations and analytical results reveal that A{beta} concentrations in the brain are sensitive to receptor number ratios, while concentrations in the blood are primarily affected by the blood clearance rate. Additionally, we use the model to investigate A{beta} clearance during sequential sleep cycles and due to a pathological phenomenon, spreading depolarization. This work presents the first biophysically consistent boundary condition for A{beta} transport across the BBB, offering a powerful tool for studying brain waste clearance under both physiological and pathological conditions.

Inter-brain functional connectivity: Are we measuring the right thing?
Hyperscanning - the simultaneous recording of brain activity from multiple individuals - and the study of inter-brain synchronization is gaining popularity in social neuroscience. MEG/EEG hyperscanning studies often estimate inter-brain functional connectivity using phase-based metrics applied to oscillatory brain signals, assuming matching peak frequencies between the individuals studied. However, in reality, peak frequencies typically differ between subjects and between brain regions. Using simulated MEG/EEG signals, we systematically assessed how inter-individual frequency differences affect commonly used connectivity measures. Phasebased metrics were highly sensitive to frequency differences across individuals, whereas amplitude envelope correlation remained robust, offering more reliable connectivity estimates. Our results underscore the need for connectivity metrics specifically tailored to inter-brain analyses. These findings are relevant to a range of disciplines that are increasingly integrating hyperscanning into their methodological toolkits.

Pre-stimulus alpha power modulates trial-by-trial variability in theta rhythmic multisensory entrainment strength and theta-induced memory effect
Binding multisensory information into episodic memory depends partly on the timing of the hippocampal theta rhythm which provides time windows for synaptic modification. In humans, theta rhythmic sensory stimulation (RSS) enhances episodic memory when the stimuli are synchronised across the visual and auditory domain compared to when they are out-of-synchrony. However, recent studies show mixed evidence if the improvement in episodic memory is the result of modulating hippocampal theta activity. In the current study, we investigated whether pre-stimulus brain state could explain part of this variance in the neural and behavioural effects induced by the RSS, via recording participants' brain activity with MEG during a multisensory theta RSS memory paradigm. Our findings suggest that pre-stimulus alpha power modulates entrainment strength in sensory regions, which in turn predicts subsequent memory formation. These findings suggest that for non-invasive brain stimulation tools to be effective it is crucial to consider brain-state dependent effects.

A single NPFR neuropeptide F receptor neuron that regulates thirst behaviors in Drosophila
Thirst is a strongly motivated internal state that is represented in central brain circuits that are only partially understood. Water seeking is a discrete step of the thirst behavioral sequence that is amenable to uncovering the mechanisms for motivational properties such as goal-oriented behavior, value encoding, and behavioral competition. In Drosophila water seeking is regulated by the NPY-like neuropeptide NPF, however the circuitry for NPF-dependent water seeking is unknown. To uncover the downstream circuitry, we identified the NPF receptor NPFR and the neurons it is expressed in as being acutely critical for thirsty water seeking. Refinement of the NPFR pattern uncovered a role for a single neuron, the L1-l, in promoting thirsty water seeking. The L1-l neuron increases its activity in thirsty flies and is involved in the regulation of dopaminergic neurons in long-term memory formation. Thus, NPFR and its ligand NPF, already known for its role in feeding behavior, are also important for a second ingestive behavior.

CACNA1C TS-II variants alter single-cell dynamics in computational models of cortical pyramidal cells
Timothy Syndrome (TS) is a rare multi-system disorder and a monogenic calcium channelopathy. Previous computational work on this disorder has focused on the myocardium, ignoring the effects of TS on neural development and its strong association with autism spectrum disorder. Variation in the TS-causative gene, CACNA1C, is indeed also associated with a variety of complex neurodevelopmental and neuropsychiatric disorders. We apply computational methods, drawing on experimental data, to understand the mechanisms of calcium dysregulation in TS, and validate our findings in four well-established multi-compartmental neuronal models. CACNA1C encodes the L-type voltage-gated calcium channel, Cav1.2, which modulates neuronal excitability and several activity-dependent pathways. We investigate two mutations in CACNA1C causative of TS type II, G402R and G406R. Both variants show a loss of voltage-dependent inactivation and changes in their voltage dependence of activation. We incorporate the altered steady-state activity of these variants with additional morphological data indicating a significant increase in activity-dependent dendritic retraction of layer II/III pyramidal cells in TS mutant neurones. Our findings replicate experimental work suggesting that increased calcium flux reduces firing frequency but does not affect the rheobase current for action potential initiation. Furthermore, models expressing dendritic Cav1.2 current show altered apical-somatic signal integration in mutant neurones. All models with shortened dendrite morphology show hyperexcitability, denoted by reduced rheobase current and increased responsiveness to current injection compared to their full-length counterparts. Importantly, our approach identifies robust and testable predictions on the impacts of TS on single-cell dynamics. We also discuss the broader implications of our findings for other calcium channel-related neurodevelopmental and neuropsychiatric disorders.

Dynamics of sensorimotor plasticity during exoskeletal finger augmentation
How does the brain integrate artificial body extensions into its somatosensory representation? While prior work has shown that tool use alters body representation, little is known about how artificial augmentations alter body representations as they are worn and used. Here, we investigated the dynamics of somatosensory plasticity using a custom-built exoskeletal device that extended users' fingers by 10 cm. Across four time points, before, during (pre- and post-use), and after exoskeleton wear, participants completed a high-density proprioceptive mapping task. We observed three distinct phases of plasticity. First, simply wearing the exoskeleton led to a contraction of the perceived length of the biological finger. Second, following active use, both biological and artificial finger representations expanded significantly, an effect absent when participants trained with a non-augmenting control device. Third, a lasting aftereffect on biological finger representation was observed even after device removal. Our findings demonstrate that wearable augmentations are rapidly integrated into the body representation, with dynamic adjustments in proprioceptive space shaped by both structural and functional properties of the device. This work advances our understanding of how the sensorimotor system accommodates artificial extensions and highlights the potential for body-augmenting technologies to be intuitively integrated into body representation. These results have direct implications for the design of prosthetics, exoskeletons, and other assistive technologies aimed at extending human physical capacity.

Connectome analysis of a cerebellum-like circuit for sensory prediction
Stable and accurate perception involves comparing incoming sensory input with internally-generated predictions. A mechanistic understanding of this process has been elusive due to the size and complexity of the relevant brain regions in mammals. Here we leverage connectomics to comprehensively map the cell types and synaptic connections underlying a well-characterized and ecologically relevant form of predictive sensory processing in the cerebellum-like electrosensory lobe (ELL) of weakly electric fish. Connectome analysis reveals highly-structured feedforward and recurrent synaptic connectivity mediating the cancellation of predictable electrosensory input. A computational model constrained by prior electrophysiological recordings shows how this connectivity supports the formation of predictions at multiple sites within the network and how the ELL solves a continual learning problem by maintaining fast and accurate predictions despite noise and changes in environmental context. Overall, these findings provide a blueprint for using connectomics to elucidate learning in vertebrate nervous systems.

Temporal and cell-specific changes to cellular iron sequestration and lipid peroxidation in a murine model of neonatal hypoxic-ischemic brain injury.
Background: Iron accumulation and lipid peroxidation are pathophysiologic mechanisms that drive neonatal hypoxic-ischemic (HI) brain injury. Characterization of spatiotemporal changes in these processes will help elucidate their role in ischemic neuronal injury as an initial step towards developing targeted interventions. Methods: HI was induced in post-natal day 9 mice using the modified-Vannucci model. Hippocampal tissue from ipsilateral HI exposed, contralateral hypoxia exposed and sham animals was collected at 6h, 24h, 72h and 7d post-HI. Tissue was subsequently evaluated for markers of cell death (TUNEL), intracellular iron changes (FerroOrange, fluorescent in situ and immunofluorescence), and lipid peroxidation (real time PCR, Gpx4 immunofluorescence and mass spectrometry). Mass spectrometry measured isoprostanes (15-F2t-IsoP) and neuroprostanes (4-F4t-NP) as lipid peroxidation markers of arachidonic (ARA) and docosahexaenoic acid (DHA), respectively. Results: Compared to sham, the HI hippocampus showed increased intracellular labile iron levels that was maximal at 6h post-HI with subsequent elevation in only neuroprostanes at 24h post-HI. TUNEL labeling peaked at 24h post-HI. At 72h, labile iron levels and lipid peroxidation declined corresponding with peak infiltration of ferritin positive microglia/macrophages and the start of TUNEL staining decline. In addition, surviving neurons had increased expression of Gpx4 peaking at 72h post-HI that normalized by 7d post-HI. Conclusions: These findings suggest that following HI, an acute increase in labile iron and DHA peroxidation are correlated with markers of cell death that peak at 24h post-HI. Microglial/macrophage iron sequestration and neuronal antioxidant responses may ameliorate further injury and represent targets for neuroprotective therapies.

Advancing Inter-brain Synchrony Measurement: A Comparative Hyperscanning Study of High-Density Diffuse Optical Tomography and Functional Near-infrared Spectroscopy
Inter-brain synchrony (IBS), measured by hyperscanning, refers to the synchronization of multiple individuals' brain activities during social interactions. Traditional fNIRS-based hyperscanning suffers shortcomings like low spatial resolution and high susceptibility to superficial interference, causing imprecise estimation of IBS in complex social tasks. This study aims to fill the knowledge gap by comprehensively assessing how high-density diffuse optical tomography (HD-DOT), an enhanced alternative to fNIRS, can benefit hyperscanning studies of complex social interactions. Sixteen dyads were engaged in both collaborative and individual tangram puzzle tasks, and their brain activities were recorded simultaneously using HD-DOT and fNIRS. We found that HD-DOT demonstrated significantly stronger IBS and identified more brain regions with significant IBS compared to fNIRS during the collaborative task. Specifically, while fNIRS detected IBS only in the dorsolateral prefrontal cortex (DLPFC) and supramarginal gyrus (SMG), HD-DOT revealed additional IBS in the superior temporal gyrus (STG). Additionally, compared to the individual task, the collaborative task showed increased IBS in HD-DOT, not only in the DLPFC but also in the SMG, frontal eye fields (FEF), and inferior frontal gyrus (IFG). By highlighting the superior spatial resolution and sensitivity of HD-DOT in capturing detailed and extensive neural activity during complex social interactions, our findings for the first time clarified the potential strengths of HD-DOT in measuring IBS over traditional fNIRS. These advances provide a stronger empirical foundation for investigating the neural basis of social interaction, paving the way for future research on real-world, dynamic group behaviors.

Neural trajectories improve motor precision
Populations of neurons in motor cortex signal voluntary movement. Most classic neural encoding models and current brain-computer interface decoders assume individual neurons sum together along a neural dimension to represent movement features such as velocity or force. However, large population neural analyses continue to identify trajectories of neural activity evolving with time that traverse multiple dimensions. Explanations for these neural trajectories typically focus on how cortical circuits processes learn, organize, and implement movements. However, descriptions of how these neural trajectories might improve performance, and specifically motor precision, are lacking. In this study, we proposed and tested a computational model that highlights the role of neural trajectories, through the selective co-activation and selective timing of firing rates across the neural populations, for improving motor precision. Our model uses experimental results from a center-out reaching task as inspiration to create several physiologically realistic models for the neural encoding of movement. Using a recurrent neural network to simulate how a downstream population of neurons might receive such information, like the spinal cord and motor units, we show that movements are more accurate when neural information specific to the phase and/or amplitude of movement are incorporated across time instead of an instantaneous, velocity-only tuning model. Our finding suggests that precise motor control arises from spatiotemporal recruitment of neural populations that create distinct neural trajectories. We anticipate our results will significantly impact not only how neural encoding of movement in motor cortex is described but also future understating for how brain networks communicate information for planning and executing movements. Our model also provides potential inspiration for how to incorporate selective activation across a neural population to improve future brain-computer interfaces.

Cytoplasmic and nuclear protein interaction networks of the synapto-nuclear messenger CRTC1 in neurons reveal cooperative chromatin binding between CREB1 and CRTC1, MEF2C and RFX3
Glutamatergic stimulation of excitatory neurons triggers the synapto-nuclear translocation of the cAMP response element (CRE) binding protein (CREB) regulated transcription coactivator 1 (CRTC1), resulting in the transcription of CREB1 target genes. Whether and how CRTC1 and CREB1 interact with other transcription factors to regulate activity-dependent transcription, and what the role of CRTC1 is in neurons beyond the activation of CREB1 regulated transcription, remains unknown. To address these questions in an unbiased manner, we used proximity labeling to identify CRTC1-proximal proteins in cytoplasmic and nuclear compartments of rodent forebrain neurons. The cytoplasmic CRTC1 proxisome included a variety of signaling pathways and downstream cellular processes involved in synaptic plasticity. In contrast, the nuclear CRTC1 proxisome included transcription factors that mediate activity-dependent transcription, chromatin factors, and splicing factors. Our data revealed that CRTC1 and CREB1 interact with MEF2C and RFX3 transcription factors in an activity-dependent manner. Thus, in chromatin immunoprecipitation-sequencing experiments, CREB1 was prebound to chromatin regions containing bZIP motifs in a manner that was unchanged by neuronal activity, while glutamatergic stimulation triggered the recruitment of CRTC1 and CREB1 to activity-dependent enhancers enriched in motifs for MEF2C and RFX3. Collectively, these results not only enhance our understanding of the role of cytoplasmic and nuclear CRTC1 in neurons, but also reveal a role for CRTC1 in promoting cooperativity of CREB1 with other transcription factors in response to synaptic activity.

MoMo - Combining Neuron Morphology and Connectivity forInteractive Motif Analysis in Connectomes
Connectomics, a subfield of neuroscience, reconstructs structural and functional brain maps at synapse-level resolution. These complex spatial maps consist of tree-like neurons interconnected by synapses. Motif analysis is a widely used method for identifying recurring subgraph patterns in connectomes. These motifs, thus, potentially represent fundamental units of information processing. However, existing computational tools often oversimplify neurons as mere nodes in a graph, disregarding their intricate morphologies. In this paper, we introduce MoMo, a novel interactive visualization framework for analyzing neuron morphology-aware motifs in large connectome graphs. First, we propose an advanced graph data structure that integrates both neuronal morphology and synaptic connectivity. This enables highly efficient, parallel subgraph isomorphism searches, allowing for interactive morphological motif queries. Second, we develop a sketch-based interface that facilitates the intuitive exploration of morphology-based motifs within our new data structure. Users can conduct interactive motif searches on state-of-the-art connectomes and visualize results as interactive 3D renderings. We present a detailed goal and task analysis for motif exploration in connectomes, incorporating neuron morphology. Finally, we evaluate MoMo through case studies with four domain experts, who asses the tools usefulness and effectiveness in motif exploration, and relevance to real-world neuroscience research. The source code for MoMo is available here: https: //github.com/VCG/momo

Characterization of mice with cell type-specific Gnal loss of function provides insights on GNAL-linked dystonia
Isolated dystonia can be caused by loss-of-function mutations in the GNAL gene (DYT-GNAL). This gene encodes the olf heterotrimeric G protein subunit, which, together with {beta}2{gamma}7 subunits, mediates the stimulatory coupling of dopamine D1 and adenosine A2A receptors to adenylyl-cyclase. These receptors are expressed in distinct striatal projection neurons (SPNs) with complementary functions on motor behavior. To dissect the specific roles of Golf in each subpopulation of SPNs, we generated and characterized mouse models in which Gnal was conditionally deleted in neurons expressing either D1 receptors (D1-SPNs) or A2A receptors (A2A-SPNs). Our results confirmed the critical role of Golf in regulating adenylyl-cyclase 5 and its coupling with D1 and A2A receptors. Mice with a selective loss of Golf in D1-SPNs showed nocturnal hyperactivity, deficits in motor performances, but no overt abnormal movements or generalized motor disability. Our experiments also revealed that Golf in D1-SPNs is not systematically required for locomotor responses induced by D1 agonists or psychostimulants. Selective loss of Golf in A2A-SPNs did not affect motor abilities nor learning. However, this loss strikingly increased spontaneous locomotor activity that was not further enhanced by psychostimulant drugs (cocaine, D-amphetamine, methylphenidate) or a selective A2 agonist, KW6002, and was paradoxically reduced by caffeine Our study identified specific roles of Golf downstream of D1 and A2A receptors in the control of motor behavior and drug responses, highlighting their respective individual contribution in diseases associated with dysfunctional striatal signaling, including dystonia.

Neural mechanisms underlying reward processing and social cognition: a replication study with a Japanese sample
Neural functions underlying reward processing and social cognition play a critical role in everyday decision-making. Given that these processes may be shaped by cultural factors, it is essential to examine their cross-cultural generalizability. In this study, we used functional MRI to scan native Japanese speakers as they performed two well-established experimental paradigms: the Monetary Incentive Delay (MID) task for reward processing and the Theory of Mind (ToM) task for social cognition. We successfully replicated previous findings. Specifically, in the MID task, reward expectation and reward outcome were associated with neural activity in the ventral striatum and ventromedial prefrontal cortex. In the ToM task, social cognition was linked to activation in the temporoparietal junction. Notably, the posterior cingulate cortex was engaged in both tasks, suggesting its integrative role across cognitive domains. Together, these results replicate and extend earlier work, supporting the cross-cultural generalizability of the neural mechanisms underlying reward and social cognition, and further validating our fMRI protocol for future research.

Early Detection of Neuroinflammation and White Matter Damage Following Dorsal Spinal Nerve Root Sectioning in a Nonhuman Primate Model
Purpose: Dorsal rhizotomy, or spinal dorsal nerve root lesioning, is a surgical procedure used to treat intractable nerve pain by selectively severing sensory afferent nerve roots. This study aimed to evaluate whether multiparametric MRI, including diffusion tensor imaging (DTI), quantitative magnetization transfer (qMT), and chemical exchange saturation transfer (CEST), can sensitively detect structural and biochemical changes in the intact spinal cord following a focal dorsal nerve root section in a non-human primate model. Methods: In four squirrel monkeys, unilateral dorsal nerve roots at cervical segments C4 and C5 were surgically transected. MRI data were collected using a 9.4 T scanner with a custom saddle-shaped transmit-receive quadrature coil before and one week after lesioning. DTI-derived fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD); qMT-derived pool size ratio (PSR); and CEST and nuclear Overhauser enhancement (NOE) effects were quantified across seven regions of interest. CEST and NOE effects were extracted using five-pool Lorentzian fitting of Z-spectra. Results: At the lesioned dorsal nerve root bundles, FA, PSR, and NOE(-1.6 ppm) values decreased, while RD and CEST(3.5 ppm) increased, consistent with fiber degeneration, demyelination, and inflammation. Similar, though less pronounced, changes were observed in the dorsal root entry zone, particularly within the first week post-lesion. Conclusion: Multiparametric MRI enables region-specific detection of early spinal cord pathology as soon as one week following dorsal nerve root injury. These findings support its potential as a noninvasive tool for monitoring secondary degeneration due to spinal nerve damage and for evaluating outcomes of therapeutic interventions.

REMI: Reconstructing Episodic Memory During Intrinsic Path Planning
Grid cells in the medial entorhinal cortex (MEC) are believed to path integrate speed and direction signals to activate at triangular grids of locations in an environment, thus implementing a population code for position. In parallel, place cells in the hippocampus (HC) fire at spatially confined locations, with selectivity tuned not only to allocentric position but also to environmental contexts, such as sensory cues. Although grid and place cells both encode spatial information and support memory for multiple locations, why animals maintain two such representations remains unclear. Noting that place representations seem to have other functional roles in intrinsically motivated tasks such as recalling locations from sensory cues, we propose that animals maintain grid and place representations together to support planning. Specifically, we posit that place cells auto-associate not only sensory information relayed from the MEC but also grid cell patterns, enabling recall of goal location grid patterns from sensory and motivational cues, permitting subsequent planning with only grid representations. We extend a previous theoretical framework for grid-cell-based planning and show that local transition rules can generalize to long-distance path forecasting. We further show that a planning network can sequentially update grid cell states toward the goal. During this process, intermediate grid activity can trigger place cell pattern completion, reconstructing experiences along the planned path. We demonstrate all these effects using a single-layer RNN that simultaneously models the HC-MEC loop and the planning subnetwork. We show that such recurrent mechanisms for grid cell-based planning, with goal recall driven by the place system, make several characteristic, testable predictions.

Prior Information Shapes Perceptual Evidence Accumulation Dynamics Differentially in Psychosis
Humans rely on prior information to navigate sensory uncertainty: Such priors could shape the decision process before sensory evidence is gathered (origin model), or could amplify sensory evidence dynamically (gain model). Dysfunctionalities in the utilisation of priors may underlie hallucinatory percepts and delusional ideation in psychosis, yet their impact on decision-making across sensory modalities has remained unclear. Using a perceptual target-detection task across auditory and visual domains in laboratory and online samples, we applied hierarchical drift diffusion modelling to examine how prior probabilities shape evidence accumulation in clinical and non-clinical populations. We show that in healthy individuals, prior information enhances sensory gain and decision flexibility, as represented by drift criterion and rate, consistent with the gain model. In contrast, individuals with psychosis exhibit diminished sensory gain, relying instead on pre-evidence biases, consistent with the origin model. Notably, greater positive symptom severity predicted a reduction in traditional criterion decision bias. These results suggest that sensory gain deficits may serve as a computational marker for psychosis progression, linking dysfunctional prior use to perceptual aberrancies. By demonstrating how prior information modulates evidence accumulation across sensory modalities, our study advances the understanding of psychotic perception and decision-making, offering insights for computational psychiatry and fine-tuned clinical diagnostics.

Timing, movement, and reward contributions to prefrontal and striatal ramping activity
Across species, prefrontal and striatal neurons exhibit time-dependent ramping activity, defined as a consistent monotonic change in firing rate across temporal intervals. However, it is unclear if ramping activity is related to the cognitive process of estimating time, or to other behavioral factors such as anticipating reward or regulating movements. Here, we harnessed two novel approaches to determine how these factors contribute to prefrontal and striatal ramping activity in mice performing an interval timing task. First, to determine how movement contributes to ramping activity, we tracked movement velocity using DeepLabCut as well as task-specific movements while recording prefrontal or striatal ensembles during interval timing. We found that time was more accurately decoded by ramping neurons than movement-modulated neurons, with the exception of prefrontal velocity-modulated neurons. Second, to disambiguate temporal signals from anticipatory reward signals we compared activity patterns in neurons that were recorded during interval timing to the same neurons recorded during a Pavlovian conditioning task. We found more ramping activity and more accurate temporal decoding by neuronal ensembles during interval timing compared to Pavlovian conditioning. Together, these data quantify contributions of time estimation, movement, and reward anticipation in prefrontal and striatal ensembles, and they suggest that ramping is a cognitive signal that estimates time. Our results provide insight into how prefrontal and striatal ensembles multiplex information to effect temporal control of action.

Developmental and Aging Changes in Brain Network Switching Dynamics Revealed by EEG Phase Synchronization
Adaptive behavior depends on the brains capacity to vary its activity across multiple spatial and temporal scales. Yet, how distinct facets of this variability evolve from childhood to older adulthood remains poorly understood, limiting mechanistic models of neurocognitive aging. Here, we characterize lifespan neural variability using an integrated empirical-computational approach. We analyzed high-density EEG cohort data spanning 111 healthy individuals aged 9-75 years, recorded at rest and during passive and attended auditory oddball stimulation task. We extracted scale-dependent measures of EEG fluctuations amplitude and entropy, together with millisecond-resolved phase-synchrony networks in the 2-20 Hz range. Multi-condition partial least squares decomposition analysis revealed two independent lifespan trajectories. First, slow-frequency power, variance and complexity at longer timescales declined monotonically with age, indicating a progressive dampening of low-frequency fluctuations and large-scale coherence. Second, the temporal organization of phase-synchrony reconfigurations followed an inverted U-trend: young adults exhibited the slowest yet most diverse switching--characterized by low mean but high variance and low kurtosis of jump lengths at 2-6 Hz and the opposite pattern at 8-20 Hz--whereas children and older adults showed faster, more stereotyped dynamics. To mechanistically account for these patterns, we fitted a ten-node phase-oscillator model constrained by the human structural connectome. Only an intermediate, metastable coupling regime reproduced the empirical combination of reduced low-frequency variability and maximally heterogeneous synchrony dynamics observed in young adults, while deviations toward weaker or stronger coupling mimicked the childrens and older adults profiles. Our results demonstrate that development and aging entail changes in the switching dynamics of EEG phase synchronization, by differentially sculpting stationary and transient aspects of neural variability. This establishes time-resolved phase-synchrony metrics as sensitive, mechanistically grounded markers of neurocognitive status across the lifespan.

Causal inference shapes crossmodal postdictive perception within the temporal window of multisensory integration
In our environment, stimuli from different sensory modalities are processed within a temporal window of multisensory integration that spans several hundred milliseconds. During this window, the processing and perception of stimulus are influenced not only by preceding and current information, but also by input that follows the presentation of the stimulus. To date, the computational mechanisms underlying crossmodal backward processing, which we refer to as crossmodal postdiction, are not well understood. In this study, we examined crossmodal postdiction in the audiovisual (AV) rabbit illusion, in which postdiction occurs when flash-beep pairs are presented shortly before and shortly after a single flash or a single beep. We collected behavioral data from 32 human participants and fitted four competing models: a Bayesian causal inference (BCI) model, a forced-fusion (FF) model, forced-segregation (FS) model, and a non-postdictive BCI (BCI-NP) model. The BCI model fit the data well and outperformed the other models. Building on previous findings demonstrating causal inference during non-postdictive multisensory integration, our study shows that the BCI framework is also an effective means of explaining crossmodal postdiction. Observers accumulate causal evidence that can retroactively influence the crossmodal perception of preceding sensory stimuli following the causal decision. Our study demonstrates that the AV rabbit illusion forms within a temporal window of multisensory integration that encompasses past, present, and future sensory inputs, and that this integration can be effectively explained by the Bayesian causal inference framework.

Distinct neural architectures underlie motor skill acquisition and transfer in human sensorimotor cortex
Motor learning typically emerges from repetitive practice but can also arise through transfer or generalization, where improvements extend to untrained actions. While training-based (training effect) and transfer/generalization-based (transfer effect) learning often result in comparable motor performance, little is known about the extent to which they share similar neural underpinnings or if they are two separate phenomena that rely on distinct cortical architecture. Here, we employed between-subject multivariate decoding of hyperaligned functional data obtained with high-field (7 Tesla) magnetic resonance imaging to characterize the universal neural codes underlying the training and transfer effects, and compared their resultant motor engrams in the sensorimotor cortex. We found that both learning mechanisms have reliable neural representations that are shared across individual brains, highlighting similar representational geometry despite idiosyncratic functional topographies. While their codes are embedded in overlapping cortical areas, the training effect has a more stable representation centered in the primary sensorimotor cortex, indicative of execution-level learning. In contrast, transfer effects elicited more abstract, variable codes in adjacent premotor and postcentral areas, suggesting flexible recombination of motor chunks. Moreover, the resultant cortical engrams shaped by them are particularly distinct in the left inferior part of the precentral sulcus, and in the right side of the superior part of the precentral sulcus, postcentral gyrus and postcentral sulcus. Our findings support the notion that motor skill learning is hierarchically organized in the sensorimotor cortex, and extend current models by revealing how training and transfer encode distinct, mechanism-dependent, and high-dimensional representations embedded in a neural code that is shared across brains.

Simultaneous cortical tracking of competing speech streams during attention switching
Successful speech communication in multi-talker scenarios requires a skilful combination of sustained attention and rapid attention switching. While the neurophysiology literature offers detailed insights into the neural underpinnings of sustained attention, there remains considerable uncertainty on how attention switching takes place. In this study, using EEG recordings from normal-hearing adults in an immersive multi-talker environment, we measured the neural encoding of two competing speech streams amid background babble. Participants were cued to switch attention between streams every 15-30 seconds. Neural tracking was assessed via Temporal Response Functions (TRF), confirming reliable decoding of attentional focus. Our results indicate asymmetric disengagement and engagement processes during attention switches, where the neural tracking of the new target stream emerges before disengaging from the previous target, revealing a transient simultaneous encoding of two speech streams. That transition was closely mirrored by a reduction in EEG alpha power, informing on the cognitive effort during different phases of the attention switch. We then isolated cortical activity reflecting lexical prediction mechanisms to determine how lexical context is updated after an attention switch, comparing four numerical hypotheses that were constructed using Large Language Models. Our findings elucidate both the temporal and contextual mechanisms underlying auditory attention shifts, pointing to the possibility that listeners carry out a reset in lexical context after switching attention. By focusing on dynamic attentional reallocation, this study offers insights into the brain's capacity for flexible speech processing in complex listening environments.

Piccolo Regulates Secretion of the Extracellular Matrix Components Brevican and Tenascin R from Astrocytes to Drive Synapse Formation: Implications for Pontocerebellar Hypoplasia Type 3 (PCH3)
Background: Astrocytes are crucial for CNS health, for instance via the secretion of extracellular matrix (ECM) components that are vital for synapse formation and maturation. While the scaffolding protein Piccolo is known for its role at synapses, its function in astrocytes and contribution to neurodegenerative disorders like Pontocerebellar Hypoplasia Type 3 (PCH3) are largely unknown. Understanding these mechanisms is key to elucidating PCH3 pathology. Methods: We used a multi-faceted approach with a Pclogt/gt rat model. Methods included RNA-sequencing for gene expression and GO analysis. Immunohistochemistry and immunocytochemistry assessed Piccolo localization, ECM component (Brevican [Bcan], Tenascin-R [TNR]) levels, distribution, and secretion in brain sections and primary astrocytes. Golgi morphology was evaluated via GM130 staining. Neuronal network formation and function were investigated by co-culturing wild-type neurons with Pclowt/wt or Pclogt/gt astrocytes in a Banker setup, assessing synapse density (immunostaining, RRP electrophysiology) and spontaneous activity (mEPSCs, mIPSCs). Astrocyte-conditioned media (ACM) experiments determined secreted factor roles. Results: RNA-seq showed significant DEG increases in older versus young Pclogt/gt rats (P25 vs. P5), which were strongly enriched in cell communication, signaling, and ECM GO terms. We identified a novel astrocyte-specific Piccolo isoform that partially localizes at the Golgi. Piccolo gene trap transposon mutation led to impaired ECM secretion (reduced extracellular Bcan, altered TNR) from astrocytes, correlating with a fragmented Golgi in Pclogt/gt astrocytes. Functionally, Pclogt/gt astrocytes significantly reduced synapse density and altered intrinsic activity (increased mEPSC frequency) in neuronal networks. This synaptic deficit was substantially rescued by Pclowt/wt astrocyte conditioned media (ACM). Conclusion: Our findings reveal a critical, unrecognized role for Piccolo in regulating astrocytic ECM secretion, essential for proper neuronal network formation and activity. Astrocytic Piccolo dysfunction disrupts this process, causing impaired synaptogenesis and altered intrinsic network activity, providing a novel cellular and molecular mechanism for neurodegenerative diseases like PCH3 and highlights astrocytes as potential therapeutic targets.

Ptbp1 is not required for retinal neurogenesis and cell fate specification.
The RNA-binding protein Ptbp1 has been proposed as a master regulator of neuronal fate, repressing neurogenesis through its effects on alternative splicing and miRNA maturation. While prior studies using RNA interference suggested that Ptbp1 loss promotes neurogenesis, recent genetic studies have failed to replicate glia-to-neuron conversion following Ptbp1 loss of function. To evaluate the role of Ptbp1 in developmental neurogenesis in vivo, we conditionally disrupted Ptbp1 in retinal progenitors. Ptbp1 was robustly expressed in both retinal progenitors and Muller glia but absent from postmitotic neurons, and efficient loss of function in mutant animals was confirmed using immunostaining for Ptbp1. Furthermore, bulk RNA-Seq at E16 revealed accelerated expression of late-stage progenitor and photoreceptor-specific genes and altered splicing patterns in Ptbp1 mutants, including increased inclusion of rod photoreceptor-specific exons. However, we observed no defects in retinal lamination, progenitor proliferation, or cell fate specification in mature retina. ScRNA-Seq of mature mutant retinas revealed only modest transcriptional changes which partially recapitulate alterations seen following selective deletion of Ptbp1 in mature glia. Our findings demonstrate that Ptbp1 is dispensable for retinal development and suggest that its proposed role as a central repressor of neurogenesis should be reevaluated.

AxoMetric: A Rapid and Unbiased Tool for Automated Quantification of Axon Regeneration in Tissue Sections
Recent advances in experimental strategies that promote axon regeneration in adult mammals lay the foundation for future therapies. Reliable and unbiased quantification of regenerated axons is challenging, yet essential for comparing the efficacy of individual treatments and identification of most efficacious combinatorial therapies. Here, we introduce AxoMetric, a user-friendly and freely available software for the rapid quantification of regenerated axons in longitudinal nerve tissue sections. AxoMetric automatically identifies and traces regenerated axons, generating quantitative measurements that closely match conventional manual quantification but with significantly greater speed. Key features include length-dependent axon quantification at defined intervals from the injury site and normalization of axon density to nerve diameter to account for anatomical variability. To facilitate high-throughput analysis, the software includes an image queuing function. Additional features of AxoMetric allow quantification of a range of labeled cellular structures. As a proof of concept, we demonstrate accurate quantification of regenerated axons in the optic nerve, retinal ganglion cells density in retinal flat-mounts, and regenerated axon bundles in injured sciatic nerves. Collectively, we introduce a new platform that is expected to streamline and standardize regenerative outcome assessments across diverse experimental conditions and laboratories.

Cell Type-Specific Changes in Dendritic Spines Across Adolescence Within Mouse Medial Prefrontal Cortex
Across species, cognitive capacities that rely on the frontal cortex do not fully mature until adulthood. Adolescent circuit refinement, including structural remodeling of dendritic spines, is believed to underlie this protracted maturation. Understanding cell type-dependent patterns of structural maturation would provide important insight into frontal cortex development. Here, we leveraged retrograde adeno-associated viruses to quantify dendritic spines on pyramidal tract (PT) vs. intratelencephalic (IT) neuronal populations in parallel within the mouse medial prefrontal cortex (mPFC) across adolescence. IT-type neurons showed opposing changes in mushroom and thin spines that were: 1) consistent with increasing synaptic maturity and 2) largely absent in PT-type neurons. We next probed the function of brain-resident immune cells, microglia, by transiently ablating them within the mPFC at mid-adolescence. This led to cell type-dependent changes in dendritic spines in late adolescence, with thin spine proportion increasing on both cell types but total spine density increasing on IT-type neurons only. Meanwhile, there was no effect on performance in an mPFC-dependent task of cognitive flexibility at either late adolescent or adult time points following microglia ablation. These findings provide evidence that mPFC IT-type neurons undergo greater spine remodeling during adolescence compared to PT-type neurons and implicate microglia as potential mediators.

Molecular and cellular processes disrupted in the early postnatal Down syndrome prefrontal cortex
Down syndrome is the most common genetic cause of intellectual disability and is characterized by early-onset delays in motor, cognitive, and language development. The molecular mechanisms underlying these neurodevelopmental impairments remain poorly understood. Here, we utilized single-nucleus multiomic sequencing to simultaneously profile gene expression and chromatin accessibility in the Down syndrome prefrontal cortex during early postnatal development, a critical period for synaptogenesis, neural maturation, and developmental neuroimmune interactions. Our findings reveal widespread dysregulation of chromatin accessibility and gene expression, with deficits spanning metabolic and synaptic pathways, oligodendrocyte lineage progression, and a pronounced neuroinflammatory signature. We present a molecular atlas of Down syndrome neuropathology at a critical stage of brain development, highlighting convergent neurodevelopmental and neurodegenerative pathways and informing potential targeted therapies for Down syndrome-associated neuroinflammation.

Robust Production of Parvalbumin Cortical Interneurons and Fast-Spiking Neurons from Human Medial Ganglionic Eminence Organoids
The medial ganglionic eminence (MGE) gives rise to parvalbumin (PV)- and somatostatin (SST)-expressing cortical interneurons essential for regulating cortical excitability. Although PV interneurons are linked to various neurodevelopmental and neurodegenerative disorders, reliably generating them from human pluripotent stem cells (hPSCs) has been extremely challenging. We present a robust, reproducible protocol for generating single-rosette MGE organoids (MGEOs) from hPSCs. Transcriptomic analyses reveal that MGEOs exhibit MGE regional identity and faithfully model the developing human fetal MGE. As MGEOs mature, they generate abundant PV-expressing cortical interneurons, including putative basket and axoaxonic cells, at a scale not previously achieved in vitro. When fused with hPSC-derived cortical organoids, these interneurons rapidly migrate into cortical regions, integrate into excitatory networks, and contribute to complex electrophysiological patterns and the emergence of large numbers of fast-spiking neurons. MGEOs thus offer a powerful in vitro approach for probing human MGE-lineage cortical and subcortical GABAergic neuron development, modeling various neuropsychiatric disorders, and advancing cell-based therapies for neurodevelopmental and neurodegenerative disorders.

Subtype-Specific Roles of Nigrostriatal Dopaminergic Neurons in Motor and Associative Learning
Nigrostriatal dopaminergic neurons (DANs) in the substantia nigra pars compacta (SNc) comprise distinct subtypes defined by unique gene expression profiles and anatomical characteristics. However, their specific contributions to motor and non-motor functions remain elusive. Using Calbindin 1 (Calb1) and Aldehyde dehydrogenase 1a1 (Aldh1a1) as molecular markers, we investigated the functions of these nigrostriatal DAN subtypes in mice. Through intersectional genetics and chemogenetic manipulation, we selectively inhibited Calb1+ or Aldh1a1+ DANs by stereotactically delivering an adeno-associated viral vector (AAV-CreOn-FlpOn-hM4Di-P2A-mCherry) into the SNc of ThFlp; Calb1IRESCre or ThFlp; Aldh1a1CreERT2 double knock-in (KI) mice. This approach enabled subtype-specific neuronal inhibition via designer receptors exclusively activated by designer drugs (DREADD). Following DREADD ligand administration, both Calb1+ and Aldh1a1+ DAN-inhibited mice exhibited significant reduction in voluntary movement and impaired motor skill learning, demonstrating their essential roles in motor function. However, only Calb1+ DAN inhibition affected early associative-learning behavior, suggesting a unique role in reinforcement learning. These findings establish Calb1+ and Aldh1a1+ nigrostriatal DANs as key regulators of movement and motor learning, with Calb1+ neurons additionally modulating reward-based associative learning. This study advances our understanding of the functional heterogeneity of nigrostriatal DAN subtypes and identifies potential therapeutic targets for addressing motor and non-motor deficits in Parkinson's disease.

CB1 receptor inhibition in fragile X syndrome mice impacts alternative splicing alterations in hippocampal synaptoneurosomal transcriptome
Background Fragile X syndrome (FXS) conveys the most frequent heritable genetic cause of intellectual disability and autism. It is caused by a CGG repeat expansion in FMR1 gene that leads to the loss of fragile X messenger ribonucleoprotein 1 (FMRP). FMRP is highly abundant in synapses, where regulates mRNAs to maintain synaptic plasticity. Treatments under development significantly ameliorate neurological and behavioral landmarks in the mouse model of the disorder, the Fmr1 knockout (FX) mouse. Specifically, previous studies revealed that pharmacological and genetic inhibition of cannabinoid type-1 receptor (CB1R) restored phenotypic traits in FX mice. However, the molecular hallmarks associated with this experimental therapeutic intervention are largely unknown. Methods First, we aimed to evaluate the validity of synaptoneurosomes preparations to investigate specific mRNA modifications at synapses. Afterwards, combining in silico high-throughput analysis and biochemical determinations, we analyzed the hippocampal synaptoneurosomal transcriptome after pharmacological inhibition of CB1R with the specific antagonist/inverse agonist rimonabant in FX male mice Results We verified that synaptoneurosomes provide an accurate representation of synaptic composition and function. Then, we found that rimonabant treatment had a limited impact at gene expression level but produced significant modifications in transcript expression. Indeed, detailed analysis of alternative splicing events revealed a relevant number of events in which splicing was reverted from the FX form to the WT form by the treatment. Limitations We demonstrated that rimonabant treatment alters the AS landscape in FX hippocampal synaptoneurosomes; however, further studies are needed to elucidate if other neural components also contribute to the modifications and whether the findings are specific to rimonabant treatment or to CB1R inhibition at synapses. In addition, additional research could be required to clarify whether the changes in AS events could be affected by interindividual variability or technical protocols. Conclusions We determined that the AS landscape is modified in FX hippocampal synaptoneurosomes and that these changes are sensitive to rimonabant treatment which could explain the beneficial effects of this experimental therapeutic approach in FXS. Altogether, our results reveal a new level of complexity in the effect of pharmacological treatment to improve symptoms in the context of FXS.

Sex effects on gene expression across the human cerebral cortex at single cell resolution
Sex differences in brain-related health outcomes may be a consequence of differences in gene expression. However, most current knowledge relies on studies of bulk tissue or isolated brain regions. Here, we present a large-scale single-cell analysis of transcriptomic sex differences in the human brain, using 169 samples from 15 females and 15 males across six cortical regions, selected based on in vivo neuroimaging measures of sex-biased volume. We find that sex effects on gene expression are highly patterned across cortical regions, cell types, and genes. They are most pronounced in: i) multiple cell types in the fusiform cortex (linked to male-biased volume and sex-biased behaviors); ii) oligodendrocytes, astrocytes, and excitatory neurons across regions; and iii) a subset of sex chromosome and autosomal genes. Over 3,000 unique genes exhibit sex-biased expression, with 133 genes (119 autosomal) showing consistent sex differences across all region x cell type combinations. Sex chromosome genes show the largest sex differences in expression, driven by conserved X-Y gametologs, cell-type-specific biases in certain X- and Y-linked genes, and escape from X-inactivation - with the list of known escapees substantially expanded through our single-cell allele-specific expression analysis. Broader effects of sex on autosomal expression are captured in 13 core signatures with varying cell type vs. region specificity. These signatures are: i) shaped by regional differences in metabolism and laminar architecture; ii) enriched for diverse cellular compartments and biological processes; iii) regulated by sex steroids and X-linked transcription factors; and iv) linked to sex-specific genetic risk factors in sex-biased neuropsychiatric and neurodegenerative diseases. This study substantially advances the breadth, depth, and granularity of knowledge on sex differences in the human brain, and provides a new open data resource to support future research.

One-step induction of human GABAergic neurons promotes presynaptic development & synapse maturation
Human induced pluripotent stem cells (iPSCs) present a powerful approach to study human brain physiology and disease, yet robust, pure GABAergic induction has remained difficult. Here we present improved, single-step, transposon-based GABAergic induction with Ascl1/Dlx2, which yields pure GABAergic neurons, in contrast to lentiviral approaches, and was tested across three independent iPSC lines. Proteomic and electrophysiological characterization at different developmental time points showed that these neurons gain a proteomic profile that maps to different cortical interneuron subtypes, particularly VIP+ interneurons, and display typical GABAergic synaptic properties, producing large, synchronous and picrotoxin-sensitive currents. During early development synaptic strength increased threefold, which was accompanied by enhanced expression of multiple GABA-specific presynaptic gene sets, but few changes in postsynaptic gene sets. Synaptic strength continued to improve during late development but with only minor proteomic changes. Co-seeding with NGN2 neurons created stable networks of predefined excitation/inhibition ratios, with corresponding synapse ratios. Taken together, transposon-based GABAergic induction yields pure, mature GABAergic neurons suitable for studying gene sets involved in synaptic maturation and to build excitation/inhibition networks for disease modelling.

Different representations in layer 2/3 and layer 5 excitatory neurons of the primary visual cortex
The cortex contains multiple types of excitatory neuron, differentiated primarily by their layer of residence. We recorded from neuronal populations in the mouse visual cortex using 2-photon calcium imaging or Neuropixels probes, and found that excita-tory neurons in layer 2/3 (L2/3) and layer 5 (L5) differ in their encoding of visual vs. nonvisual signals, with L2/3 more strongly modulated by visual stimuli and L5 more strongly modulated by movement. Movement has opposite effects on population synchrony in the two layers, desynchronizing L2/3 by abolishing spontaneous population oscillations, and synchronizing L5, where excitatory cells are less entrained by oscillation and more strongly correlated with movement itself. Spontaneous activity is lower-dimensional in L2/3 than L5, with L2/3 population activity dominated by a single dimension of overlap between spontaneous and stimulus-evoked subspaces. We conclude that the population code of in different layers of the visual cortex differentially balances visual and non-visual signals.

Obesogenic diet impairs memory consolidation via the hippocampal endocannabinoid system
Although obesogenic high-fat/high-sugar diets impair memory function in humans and rodents, the underlying mechanisms remain elusive. Given that the brain endocannabinoid system and type-1 cannabinoid receptors (CB1R) control memory processes and are overactive under obesogenic conditions, we studied whether the effects of obesogenic diet consumption on memory function are dependent on this system. Using an object recognition memory (ORM) task in male mice, we showed that CB1R activity is required for obesogenic diet-induced impairment of long-term memory performance. This impairment was prevented by post-training systemic blockade of CB1R, which also normalized training-induced hippocampal cellular and synaptic overactivation. Consistently, obesogenic diet potentiated the increase of hippocampal endocannabinoid levels and enhanced CB1R expression induced by ORM, and genetic CB1R deletion from hippocampal glutamatergic neurons abolished diet-induced memory deficits. Strikingly, obesogenic diet enhanced the hippocampal mTOR pathway in a CB1R-dependent manner, and pharmacological mTOR inhibition after training rescued diet-induced ORM consolidation deficits. Together, these results establish how an obesogenic environment can lead to hippocampal overactivation of the endocannabinoid system and of the mTOR pathway to eventually impair memory consolidation. Thus, these results shed light on the mechanisms of diet-induced cognitive alterations and may pave the way to novel therapeutic strategies.

Lesions in the cerebellum impact cross-modal temporal predictions
The cerebellum (CE) supports the encoding of the precise sensory event timing and the generation of temporal predictions. Here we investigated whether focal CE lesions impact temporal predictions in a cross-modal context. Individuals with CE lesion (n=9) and healthy-matched controls (HC) were presented with visuo-auditory stimulus pairs, presented in a temporally regular (predictable) or irregular (unpredictable) manner while EEG was recorded. We hypothesized cross-modal temporal predictions to be mediated by pre-stimulus cerebello-cortical beta-band (12-25Hz) activity. In turn, we expected HC, but not CE patients, to show a modulation of pre-stimulus beta power as a function of temporal prediction. HC showed greater pre-stimulus beta-band suppression in anticipation of sound onsets, and stronger post-stimulus delta- and theta-band (1-4Hz; 4-8Hz) power in the predictable than the unpredictable condition. Furthermore, they displayed a significant modulation of pre-stimulus delta-beta cross-frequency coupling as a function of temporal prediction. These effects were not observed in the CE group. Results confirm that cerebellar lesions impair the generation of temporal predictions in cross-modal (visuo-auditory) stimulus processing, extending the role of cerebellar predictive timing from sensorimotor to motor-independent cross-modal perception.

Efficient planning and implementation of optimal foraging strategies under energetic constraints
To successfully forage for food, animals must balance the energetic cost of searching for food sources with the energetic benefit of exploiting those sources. While the Marginal Value Theorem provides one normative account of this balance by specifying that a forager should leave a food patch when its energetic yield falls below the average yield of other patches in the environment, it assumes the presence of other readily reachable patches. In natural settings, however, a forager does not know whether it will encounter additional food patches, and it must balance potential energetic costs and benefits accordingly. Upon first encountering a patch of food, it faces a decision of whether and when to leave the patch in search of better options, and when to return if no better options are found. Here, we explore how a forager should structure its search for new food patches when the existence of those patches is unknown, and when searching for those patches requires energy that can only be harvested from a single known food patch. We identify conditions under which it is more favorable to explore the environment in several successive trips rather than in a single long exploration, and we show how the optimal sequence of trips depends on the forager's beliefs about the distribution and nutritional content of food patches in the environment. This optimal strategy is well approximated by a local decision that can be implemented by a simple neural circuit architecture. Together, this work highlights how energetic constraints and prior beliefs shape optimal foraging strategies, and how such strategies can be approximated by simple neural networks that implement local decision rules.

Microglial GSDMD-Mediated Pyroptosis Drives Neuroinflammation in Parkinson's Disease
Rationale Parkinson's disease (PD), a globally prevalent neurodegenerative disorder, is characterized by substantia nigra dopaminergic neuron degeneration and striatal dopamine depletion. While microglial pyroptosis is implicated in neuroinflammation and neural injury via inflammatory cytokine release, the role of the CASPASE-1/GSDMD pathway in PD pathogenesis remains incompletely defined. Methods 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) was used to construct PD model in vivo, GSDMD-knockout mice was employed to assess pyroptotic mechanisms. MPP+-stimulated BV2 microglia were treated with a CASPASE-1 inhibitor in vitro. Microglia-specific GSDMD conditional knockout mice were generated to evaluate cell-type contributions to neuroinflammation and motor deficits. Results GSDMD deficiency attenuated MPTP-induced neuroinflammation, dopaminergic neuron loss, and motor dysfunction in vivo. MPP+ exposure triggered NLRP3 inflammasome activation and pyroptosis in BV2 microglia, which was suppressed by CASPASE-1 inhibition. Critically, microglia-specific GSDMD ablation mitigated nigrostriatal degeneration and dyskinesia in PD mice, confirming the centrality of microglial pyroptosis. Conclusion Our findings demonstrate that microglia drive neuroinflammation in PD via CASPASE-1/GSDMD-mediated pyroptosis, directly linking this pathway to dopaminergic neurodegeneration and motor impairment. Targeting GSDMD-dependent pyroptosis represents a promising therapeutic strategy.

Exploring neural manifolds across a wide range of intrinsic dimensions
Recent technical breakthroughs have enabled a rapid surge in the number of neurons that can be simultaneously recorded, calling for the development of robust methods to investigate neural activity at a population level. In this context, it is becoming increasingly important to characterize the neural activity manifold, the set of configurations visited by the network within the space defined by the instantaneous firing rates of all neurons. The intrinsic dimension (ID) of the manifold is a key parameter allowing to relate neural trajectories with the ongoing network computations. While several studies suggested that the ID may be typically low in neural manifolds, contrasting findings have disputed this statement, leading to a wide debate. Part of the disagreement may stem from the lack of a shared and robust methodology to measure the ID. In the case of curvature, linear methods tend to overestimate the ID; in the case of undersampling, nonlinear methods tend underestimate it. Here we show that adapting the full correlation integral (FCI) method yields an estimator that is robust to both curvature and undersampling. We tested our metric on artificial data, including neural trajectories generated recurrent neural networks (RNNs) performing simple tasks and a benchmark dataset consisting of non-linearly embedded high-dimensional data. Our methodology provides a reliable and versatile tool for the analysis of neural geometry.

LatenZy, non-parametric, binning-free estimation of latencies from neural spiking data
Precisely estimating the onset of neural spiking responses and the timing at which activity begins to diverge between conditions is crucial for understanding temporal dynamics in brain information processing. Conventional methods require arbitrary parameter choices such as bin widths and response thresholds, limiting reproducibility and comparability. Here, we present latenZy and latenZy2, two non-parametric, binning-free methods that directly analyze spike times using cumulative statistics and iterative refinement, without assumptions about response shape. LatenZy estimates neuronal response onset latency, while latenZy2 detects when spiking activity diverges between conditions. We validate these methods on electrophysiological datasets from mouse and macaque visual cortex, and show that they outperform standard approaches in precision, robustness, sensitivity, and statistical power. LatenZy captures contrast-dependent latency shifts and hierarchical timing across visual areas, and latenZy2 reveals earlier attentional modulation in higher visual cortex consistent with top-down feedback. Together, they offer scalable, parameter-free tools for reliable latency estimation in large-scale neural recordings. Open-source implementations are available in Python and MATLAB.

Decoding the sex of faces using the power, phase, and the Fourier spectrum of the time-frequency representation
The EEG activity related to face processing has been studied extensively with machine learning techniques and most of these studies apply preprocessed data without further data transformation. Here we analyzed the data of two experiments and explored the potential in decoding the time-frequency representation in face processing, thus extracting not only temporal but also the frequency distribution. In the two experiments, participants were presented with faces and through changing the presentation number per face, we manipulated their familiarity. Then we determined the time window of facial sex related cortical activities with frequently employed decoding techniques on the preprocessed data. Subsequently, we performed Fourier transformation on the data and decoded time-frequency spectrum of the amplitude, the phase and also the complex Fourier spectrum. This analysis revealed a 500 ms long time window at the beginning of the stimulus presentation in the 2 to 17 Hz frequency range, which showed above-chance decoding accuracies in the case of more familiar faces. Less familiar faces showed similar, albeit more restricted time-frequency windows. By comparing the two experiments we also observed 350 ms long window in the low frequencies of 4-10 Hz, where familiar faces exhibited greater decoding accuracies. This method expanded on the generally observed time-window and complemented it with a frequency distribution related to facial sex processing. The current study demonstrates that machine learning applications can be applied to higher dimensional data, like the time-frequency representation in cognitive studies.

Single-Domain Antibody-Based Autophagosome-Targeting Chimera for Tau Clearance and Motor Function Restoration in Tauopathies
Tauopathies are neurodegenerative diseases characterized by pathological tau accumulation, leading to motor and neuropsychiatric symptoms. Effective tau-targeting therapies remain a major challenge. Here, we present 1D9-LIR{Delta}TP53INP2, a single-domain antibody (sdAb)-based protein degrader that facilitates tau clearance via the autophagy-lysosomal pathway. This engineered molecule combines the anti-tau sdAb 1D9 with an LC3-interacting region (LIR{Delta}TP53INP2) to promote autophagosomal recruitment, mimicking autophagy receptors by simultaneously binding tau and LC3. In frontotemporal dementia (FTD) patient-derived neurons and JNPL3 tauopathy mice, both harboring the P301L tau mutation, 1D9-LIR{Delta}TP53INP2 significantly reduced tau levels and improved motor function in mice. These findings underscore the therapeutic potential of sdAb-based protein degraders for tauopathies. Given the challenges of brain delivery for conventional antibodies, sdAbs with enhanced brain penetration and efficacy offer a promising strategy for treatment of neurodegenerative diseases.

Neural entrainment predicts the anticipatory P300 component during musical meter perception: An EEG study using dual-meter sound stimuli
Meter, the organization of beats into regular groupings, is a core element of music perception. Switches in meters frequently occur in music, reflecting the interplay between top-down attentional processes and the bottom-up processing of acoustic features. To disentangle this interplay in meter perception, we had previously invented a sound stimulus that simultaneously contained two meters. This dual-meter stimulus consisted of band-limited noise bursts that varied in center frequency and duration, with one feature following a triple-meter pattern and the other following a quadruple-meter pattern. Thus, the perceived meter switches between the two by changing attention from one acoustic feature to another, even when listening to identical stimuli. Using these stimuli, we here demonstrated the neural processes involved in meter perception by recording electroencephalogram (EEG) signals, while dissociating the influence of acoustic differences. We first found that the perceived meter structure was reflected in the entrained neural oscillations by comparing the spectral profiles of EEG signals when the participants focused on triple-meter versus quadruple-meter features. Second, an event-related potential component for anticipation (P300) was observed when the expected meter structure was disrupted by altering the frequency or duration of one sound at the end of the stimulus. Notably, individuals with stronger neural entrainment exhibited larger P300 responses to these disruptions. Our findings suggest that top-down attention modulates anticipation of the meter structure, and this anticipation induces neural entrainment that is involved in meter perception.

Functionally-structured Bayesian model for localizing neural activity and information in magnetoencephalography signals
Magnetoencephalography (MEG) is a noninvasive method that can measure human brain activity with high temporal resolution. However, the spatial resolution of MEG is not sufficient to reveal neural mechanisms. Although MEG source estimation overcomes this problem to some extent, the combination of MEG source estimation and multivariate analysis results in ''information spreading'', where significant predictions are observed in brain areas outside the true signal source location. This paper describes a model that achieves high source estimation accuracy and suppresses information spreading simultaneously. The proposed approach is based on a Bayesian estimation model that utilizes functional structure of the human brain. We compare the performance of the proposed model with simulated data generated under various signal-to-noise ratio conditions. The results show that the functionally-structured Bayesian model achieves source estimation accuracy that is better than that of conventional source estimation models. Additionally, the comparison of information spreading among the models reveals that our model outperforms the conventional ones. These results suggest that information spreading in the MEG source estimation can be suppressed while maintaining high source estimation accuracy.

Lumbar spinal Shox2 interneurons receive monosynaptic excitatory input from the lateral paragigantocellular nucleus in the adult mouse
Locomotor output in vertebrates is generated in the spinal cord but is initiated and controlled by descending projections from supraspinal structures. Spinal interneurons involved in locomotion have been revealed through manipulation of genetically identified interneurons in transgenic mouse lines. Lumbar spinal interneurons expressing the transcription factor Shox2 include putative locomotor rhythm generating neurons in mice. The direct connection between supraspinal and lumbar spinal locomotor-related interneurons is comprised of reticulospinal neurons which are thought to directly provide drive to spinal rhythm generating interneurons that receive descending input and convert it to a rhythmic output. Excitatory neurons in the lateral paragigantocellular nucleus (LPGi) within the medulla have been shown to provide this descending drive in the context of forward locomotor initiation. However, a direct connection between excitatory LPGi neurons and identified spinal rhythm generating neurons has yet to be demonstrated. Here, we performed viral tracing and electrophysiological recordings to test for direct connections between the LPGi and lumbar Shox2 interneurons in adult mice. Using both monosynaptic-restricted transsynaptic rabies and anterograde AAV tracing, we show that excitatory neurons from the LPGi make direct putative excitatory synaptic contacts onto lumbar spinal Shox2 interneurons. A monosynaptic connection was confirmed via recordings of excitatory postsynaptic potentials in Shox2 interneurons in lumbar spinal slices evoked by optogenetic activation of LPGi terminals. These results demonstrate that at least a subset of lumbar spinal Shox2 interneurons receive monosynaptic excitatory input from the LPGi in the medulla, a connection which may provide the substrate for the initiation of locomotion.

Age-dependent remodeling of the sciatic proteome in 5xFAD mice can be attenuated by exercise or donepezil treatment to maintain neuromuscular function
Background: Alzheimers disease (AD) progresses along a continuum for years to possibly decades prior to cognitive decline and clinical diagnosis. Preclinical AD is associated with neuromuscular dysfunction. We previously characterized early neuromuscular impairment prior to cognitive decline at 4 months of age in the 5xFAD mouse model of AD. However, the underlying cause(s) for peripheral nerve dysfunction leading to impaired skeletal muscle torque production are not understood, therefore limiting interventional capacity. We hypothesized that either voluntary wheel running or donepezil treatment, begun prior to neuromuscular decline, would delay manifestation of neuromuscular impairment in 5xFAD mice. Methods: Sciatic nerves from 5xFAD and wild-type (WT) mice were analyzed by tandem mass tag (TMT)-labeled proteomics at 3, 4, and 7 months to investigate proteome remodeling. Separate cohorts, using 3-month-old 5xFAD mice and WT littermates given voluntary wheel access for 4 weeks or treated with the acetylcholinesterase inhibitor donepezil to test if neuromuscular dysfunction could be attenuated. Afterwards, we assessed tibial nerve stimulated plantar flexion torque and sciatic nerve compound (motor) neuron action potential (CNAP) in-vivo at 4 months. Additionally, we performed TMT-labeled proteomics to ascertain the effect of exercise and donepezil treatments on sciatic proteome. Results: Sciatic nerves in 5xFAD mice exhibited proteomic remodeling from 3 to 4 months, particularly in pathways linked to mitochondrial turnover, calcium handling, lipid metabolism, and inflammation, coinciding with onset of neuromuscular dysfunction. Both exercise and donepezil attenuated in nerve-stimulated muscle torque and CNAP dysfunction. Both exercise and donepezil attenuated proteomic remodeling of the sciatic nerve involving mitochondrial-centric processes through both shared and independent mechanisms. Conclusions: Declines in neuromuscular function may be pre-clinical identifiers for AD that share pathway similarities with noted central effects of the pathology on the brain. Our findings highlight the importance of a systemic approach to AD pathology and importance of disease state in interventional efficacy.

Alpha Oscillatory Imbalance Predicts Attention Deficits in Visuospatial Neglect
Background and Objectives: Visuospatial neglect (VSN) is a common consequence of unilateral stroke, characterized by reduced awareness on the contralesional side of space. This study examines resting-state electrophysiological mechanisms underlying VSN, with a focus on interhemispheric differences in alpha-band oscillations and their association with deficits in visual perception and attention. Methods: Resting-state EEG was recorded during three-minute eyes-closed and eyes-open periods in VSN patients. Participants also completed a battery of perceptual and attentional assessments, including the Star Cancellation Task, the Computerized Visual Detection Task, and the Line Bisection Task. Measures of alpha activity, specifically amplitude, peak frequency, and fronto-parietal connectivity, were compared between VSN patients and age- and gender-matched healthy controls. Within the VSN group, alpha activity in the lesioned and non-lesioned hemispheres was used to predict task performance. Results: Compared to healthy controls, VSN patients displayed a distinct resting-state alpha profile, characterized by slower and less synchronized alpha oscillations and reduced fronto-parietal alpha connectivity in the lesioned hemisphere. In contrast, controls showed symmetrical alpha activity across hemispheres. Crucially, the degree of interhemispheric alpha asymmetry in VSN patients consistently predicted attentional impairments across all behavioral tasks. Discussion: VSN is linked to disrupted alpha oscillatory dynamics and interhemispheric imbalance. The extent of alpha desynchronization between hemispheres predicts symptom severity, supporting the interhemispheric competition model of attention. These findings suggest that hyperactive alpha activity in the non-lesioned hemisphere may suppress the lesioned hemisphere, contributing to attentional bias away from the contralesional space.

Neurocognitive mechanisms of mathematics vocabulary processing in L1 and L2 in South African first graders: An fNIRS study
Significance: To learn mathematics, young children require accurate interpretations of mathematics vocabulary. When school language differs from childrens home language, mathematics performance often decreases. Little is known about cortical activation during mathematics vocabulary processing in different languages. This insight will help us to better understand childrens mathematical learning in multilingual societies. Aim and approach: We investigated behavioral and brain responses (fNIRS) of 42 isiZulu and Sesotho (L1) first graders (6.75-7.83 years, 22 girls) who learn mathematics in English (L2) at school when they encounter mathematics vocabulary in L2 compared to L1; and mathematics vocabulary compared to object recognition in L1. Results: The results show that higher accuracy in the L1 mathematics vocabulary, as compared to the L2 mathematics vocabulary, comes with the costs of higher cognitive demands in the right superior and middle frontal gyri for first graders. Mathematics vocabulary required longer response time than object recognition and a higher activation in the right superior frontal gyrus. No parietal difference was observed between conditions. Conclusions: First graders with no automatization of mathematics vocabulary processing, still demand frontal cognitive resources. This study is a good example of how educational neuroimaging compliments our interpretation of behavioral outcomes and environmental factors such as multilingualism.

Predicting therapeutic windows for synaptic intervention in ALS
Amyotrophic Lateral Sclerosis (ALS) is a fatal and increasingly prevalent disease. We previously identified spinal network changes that contribute to ALS, including a loss of connectivity between spinal V1 inhibitory interneurons and motoneurons. Experimentally stabilizing this connectivity slows disease progression, but the dynamics of network degeneration and optimal time windows for intervention remain elusive. Using a data-driven spiking model with stage-specific degeneration and dynamic synaptic kinetics, we predict that V1 dysregulation induces hyperexcitation and flexor-biased motoneuron activity, disrupting flexor-extensor coordination, potentially contributing to selective vulnerability of flexor motoneurons. Synaptic stabilization that strengthens remaining inhibitory synapses can rescue motor output features even after loss of motoneurons. However, after sustained synaptic loss and the development of slower synaptic dynamics, synaptic stabilization leads to maladaptive extensor-biased activity, suggesting that excitatory/inhibitory balance impacts treatment effectiveness. Our models inform preclinical strategies by predicting the most effective time window for spinal circuit interventions.

In vivo selection and glymphatic delivery of AAV5 capsids engineered to target human glial progenitor cells
To establish a means of efficiently transducing human glial progenitor cells (hGPCs) in vivo with therapeutic transgenes, we targeted PDGFRA-driven Cre-recombinase expressing hGPCs in human glial chimeric mice with a library of capsid-modified, recombination-reported adeno-associated viruses (AAVs). PCR screening for gliotropic viral capsid sequences, filtered against visceral organs, identified a set of AAV5-based vectors that preferentially infected human GPCs and/or their derived astrocytes and oligodendrocytes in vivo, with minimal systemic infection. To maximize the intracerebral distribution of these viruses while minimizing their dosing and extracerebral spread, we paired their intracisternal delivery with systemic hypertonicity. This method exploited intracerebral glymphatic flow to bypass the blood-brain barrier, delivering AAV directly into the brain parenchyma. Glymphatic delivery of capsid-modified AAV5s, evolved on human GPCs in vivo, thus enables efficient, brain-wide transgene delivery to human glia and their progenitors in the adult brain, with minimal off-target transduction.

Polarity-dependent modulation of sleep oscillations and cortical excitability in aging
During non-rapid eye movement (NREM) sleep, cortical slow oscillation (SO; <1 Hz) activity and thalamic sleep spindles (12-15 Hz) interact through precise phase coupling to support memory consolidation. Slow oscillatory transcranial direct current stimulation (so-tDCS) can modulate these oscillations. Traditionally, anodal so-tDCS is used to depolarize the cortex during SO up-states, thereby promoting SO activity and SO-spindle coupling. However, intracranial findings suggest that SO down-states, characterized by cortical hyperpolarization, can trigger thalamic spindle bursts. This raises the hypothesis that cathodal so-tDCS, by promoting hyperpolarization, could selectively enhance down-states and more effectively improve SO-spindle coupling. We tested this hypothesis in twenty-two healthy older adults, a population known to exhibit diminished NREM oscillatory activity. Each participant received cathodal, anodal, and sham so-tDCS in separate nap sleep sessions. We quantified SO and spindle characteristics, their temporal coupling, and cortical excitation/inhibition (E/I) balance using EEG spectral slope. We also assessed individual circadian preference (chronotype) as a potential moderator. We found that anodal so-tDCS improved SO-spindle synchrony, and increased spindle power over sham in participants with intermediate or evening chronotypes, while cathodal so-tDCS did not enhance these oscillatory measures compared to sham, despite prolonging SO down-states. Anodal stimulation also elevated E/I balance, indicating increased cortical excitability, while cathodal stimulation did not produce the anticipated opposite shift. In summary, anodal, but not cathodal so-tDCS, effectively enhanced thalamocortical interactions underlying memory consolidation. Furthermore, these findings highlight the importance of individual factors such as chronotype in brain stimulation responsiveness.

Attraction of population receptive fields towards the attended locus is invariant to contrast
Attention enhances perception and spatial resolution. One mechanism by which attention achieves this is by attracting receptive fields towards the attended locus. The literature remains unclear on whether stimulus-driven parameters like contrast should alter this attraction. On one hand, Bayesian interpretation predicts changes in attraction due to contrast, whereas attention field models do not. Here we investigate whether stimulus contrast alters attention-driven attraction towards the attended locus. We used a demanding attentional task at fixation (0.1{ring}) while mapping population receptive fields (pRFs) using either a low-contrast (5% Michelson contrast) or a high-contrast (80% Michelson contrast) checkerboard bar. Behavioral performance across conditions was matched. We show large and consistent differences in the amplitude of responses, but surprisingly, no difference in the amount of attraction towards the attended locus. The variance explained in this experiment was comparable to that of similar studies, which did observe pRF property changes, suggesting sufficient sensitivity to detect attraction towards the attended locus had it occurred at a similar magnitude. Our results cannot be explained by the Bayesian interpretation that predicts attention-based attraction effects varying with contrast. Instead, attention field models better account for our observations.

XBP1s as a Therapeutic Target to Preserve Retinal Function During Aging and Neurodegeneration
Loss of physiological complexity, characterized by reduced adaptive multiscale coordination among system components, is increasingly recognized as a hallmark of aging and neurodegenerative disease. The retina, a window into the brain, offers a unique, accessible platform to monitor neurodegenerative disorders such as Alzheimer's disease (AD). Here, we investigate the therapeutic potential of the unfolded protein response transcription factor XBP1s in preserving retinal function during aging and AD-related pathology in murine models. Using micro-electroretinography with multielectrode arrays, we recorded retinal responses to chirp and white noise stimuli in four mouse models: wild-type (WT), XBP1s-overexpressing (TgXBP1s), AD model (5xFAD), and their crossbreed (TgXBP1s/5xFAD) at approximately 3 and 7 months of age. We assessed retinal signals through entropy-based complexity measures and wavelet coherence between stimulus and response. While WT and 5xFAD mice exhibited age-related decline in retinal complexity, TgXBP1s and TgXBP1s/5xFAD mice maintained higher complexity levels and increased Wcoh in adulthood, indicating functional preservation. These results demonstrate that sustained XBP1s expression protects retinal electrophysiological integrity and highlight the retina's value as a scalable, noninvasive biomarker platform to evaluate therapeutic efficacy targeting neurodegenerative mechanisms.

An Early Olfactory Transcriptomic Signature of Tauopathy: Gbp2b Emerges as a Candidate Biomarker of Tau-Driven Neuroinflammation
Olfactory dysfunction is increasingly recognized as an early feature of neurodegenerative diseases such as Alzheimer's disease. PS19 mice, a well-established tauopathy model, exhibit hallmarks of tau pathology - including hyperphosphorylated tau and pretangle formations - in various regions of the olfactory system. Notably, very recent data demonstrated that aberrantly hyperphosphorylated tau (pTau) was detected as early as 1.5 months of age in the olfactory epithelium (OE). This region contains olfactory sensory neurons projecting to the olfactory bulb (OB), where similar pTau pattern was also observed at this early stage. By 6 months, tau pretangles were evidenced in higher olfactory areas such as the piriform and entorhinal cortices. Given the early involvement of the OE and OB in tau pathology, we performed transcriptomic analyses at 3, 6, and 9 months to investigate the molecular pathways underlying tau pathology in these olfactory regions. Due to the OE's peripheral location and anatomical accessibility, we also aimed in that respect to identify potential early biomarkers of tauopathy. The hippocampus, a key brain region affected in Alzheimer's disease and related disorders, was included in the analysis as a comparative reference due to its known vulnerability and clinical relevance. Our analyses revealed region- and age-specific gene expression changes in PS19 mice. Functional enrichment analyses indicated a temporal progression of molecular alterations associated with tau pathology. We identified a subset of genes differentially expressed across different time points and/or regions. Among these, Gbp2b emerged as a particularly promising early biomarker candidate for tauopathy in the OE, showing consistent upregulation across tau pathological stages and brain regions.

Linking age changes in human cortical microcircuits to impaired brain function and EEG biomarkers
Human brain aging involves a variety of cellular and synaptic changes, but how these changes affect brain function and signals remains poorly understood due to experimental limitations in humans, meriting the use of detailed computational models. We identified key human cellular and synaptic changes occurring with age from previous studies, including a loss of inhibitory cells, NMDA receptors, and spines. We integrated these changes into our detailed human cortical microcircuit models and simulated activity in middle-age (~50 yrs) and older (~70 yrs) microcircuits, and linked the altered mechanisms to reduced spike rates and impaired signal detection. We then simulated EEG potentials arising from the microcircuit activity and found that the emergent power spectral changes due to these aging cellular mechanisms reproduced most of the resting-state EEG biomarkers seen in human aging, including reduced aperiodic offset, exponent, and periodic peak center frequency. Using machine learning, we demonstrated that the changes to the cellular and synaptic aging mechanisms can be estimated accurately from the simulated EEG aging biomarkers. Our results link cellular and synaptic mechanisms of aging with impaired cortical function and physiological biomarkers in clinically-relevant brain signals.

A human pluripotent stem cell tri-culture platform to elucidate microglial regulation of retinal ganglion cells in neuroinflammation
Optic neuropathies, including glaucoma, are characterized by the progressive degeneration of retinal ganglion cells (RGCs), ultimately leading to irreversible vision loss. Increasing evidence implicates microglia, the resident immune cells of the central nervous system, as key modulators of RGC health and disease progression. However, the precise mechanisms by which microglia influence RGCs remain poorly understood, particularly in the human context. In this study, we established human pluripotent stem cell (hPSC)-derived co-culture systems incorporating microglia, astrocytes, and RGCs to explore how microglia shape RGC growth and maturation under physiological conditions. We first examined the impact of homeostatic microglia on RGCs in both co-culture and tri-culture systems, revealing distinct influences of cell types in co-culture compared to when they were grown individually. We then modeled inflammatory states by activating microglia with lipopolysaccharide (LPS) and evaluated their effects on RGCs both directly and in the context of astrocyte co-culture. This stepwise, reductionist approach enabled us to dissect the cellular interactions driving RGC vulnerability in inflammatory conditions relevant to optic neuropathies. Our findings provide new insight into the complex neuroimmune landscape that underlies RGC degeneration and identify key pathways that may serve as therapeutic targets across a range of optic nerve diseases.

Distinct patterns of directed brain connectivity in focused attention, open monitoring and loving kindness meditation: An EEG Granger causality study with long-term meditators
The present study applied spectral Granger causality analysis to electroencephalographic (EEG) recordings obtained during Focused Attention Meditation (FAM), Open Monitoring Meditation (OMM), and Loving Kindness Meditation (LKM) in highly experienced meditators. The aim of the investigation was to uncover distinct connectivity signatures associated with each meditation style by examining the strength, frequency band, and direction of inter-regional information transfers. These differences were expected to highlight the neural grounds of the cognitive and affective state of each meditative practice. Multivariate Granger causality (GC) was computed from high-resolution EEG signals recorded from long-term meditators (n = 22) in four conditions: rest, FAM, OMM, and LKM. GC was analyzed in the frequency domain for key cortical regions (frontal and parietal) in the two hemispheres to compare frequency-specific directed connectivity between rest and each meditation type. Main results demonstrated that each meditation state produced highly specific alterations in information transfer relative to rest. In FAM, there was significant reduction in posterior-to-anterior GC in the alpha and beta bands, and decreased multi-spectral inter-hemispheric frontal GC pointing to attenuated bottom-up sensory and associative inputs. In OMM, multi-spectral GC was significantly increased from the left hemisphere to the right posterior cortex implying expanded awareness in the right posterior regions through enhanced top-down modulation by the left-hemisphere. The distinctive features of LKM profile were the inter-hemispheric symmetry, the posterior-anterior bi-directionality, and the specific beta-band engagement, implying a co-activation of systems that support an emotionally balanced stance, equanimity and pro-social attitude. These novel findings demonstrate that the direction and frequency specificity of information flows provide complementary insights into neural processes underlying distinct meditative states.

Functional connectivity, structural connectivity, and inter-individual variability in Drosophila melanogaster
Clarifying the relationship between structure and function is important for understanding the brain. In Drosophila melanogaster, whole-brain and hemibrain electron microscopy connectome data, as well as whole-brain calcium imaging data are available. We applied pre-processing methods from fMRI to whole-brain calcium imaging data and comprehensively investigated the optimal parameters. Then, we found that the FC-SC (functional and structural connectivity) correlation decreased linearly with ROI count, and this trend was the same in flies and humans. We also developed a new, more robust method to quantify the degree of pre- and post-synaptic segregation and investigated this in the fly whole-brain. This revealed that many neurons have unsegregated synapses. We extracted highly unsegregated synapses and compared them with random-extracted null SC matrices. Their FC-SC correlation was significantly higher, indicating that these synapses contribute to FC well. Conversely, highly segregated-synapses showed significantly lower FC-SC correlation and contribute less to FC. Therefore, neurons with unsegregated synapses like non-spiking neurons are spread throughout the whole brain, and they are thought to have a significant influence on FC.

Multiplexed BOLD oscillations reveal the interplay of normalization and attention
Monkey electrophysiology has linked attention to divisive normalization, yet noninvasive evidence in humans remains limited. We use frequency tagged fMRI to isolate visual cortical populations that simultaneously encode multiple competing inputs. We show that responses of these sites are suppressed during inattention and enhanced during attention, consistent with the normalization model, which predicts that attention selectively disinhibits competing inputs, offering a noninvasive translational bridge to study fine-grained computations underlying attentional selection.

Perceptual processing of tastes is performed by the amygdala-cortical loop
Reciprocal connectivity, which generates nonlinear dynamics within a system, should do the same in the taste circuit, which is rife with between-region feedback. Much evidence supports the existence of specific, characterizable within-region dynamics in taste processing, but scant attention has been paid to dynamic inter-region interactions in taste processing. To fill this gap, we apply investigate simultaneous recordings from rodent Gustatory Cortex (GC) and Basolateral Amygdala (BLA), testing specific hypotheses about reciprocal amygdala-cortical interactions. We find that initially GC and BLA responses are independent, but evolve into synchronous, zero-lag ensemble transitions (surprising given the long axons connecting the two regions) within a few hundred milliseconds of taste delivery. Spectral Granger Causality (which infers directional influences) revealed that this tight synchrony also characterizes the system's asymmetric inter-region influences wherein the BLA[->]GC influence is dominant prior to the generation of the behavioral response and the GC[->]BLA influence becomes strong at the time that GC has been shown to release a behavior-relevant signal. To better understand the function of single neurons in this process, we then used Poisson Generalized Linear Modeling to categorize GC neurons in terms of their inferred connectivity. This analysis revealed that GC neurons that both influence and receive influence from BLA - the neurons most deeply embedded in the reciprocal circuit - are the ones most strongly involved in taste processing (quantified as taste-specificity and palatability-relatedness). These results, which are consistent with findings in multiple systems and species, support the notion that taste processing is a function of the amygdala-cortical loop.

The difficulty in numerical computation impacts motor decisions in a Stop Signal task
The proper interpretation of environmental information is necessary for effective decision-making. The resulting cognitive burden may affect the entire process if interpretation is not instantaneous. In this study, we investigated how numerical distance (ND), a measure of cognitive demand in numerical comparisons, influences movement initiation and inhibition. To this end, 32 participants completed a novel numerical comparison Stop-Signal Task (NC-SST), in which the cognitive demand of each trial was manipulated by varying the ND between pairs of numbers in both Go and Stop signals. Participants were required to initiate or stop a movement if an upcoming number was higher or smaller than the one presented previously. Results showed that larger NDs (i.e., easier comparisons) facilitated faster and more accurate responses during movement initiation and enhanced stopping performance. Using a generalized drift-diffusion model, we found that drift rates increased with ND and were modulated by the spatial location of numerical stimuli, consistent with a left-to-right space number association. A generalized linear mixed-effects model further revealed that Go process parameters, particularly the drift rate, strongly predicted successful stopping and interacted with Stop ND and Stop signal delay (SSD). These findings demonstrate that higher cognitive load impairs both movement initiation and inhibition, and that motor decisions result from the integration of cognitive information onto perceptual features, extending the classical race model framework.

Brainwide blood volume reflects opposing neural populations
The supply of blood to brain tissue is thought to depend on the overall neural activity in that tissue, and this dependence is thought to differ across brain regions and across levels of arousal. Studies supporting these views, however, measured neural activity as a bulk quantity, and related it to blood supply following disparate events in different regions. Here we measure fluctuations in neuronal activity and blood volume associated with the same events across the mouse brain, and find that their relationship is consistent across brain regions but differs in two opposing brainwide neural populations. Functional Ultrasound Imaging (fUSI) revealed that whisking, a marker of arousal, is associated with brainwide fluctuations in blood volume. Simultaneous fUSI and Neuropixels recordings in cortex and hippocampus showed that neurons that increase vs. decrease activity with whisking have distinct hemodynamic response functions. Brainwide Neuropixels recordings revealed that these two opposing populations are present in the entire brain. When summed, their contributions predicted blood volume across brain regions better than predictions from bulk neural activity. The mouse brain thus contains two neural populations with opposite relation to brain state and distinct relationships to blood supply, which together account for brainwide fluctuations in blood volume.

CaMKII monomers are sufficient for GluN2B binding, co-condensation, and synaptic potentiation
Cognitive functions require synaptic plasticity, specifically long-term potentiation (LTP). LTP is thought to require CaMKII binding to the NMDA-type glutamate receptor subunit GluN2B, but this poses a major conundrum: Truncated CaMKII monomers (without the hub domain that forms 12meric holoenzymes) fail to bind GluN2B, but still potentiate synapses when made constitutively active. We hypothesized that CaMKII monomer binding to GluN2B has just eluded detection. Instead, even though full-length CaMKII monomers (with hub domain mutations) were found to indeed bind and even co-condensate with GluN2B, truncated monomers were not. Nonetheless, truncated monomers still potentiated synapses, even in neurons with GluN2B mutations that ablate CaMKII binding. However, potentiation occurred only with monomers that were made Ca2+-independent by artificial phosphatase-resistant thio-autophosphorylation, not by regular autophosphorylation of T286. These findings support that CaMKII binding to GluN2B is required during physiological LTP induction because it generates the phosphatase-resistant autonomous activity that mediates LTP expression.

AAV-mediated gene therapy for SLC13A5 citrate transporter disorder rescues epileptic and metabolic phenotypes
SLC13A5 citrate transporter disorder is a rare epileptic encephalopathy caused by loss of function pathogenic variants in the SLC13A5 gene. Loss of sodium/citrate cotransporter (NaCT) function causes a severe early life epilepsy resulting in life-long developmental disabilities and increased extracellular citrate. Current antiseizure medications may reduce seizure frequency, yet more targeted treatments are needed to address the epileptic and neurodevelopmental SLC13A5 phenotype. We performed preclinical studies in SLC13A5 deficient mice evaluating phenotype rescue with adeno-associated virus (AAV) vector carrying a functional copy of the human SLC13A5 gene (AAV9/SLC13A5). Cerebrospinal fluid-delivery of AAV9/SLC13A5 decreased extracellular citrate levels, normalized electrophysiologic and sleep architecture abnormalities, and restored resistance to chemically induced seizures and death. Treatment benefits were achieved with administration during early brain development and in young adult mice, supporting a broad therapeutic window for this disorder. Comparison of delivery routes in young adult KO mice showed that higher brain targeting achieved with intra-cisterna magna delivery resulted in greater treatment benefit as compared to intrathecal lumbar puncture delivery. Together, these results support further development of AAV9/SLC13A5 for treating SLC13A5 citrate transporter disorder.

Human induced pluripotent stem cell-derived microglia with a CX3CR1-V249I genetic variant exhibit dysfunctional phenotypes and modulate neuronal growth and function
The involvement of microglia in neurodegenerative diseases has drawn increasing attention, as many genetic risk factors are preferentially expressed in microglia. Microglial fractalkine receptor (CX3CR1) signaling regulates many key microglial functions, and the CX3CR1-V249I single nucleotide polymorphism has been associated with increased risk for multiple neurodegenerative conditions, including Alzheimer's disease, yet its functional consequences in human microglia remain unexplored. In this study, we generated iPSC-derived human microglia-like cells (hMGLs) and found that the CX3CR1-V249I variant increased susceptibility to starvation-induced cell death, reduced amyloid-beta uptake, altered microglial morphology, and impaired migration, with more pronounced effects in homozygous cells. Co-culture with neurons demonstrated that hMGLs with the CX3CR1-V249I variant misregulated neuronal properties, including abnormal neuronal growth as well as an induction of neuronal hyperexcitability. These findings highlight the critical role of CX3CR1 in regulating microglial function and implicate the V249I variant in driving pathogenic microglial states relevant to neurodegeneration.

Ensembles and engrams in mouse cortical and sub-thalamic brain regions supporting context and memory recall.
Associative learning supports learning about outcomes associated with contexts and cues. During learning, cellular ensembles that become active can be incorporated into a memory engram and later reactivated to support memory recall. Studies exploring engram formation and reactivation have primarily used contextual conditioning in mice and made little distinction between engrams encoding contextual information versus cue-associated learning and recall. Furthermore, often missing in such analyses is exploration of sex differences in engram profiles. Using auditory fear conditioning and activity-dependent tagging in mice, we set out to disaggregate context-associated engrams from those associated with learning and recall while also profiling potential sex differences. Specifically, we quantified cellular activity during context exposure, fear recall, extinction training, and extinction recall in cortical and subthalamic brain regions supporting learning and memory. We found that male mice had larger ensembles of cells active in the infralimbic prefrontal cortex (IL-PFC) during context exposure while female mice recalling a fear memory had a significantly greater proportion of cells that were active in the IL-PFC independent of context. Across sexes, we found greater reactivation of extinction engrams in the IL-PFC compared to contextual engrams. While we found ensembles and engrams in the prelimbic prefrontal cortex (PL-PFC) and zona incerta (ZI), no sex differences were noted in these regions. These results not only emphasize that there is a distinction to be made between ensembles and engrams encoding contextual information from those encoding cue-associated learning and recall, but also highlight sex differences in ensemble and engrams allocation.

Functional characterization of Ixodes neuropeptide receptors
Neuropeptidergic systems control feeding behaviors in animals, including arthropods. Given the wide variety of pathogens transmitted by ticks during hematophagy, there is an urgency to understand the neural mechanisms responsible for tick feeding behavior. We characterized three Ixodes signaling systems that are involved in feed-ing regulation in other arthropods: neuropeptide CCHamide (CCHa), short neuropeptide F (sNPF) and sulfakinin. RNAs encoding the preproneuropeptides and their re-ceptors were characterized and cDNAs for the receptors were expressed in HEK293T cells by transient transfection. Activation of the receptors by synthetic peptides was monitored by a calcium release (FLIPR) fluorescence assay. There was a single receptor (CCHaR) activated by CCHa (NH2-SCKMYGHSCLGGH-amide) containing a disulfide bond with an EC50=12 pM, while a scrambled cyclic peptide was inactive at 1 M. Of the two Ixodes NPY-like receptors, NPYLR1A was activated by sNPF (NH2-GGRSPSLRLRF-amide) with an EC50=1.9 nM. NPYLR1B did not respond to 10 M sNPF. A single sulfakinin receptor was activated by a sulfated sulfakinin (NH2-SDDY(SO3H)GHMRF-amide) with an EC50=220 pM but not by 1 M non-sulfated sulfakinin. The Ixodes GPCRs were able to couple to endogenous HEK293T G-protein(s). Surprisingly, human but not Ixodes GNAQ restored CCHaR responsiveness in HEK293T cells with GNAQ/GNA12 disruptions. Quantitative RT-PCR analysis indicated that all three receptors were expressed in the synganglion. CCHaR/CCHa were found at high levels in the midgut from unfed ticks, and CCHaR expression in the mid-gut was confirmed by RNAScope in situ hybridization. These results establish ligand-receptor identities for three central neuropeptide systems in Ixodes and set the stage for structure-function and physiological investigations.

Wnt-3a exacerbates production of TNF-α in LPS stimulated microglia independent of the β-catenin canonical pathway
Background: Neuroinflammatory pathways are emerging therapeutic targets for neurological conditions such as Parkinson's disease (PD). Studies have indicated Wnt-3a, a member of the wingless type MMTV integration (Wnt) signalling cascade, may exert anti-inflammatory effects via canonical pathway activation and {beta}-catenin stabilisation. Furthermore, dysregulation of the Wnt/{beta}-catenin pathway has been implicated in the degeneration of dopamine neurons in PD, however, stimulation of the canonical pathway via application of Wnt-3a to protect against inflammation and dopaminergic degeneration has not been explored. Methods: Primary microglial cultures were stimulated with lipopolysaccharide (LPS) for 24 hours with or without Wnt-3a. TNF- levels were measured via ELISA while changes in NF{kappa}B inflammatory pathway proteins and phosphorylated and non-phosphorylated {beta}-catenin were analysed via capillary western blot. To assess Wnt pathway involvement, cultures were treated with DKK1 ({beta}-catenin canonical pathway inhibitor), SP600125 (Wnt/Pcp pathway inhibitor) or U73122 (Wnt/Ca2+ pathway inhibitor). Finally, C57BL/6 mice received continuous intracerebroventricular infusion of Wnt-3a via osmotic pumps to investigate the effects of Wnt-3a on dopaminergic neuron survival and on microglial numbers in the MPTP model of PD. Results: Wnt-3a alone had no effect on TNF- release from microglia. However, when co-administered with LPS, there was a significant increase in cytokine release beyond that seen with LPS alone. Protein analysis revealed that this exacerbation in TNF- levels was not due to alterations in the NF{kappa}B pathway or differences in activation of {beta}-catenin. Furthermore, DKK1 treated cells showed no changes in TNF-, however both SP600125 and U723122 were able to block Wnt-3a + LPS induced TNF- release, implicating the non-canonical pathways. Meanwhile Wnt-3a in vivo did not alter dopaminergic or microglial populations in the substantia nigra in MPTP lesioned animals. Conclusion: Together, these results suggest a pro-inflammatory response to Wnt-3a in an inflammatory context with little or no effect on resting microglia. Importantly, this outcome was independent of the {beta}-catenin canonical pathway, revealing that Wnt-3a can increase pro-inflammatory TNF- release via non-canonical signaling in an inflammatory environment. This demonstrates the importance of cellular context when identifying potential therapies for neurodegenerative diseases where neuroinflammation is a critical mediator of pathology.

Neural variability structure in primary visual cortex is optimal for robust representation of visual similarity
How different neuronal populations construct a robust representation of the sensory world despite neural variability is a mystery. We found that neural variability in mouse primary visual cortex observe a simple rule: For a given sensory stimulus, the mean and the variance of spike counts follow a linear relationship across neurons. To understand how this neural variability structure affects the sensory representation, we artificially varied the slope of the log-mean and log-variance relationship. We found that the intrinsic structure of neural variability allows representations of distinct sensory information to be continuous while minimizing overlap, enabling the neural code to be roust while still being efficient. Further, representational similarity was maximally consistent between different sets of neurons at slope 1, both within and across mice. Thus, the neural variability structure may enable the neocortex to build robust representations of the sensory world, both within and across individuals.

Anticipatory modulation as a unifying principle of sensory coding during locomotion
Locomotion modulates the activity of sensory systems in multiple ways: from gain changes in individual neurons to changing interactions in neural populations. These effects are not universal; while movement has a strong influence on sensory coding in rodents, its impact on primates is less prominent. The diversity of effects that locomotion exerts on sensory neurons, as well as disparities between species, raises questions about the existence of universal principles that may underlie sensation during behavior. We propose that sensory systems are modulated in anticipation of systematic changes in stimulus statistics caused by locomotion to maintain an accurate and efficient sensory code across behavioral states. Model neurons optimized to encode stimuli recorded during movement in natural environments predict and reproduce a broad spectrum of experimental observations. The proposed, simple principle of anticipatory modulation reconciles the diversity of ways in which locomotion modulates visual coding in different animal species.

High frequency electrical stimulation entrains fast spiking interneurons and bidirectionally modulates information processing
Background: Clinical intracranial electrical stimulation often deploys trains of high frequency pulses. While brief bursts of stimulation are known to heterogeneously modulate neuronal spiking, it is unclear how trains of high frequency pulses influence neural dynamics. Objective: As fast spiking interneurons (FSIs) can support rapid firing, we seek to determine how high frequency stimulation modulates FSIs. Methods: We characterized the real-time effect of one-second-long local stimulation at 40 versus 140 Hz on parvalbumin positive interneurons, known as FSIs, in motor and visual cortices in awake mice using near kilohertz voltage imaging, free of electrical stimulation artifact. Results: Stimulation at 140 Hz, like 40 Hz, heterogeneously modulates individual FSIs membrane voltage in both cortices, leading to complex temporal dynamics. FSIs in both cortices are robustly entrained by 40 Hz stimulation, even though 40 Hz led to prominent membrane hyperpolarization in visual cortex but not motor cortex. Intriguingly, visual cortical FSIs, but not motor cortical ones, were reliably entrained by 140 Hz stimulation. Finally, while stimulation consistently reduced the response amplitude of visual cortical FSIs to visual flickers, response temporal precision is bidirectionally modulated. Conclusion: High frequency electrical stimulation mediates brain-region specific entrainment of FSIs, and bidirectionally modulates FSI temporal processing of synaptic inputs. Thus, high frequency stimulation can differentially engage inhibitory neurons in different brain regions to modulate network information processing.

Developmental, time-of-day, and stimulus-specific Golgi-Cox staining patterns detected in the mouse brain
Well-coordinated brain activity is a crucial driver of bodily functions and is refined by environmental input. Understanding the structure of brain areas that regulate various functions and how the environment affects the neural responses in the brain has been fundamental in advancing the field of neuroscience and medicine. The Golgi-Cox method is a histological approach that has allowed researchers to view neuronal structures with unmatched and detailed resolution, allowing for the comparison between non-diseased and diseased models, for instance. However, this method is known to stain neurons sparsely, which is useful for distinguishing structural components, but unpredictably, which is difficult for reproducibility and targeted studies. Here, we use three approaches to demonstrate a predictable pattern of cell staining using the Golgi-Cox method. We show that neuronal maturity, time of day, and response to environmental stimuli affect the number of cells stained by the Golgi-Cox method. Furthermore, we found low variability within each experimental group, which indicates staining reproducibility under controlled environments. Our study highlights important parameters for using the Golgi-Cox method and demonstrates its feasibility for broader application in answering neuroscience-based questions.

In pursuit of saccade awareness: Limited control and minimal conscious access to catch-up saccades during smooth pursuit eye movements.
Observers use smooth pursuit to track moving objects--like koi carp gliding through a pond. When positional errors accumulate, rapid catch-up saccades correct for them. Despite their abruptness, these saccades usually go unnoticed, creating the seamless experience of smooth tracking. We conducted three experiments to examine awareness and control of catch-up saccades (Experiment 1), the effect of training (Experiment 2), and of movement intention (Experiment 3). All experiments followed a similar protocol. On each trial, a target moved horizontally at one of three constant speeds (3-12 dva/s). Two horizontal stimulus bands with vertically oriented gratings appeared above and below the trajectory. These bands were rendered invisible during pursuit by rapid phase shifts (>60 Hz), but became visible when briefly stabilized on the retina--either by a catch-up saccade or its replayed retinal consequence--providing immediate, saccade-contingent visual feedback. Observers reported whether they had seen the stimulus bands (visual sensitivity) and whether they were aware of making a catch-up saccade (saccade sensitivity). Visual sensitivity was consistently higher in trials with a catch-up saccade, confirming that these movements reduce retinal motion and enhance visibility. Higher target speeds increased saccade rate, but observers struggled to control them consciously: Visual feedback and training had no effect on the ability to control catch-up saccades. Only suppression-instructions yielded a small reduction. Saccade sensitivity was near zero, even in trials with saccade-contingent feedback. Neither training nor intention improved awareness. Together, our data suggest a limited ability to control and a low level of sensorimotor awareness of catch-up saccades during pursuit.

The chloride cotransporter NKCC1 regulates self-renewal of hippocampal neural stem cells via the transcription factor Sox11
The GABAergic-mediated depolarization plays a key role in controlling stem cell fate and neurogenesis within the dentate gyrus of the hippocampal formation. This depolarization effect is highly dependent on the balance between the chloride co-transporters NKCC1 and KCC2. It is not known how changes in NKCC1 modulate the fate of Nestin-positive stem cells (NSCs) in the hippocampus during adult neurogenesis. In our study, we demonstrate that a knockout of Nkcc1 in NSCs increase their proliferation by symmetric self-renewal and expand the stem cell pool. Using single-cell RNA sequencing, we identified Sox11 as a key transcription factor that is significantly downregulated following Nkcc1 knockout. In agreement with this finding, we found that Sox11 knockout enhances proliferation and self-renewal of NSCs, which is also marked by an increase in symmetric stem cell division. Based on these findings, we propose that altering Nkcc1 expression in NSCs shifts their fate from neurogenesis towards self-renewal via Sox11 regulation. Furthermore, we observed that NKCC1 levels decline in NSCs during aging, which correlates with a further increase in self-renewal. Our data strongly suggest that the age-related decline in NKCC1 levels promote symmetric division and self-renewal contributing to the age-dependent decrease in neurogenesis. NKCC1 via Sox11 is a key regulator of NSCs fate decision, critically balancing self-renewal and neuronal differentiation in the adult hippocampus.

Feature Misbinding Underlying Serial-Order Effects of Visuospatial Working Memory
The accurate processing of incoming visual information in serial order is fundamental to visual cognition. Prior studies have demonstrated primacy and recency effects in tasks requiring the serial recall of visual stimuli such as letters, digits, words, or locations. However, there is still ongoing debate about whether these primacy/recency effects on working memory retrieval reflect variable representational precision for multiple items in memory or misbinding of item features (e.g., location) and their ordinal position. This study sought to examine potential sources contributing to serial-position effects in visuospatial working memory using eye tracking and statistical modeling approaches. In two eye-tracking experiments, we measured the latency and endpoint error of serial-order memory-guided saccades under varying cue conditions (order cue vs. quadrant cue) from a total of 92 participants. The first memory-guided saccade (MGS) showed primacy and recency effects on endpoint error, latency, and transposition error in the order cue condition but not in the quadrant cue condition. Probabilistic modeling of MGS distribution showed a better fit of a standard (non-swapping) model to the quadrant-cue condition and a swap model to the order-cue condition. These findings indicate that visuospatial working memory representation varies across serial positions primarily due to location-serial-position misbinding rather than variable memory precision about location.

Stress-induced plasminogen activator inhibitor-1 (PAI-1) as a blood biomarker and brain risk factor for PTSD
Post-traumatic stress disorder (PTSD) is a severe stress-related psychiatric condition triggered by traumatic life-threatening events, characterized notably by an altered memory profile. Although clinically well-documented, no specific biomarker exists. This translational study identifies plasminogen activator inhibitor-1 (PAI-1) as a brain risk factor for PTSD, thereby supporting its potential as a blood-derived biomarker. Mice with genetically ablated PAI-1 were protected from developing a PTSD-like memory profile. Conversely, mice exhibiting PTSD-like cognitive impairment showed increased blood PAI-1 levels, correlating with their profile severity. In the brain, PAI-1 levels were specifically increased in the dorsal hippocampus, a key region for cognitive functions and in the etiology of PTSD. Finally, a longitudinal study of soldiers revealed that those developing PTSD symptoms exhibit rising blood PAI-1 levels over a 12-month period. Its significant association with various indicators of PTSD-related psychological distress attests to PAI-1's potential as a blood biomarker and brain therapeutic target for PTSD.

Complementary Structural and Chemical Biology Methods Reveal the Basis for Selective Radioligand Binding to α-Synuclein in MSA Tissue
Fibrillar aggregation of alpha-synuclein (aSyn) is a hallmark of Parkinson's disease (PD) and related disorders, including multiple system atrophy (MSA) and dementia with Lewy bodies (DLB). Despite advances in aSyn fibril structural characterization, the relevance of in vitro and ex vivo structures to patient aggregates remains unclear, particularly for developing therapeutic or diagnostic molecules. Cryo-electron microscopy (cryo-EM) studies of aSyn fibrils with ligands often reveal binding at multiple sites, likely due to high ligand concentrations. Here, various structural and chemical biology techniques were used to characterize aSyn fibrils in the presence of EX-6, a candidate ligand for positron emission tomography (PET) imaging of synucleinopathies. Transmission electron microscopy (TEM) and cryo-EM revealed no significant fibril core changes upon binding. Forster resonance energy transfer (FRET) further demonstrated that the disordered C-terminus was unaltered. Cryo-EM and crosslinking mass spectrometry (XL-MS) identified consistent binding sites, with one (Site 2*) providing a well-defined pocket for high-resolution analysis. Site 2* showed similar residue positioning in MSA patient-derived structures, suggesting MSA selectivity. [3H]-EX-6 binding assays demonstrated a 10-fold preference for MSA over PD tissue, with autoradiography further confirming MSA selectivity. Taken together, the combined use of structural and chemical biology techniques provides a comprehensive understanding of EX-6 binding that would not be possible with any single method. Optimization of ligand-protein and ligand-ligand interactions observed in the cryo-EM structure will enable the development of EX-6 as a PET imaging probe for MSA.

Perception of first and second pain during offset analgesia
Introduction: Offset analgesia (OA) is defined as a disproportionate reduction in pain perception following a small decrease in noxious stimulation. However, the mechanisms underlying this phenomenon remain unclear, with ongoing debate on peripheral versus central contributions. Objectives: This experimental study aimed to differentiate first and second pain perception during the OA paradigm, thereby assessing fiber-specific influences on OA. Methods: Thirty-two healthy participants were asked to distinguish a double pain sensation (first and second pain), to assess pain quality descriptors related to A-delta; and C-fibers, and to indicate response times to brief noxious heat stimuli. This procedure was repeated while implementing heat pulses in an OA paradigm. Results: No significant differences were found between offset and constant trials in the reported double pain sensation or the fiber specific pain descriptors (p > 0.05). Nevertheless, significant differences in response times were observed depending on the type of trial and the timing of the stimulus. Response time to noxious stimuli was delayed after prolonged stimulation in both offset and constant trials (p < 0.05). Conclusions: The findings suggest that A-delta and C-fiber response characteristics were unaffected during the OA paradigm; however, higher stimulation intensities or prolonged pain induce a notable response delay. This indicates a negligible role of specific peripheral nerve fibers in OA, emphasizing the predominance of central mechanisms, particularly those related to attention and cognitive resources, which merit further investigation.

Hypermyelination Improves Strength and Detection of Neuronal Activity in the CA1 Hippocampus and Facilitates Neuroprotection in FusOLcKO Mice
Loss of oligodendrocytes (OLs) and myelin impairs cortical neuronal firing and network stability, whereas enhancement of oligodendrogenesis improves electrophysiological stability in cortex and, to a lesser extent, hippocampus. OLs exhibit regional heterogeneity, especially in their ability to synthesize cholesterol, a critical driver of myelin wrapping and ensheathment of axons. Conditional depletion of the Fused in sarcoma (Fus) gene in OLs, referred to as FusOLcKO, increases cholesterol biosynthesis, myelin thickness, and tissue cholesterol content. We examine whether this hypermyelination alters extracellular recordings across the layers of visual cortex and the underlying hippocampal CA1 over 16 weeks. In FusOLcKO mice, visually-evoked single-unit detectability and firing rate in CA1 increased relative to wild-type littermates, whereas cortical recordings showed no improvement. At the population level, FusOLcKO cortex exhibited reduced firing rates and lower functional connectivity, indicating altered network dynamics. Post-mortem histology revealed higher neuron density in recorded cortex and greater excitatory synapse density in CA1 of FusOLcKO mice suggesting region-specific neuroprotection and synaptic strengthening. These results demonstrate that cholesterol-driven hypermyelination enhances chronic hippocampal recordings while disrupting cortical network communication. Our study highlights myelin s region-dependent roles in supporting single-cell reliability, tuning population dynamics, and maintaining circuit integrity under chronic perturbation.

Denoising 7T Structural MRI with Conditional Generative Diffusion Models
7T MRI offers ultra-high resolution and improved sensitivity for iron deposition in neurodegenerative disorders, but commonly used acquisitions are long and hence challenging, especially for elderly subjects. Efficiently denoising a short acquisition to achieve the image quality of a longer acquisition would be of translational benefit. We introduce a conditional diffusion model derived from generative AI (a 7T Conditional Diffusion Model, 7TCDM) that was trained on native single-acquisition 2D reconstructions and referenced multi-repetition images to guide the denoising process and improve SNR and contrast. 7TCDM model was tested on 2D T2-weighted gradient-echo imaging from 19 participants, including healthy controls and individuals with mild cognitive impairment or Alzheimer's disease (AD). 7TCDM's performance was assessed using Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and comprehensive reader studies. Referencing the multi-repetition ground truth, 7TCDM improved the single-acquisition original image by 29.1% in MSE, 5.8% in PSNR, and 9.4% in SSIM, and outperformed convolutional neural network-based models in all metrics. Expert rater evaluations confirmed superior image quality, with significantly enhanced detail and contrast preservation in regions such as the hippocampi, white matter lesions, and small cortical veins. The model also demonstrated robust performance in both the concurrently acquired and publicly available 3D multi-echo gradient echo acquisitions, which the model was not trained on. The 7T Conditional Diffusion Model provides high-quality denoised images from shorter scans, increasing the feasibility of scanning patients in shorter times while preserving essential anatomical and pathological details.

Motor Planning Sensitivity to Affective Looming Sounds Within The Peri-personal Space: An Interplay of Exogenous and Endogenous Influences
Our brain maps the space immediately surrounding the body, the peripersonal space (PPS), to sharpen sensory-motor coordination whenever an object enters it. Within PPS, past research demonstrated how several factors influence motor readiness: from exogenous factors, such as body-object distance and stimulus semantics, to endogenous traits like personality traits. Nevertheless, most paradigms rely on vision or touch, relegating hearing to a supporting role and leaving auditory-only contributions unclear. Here, we tested whether affective content and individual traits modulate motor planning for looming sounds that stop within PPS. Thirty-three adults completed three auditory-only tasks in which positive, negative, or neutral sounds halted at five simulated distances from the participant's ears (0.3-0.7 m). We recorded anticipatory postural adjustments, distance estimates, affective ratings, and sensory suggestibility via a questionnaire. Motor responses were largely anticipated as sounds stopped nearer the body, while delayed and less precise for semantic (positive or negative) than neutral sounds. Higher suggestibility predicted longer and more variable premotor latencies, particularly for non-semantic sounds. These findings show that auditory cues alone engage flexible sensorimotor mechanisms within PPS, where exogenous (distance, semantics) and endogenous (suggestibility) factors jointly shape motor readiness and spatial perception.

Attention robustly dissociates objective performance and subjective visibility reports
Attention generally enhances both visual performance and subjective appearance. Yet, at matched performance, unattended items can appear more visible than attended ones, a phenomenon called "subjective inflation." Inflation, however, has only been narrowly tested near detection thresholds, making it unclear whether attention regularly dissociates objective and subjective aspects of perception with broad implications for everyday vision--where attention is usually unevenly distributed--and for studies of consciousness. Here, in four experiments, we tested inattentional inflation over varied stimulus and task conditions, spanning threshold to suprathreshold regimes. Using a new analytic approach to relate objective and subjective reports over full psychometric functions, we measured subjective inflation over wide ranges of matched performance. In all experiments, inattention inflated subjective stimulus visibility. But when subjective reports specified visibility of the task-relevant feature, we only found evidence for inflation at threshold. Thus, what we think we see may regularly dissociate from what we can visually discriminate.

Reading specific memories from human neurons before and after sleep
The ability to retrieve a single episode encountered just once is a hallmark of human intelligence and episodic memory [1]. Yet, decoding a specific memory from neuronal activity in the human brain remains a formidable challenge. Here, we develop a transformer neural network model [2, 3] trained on neuronal spikes from intracranial microelectrodes recorded during a single viewing of an audiovisual episode. Combining spikes throughout the brain via cross-channel attention [4], capable of discovering neural patterns spread across brain regions and timescales, individual participant models predict memory retrieval of specific concepts such as persons or places. Brain regions differentially contribute to memory decoding before and after sleep. Models trained using only medial temporal lobe (MTL) spikes significantly decode concepts before but not after sleep, while models trained using only frontal cortex (FC) spikes decode concepts after but not before sleep. These findings suggest a system-wide distribution of information across neural populations that transforms over wake/sleep cycles [5]. Such decoding of internally generated memories suggests a path towards brain-computer interfaces to treat episodic memory disorders through enhancement or muting of specific memories.

Converting Spectral Evoked-to-Background Ratio intoTime-Domain Signal-to-Noise Ratio - Validation for HighFrequency Oscillations
N-Interval Fourier Transform Analysis (N-FTA) allows for spectral separation of an evoked target signal from uncorrelated background activity. It computes the frequencydependent evoked-to-background ratio (EBR). The developed method allows for conversion of the spectral EBR into expected values for improvement of signal-to-noise ratio with progressing sweep count. Our study presents the mathematical basis for this conversion along with a validation for simulated and recorded data. The major findings are: Three factors enter the calculus of the expected SNR: the ratio of durations of the single sweep cycle and the evoked response window, the mean EBR in the spectral target band, and the sweep count. By conversion of all factors to dB, the expected SNR is defined by their sum. The two fundamental theories governing the improvement of SNR with increasing sweep count, the law of large numbers and the uncertainty principle of signal processing, deliver identical results. Conversion of EBR to expected SNR was successfully validated by simulated and recorded data and can be applied to all types of evoked data.

FREQ-NESS reveals age-related differences in frequency-resolved brain networks during auditory recognition and resting state
Understanding how brain networks operate across different frequencies during cognitive tasks, and how these dynamics change with age, remains a central challenge in cognitive neuroscience. While previous studies have focused on resting-state activity and passive listening, less is known about frequency-specific brain dynamics during event-related tasks that require active memory engagement. In this study, we extend the recently developed FREQ-NESS analytical pipeline by adapting it to event-related task and resting state source-reconstructed magnetoencephalography (MEG) data from 70 healthy participants. This method quantified the variance explained by frequency-specific brain networks, their spatial organization, and associated time-resolved power estimates. We found significant effects of age, condition, and their interaction in the variance explained by leading components at 1.07 Hz, 2.86 Hz, and 10.00 Hz. Younger adults exhibited stronger peaks at 1.07 and 2.86 Hz during the task and a more pronounced 10.00 Hz peak at rest, whereas older adults showed the opposite pattern. Time-frequency analysis revealed age- and condition-dependent desynchronization in the alpha and beta bands (7.10-22.90 Hz). These findings demonstrate the effectiveness of the adapted FREQ-NESS pipeline for event-related tasks and highlight the importance of frequency-resolved network analysis for characterizing age-related changes in active auditory memory processing.

The role of feedback for sensorimotor decisions under risk
For goal-directed movements like throwing darts or shooting a soccer penalty, the optimal location to aim depends on the endpoint variability of an individual. Currently, there is no consensus whether people can optimize their movement planning based on information about their motor variability. Here, we tested the role of different types of feedback for movement planning under risk. We measured saccades towards a bar that consisted of a reward and a penalty region. Participants either received error-based feedback about their endpoint or reinforcement feedback about the resulting reward. We additionally manipulated the feedback schedule to assess the role of feedback frequency and whether feedback focusses on individual trials or a group of trials. Participants with trial-by-trial reinforcement feedback performed best and had the least endpoint deviation from optimality. Our results are consistent with a slow gradual drift in the participants' internal aiming location under summary feedback. Feedback focusing on individual trials reduces this drift, thereby enabling consistent movement planning from one trial to the next. Our results therefore suggest that reinforcement feedback about a single movement is most effective to optimize movement planning under risk.

Methodological determinants of signal quality in electrobulbogram recordings
The electrobulbogram (EBG) is a new, non-invasive method for measuring the functional activity of the human olfactory bulb (OB). To date, the EBG has been used to assess how the OB process odor identity, valence, intensity, and it has shown promise as an early biomarker for Parkinson's disease. However, current implementation of the EBG method depends on several methodological components, including subject specific co-registration of electrode positions through neuronavigation and EEG source reconstruction, which may limit accessibility for many research groups. In this study, we test the quality and reliability of the OB signal under different configurations to potentially remedy this. Specifically, we compare six EBG setups that vary in the use of subject-specific T1 scans versus a template head model, co-registered versus template electrode positions, and individualized versus template-based OB location. Our results indicate that strongest EBG signals are obtained when using subject-specific T1 scans in combination with co-registered electrode positions. However, we obtained significant EBG activity even when using a fully template-based configuration. Our anatomical analysis of OB location of 941 individuals reveals that in 86% of cases, the OB is centered within the spatial resolution bounds of the EEG source dipole, supporting the feasibility of detecting olfactory bulb signals without precise individual anatomical mapping using template coordinates. These findings suggest that while subject-specific configurations enhance signal quality, the EBG method remains robust enough to yield meaningful results even with less complex setups. This enables a broader adoption of the EBG method in both clinical and research settings.

WaveLimit: An optimal spike sorting inclusion boundary
Spike sorting is the process of assigning neuronal action potentials to individual putative neurons based on extracellular recordings. Spike sorting may be partitioned into five major components: i) raw neural data is filtered, ii) spiking events are extracted as waveforms, iii) features are extracted from the waveforms, iv) clusters of waveforms are defined, and v) individual waveforms are assigned to their respective clusters. Here, we focus on the often underappreciated fifth component, deriving a useful principle to define a cluster boundary to maximize the theoretical information available from a single neuron. We implemented this boundary, along with an automatic cluster identifier, in a novel spike sorting algorithm, WaveLimit. We then compared WaveLimit to three state-of-the-art spike sorters. WaveLimit identified either the same or more units and included more spiking events per unit than the other sorters. WaveLimit also found units with fewer inter-spike interval violations and higher signal-to-noise ratios. Thus, better defining the cluster boundary improved spike sorting.