bioRxiv Subject Collection: Neuroscience's Journal

Age-related increases in PDE11A4 protein expression trigger liquid:liquid phase separation (LLPS) of the enzyme that can be reversed by PDE11A4 small molecules inhibitors
PDE11A is a little-studied phosphodiesterase sub-family that breaks down cAMP/cGMP, with the PDE11A4 isoform being enriched in the memory-related brain region called the hippocampus. Age-related increases in PDE11A expression occur in human and rodent hippocampus and cause age-related cognitive decline of social memories. Interestingly, the age-related increase in PDE11A4 protein ectopically accumulates in spherical clusters that group together in the brain to form linear filamentous patterns termed ghost axons. The biophysical/physiochemical mechanisms underlying this age-related clustering of PDE11A4 are not yet known. As such, we determine here if age-related clustering of PDE11A4 may reflect liquid:liquid phase separation (LLPS), and if PDE11A inhibitors being developed for age-related cognitive decline can reverse this biomolecular condensation. We found that human and mouse PDE11A4 exhibit several LLPS-promoting sequence features including intrinsically disordered regions, non-covalent pi-pi interactions, and prion-like domains, with multiple bioinformatic tools predicting PDE11A4 undergoes LLPS. Consistent with these predictions, age-related PDE11A4 clusters were non-membrane bound spherical droplets that progressively fuse over time in a concentration-dependent manner. 5 different PDE11 inhibitors (tadalafil, BC11-38, SMQ-02-57, SMQ-03-30 and SMQ-03-20) across 3 scaffolds reversed PDE11A4 LLPS (a.k.a. remixing) in hippocampal HT22 cells, with PDE11A4 droplets reforming (a.k.a. de-mixing) following a 5-hour washout of low but not high concentrations of these compounds. Strikingly, a single oral administration of 30 mg/kg SMQ-03-20 substantially reduced the presence of PDE11A4 ghost axon in the aged mouse brain. Thus, PDE11A4 exhibits 4 defining criteria of LLPS, and PDE11A small molecule inhibitors reverse this age-related phenotype both in vitro and in vivo.

Computational Modeling of Proactive, Reactive, and Attentional Dynamics in Cognitive Control
We developed a novel Proactive Reactive and Attentional Dynamics (PRAD) computational model designed to dissect the latent mechanisms of inhibitory control in human cognition. Leveraging data from over 7,500 participants in the NIH Adolescent Brain Cognitive Development study, we demonstrate that PRAD surpasses traditional models by integrating proactive, reactive, and attentional components of inhibitory control. Employing a hierarchical Bayesian framework, PRAD offers a granular view of the dynamics underpinning action execution and inhibition, provides debiased estimates of stop-signal reaction times, and elucidates individual and temporal variability in cognitive control processes. Our findings reveal significant intra-individual variability, challenging conventional assumptions of random variability across trials. By addressing nonergodicity and systematically accounting for the multi-componential nature of cognitive control, PRAD advances our understanding of the cognitive mechanisms driving individual differences in cognitive control and provides a sophisticated computational framework for dissecting dynamic cognitive processes across diverse populations.

Generalizable gesture recognition usingmagnetomyography
The progression of human-computer interfaces into immersive and touchless realities requires new ways of interacting with machines that are correspondingly intuitive and seamless. Among these are gesture-based systems that use natural hand movements to interact with and control digital devices. Today, these systems are most commonly implemented through the use of cameras or inertial sensors, which have drawbacks in environments that are poorly lit, in conditions where the hands are obscured, or for applications that require fine motor control. More recent studies have advocated for the use of surface electromyography (sEMG) to capture gesture information by sensing electrical activity generated by muscle contraction. While promising demonstrations have been shown, studies have also outlined limitations in sEMG when it comes to generalization across a population, largely due to physiological differences between individuals. Magnetomyography (MMG) is an alternative modality for measuring the same motor signals at the muscle, but is impervious to distortions caused by tissue, hair, and moisture; this indicates potential for lower variability caused by physiological differences and changes in skin conductivity, making MMG a promising generalizable solution for gesture control. To test this theory, we developed wristbands with magnetic sensors and implemented a signal processing pipeline for gesture classification. Using this system, we measured MMG across 30 participants performing a gesture task consisting of nine discrete gestures. We demonstrate average single-participant classification accuracy of 95.4%, rivaling state-of-the-art accuracy with sEMG. In addition, we achieved higher cross-session and cross-participant accuracy compared to sEMG studies. Given that these results were obtained with a non-ideal recording system, we anticipate significantly better results with better sensors. Together, these findings suggest that MMG can provide higher performance for control systems based on gesture recognition by overcoming limitations of existing techniques.

Spatiotemporal patterns of theta-band activity during rapid-eye movement sleep: a magnetoencephalography analysis
Theta oscillations (4-8 Hz) in frontal cortical regions are present to different degrees across states of consciousness. In sleep, theta is prominent in periods of rapid eye-movement (REM) sleep. Theta has been linked to processes of memory consolidation; however, its mechanistic contribution specifically during REM sleep is not well understood. Interestingly, in the wake state, frontal theta activity increases during effortful cognitive tasks involving executive functions such as working memory, hinting at similarities in circuitry, and potentially, function. The aim of the present work is to create a spatially resolved, whole-brain characterisation of REM oscillatory activity in healthy human subjects, distinguishing theta from neighbouring frequency bands, differentiating substages of REM sleep (phasic and tonic REM), and comparing REM theta to that which is evoked during a working memory task. To that end, we analysed magneto- and electroencephalography (M/EEG) data recorded during overnight sleep in 10 healthy subjects, and similar data from 17 healthy subjects who performed a working memory task, using a novel whole-brain, source-localised MEG approach. Our results show that (i) theta activity has a frontal midline topography that is distinct from those of other prominent frequency bands in REM (delta, alpha, beta), (ii) theta activity in frontal midline regions is best observed within a focused 5-7 Hz range, separating it from occipital alpha activity, (iii) REM theta is dominant over the frontal midline but is also observed in several sub-cortical areas, (iv) theta is more widespread in tonic than phasic REM sleep, and (v) the focused frontal midline theta pattern observed in REM phasic sleep is the most similar of all observed sleep substages to theta evoked by a working memory task. These results enhance our understanding of theta physiology in REM sleep and suggest future targets for research into REM's role in learning and memory.

Attenuated ectopic action potential firing in parvalbumin expressing interneurons in a mouse model of Dravet Syndrome
Dravet syndrome is caused by heterozygous loss-of-function variants in SCN1A, which encodes the voltage-gated sodium channel Nav1.1. Our recent work suggests that a primary pathogenic mechanism of Dravet syndrome is impaired action potential propagation along axons of cortical parvalbumin-positive fast-spiking GABAergic interneurons (PVINs). Ectopic action potentials (EAPs) are action potentials that initiate distal to the axon initial segment. We recently demonstrated that a large proportion of PVINs fire EAPs during periods of increased excitation. Although their function remains unknown, EAPs may play a role in amplifying (when occurring in excitatory cells) and/or preventing seizures (when occurring in interneurons). Regardless of function, their generation in distal axons suggests that EAP frequency could be a useful proxy for distal axonal excitability. We hypothesized that EAPs are attenuated in PVINs from Dravet syndrome (Scn1a+/-) mice due to dysfunction of the distal axon. We induced EAPs in PVINs in acute brain slices prepared from male and female wildtype (WT) and Scn1a+/- mice at P18-21 and P35-56, when we have previously identified axonal conduction deficits in Scn1a+/- PVINs. We elicited EAPs in 17/22 (77%) of WT PVINs, including 6 (22%) that exhibited barrages of EAPs. In contrast, Scn1a+/- PVINs never fired barrages (0%), and only 8/23 (34%) exhibited even single EAPs. This finding adds to the body of evidence supporting impaired action potential propagation in Dravet syndrome PVINs, and is the first evidence of impaired EAP firing in a disease model, suggesting that dysregulation of EAPs could be involved in the pathophysiology of human disease.

Mapping grey and white matter activity in the human brain with isotropic ADC-fMRI
Functional MRI (fMRI) using the blood-oxygen level dependent (BOLD) signal provides valuable insight into grey matter activity. However, uncertainty surrounds the white matter BOLD signal. Apparent diffusion coefficient (ADC) offers an alternative fMRI contrast sensitive to transient cellular deformations during neural activity, facilitating detection of both grey and white matter activity. Further, through minimising vascular contamination, ADC-fMRI has the potential to overcome the limited temporal specificity of the BOLD signal. However, the use of linear diffusion encoding introduces sensitivity to fibre directionality, while averaging over multiple directions comes at great cost to temporal resolution. In this study, we used spherical b-tensor encoding to impart diffusion sensitisation in all directions per shot, providing an ADC-fMRI contrast capable of detecting activity independently of fibre directionality. We provide evidence from two task-based experiments on a clinical scanner that isotropic ADC-fMRI is more temporally specific than BOLD-fMRI, and offers more balanced mapping of grey and white matter activity. We further demonstrate that isotropic ADC-fMRI detects white matter activity independently of fibre direction, while linear ADC-fMRI preferentially detects activity in voxels containing fibres perpendicular to the diffusion encoding direction. Thus, isotropic ADC-fMRI opens avenues for investigation into whole-brain grey and white matter functional connectivity.

STARTS: A self-adapted spatio-temporal framework for automatic E/MEG source imaging
To obtain accurate brain source activities, the highly ill posed source imaging of electro and magneto encephalography (E/MEG) requires proficiency in incorporation of biophysiological constraints and signalprocessing techniques. Here, we propose a spatiotemporal-constrainted E/MEG source imaging framework-STARTS that can reconstruct the source in a fully automatic way. Specifically, a block diagonal covariance was adopted to reconstruct the source extents while maintain spatial homogeneity. Temporal basis functions (TBFs) of both sources and noises were estimated and updated in a data-driven fashion to alleviate the influence of noises and further improve source localization accuracy. The performance of the proposed STARTS was quantitatively assessed through a series of simulation experiments,wherein superior results were obtained in comparison with the benchmark ESI algorithms (including LORETA, EBIConvex,& SISTBF). Additional validations on epileptic and resting state EEG data further indicate that the STARTS can produce neurophysiologically plausible results. Moreover,a computationally efficient version of STARTS: smooth STARTS was also introduced with an elementary spatial constraint, which exhibited comparable performance and reduced execution cost. In sum, the proposed STARTS, with its advanced spatio-temporal constraints and self-adapted update operation, provides an effective and efficient approach for E/MEG source imaging.

A Drosophila screen of schizophrenia-related genes highlights the requirement of neural and glial matrix metalloproteinases for neuronal remodeling
Schizophrenia (SCZ) is a multifactorial neuropsychiatric disorder of complex and mostly unknown etiology, affected by genetic, developmental and environmental factors. Neuroanatomical abnormalities, such as loss of grey matter, are apparent prior to the onset of symptoms, suggesting neurodevelopmental origin. Indeed, it has been hypothesized, and recently experimentally supported, that SCZ is associated with dysregulation of developmental synaptic pruning. Here, we explore the molecular link between SCZ-associated genes and developmental neuronal remodeling, focusing on the Drosophila mushroom body (MB), which undergoes stereotypic remodeling during metamorphosis. We conducted a loss-of-function screen in which we knocked down Drosophila homologs of human genes that genomic studies have associated with SCZ. Out of our positive hits, we focused on matrix metalloproteinases (MMPs), mostly known for their role in remodeling of the extracellular matrix. We found that both Mmp1 and Mmp2, which are closely-related to mammalian MMPs, are required in neurons and in glia for the pruning of MB axons. Our combinatorial loss-of-function experiments suggest that Mmp2 secretion from glia is the most important promoter of axon pruning. Our results shed new light on potential molecular players underlying neurodevelopmental defects in SCZ and highlight the advantage of genetically tractable model organisms in the study of human neurodevelopmental disorders.

History bias and its perturbation of the stimulus representation in the macaque prefrontal cortex.
Multiple history biases affect our representation of magnitudes, such as time, distance, and size. It is not clear whether the previous stimuli interfere with the discrimination process from the moment of stimulus presentation, during working memory retention, or even later during the decision-making phase. We used a spatial discrimination task involving two stimuli of different magnitudes, presented sequentially at various distances from the center. The monkey's task was to select the farthest of them. We showed that the previous stimulus magnitude generated a contraction bias effect, but only when its stimulus features differed from those of the current stimulus. In this case, at the neural level we also observed that the decoding of the stimulus magnitude achieved the highest accuracy when it matched the magnitude of the preceding stimulus for which the decoder was trained. This indicates that past stimuli can affect magnitude processing already during the stimulus presentation, even before the decision process. Interestingly, this effect manifested when the trace of the previous stimulus magnitude reactivated in the second part of the stimulus presentation after an activity-silent period.

Estimating descending activation patterns from EMG in fast and slow movements using a model of the stretch reflex
Due to spinal reflex loops, descending activation from the brain is not the only source of muscle activation that ultimately generates movement. This study directly estimates descending activation patterns from measured patterns of muscle activation (EMG) during human arm movements. A simple model of the spinal stretch reflex is calibrated in a postural unloading task and then used to estimate descending activation patterns from muscle EMG patterns and kinematics during voluntary arm motion performed at different speeds. We observed three key features of the estimated descending activation patterns: (1) Within about the first 15% of movement duration, descending and muscle activations are temporally aligned. Thereafter, they diverge and develop qualitatively different temporal profiles. (2) The time course of descending activation is monotonic for slow movements, non-monotonic for fast movements. (3) Varying model parameters like the spinal reflex gain or the level of co-contraction does not qualitatively change the temporal pattern of estimated descending activation. Our findings highlight the substantial contribution of spinal reflex loops to movement generation, while at the same time providing evidence that the brain must generate qualitatively different descending activation patterns for movements that vary in their mechanical dynamics.

Robust Detection of Brain Stimulation Artifacts in iEEG Using Autoencoder-Generated Signals and ResNet Classification
Background: Intracranial EEG (iEEG) is crucial for understanding brain function, but stimulation-induced noise complicates data interpretation. Traditional artifact detection methods require manual user input or struggle with noise variability, especially with limited labeled data. Objective: We developed a supervised method to automatically detect stimulation-induced noise in human iEEG recordings using synthetic data generated by Variational Autoencoders (VAEs) to train a ResNet-18 classifier. Methods: Multi-lead iEEG data were collected, preprocessed, and used to train VAEs for generating synthetic clean and noisy signals. The ResNet-18 model was trained on images of spectra generated from these synthetic signals and validated on real iEEG data from five participants. Results: The classifier, trained exclusively on synthetic data, demonstrated high accuracy, precision, and recall when applied to real iEEG recordings, with AUC values greater than 0.99 across all participants. Conclusion: We present a novel approach to effectively detect stimulation-induced noise in iEEG, offering a robust solution for improving data interpretation in scenarios with limited labeled data. Additionally, the pre-trained ResNet-18 model is available for the community to use, facilitating further research and application in similar datasets.

Diverse calcium dynamics underlie place field formation in hippocampal CA1 pyramidal cells
Every explored environment is represented in the hippocampus by the activity of distinct populations of pyramidal cells (PCs) that typically fire at specific locations called their place fields (PFs). PFs are constantly born even in familiar surroundings (during representational drift), and many rapidly emerge when the animal explores a new or altered environment (during global or partial remapping). Behavioral time scale synaptic plasticity (BTSP), a plasticity mechanism based on prolonged somatic bursts induced by dendritic Ca2+ plateau potentials, was recently proposed as the main cellular mechanism underlying new PF formations (PFF), but it is unknown whether burst-associated large somatic [Ca2+] transients are necessary and/or sufficient for PFF. To address this issue, here we performed in vivo two-photon [Ca2+] imaging of hippocampal CA1 PCs in head-restrained mice to investigate somatic [Ca2+] dynamics underlying PFFs in familiar and novel virtual environments. Our results demonstrate that although many PFs are formed by BTSP-like events, PFs also frequently emerge with initial [Ca2+] dynamics that do not match any of the characteristics of BTSP. BTSP and non-BTSP-like new PFFs occur spontaneously in familiar environments, during neuronal representational switches and instantaneously in new environments. Our data also reveal that solitary [Ca2+] transients that exceed in amplitude those evoking BTSP-like PFFs frequently occur without inducing PFs, demonstrating that large [Ca2+] transients per se are not sufficient for PFF.

Verifying the concordance between motion corrected and conventional MPRAGE for pediatric morphometric analysis
Purpose: To validate a retrospective motion correction technique, Distributed and Incoherent Sample Orders for Reconstruction Deblurring using Encoding Redundancy (DISORDER), for pediatric brain morphometry. Methods: Two T1-weighted MPRAGE 3D datasets were acquired at 3T in thirty-seven children, median age 7.75 years; one with conventional linear phase encoding and one using DISORDER. MPRAGE images were scored as motion-free or motion-corrupt. Cortical morphometry and regional brain volumes were measured with FreeSurfer, subcortical grey matter (GM) with FSL-FIRST, and hippocampal volumes with HippUnfold. Intraclass correlation coefficient (ICC) was used to determine agreement between the 2 MPRAGE acquisitions. Mann-Whitney U was used to test the difference between measures obtained using DISORDER and (i) motion-free and (ii) motion-corrupt conventional MPRAGE data. Results: ICC measures were good/excellent for most subcortical GM (motion-free, 0.75-0.96; motion-corrupt, 0.62-0.98) and regional brain volumes (motion-free 0.47-0.99; motion-corrupt, 0.54-0.99) between conventional MPRAGE and DISORDER data, except for the amygdala and nucleus accumbens (motion-free, 0.38-0.65; motion-corrupt, 0.1-0.42). However, these values were less consistent for motion-corrupt conventional MPRAGE data for hippocampal volumes (motion-free 0.65-0.99; motion-corrupt, 0.11-0.91) and cortical measures (motion-free 0.76-0.98; motion-corrupt, 0.09-0.74). Mann-Whitney U showed percentage differences in measures obtained with motion-corrupt conventional MPRAGE compared to DISORDER data were significantly greater than in those obtained using motion-free conventional MPRAGE data in 22/58 structures. Conclusion: In the absence of motion, morphometric measures obtained using DISORDER are largely consistent with those from conventional MPRAGE data, whereas improved reliability is obtained by DISORDER for motion-degraded scans. This study validates DISORDER for brain morphometric studies in children.

Computational modelling reveals neurobiological contributions to static and dynamic functional connectivity patterns
Functional connectivity (FC) is a widely used indicator of brain function in health and disease, yet its neurobiological underpinnings still need to be firmly established. Recent advances in computational modelling allow us to investigate the relationship between FC and neurobiology non-invasively. These techniques allow for targeted manipulations to study the effect of network disturbances on FC. Most modelling research has concentrated on replicating empirical static FC (sFC). However, FC changes over time, and its dynamic properties are closely linked to behaviour and symptomatology. In this study, we adapted computational models to reflect both sFC and dynamic FC (dFC) of individuals, allowing for a more comprehensive characterisation of the neurobiological origins of FC. We modelled the brain activity of 200 healthy individuals based on empirical resting-state functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) data. Simulations were conducted using a group-averaged structural connectome and four parameters guiding regional brain activity: i) G, a global coupling scaling parameter; ii) J_i, the local inhibitory current; iii) J_NMDA, the excitatory NMDA synaptic coupling parameter; and iv) w_p, the excitatory population recurrence weight. We evaluated the models based on four metrics: a) the sFC, b) the FC variance, c) the temporal correlation (TC), and d) the node cohesion (NC). The optimal model for each subject was identified by the fit to both sFC and TC. We analysed associations between brain-wide sFC and TC features with optimal model parameters and fits with a univariate correlation approach and multivariate prediction models. In addition, we used a group-average perturbation approach to investigate the effect of coupling in each region on overall network connectivity. Our models could replicate empirical sFC and TC but not the FC variance and NC. Both fits and parameters exhibited strong associations with brain connectivity. G correlated positively and J_NMDA negatively with a range of static and dynamic FC features (|r| > 0.2, p(FDR) < 0.05). TC fit correlated negatively, and sFC fit positively with static and dynamic FC features. TC features were predictive of TC fit, sFC features of sFC fit (R^2 > 0.5). Perturbation analysis revealed that the sFC fit was most impacted by coupling changes in the left paracentral gyrus ({Delta}r = 0.07). In contrast, the left pars triangularis impacted the TC fit most strongly ({Delta}r = 0.24). Our findings indicate that neurobiological characteristics are associated with individual variability in sFC and dFC, and that sFC and dFC are shaped by small sets of distinct regions. In addition, we show that brain network modelling can replicate some, but not all, properties of dFC, and model fits are strongly influenced by specific FC patterns. By modelling both sFC and dFC, we could produce new insights into neurobiological mechanisms of brain network configurations.

Hierarchical Organization of Visual Feature Attention Control
Attention can be deployed in anticipation of visual stimuli based on features such as their color or direction of motion. This anticipatory feature-based attention involves top-down neural control signals from a frontoparietal network that bias visual cortex to enhance the processing of attended information and suppress distraction. So, for example, anticipatory attention control can enable effective selection based on stimulus color while ignoring distracting information about stimulus motion. But as well, anticipatory attention can be focused more narrowly, for example, to select specific colors or motion directions. One important question that remains open is whether anticipatory attention control first biases broad feature dimensions such as color versus motion before biasing the specific feature attributes (e.g., blue vs. green). To investigate this, we recorded EEG activity during a task where participants were cued to either attend to a color (blue or green) or a motion direction (up or down) on a trial-by-trial basis. Applying multivariate decoding approaches to the EEG alpha band (8-12 Hz) activity during the attention control period (cue-target interval), we observed significant decoding for both the attended dimensions (color vs. motion) and specific feature attributes (blue vs. green; up vs. down). Importantly, the temporal onset of the dimension-level biasing (color vs. motion) preceded that of the attribute-level biasing (e.g., blue vs. green). These findings demonstrate that the top-down control of feature-based attention proceeds in a hierarchical fashion, first selecting the broad feature dimension, and then narrowing selection to the specific feature attribute.

Neural dynamics of spontaneous memory recall and future thinking in the continuous flow of thoughts
The human brain constantly recalls past experiences and anticipates future events, generating a continuous flow of thoughts. However, the neural mechanisms underlying the natural transitions and trajectories of thoughts during spontaneous memory recall and future thinking remain underexplored. To address this gap, we conducted a functional magnetic resonance imaging study using a think-aloud paradigm, where participants verbalize their uninterrupted stream of thoughts during rest. We found that transitions between thoughts, particularly those involving significant shifts in semantic content, activate the brain's default and control networks. These neural responses to internally generated thought boundaries produce activation patterns resembling those triggered by external event boundaries. Moreover, interactions within and between these networks shape the overall semantic structure of thought trajectories: stronger functional connectivity within the medial temporal subsystem of the default network predicts greater variability in thoughts, while stronger connectivity between the control and core default networks is associated with reduced variability. Together, our findings highlight how the default and control networks guide the dynamic transitions and structure of naturally arising memory and future thinking.

Susceptibility to auditory feedback manipulations and individual variability
Monitoring auditory feedback from hearing one's own voice is important for fluent speech production as it enables detection and correction of speech errors. The influence of auditory feedback is best illustrated by manipulating it during speech production. A common temporal manipulation technique, delaying auditory feedback (DAF), leads to disruptions in speech fluency, while a common spectral manipulation technique, perturbing the pitch of auditory feedback (PAF), results in vocal alterations. Previous research involving clinical populations has revealed diverse susceptibility profiles to auditory feedback manipulations, yet the extent of such diversity within the neurotypical population remains unclear. Furthermore, different types of manipulations elicit distinct speech errors (i.e. fluency/coordination versus acoustic errors), which may be processed by distinct error correction mechanisms. It is yet to be understood whether individuals affected by one manipulation are similarly impacted by the other. Lastly, based on evidence from clinical studies, which demonstrated that visual feedback can improve impaired speech production, it is an open question whether visual feedback can alleviate the disruptive effects of altered auditory feedback. We recorded voice samples from 40 neurotypical participants during both a DAF and a PAF task. DAF significantly prolonged articulation duration and increased voice pitch and intensity. In some trials, participants received immediate visual feedback, however visual feedback did not alleviate but rather strengthened the disruptive effects of DAF. During the PAF task, participants adjusted their voice pitch in the opposite direction of the perturbation in majority of the trials to compensate for the perturbation. We assessed susceptibility of the participants to the effects of DAF and PAF by examining articulation duration and compensatory vocal response magnitude, respectively. Susceptibility varied widely among participants for both manipulations, but individuals susceptible to one manipulation did not consistently exhibit susceptibility to the other, indicating distinct processing mechanisms for these different types of auditory feedback manipulations.

Intellectual disability-causing mutations in KIF11 impair microtubule dynamics and dendritic arborization
Precise control of axonal and dendritic architecture is vital for proper brain function, with microtubule (MT) dynamics playing a central role in this process. Here, we uncover a previously unrecognized function of the molecular motor protein KIF11, which acts as a MT dynamics rheostat in hippocampal neurons to modulate dendritic branching. Known for its role in mitotic spindle bipolarity, KIF11 is also implicated in Microcephaly with or without chorioretinopathy, lymphedema, or intellectual disabilities (MCLID). However, the specific neuronal functions of KIF11 and the impact of its mutations in MCLID have remained largely unexplored. Our studies, using quantitative imaging of MT dynamics following KIF11 inhibition, indicate that KIF11 preferentially binds to parallel MTs in mature neurons. This binding is associated with a marked increase in minus-end-out MT dynamics in both axons and dendrites upon KIF11 loss of function, coupled with enhanced MT flux and extended growth in tertiary dendrites. These changes suggest a novel role for KIF11 in orchestrating dendritic branching. Moreover, introducing MCLID-associated KIF11 mutations, KIF11Y82F, and KIF11{Delta}Cterm, which cause minor microcephaly but severe intellectual disabilities, leads to significantly reduced MT dynamics and impaired dendritic arborization. In a microtubule sliding assay, KIF11Y82F significantly reduced KIF11 velocity while KIF11{Delta}Cterm increased it. Temporal inhibition of KIF11 using a photo-inhibitable KIF11, show increased MT dynamics and dendritic growth, while activation results in kinked and twisted branches. Together, these data reveal that KIF11 is MT dynamics rheostat and regulator of dendritic arborization in mature neurons and provide new insights into the molecular mechanisms driving MCLID.

Striatal modulation supports policy-specific reinforcement and not action selection
Two contrasting models dominate our understanding of basal ganglia function: action selection and reinforcement learning. Prolonged, indiscriminate stimulation of direct and indirect pathway striatal neurons produces effects consistent with the action selection; however this approach ignores the transient, movement-specific dynamics that characterize these cells. To determine how striatal subpopulations contribute to mouse behavior, we applied brief closed-loop optogenetic stimulation to modulate ongoing activity in a manner that directly dissociates the contrasting models: upon the detection of locomotor arrest or leftward turns. While action selection models predict that increased direct pathway stimulation should induce locomotion and turning contralaterally to the side of stimulation, selective stimulation biased behavioral policies towards more frequent locomotor arrest and leftward turns, regardless of the side of stimulation. Indirect pathway stimulation had the opposite effect. Behavior followed the policy associated with the change in striatal activity, providing a mechanism to enable the reinforcement a wide range of behavioral features to shape performance.

Pituitary adenylate cyclase-activating polypeptide (PACAP) overexpression in the paraventricular nucleus of the thalamus alters motivated and affective behavior in female rats
Background: Pituitary adenylate cyclase-activating polypeptide (PACAP) has been found to be involved in a wide range of motivated and affective behaviors. While the PACAP-38 isoform is more densely expressed than PACAP-27 in most of the brain, PACAP-27 is more highly expressed in the rodent paraventricular nucleus of the thalamus (PVT), where females also have greater expression than males. Notably, the role of PACAP-27 expression in cells of the PVT has not been explored. Methods: Adult, female Long-Evans rats were injected in the PVT with an AAV to increase expression of PACAP or a control AAV. They were then investigated for subsequent gene and peptide levels of PACAP in the PVT; ethanol drinking and preference; sucrose drinking and preference; or locomotor activity in a novel chamber, behavior in a light-dark box, behavior in a novelty suppression of feeding test, locomotor activity in a familiar activity chamber, and behavior in a forced swim test. Results: Gene expression of PACAP was significantly increased in the PVT by four weeks after injection with the PACAP AAV, and this resulted in a specific increase in levels of PACAP-27. Rats injected with the PACAP AAV demonstrated reduced drinking and preference for ethanol under the intermittent-access procedure compared to those injected with the control AAV. In contrast, rats injected with the PACAP AAV showed no significant difference in drinking or preference for sucrose, or in any affective behavior tested, except that they spent less time swimming in the forced swim test. Conclusions: In light of the low overall level of expression of PACAP-27 in the brain, the ability of PACAP-27 in the PVT to control ethanol drinking, with minimal effects on other motivated or affective behaviors, supports the idea that compounds related to PACAP-27 should be investigated as potential therapeutics for the treatment of alcohol use disorder.

Expectation elicits music-evoked chills
Music-evoked chills (MECs) are physiological responses to pleasurable events in music. Existing research on properties of music that elicit MECs has focused on low-level acoustic features in small samples of music. We created a large dataset of over 1,000 pieces of music timestamped with MECs and used computational methods to predict MEC onsets from both low-level acoustic features and high-level musical expectations. A machine learning classifier was trained to distinguish MEC onsets from non-MEC passages in the same pieces. The results show that MEC onsets are predicted better than chance and corroborate evidence for acoustic elicitors of chills with a much larger dataset. They also produce new empirical evidence that MECs are elicited by expectation, which is a more effective predictor of MEC onsets than acoustic elicitors, and may generalise to pleasurable experience in other domains such as language comprehension or visual perception.

Prosocial reward relates to speech reception thresholds and age relates to subjective ratings of speech perception in noise
This study explores how prosocial motivation and social reward relate to speech perception in noise (SPiN). We investigated SPiN performance and subjective listening experiences across different masker conditions: 1-speaker, 2-speaker, and steady-state noise (SSN). Results indicate that individuals who rated themselves higher in prosocial traits performed better in the condition that yielded the worst threshold out of the three conditions i.e., the 2-speaker condition. Age significantly influenced subjective ratings of listening effort across all conditions where older participants reported greater effort. These findings highlight prosocial motivation as a potential factor influencing SPiN abilities, particularly in complex listening scenarios, alongside the role of age in shaping subjective auditory experiences.

Sex differences in the clinical manifestation of autosomal dominant frontotemporal dementia
INTRODUCTION: Sex differences are apparent in neurodegenerative diseases, but have not been comprehensively characterized in frontotemporal dementia (FTD). METHODS: Participants included 337 adults with autosomal dominant FTD enrolled in the ALLFTD Consortium. Clinical assessments and plasma were collected annually for up to six years. Linear mixed-effects models investigated how sex and disease stage associated with longitudinal trajectories of cognition, function, and neurofilament light chain (NfL). RESULTS: While sex differences were not apparent at asymptomatic stages, females showed more rapid declines across all outcomes in symptomatic stages compared to males. In asymptomatic participants, the association between baseline NfL and clinical trajectories was weaker in females versus males, a difference that attenuated in symptomatic participants. DISCUSSION: In genetic FTD, females show cognitive resilience in early disease stages followed by steeper clinical declines later in disease. Baseline NfL may be a less sensitive prognostic tool for clinical progression in females with FTD-causing mutations.

The PHD3-FOXO3 axis modulates the interferon type I response in microglia aggravating Alzheimer's disease progression
Microglia respond to Alzheimer's disease (AD) with a variety of transcriptional responses. However, the regulation of specific transcriptional signatures and the contribution of each individual response to disease progression is only starting to be characterized. We have previously shown that hypoxia via hypoxia inducible factor 1 (HIF1) is a strong regulator of A{beta} plaque-associated microglia (A{beta}AM). Here, we characterize the role of HIF1-mediated transcription of Egln3, encoding for PHD3, in A {beta}AM. We show that oligomeric A {beta} treatment (oA{beta}) in vitro induces the expression of Hif1a and Egln3 in microglia, which correlates with the transcriptional activation of genes involved in the interferon type I signature (IFNS) in a PHD3-dependent manner. Mechanistically, we demonstrate FOXO3 to be an important repressor of IFNS in microglia, whose abundance decreases upon A{beta} presence, and, correspondingly, both in human single-nucleus (sn) and mouse A{beta}AM transcriptomics, FOXO3 DNA binding sites define the IFNS. FOXO3 repression of the IFNS is dependent on PHD3, with our results suggesting a physical interaction between both proteins in vitro. In vivo, loss of PHD3 correlates with abrogation of the IFNS and activation of the disease-associated microglia signature (DAM) in A{beta}AM. Transcriptional changes in microglia associate with increased microglia proximity to A{beta} plaques, augmented phagocytosis of A{beta} by microglia, reduced parenchymal levels of A{beta}, and an increase in small-sized plaques. PHD3 deficiency also reduced the A{beta} plaque-associated neuropathology and rescued behavioural deficits of an AD mouse model. Finally, we also demonstrate that microglial PHD3 overexpression during development in the absence of A{beta} pathology is sufficient to induce the IFNS and behavioural alterations. Altogether, our data strongly indicate that the PHD3-FOXO3 axis controls the microglial IFNS in a cell autonomous manner, contributing to the progression of AD.

Representation of male features in the female mouse Accessory Olfactory Bulb, and their stability during the estrus cycle
Most behaviors result from integration of external and internal inputs. For example, social behavior requires information about conspecifics and internal physiological states. Like many other mammals, female mice undergo a reproductive cycle during which their physiology and behavioral responses to males change dramatically: during estrus, they are more receptive to male mating attempts. A critical element in reproductive behavior is the investigative stage, which in mice, and many other species, strongly relies on chemosensation. While the initial approach mostly involves the main olfactory system (MOS), once physical contact is established, the vomeronasal system (VNS) is engaged to provide information about potential partners' characteristics. Given the estrus-stage dependent behavioral response, we asked whether representations of male features in the first brain relay of the VNS, namely, the accessory olfactory bulb (AOB), change during the cycle. To this end, we used a stimulus set comprising urine samples from males from different strains and virility levels, and from estrus and non-estrus females. The stimulus set was designed to reveal if response patterns of AOB neurons conform to ethologically relevant dimensions such as sex, strain, and particularly, male virility state. Using extracellular recordings in anesthetized female mice, we find that most ethological categories contained in our data set are not over-represented by AOB neurons, suggesting that early stages of VNS processing encode conspecific information efficiently. Then, comparing neuronal activity in estrus and non-estrus females, we found that overall, response characteristics at the single neuron and population levels remain stable during the reproductive cycle. The few changes that do occur, are not consistent with a systematic modulation of responses to male features. Our findings imply that the AOB presents a stable account of conspecific features to more advanced processing stages.

A combinatorial approach to ALS therapies in the PrP.TDP43-315 model of ALS; complications and tribulations
Effective treatment for sporadic amyotrophic lateral sclerosis has been steadily advancing towards combinatorial therapies. For many years, riluzole was the only approved drug and it offered modest benefits. In 2017, edaravone was approved for ALS and became the first drug to be used in combination with riluzole. In the present study, we have attempted to build on the concepts of combinatorial therapy by testing novel drug combinations in a transgenic mouse model. Mice that express A315T mutant TDP43, using the mouse prion promoter, have been reported to develop many of the symptoms of ALS, including paralysis. Aberrant TDP43 function is a common feature in sporadic ALS, and thus TDP43 transgenic models may recapitulate disease processes that occur in humans with sporadic ALS. Although the PrP.TDP43-A315T model has been reported to develop abnormalities in gut motility that contribute to early mortality, recent studies indicated that gut motility issues could be mitigated by feeding mice with gel-based diets rather than the standard dry chow. In the present study, we have attempted to use the PrP.TDP43-A315T model to test whether we could identify a drug combination that synergized to extend life span in this model substantially. The drug combinations were built around the existing drug modalities, adding additional drugs that had indications of utility from the literature. To mitigate gut motility issues, we fed the mice gel-based diets with or without added drug combinations. Although the gel-based diets extended life expectancy in PrP.TDP43-A315T mice, most of the animals still developed gut motility abnormalities that may have contributed to early mortality. None of the drug combinations we tested extended life expectancy in this model substantially.

Filtered Point Processes Tractably Capture Rhythmic And Broadband Power Spectral Structure in Neural Electrophysiological Recordings
Neural electrophysiological recordings arise from interacting rhythmic (oscillatory) and broadband (aperiodic) biological subprocesses. Both rhythmic and broadband processes contribute to the neural power spectrum, which decomposes the variance of a neural recording across frequencies. Although an extensive body of literature has successfully studied rhythms in various diseases and brain states, researchers only recently have systematically studied the characteristics of broadband effects in the power spectrum. Broadband effects can generally be categorized as 1) shifts in power across all frequencies, which correlate with changes in local firing rates and 2) changes in the overall shape of the power spectrum, such as the spectral slope or power law exponent. Shape changes are evident in various conditions and brain states, influenced by factors such as excitation to inhibition balance, age, and various diseases. It is increasingly recognized that broadband and rhythmic effects can interact on a sub-second timescale. For example, broadband power is time-locked to the phase of <1 Hz rhythms in propofol induced unconsciousness. Modeling tools that explicitly deal with both rhythmic and broadband contributors to the power spectrum and that capture their interactions are essential to help improve the interpretability of power spectral effects. Here, we introduce a tractable stochastic forward modeling framework designed to capture both narrowband and broadband spectral effects when prior knowledge or theory about the primary biophysical processes involved is available. Population-level neural recordings are modeled as the sum of filtered point processes (FPPs), each representing the contribution of a different biophysical process such as action potentials or postsynaptic potentials of different types. Our approach builds on prior neuroscience FPP work by allowing multiple interacting processes and time-varying firing rates and by deriving theoretical power spectra and cross-spectra. We demonstrate several properties of the models, including that they divide the power spectrum into frequency ranges dominated by rhythmic and broadband effects, and that they can capture spectral effects across multiple timescales, including sub-second cross-frequency coupling. The framework can be used to interpret empirically observed power spectra and cross-frequency coupling effects in biophysical terms, which bridges the gap between theoretical models and experimental results.

Brainstem neurons coordinate the bladder and urethra sphincter for urination
Urination, a vital and conserved process of emptying urine from the urinary bladder in mammals, requires precise coordination between the bladder and external urethra sphincter (EUS) that is tightly controlled by a complex neural network. However, the specific subpopulation of neurons that accounts for such coordination remains unidentified, limiting the development of target-specific therapies for certain urination disorders, e.g. detrusor-sphincter dyssynergia. Here, we find that cells expressing estrogen receptor 1 (ESR1+) in the pontine micturition center (PMC) initiate voiding when activated and suspend ongoing voiding when suppressed, each at 100% reliability, respectively. Transection of either the pelvic or the pudendal nerve does not impair PMCESR1+ control of the downstream target through the other nerve at all. Anatomically, PMCESR1+ cells possess two subpopulations projecting to either the pelvic or pudendal nerve and a third, dual-projecting subpopulation, locking in the coordination of bladder contraction and sphincter relaxation in a rigid temporal order. We identify a cell type in the brainstem that controls the bladder-urethra coordination for urination.

Onco-fetal protein Nogo-A restricts human and mouse glioma vascularization and growth via VEGF-Notch-hippo-metabolic signaling
Glioblastoma is one of the most deadly human cancers characterized by high degrees of vascularization, but targeting its vasculature has resulted in very limited success so far. Angiogenesis, the growth of new blood vessels, is highly dynamic during brain development, enters a mostly quiescent state in the adult homeostatic brain, and is reactivated in vascular-dependent CNS diseases including brain tumors. In consequence, a better understanding of the relevance of the onco-fetal axis - describing the reactivation of fetal signaling programs in tumors - in endothelial- and perivascular cells of the human brain tumor vasculature harbors great translational potential, yet remains poorly defined. In development, neurovascular link (NVL) molecules guide both neuronal growth cones as well as capillary endothelial tip cells. Nogo-A is an NVL molecule known to inhibit axonal growth in the developing and adult CNS and to restrict angiogenesis during brain development, but its role in the mouse and human brain tumor vasculature along the onco-fetal axis remains unknown. Here, we characterize Nogo-A as an onco-fetal protein expressed in the neurovascular unit (NVU) in human fetal brains and human gliomas in vivo that negatively regulates sprouting angiogenesis and endothelial tip cells in glioma vascularization. The Nogo-A-specific Delta 20 domain restricts angiogenic sprouting and branching and promotes vascular normalization while inhibiting glioma growth in experimental gliomas. Moreover, Nogo-A expression in tumor cells negatively correlate/s with glioma malignancy in vivo. In vitro, Nogo-A Delta 20 reduced human brain- and brain tumor endothelial cell (HBMVEC, HBTMVEC) and human umbilical vein endothelial cell (HUVEC) spreading, migration, and sprouting, in a dose-dependent manner and inhibited filopodia extension glucose metabolism. Mechanistically, RNA sequencing of Nogo-A Delta 20-treated HBMVECs and HBTMVECs revealed Nogo-A Delta 20-induced positive regulation of the angiogenesis-inhibiting Dll4-Notch-pathway and inhibition of the angiogenesis-promoting VEGF-VEGFR and Hippo-YAP-TAZ pathways, whereas metabolomics and functional metabolic assays revealed Nogo-A Delta 20-induced negative regulation of endothelial glycolysis in HBMVECs and HBTMVECs. These findings characterize Nogo-A as an onco-fetal protein in the human glial brain tumor vasculature and identify Nogo-A Delta 20 signaling as an important negative regulator of human glioma vascularization and growth. Enhancing Nogo-A signaling may be an attractive alternative or combinatorial anti-angiogenic therapy to restrict human glioma/glioblastoma vascularization and growth.

Motor Imagery Improves Force Control in Older and Young Females
Motor imagery training (MIT) is the mental rehearsal of a motor task with no overt movement that enhances physical performance through adaptations in neural excitability. MIT may prime the motor system for physical execution. In older adults, with physical practice, force steadiness (FS) improves and changes are related to improved performance of functional tasks, and associated with adaptations in neural excitability. The purpose of this study was to determine if one session of MIT influences corticospinal excitability and improves FS of isometric elbow flexion contractions in young and older female adults. To test the hypotheses that MIT would increase corticospinal excitability and improve isometric elbow flexion FS to a greater extent in older compared to young females fourteen older (67-89 years old) and twenty-two younger (19-33 years old) participants were randomly assigned to a MIT group or Control group. Participants, in a block design, performed isometric elbow flexion contractions at 10% of maximal force prior to and following MIT (training group) or no training (Control group). Elbow flexion contractions were performed in blocks 1, 3, and 5. MIT or documentary viewing was performed in blocks 2 and 4. Motor evoked potentials (MEPs) elicited by transcranial magnetic stimulation were collected within the last five seconds of each submaximal contraction. The MEPs were reduced in the older MIT group from block 1 to block 5 (p=0.039) but not the young MIT group (p=0.761). Force steadiness in the older (p=0.005) and young (p=0.001) females improved from baseline after 20 minutes of MIT. Older females improved force steadiness relative to the baseline to a greater extent than young females (older 8.44% and young 5.0%), and the improvements were significant in older females in the first 10 minutes. In older females, MIT primes the motor system and improves FS earlier and to a greater extent than in young females.

Brain Structural Organization Revealed by Unbiased Cell-Type Distribution Clustering
Cell type composition across brain regions is a crucial anatomical factor shaping both local and long-range brain circuits. In this study, we employed single-cell resolution imaging of the mouse brain, combined with automated computational analyses, to map the distribution of thirty cell types defined by unique gene marker expressions across the entire brain. Leveraging Cre recombinase mouse models for cell type labeling, we generated a comprehensive atlas of cell-type-specific distributions throughout the male and female brain. This analysis revealed that major anatomical brain areas can be characterized by distinct cell-type composition signatures. Furthermore, these distributions provide a powerful framework for identifying and refining the boundaries of different brain regions through unbiased clustering of whole-brain cell density data. This includes mapping of cortical areas and layers, hippocampal subregions, and thalamic and hypothalamic nuclei. Our findings suggest that cell type composition is intricately linked to the structural organization of the brain, with even subtle variations potentially contributing to distinct, brain region-specific brain functions.

Chemoarchitectural studies of the rat hypothalamus and zona incerta.Chemopleth 1.0, a downloadable interactive Brain Maps spatial database of five co-visualizable neurochemical systems, with novel feature- and grid-based mapping tools
The hypothalamus and zona incerta of the brown rat (Rattus norvegicus), a model organism important for translational neuroscience research, contain diverse neuronal populations essential for survival, but how these populations are structurally organized as systems remains elusive. With the advent of novel gene-editing technologies, there has been a growing need for high-spatial-resolution maps of rat hypothalamic neurochemical cell types to aid in their functional interrogation by virus-directed cell type-specific gene manipulation or to validate their expression in transgenic lines. Here, we present a draft report describing Chemopleth 1.0, a chemoarchitecture database for the rat hypothalamus (HY) and zona incerta (ZI), which will eventually feature downloadable interactive maps featuring the census distributions of five immunoreactive neurochemical systems: (1) vasopressin (as detected using its gene co-product, copeptin); (2) neuronal nitric oxide synthase (EC 1.14.13.39); (3) hypocretin 1/orexin A; (4) melanin-concentrating hormone; and (5) alpha-melanocyte-stimulating hormone. These maps are formatted for the widely used Brain Maps 4.0 (BM4.0) open-access rat brain atlas. Importantly, this dataset retains atlas stereotaxic coordinates that facilitate the precise targeting of the cell bodies and/or axonal fibers of these neurochemical systems, thereby potentially serving to streamline delivery of viral vectors for gene-directed manipulations. The maps will be presented together with novel open-access tools to visualize the data, including a new Python programming language-based workflow to quantify cell positions and fiber densities for BM4.0. The workflow produces heat maps of neurochemical distributions from multiple subjects: 1) isopleth maps that represent consensus distributions independent of underlying atlas boundary conditions, and 2) choropleth maps that provide distribution differences based on cytoarchitectonic boundaries. These multi-subject cartographic representations are produced in Python from exported atlas maps first generated in the Adobe(R) Illustrator(R) vector graphics environment, which are then reimported and placed directly into the BM4.0 atlas. The soon-to-be-released files can also be opened using the free vector graphics editor, Inkscape. We also introduce a refined grid-based coordinate system for this dataset, register it with previously published spatial data for the HY and ZI, and introduce FMRS (Frequencies Mapped with Reference to Stereotaxy), as a new adaptation of long-used ephemeris systems for grid-based annotation of experimental observations. This database, which includes all data described in greater detail in Navarro (2020) and Peru (2020), provides critical spatial targeting information for these neurochemical systems unavailable from mRNA-based maps and allows readers to place their own datasets in register with them. It also provides a space for the continued buildout of a community-driven atlas-based spatial model of rat hypothalamic chemoarchitecture, allowing experimental observations from multiple laboratories to be registered to a common spatial framework.

Reconstruct a Connectome of Single Neurons in Mouse Brains by Cross-Validating Multi-Scale Multi-Modality Data
Brain networks, often referred to as connectomes, are crucial to findings in brain science and have inspired the development of numerous technologies at macro-, meso-, and micro-scales. With the growing prevalence of single-cell analysis, there is an urgency to generate connectomes of individual neurons that project to brain-wide regions. This work reports a scalable approach to build neuron connection networks of mouse brains by mapping whole-brain single-neuron connectivity using two complementary methods at sub-neuronal levels. We first generated an arbor-net by partitioning and probabilistically pairing dendritic and axonal arbors of 20,247 neurons registered to the Allen Brain Atlas. We also produced a bouton-net based on 2.57 million putative boutons detected along single axons of 1,877 fully reconstructed neurons and probabilistic pairing of these full-morphology datasets. Our cross-validation of both the arbor-net and bouton-net showed statistical consistency in the spatially and anatomically modular distributions of neuronal connections, which also corresponded to functional modules of the mouse brain. Our single-neuron connections were also validated by two existing independent connectomes of coarser resolution based on viral tracing of neuron populations and barcoding-and-sequencing, as well as an independent synaptome containing the relative density distribution of synapses. We further found that single neuronal connections correlated more strongly with gene co-expression at both the brain region and single-cell levels than the previous full-brain mesoscale connectome of a mouse brain. Our findings allow the assembly of a new whole-brain scale single-neuron resolution connectome for all brain regions, called SEU-net. We studied the properties of our connectomes in comparison with other potential brain architectures and found a series of non-random subnetwork patterns in the form of consistent triad motifs. Overall, our data indicate a rich granularity and strong modular diversity in the brain networks of mice.

Pharmacological enhancement of slow-wave activity improves cognition and reduces amyloidosis at an early stage in a mouse model of Alzheimer's disease
Improving sleep in murine Alzheimer's disease (AD) is associated with reduced brain amyloidosis. However, the window of opportunity for successful sleep-targeted interventions regarding reduction of pathological hallmarks and related cognitive performance remains poorly characterized. Here, we enhanced slow-wave activity (SWA) during sleep via sodium oxybate (SO) oral administration for 2 weeks at early (6 months old) or moderately late (11 months old) disease stages in Tg2576 mice, and evaluated resulting neuropathology and behavioral performance. We observed that cognitive performance of 6 months old Tg2576 mice significantly improved upon SO treatment, whereas no change was observed in 11 months old mice. Histochemical assessment of amyloid plaques demonstrated that SO-treated 11 months old Tg2576 mice had significantly less plaque burden than placebo-treated ones, whereas ELISA of insoluble protein fractions from 6 months old Tg2576 mice' brains indicated lower A{beta}-42/A{beta}-40 ratio in SO-treated group vs. placebo-treated controls. Altogether, our results suggest that SWA-dependent reduction of brain amyloidosis leads to alleviated behavioral impairment in Tg2576 mice only if administered early in the disease course, potentially highlighting the key importance of early sleep-based interventions in clinical cohorts.

Top-down feedback matters: Functional impact of brainlike connectivity motifs on audiovisual integration
Artificial neural networks (ANNs) can generate useful hypotheses about neural computation, but many features of the brain are not captured by standard ANNs. Top-down feedback is a particularly notable missing feature. Its role in the brain is often debated, and it's unclear whether top-down feedback would improve an ANN's ability to model the brain. Here we develop a deep neural network model that captures the core functional properties of top down feedback in the neocortex. This feedback allows identically connected recurrent models to have different processing hierarchies based on the direction of feedforward and feedback connectivity. We then explored the functional impact of different hierarchies on audiovisual categorization tasks. We find that certain hierarchies, such as the one seen in the human brain, impart ANN models with a light visual bias similar to that seen in humans while maintaining excellent performance on all audio-visual tasks. The results further suggest that different configurations of top-down feedback make otherwise identically connected models functionally distinct from each other and from traditional feedforward only recurrent models. Altogether our findings demonstrate that top-down feedback is a relevant feature of biological brains that improves the explanatory power of ANN models in computational neuroscience.

A heteromeric nicotinic acetylcholine receptor promotes sleep by relaying GABAergic signals within a locus of motor and sensory integration
Locomotor inactivity and reduced sensory responsiveness are defining attributes of sleep, yet the underlying mechanisms are not well understood. In particular, the molecular and circuit mechanisms by which sleep-regulatory signals from the brain restrict movement and sensation remain largely ill-defined. Here we identify a nicotinic acetylcholine receptor (nAChR) that promotes sleep in Drosophila through its expression in GABAergic neurons of the ventral nerve cord (VNC), a center for motor and sensory systems. Biochemical, genetic, and pharmacological manipulations indicate that a heteromeric nAChR containing the 1 and {beta}1 subunits promotes sleep by coupling cholinergic input to GABA release in the VNC and the likely inhibition of motor neurons, sensory afferents, or both. The functional parallels of the VNC and the mammalian spinal cord suggest that disruptions of analogous inhibitory circuits in humans may impair suppression of behavioral activity and sensory inputs during sleep and contribute to sleep disorders.

Regeneration of Sensory Hair Cells and Restoration of Vestibular Function by Notch Inhibition
Sensory hair cell loss in the vestibular organs of the inner ear causes balance disorders which are essentially irreversible due to the lack of significant hair cell regeneration. Here, we administered a {gamma}-secretase inhibitor to an adult mouse model of vestibular hair cell loss. The treatment resulted in complete regeneration of type II and partial restoration of type I hair cells after one month and restored vestibuloocular reflexes across all frequencies of rotational and linear acceleration. Further recovery was apparent at 8 months. Genetic deletion of Notch1 in supporting cells identified Notch1 as the target of the drug. The results demonstrate that a single injection of a {gamma}-secretase inhibitor is a viable therapy for functional restoration of the vestibular system in patients with balance disorders.

Spectral estimation at the edge
Cognitive functions depend on neuronal communication, which is subserved by the synchronization of neuronal rhythms. Rhythms are characterized by their frequency, power and phase. If the phase of a rhythm just preceding an input is predictive of the neuronal or behavioral response to the input, this provides strong evidence for a functional role of the rhythm. Yet, this requires estimating the phase of a rhythm at the edge of the epoch. This is challenging, because any phase estimation that is spectrally specific requires a finite window length often combined with tapers that de-emphasize the signal close to the edge. To overcome this, we propose a method that builds on previously described approaches based on autoregressive modeling of the data and corresponding extrapolation beyond the edge. In contrast to related previous approaches, the modeling is based on the broadband signals, avoiding filtering-related group delays, and the extrapolation is performed multiple times, allowing averaging and thereby the reduction of extrapolation noise. The new method provided more accurate phase estimation at the edge for most simulated datasets, and for an empirical dataset from awake macaque area V4. We propose that the enhanced phase estimation accuracy at the edge might help to investigate the functional roles of brain rhythms and potentially also to improve phase-specific stimulation for clinical applications.

Does sex matter in neurons response to hypoxic stress?
Background: Stroke exhibits significant sex differences in incidence, response to treatment, and outcome. Preclinical studies suggest that hormones, particularly estrogens, are key to differential sensitivity, as female neurons demonstrate enhanced resilience compared to males in both in vivo and in vitro models. This study investigates whether these sex-specific differences in neuronal vulnerability extend to the ischemic penumbra and explores the effects of estrogens under such conditions. Methods: Primary cortical neuronal networks were generated from male and female newborn Wistar rats and cultured on micro-electrode arrays or glass coverslips. Male and female networks were subjected to hypoxic conditions, followed by a recovery phase, with or without exogenous estrogen treatment. Electrophysiological activity, including spikes and bursts, was monitored and analyzed. Apoptosis was assessed through immunocytochemistry, focusing on caspase-dependent and apoptosis-inducing factor (AIF)-dependent pathways. Results: Under hypoxic conditions, male and female neuronal networks exhibited a similar decrease in firing and network burst rates, with an associated increase in network burst durations. Estrogen treatment altered these dynamics, leading to increased network burst rates and decreased network burst duration for both sexes. During recovery, no significant differences were observed between estrogen-treated and untreated networks. Immunocytochemistry revealed that estrogen significantly influenced caspase-dependent apoptosis, and to a lesser extent AIF-dependent apoptosis. Conclusions: In our model of the ischemic penumbra, sex-dependent differences in neuronal responses to hypoxic injury are primarily driven by estrogen, rather than intrinsic neuronal characteristics. Although our electrophysiological data demonstrated that estrogen influenced network activity, it did not offer long-term neuroprotection after hypoxia.

Physiological and injury-induced microglial dynamics across the lifespan
Microglia are resident immune cells of the brain known for their dynamic responses to tissue and vascular injury. However, little is known about how microglial activity differs across the life-stages of early development, adulthood, and aging. Using in vivo two-photon imaging, we show that microglia in the adult cerebral cortex exhibit highly ramified processes and relatively immobile somata under basal conditions. Their responses to injury occur over minutes and are highly coordinated among neighboring microglia. However, microglia in neonates are more dense and mobile than adult microglia, but less morphologically complex. Their responses to focal laser-induced injuries of capillaries or parenchymal tissue are uncoordinated, delayed and persistent over days. In the aged brain, microglia somata remain immobile under basal conditions but their processes become less ramified. Their responses to focal injuries remain coordinated, but are slower and less sensitive. These studies confirm that microglia undergo significant changes in their morphology, distribution, dynamics and response to injury across the lifespan.

Baby Open Brains: An Open-Source Repository of Infant Brain Segmentations
Reproducibility of neuroimaging research on infant brain development remains limited due to highly variable protocols and processing approaches. Progress towards reproducible pipelines is limited by a lack of benchmarks such as gold standard brain segmentations. Addressing this core limitation, we constructed the Baby Open Brains (BOBs) Repository, an open source resource comprising manually curated and expert-reviewed infant brain segmentations. Markers and expert reviewers manually segmented anatomical MRI data from 71 infant imaging visits across 51 participants, using both T1w and T2w images per visit. Anatomical images showed dramatic differences in myelination and intensities across the 1 to 9 month age range, emphasizing the need for densely sampled gold standard manual segmentations in these ages. The BOBs repository is publicly available through the Masonic Institute for the Developing Brain (MIDB) Open Data Initiative, which links S3 storage, Datalad for version control, and BrainBox for visualization. This repository represents an open-source paradigm, where new additions and changes can be added, enabling a community-driven resource that will improve over time and extend into new ages and protocols. These manual segmentations and the ongoing repository provide a benchmark for evaluating and improving pipelines dependent upon segmentations in the youngest populations. As such, this repository provides a vitally needed foundation for early- life large-scale studies such as HBCD.

Afternoon to early evening bright light exposure reduces later melatonin production in adolescents
Whether light exposure during the day reduces non-visual light effects later in the evening has not been studied in adolescents. We investigate whether afternoon-early evening (AEE) light interventions (130 lx, 2500 lx, 4.5 hours, compared to 6.5 lx) would increase melatonin levels during later evening light exposure (130 lx) in a counterbalanced crossover study with 22 adolescents (14-17 years, 11 female). Contrary to our hypothesis, evening melatonin levels decreased after AEE bright light exposure, while sleepiness and vigilance were unaffected, and skin temperature showed no clear changes. The AEE light had acute alerting effects and bright light exposure in the 32 hours before laboratory entry was associated with higher evening melatonin and sleepiness. These findings suggest that bright AEE light increases alertness but may delay melatonin production by interfering with circadian rhythms. The study highlights the complex effects of light timing and its implications for managing adolescents' light exposure.

Short-term caloric restriction or resveratrol supplementation alters large-scale brain network connectivity in male and female rats
Introduction: Dietary interventions such as caloric restriction (CR) exert positive effects on brain health. Unfortunately, poor compliance hinders the success of this approach. A proposed alternative is resveratrol (Rsv), a CR-mimetic known to promote brain health. Direct comparison between the effects of Rsv and CR on brain health is lacking, with limited knowledge on their sex-specific effects. Therefore, we aimed to compare and unravel the sex-specific impact of these dietary interventions on spontaneous brain activity. Methods: Here, we used resting-state fMRI to investigate functional connectivity (FC) changes in five prominent resting-state brain networks (RSNs) in healthy four month old male and female F344 rats supplemented to either 40% CR or daily Rsv supplementation (10 mg/kg, oral) for the duration of one month. Results: Our results demonstrated a decreased body weight (BW) in CR rats, as well as an increase in body weight in male Rsv supplemented rats, compared to female Rsv supplemented rats, whereas this difference between sexes was not observed in the control or CR groups. Furthermore, we found that both CR or Rsv supplementation induce a female-specific decrease of FC between the subcortical network and hippocampal network, and between the subcortical network and lateral cortical network. Moreover, Rsv supplementation lowered FC within the hippocampal network and between the hippocampal and the default mode like network, the lateral cortical network and the sensory network - an effect not observed for the CR rats. Finally, we observed an overall lower FC in male rats compared to females, irrespective of dietary intervention, within the subcortical network and between the subcortical, the sensory and default mode like network. Discussion: Our findings reveal that both CR and Rsv induce a similar female-specific decrease of FC in RSNs associated with memory and emotion, all the while CR and Rsv induce dissimilar changes in body weight and other within- and between RSN FC measures. Altogether, this study provides insight into the effects and comparability of short-term CR and Rsv supplementation on brain connectivity within and between RSNs in both male and female F344 rats, providing a FC reference for future research of dietary effects.

Stable primary brain cell cultures from zebrafish reveal hyperproliferation of non-neuronal cells from scn1lab mutants
Zebrafish are a popular model system for studying the genetic and neural underpinnings of perception and behavior, both in wild-type animals and in the context of disease modelling. Cultured primary neurons provide a key complementary tool for such studies, but existing protocols for culturing embryonic zebrafish primary neurons are limited by short cell survival and low neuronal purity. In this study, we set out to establish a protocol to produce long lived, pure neuronal cultures from zebrafish that could be used to study the mechanistic contributions of genes to neuronal networks. We then used these primary cultures to characterize cell proliferation and differentiation in primary neurons derived from scn1lab mutant embryos, which lack a sodium channel relevant to Dravet syndrome and autism. Using our optimized protocol, we generated cultures that proliferate, diversify, and form stable networks of neurons surviving for months. These stable cultures allowed us to perform genetic experiments, in this case revealing dramatic differences in the cellular composition of cultures derived from scn1lab mutant embryos versus their wild type siblings. Specifically, we find that loss of scn1lab promotes hyperproliferation of non-neuronal cells in mixed cultures of brain cells. In pure neuronal cultures, we find alterations in neurotransmitter subtypes consistent with known effects of scn1lab loss of function. Validating the utility of this approach, we then identify a corresponding hyperproliferation phenotype in live scn1lab mutant embryos, shedding light on potential mechanisms that may be relevant for Dravet syndrome.

Bacterial Supplements Attenuate Pelvic Irradiation-Induced Brain Metabolic Disruptions via the Gut-Brain Axis: A Multi-Omics Investigation
Recent advancements in cancer treatments have increased patient survival rates but also led to treatment-related side effects, negatively impacting the quality of life for cancer survivors. Research has highlighted the crucial role of gut microbiota in overall health, including cognition and neurodegenerative disorders. Cancer patients receiving pelvic radiation often experience gut dysbiosis and this may induce changes in brain through the bi-directional connection between the gut microbiota and the brain, known as the microbiota-gut-brain axis. Bacterial supplements intended to enhance health, whether consumed orally or applied topically. However, the mechanism of bacterial supplements to mitigate pelvic radiation-induced metabolomic alterations is not understood. To investigate this, we employed a multi-omics approach to elucidate how these supplements might mitigate radiation-induced metabolomic changes in the rat brain. A single 6 Gy dose of pelvic radiation was administered to 3-4-month-old Sprague Dawley rats and formulated bacterial supplements were given accordingly. Faecal bacterial sequencing and brain metabolomics performed to identify the changes in the gut microbiota and brain metabolomic analysis to check the altered brain metabolites post pelvic radiation. High-throughput 16S rRNA sequencing revealed significant shifts in bacterial composition, with reduced diversity in the radiation group compared to controls, which was restored in the supplementation groups. Notably, the dominant genera in the radiation group included Methanobrevibacter, while Parasutterella and Brachyspira were prevalent in the supplementation cohorts. Untargeted metabolomic analysis identified 2,554 annotated metabolites, with 56 showing significant differences across groups. Principal Component Analysis demonstrated distinct metabolomic profiles between irradiated and control groups, with specific metabolomic pathways like retinol and glycerophospholipid metabolism altered by irradiation. Bacterial supplementation significantly attenuated these metabolomic disruptions. Therefore, bacterial supplementation could be a promising approach to addressing radiation-induced metabolomic reprogramming in the brains through gut dysbiosis in patients undergoing pelvic radiotherapy, enhancing overall well-being.

Dysfunctional LHX6 pallido-subthalamic projections mediate epileptic events in a mouse model of Leigh Syndrome
Deficits in the mitochondrial energy-generating machinery cause mitochondrial disease (MD), a group of untreatable and usually fatal disorders. Among many severe symptoms, refractory epileptic events are a common neurological presentation of MD. However, the neuronal substrates and circuits for MD-induced epilepsy remain unclear. Here, using mouse models of mitochondrial epilepsy that lack mitochondrial complex I subunit NDUFS4 in a constitutive or conditional manner, we demonstrate that mitochondrial dysfunction leads to a reduction in the number of GABAergic neurons in the rostral external globus pallidus (GPe) and identify a specific affectation of pallidal Lhx6-expressing inhibitory neurons. Our findings further reveal that viral vector-mediated Ndufs4 re-expression in the GPe effectively prevents seizures and improves the survival in the models. Additionally, we highlight the subthalamic nucleus (STN) as a critical structure in the neural circuit involved in mitochondrial epilepsy, as its inhibition effectively reduces epileptic events. Thus, we have identified a novel role for pallido-subthalamic projections in the development of epilepsy in the context of mitochondrial dysfunction. Our results suggest STN inhibition as a potential therapeutic intervention for refractory epilepsy in patients with MD providing new leads in the quest to identify novel and effective treatments.

Designing Experimental Protocols to Elicit Vigilance Variations in Controlled Laboratory Settings
Vigilance plays a vital role in numerous high-risk professions, where real-time monitoring of vigilance levels is highly beneficial. Brain-Computer Interfaces (BCIs) utilizing EEG signals, along with machine learning and deep learning algorithms, present a promising solution for the classification and monitoring of vigilance levels. This study aimed to create a dataset for training such models by evaluating four experimental paradigms: the Hitchcock Air Traffic Controller Task (ATC), the simultaneous line task, the successive line task, and the Oddball task. Subjective reports and behavioral performance were analyzed to determine the effectiveness of these tasks in inducing vigilance decrements over time. The findings reveal that both the ATC and simultaneous line tasks effectively induced significant declines in subjective vigilance ratings and behavioral performance. In contrast, the Oddball task was less successful in generating a noticeable vigilance decrement. This research demonstrates the potential of the ATC and simultaneous line tasks to induce vigilance variations, providing valuable datasets for training vigilance detection algorithms. Additionally, it highlights the importance of considering non-linear fluctuations in vigilance and the need for more advanced techniques to accurately classify different vigilance states. Such improvements in vigilance monitoring could substantially enhance safety and well-being in critical work environments.

Characterization of the cellular and subcellular distribution of fms-like tyrosine kinase 3 (FLT3) and other neuronal proteins using an alkaline phosphatase (AP) immunolabeling method
Precisely localizing the spatial distribution of proteins within various cell types in the brain, and in sub-cellular compartments such as the synapses, is critical for generating and testing hypothesis to elucidating the function of target proteins in the brain. The fms-like tyrosine kinase-3 (FLT3) has been studied extensively in the context of blood cell development and leukemia pathogenesis, but little is known about its role in the brain. Previous work characterizing FLT3 protein expression in the brain have not yielded convincing results, mainly limited by the low expression level of FLT3 and poor sensitivity of standard immunolabeling method using fluorescent secondary antibody. In this study, we report the systematic characterization of FLT3 protein localization during brain development using a highly sensitive immunolabeling methodology based on alkaline phosphatase (AP) polymer biochemistry. Our results reveal a previously unknown neuron-selective FLT3 expression pattern in both mouse and human cerebellum tissue samples, and demonstrate a gradual increase in the total FLT3 protein level and a cytosolic-to-dendritic change in subcellular FLT3 distribution during mouse cerebellum development. Through combining the AP immunolabeling of FLT3 with standard immunostaining of various cell type markers to achieve hybrid co-labeling of multiple antigens in tissue sections, we demonstrate that the main cell type that express FLT3 in the cerebellum is PV+, Calbindin+ Purkinje cells. To expand the use case of AP immunolabeling method in labeling neuronal proteins, we show robust labeling of Kir2.1, a potassium channel protein that is expressed at low level in neurons, in brain tissue sections collected from mouse, pig, and human brains. We further established that the AP immunolabeling method can be used in human stem cell-derived neurons to detect postsynaptic density scaffold protein PSD95 within fine subcellular structures such as dendritic spines and synapses, in cultured primary mouse cortical neurons and human stem cell-derived neurons. To our knowledge, our work represents the first report of applying AP immunolabeling to detect neuronal protein expression in brain tissue and cell samples. Moreover, our work reveals a previously unknown neuron-specific pattern of FLT3 expression in the brain, providing the foundation for further mechanistic studies to uncover its role in brain development and functioning.

Serotonin Enhances Neurogenesis Biomarkers, Hippocampal Volumes, and Cognitive Functions in Alzheimer's Disease
Research on serotonin reveals a lack of consensus regarding its role in brain volume, especially concerning biomarkers linked to neurogenesis and neuroplasticity, such as ciliary neurotrophic factor (CNTF), fibroblast growth factor 4 (FGF-4), bone morphogenetic protein 6 (BMP-6), and matrix metalloproteinase-1 (MMP-1) in Alzheimer's disease (AD). This study aimed to investigate the influence of serotonin on brain structure and hippocampal volumes in relation to cognitive functions in AD, as well as its link with biomarkers like CNTF, FGF-4, BMP-6, and MMP-1. Data from the ADNI included 133 AD participants. Cognitive function was assessed using CDR-SB, serotonin levels were measured with the Biocrates AbsoluteIDQ p180 kit and UPLC-MS/MS, and neurotrophic factors and biomarkers were quantified using multiplex targeted proteomics. Voxel-Based Morphometry (VBM) analyzed gray matter volume changes via MRI. Statistical analyses employed Pearson correlation and Bootstrap methods, with p-values < 0.05 or 0.01 considered significant. The analysis revealed a significant positive correlation between serotonin levels and total brain volume (r = 0.179, p = 0.039) and hippocampal volumes (right: r = 0.181, p = 0.037; left: r = 0.217, p = 0.012). Besides, higher serotonin levels were associated with improved cognitive function, evidenced by a negative correlation with CDR-SB scores (r = -0.198, p = 0.023). Furthermore, total brain volume and hippocampal volumes showed significant negative correlations with CDR-SB scores, indicating that greater cognitive impairment was associated with reduced brain volume (total: r = -0.223, p = 0.010; left: r = -0.246, p = 0.004; right: r = -0.308, p < 0.001). Finally, serotonin levels were positively correlated with BMP-6 (r = 0.173, p = 0.047), CNTF (r = 0.216, p = 0.013), FGF-4 (r = 0.176, p = 0.043), and MMP-1 (r = 0.202, p = 0.019), suggesting a link between serotonin and neurogenesis and neuroplasticity. In conclusion, increased serotonin levels are associated with improved cognitive function, increased brain volume, and elevated levels of neurotrophic factors and biomarkers,specifically CNTF, FGF-4, BMP-6, and MMP-1, which are related to neurogenesis and neuroplasticity in AD.

Cross-task implications: How hippocampal event boundary responses predict unrelated memory performance
Hippocampal responses at event boundaries have been shown to predict memory performance for these events. However, are these hippocampal event boundary responses specific to memory for those particular events, or can they also have predictive power across various memory tasks? We used data from the Cam-CAN project (fMRI data from continuous movie viewing and memory results from an unrelated Famous Faces Task, N = 630) to determine whether hippocampal responses at event boundaries during the continuous movie viewing were indicative of memory performance in the unrelated Famous Faces task using various machine learning algorithms. The results showed that memory performance in the Famous Faces Task could be predicted based on participants hippocampal event boundary responses in another task, which suggests that the hippocampal event boundary responses are indicative for general memory performance. This might indicate importance of these hippocampal event boundary responses in terms of general information processing of the human brain.

Enhanced Structural Brain Connectivity Analyses Using High Diffusion-weighting Strengths
Tractography is a unique modality for the in vivo measurement of structural connectivity, crucial for understanding brain networks and neurological conditions. With increasing b-value, the diffusion-weighting signal becomes primarily sensitive to the intra-axonal signal. However, it remains unclear how tractography is affected by this observation. Here, using open-source datasets, we showed that at high b-values, DWI reduces the uncertainty in estimating fiber orientations. Specifically, we found the ratio of biologically-meaningful longer-range connections increases, accompanied with downstream impact of redistribution of connectome and network metrics. However, when going beyond b=6000 s/mm2, the loss of SNR imposed a penalty. Lastly, we showed that the data reaches satisfactory reproducibility with b-value above 1200 s/mm2. Overall, the results suggest that using b-values above 2500 s/mm2 is essential for more accurate connectome reconstruction by reducing uncertainty in fiber orientation estimation, supporting the use of higher b-value protocols in standard diffusion MRI scans and pipelines.

Stimulus history, not expectation, drives sensory prediction errors in mammalian cortex
Predictive coding (PC) is a popular framework to explain cortical responses. PC states that the brain computes internal models of expected events and responds robustly to unexpected stimuli with prediction errors that feed forward. This can be studied using oddball tasks. A repetitive sequence interrupted by a novel stimulus is a "local" oddball. "Global" oddballs defy expectations while repeating the local context. This dissociates expectation-driven neuronal prediction error responses vs. merely stimulus-history-driven release from adaptation. We recorded neuron spiking activity across the visual hierarchy in mice and monkeys viewing these oddballs. Local oddball responses largely followed PC hypotheses. They were robust, emerged early in layers 2/3, and fed forward. Global oddball responses challenged PC. They were weak, absent in most visual areas, more robust in prefrontal cortex, and emerged in non-granular layers. Contrary to the most popular PC models that emphasize prediction error computations occurring in early sensory areas and feeding forward, this implies that genuine predictive coding computations take place in more cognitive, higher-order areas.

Tbc1d15 knockdown in vivo alleviates α-synuclein-induced neurotoxicity by promoting autophagy.
Parkinsons disease is a neurodegenerative disease, which is associated with accumulation of -synuclein protein aggregates and Lewy Body formation. These neurotoxic inclusions are especially harmful for dopamine-producing neurons in the substantia nigra of the brain. The cellular degradation system autophagy can reduce neurotoxicity caused by accumulated -synuclein, by targeting it for degradation. Previously, we demonstrated that human TBC1D15 inhibits autophagy in vitro, resulting in accumulation of neurotoxic protein aggregates. Conversely, lowering the TBC1D15 expression promotes autophagy and degradation of -synuclein and huntingtin proteins in various cell models. Here we show that knockdown of murine Tbc1d15 in vivo activates autophagy, reduces -synuclein-mediated neurotoxicity, and improves motor performance. Thus, targeting Tbc1d15 expression may be a therapeutic avenue for neurodegenerative diseases.

Oligodendrocytes use post-synaptic proteins to coordinate myelin formation on axons of distinct neurotransmitter classes
Axon myelination is a powerful method to tune neuronal circuit output through deposition of different patterns, lengths, and thicknesses of sheaths on many axon types. Yet the molecular mechanisms of myelin formation on distinct axon classes remain largely unknown. Recent work indicates that myelin properties on different neurons may be unique and function through distinct signaling pathways, and that neuronal activity and vesicle release promote myelin formation. Here, we use the zebrafish and the scaffold protein Gephyrin (Gphn) as a tool to examine post-synaptic protein function in OLs with respect to myelinated axon class identity. We show that Gphn protein is enriched in myelin sheaths that wrap GABAergic and glycinergic axons. Using Gphn loss-of-function approaches, we found an accumulation of long myelin sheaths across development that specifically wrap GABAergic axons. Loss of Gphn also biases glutamatergic axons for myelination at the expense of GABAergic axons. Collectively, our results suggest that OLs use post-synaptic machinery to coordinate myelin formation in an axon identity-dependent manner.

Pharmacological inhibition of Fms-like kinase 3 (FLT3) promotes neuronal maturation and suppresses seizure in a mouse model
Fms-like tyrosine kinase 3 (FLT3) is a receptor tyrosine kinase predominantly expressed in blood and brain cells. While the FLT3 signaling pathway has been extensively studied in blood cell development and leukemia, its role in the brain remains largely unexplored. Through our previous high-throughput drug screening work unexpectedly found that several small molecule FLT3 inhibitors (FLT3i), including KW-2449 and Sunitinib, enhance expression of the gene encoding chloride transporter KCC2 in neurons. KCC2 is crucial for brain development and function, and its dysregulation is linked to many brain diseases. These findings suggest previously unrecognized roles of FLT3 signaling in brain health and disease that have yet to be systematically studied. In this study, we utilized a functional genomics approach to investigate the transcriptomic changes induced by pharmacological inhibition of the FLT3 pathway in brain cells, including cultured primary mouse neurons, a human stem cell-derived neuronal model of Rett syndrome (RTT), and human stem cell-derived microglia cultures. Our results show that treating human or mouse neurons with FLT3i drugs significantly upregulates genes crucial for brain development while downregulating genes linked to neuroinflammation. In contrast, FLT3i treatment of human microglia, which do not express FLT3, has no effect on their gene expression, highlighting the cell type-specific roles of FLT3 signaling in the brain. To further understand how FLT3 signaling regulates the expression of neuronal maturation genes such as KCC2, we conducted a curated CRISPR screen that identified a number of transcription factors involved in FLT3i-mediated KCC2 activation in neurons. The mRNA and protein levels of several neurodevelopmental disorder (NDD) risk genes are significantly upregulated in FLT3i-treated neurons, indicating potential therapeutic applications of FLT3i in rescuing underexpression and/or haploinsufficiency of disease-associated genes. In our in vivo studies, we evaluated the efficacy of the FLT3i drug KW-2449 in mice, demonstrating that it can effectively cross the blood-brain barrier, induce KCC2 protein expression for up to 24 hours after a single injection, and reduces seizure activity in a chemoconvulsant-induced mouse model of temporal lobe epilepsy. Collectively, our findings uncover previously unrecognized roles of neuron-specific FLT3 signaling in promoting neuronal maturation and reducing neuroinflammation. These results suggest that FLT3 kinase signaling regulates a transcriptional program vital for brain development and function, position it as a promising therapeutic target for NDD treatment.

Optimal control of spiking neural networks
Control theory provides a natural language to describe multi-areal interactions and flexible cognitive tasks such as covert attention or brain-machine interface (BMI) experiments, which require finding adequate inputs to a local circuit in order to steer its dynamics in a context-dependent manner. In optimal control, the target dynamics should maximize a notion of long-term value along trajectories, possibly subject to control costs. Because this problem is, in general, not tractable, current approaches to the control of networks mostly consider simplified settings (e.g., variations of the Linear-Quadratic Regulator). Here, we present a mathematical framework for optimal control of recurrent networks of stochastic spiking neurons with low-rank connectivity. An essential ingredient is a control-cost that penalizes deviations from the default dynamics of the network (specified by its recurrent connections), which motivates the controller to use the default dynamics as much as possible. We derive a Bellman Equation that specifies a Value function over the low-dimensional network state (LDS), and a corresponding optimal control input. The optimal control law takes the form of a feedback controller that provides external excitatory (inhibitory) synaptic input to neurons in the recurrent network if their spiking activity tends to move the LDS towards regions of higher (lower) Value. We use our theory to study the problem of steering the state of the network towards particular terminal regions which can lie either in or out of regions in the LDS with slow dynamics, in analogy to standard BMI experiments. Our results provide the foundation of a novel approach with broad applicability that unifies bottom-up and top-down perspectives on neural computation.

A membrane-targeted photoswitch restores physiological ON/OFF responses to light in the degenerate retina
The lack of effective therapies for visual restoration in Retinitis pigmentosa and macular degeneration has led to the development of new strategies such as optogenetics and retinal prostheses. However, visual restoration is poor due to the massive light-evoked activation of retinal neurons, regardless of the segregation of visual information in ON and OFF channels, essential for contrast sensitivity and spatial resolution. Here, we show that Ziapin2, a membrane photoswitch which modulates neuronal capacitance and excitability in a light-dependent manner, is capable of reinstating, in two distinct genetic models of photoreceptor degeneration, brisk and sluggish ON, OFF, and ON-OFF responses in retinal ganglion cells evoked by full-field stimuli, with reactivation of their excitatory and inhibitory conductances. Intravitreally injected Ziapin2 in fully blind rd10 mice restored light-driven behavior and optomotor reflexes. The results indicate that Ziapin2 is a promising molecule for reinstating physiological visual responses in the late stages of retinal degeneration.

Pannexin-2 deficient zebrafish develop ocular and visual motor behaviour defects
Pannexin-2 (Panx2), unlike the other pannexin channels Panx1 and Panx3, exhibits a unique intracellular distribution, localizing at ER-mitochondria contact sites. These specialized microdomains are crucial for important cellular functions, including calcium homeostasis, lipid transfer, inflammation, and apoptosis. Despite their presence in neurons and glial cells, the function of Panx2 at ER-mitochondria contact sites in neurotransmission remains unclear. Here, we used TALEN technology to develop a Panx2 knockout (Panx2-/-) zebrafish model, to investigate its role in neuronal communication. In 6 days, post fertilization TL (Panx2+/+) larvae, Panx2 expression was observed in the inner and outer plexiform layers of the retina and the arborization fields of the optic tract. Transcriptome profiling of Panx2-/- larvae by RNA-seq analysis revealed down-regulation of vision-related genes, specifically those involved in visual and sensory perception and lens development. Behavioral tests showed that loss of Panx2 leads to altered visual motor response (VMR); Panx2-/- larvae exhibited reduced locomotor activity during light phases and increased activity during dark phases. Additionally, the knockout larvae displayed significantly impaired optomotor response (OMR). When we tested the geometric and refractive properties of adult eyes, optical coherence tomography (OCT) analysis of Panx2-/- fish revealed a longer mean axial length and a negative shift in retinal refractive error (RRE) values, both indicative of myopia. Furthermore, the increased corneal thickness observed in Panx2-/- fish corroborated the molecular and behavioural alterations. Our findings highlight a novel role of Panx2 in retinal development, visual perception, and ocular health.

Reward processing in children with Affective Dysregulation
Introduction: Affective dysregulation (AD) in children is characterized by irritability, anger, and frequent intense temper outbursts. Considerable evidence implies altered processing of frustration about missed rewards, but few studies investigated the preceding and thus potentially predictive reward anticipation and initial delivery processing in children with AD. Methods: A total of 103 children aged 8 to 12 years (50 with AD and 53 without AD) were examined during a monetary reward anticipation task with event-related potential (ERP) components resolving reward anticipation (cue-CNV [Contingent Negative Variation]) and reward delivery phases (Reward Positivity and Feedback-Related Negativity). All components were analyzed by repeated measures ANOVA. Regression analyses also evaluated the associations between those ERP components and dimensional AD symptoms. Results: Children with AD showed attenuated anticipatory reward processing compared to No-ADs. The CNV at fronto-central site (FCz) showed a significant group effect (No AD>AD, p=0.017). Post-hoc test showed that this group difference was stronger for the cue monetary condition (monetary cue: p=.007, d=0.56, verbal cue: p=.901, d=0.16), and that only the No AD group showed a significant difference between conditions (p<0.001). No significant effects were obtained for the delivery phase. Regression analysis showed that a reduced anticipatory CNV at FCz significantly explained AD symptoms, and that anger/irritability and anxiety/depressive symptoms predicted a reduced anticipatory CNV at FCz. Conclusion: This neurophysiological characterization of reward anticipation and delivery in children with AD demonstrates altered neural activity in AD during anticipation of reward rather than following the delivery (or omission) of the reward itself. Our results highlight that altered reward anticipation in AD can occur outside frustration-prone tasks or settings, and underline the important role of both anger/irritability and anxiety/depressive symptoms in the pathophysiology of AD for atypical reward anticipation.

Theta-gamma transcranial alternating current stimulation enhances motor skill acquisition in healthy young and older adults
Theta-gamma transcranial alternating current stimulation (TG tACS) over primary motor cortex (M1) can improve motor skill acquisition in young adults, but the effect on older adults is unknown. This study investigated the effects of TG tACS on motor skill acquisition and M1 excitability in 18 young and 18 older adults. High-definition TG tACS (6 Hz theta, 75 Hz gamma) or sham tACS was applied over right M1 for 20 minutes during a ballistic left-thumb abduction motor training task performed in two experimental sessions. Motor skill acquisition was quantified as changes in movement acceleration during and up to 60 minutes after training. Transcranial magnetic stimulation (TMS) was used to assess changes in M1 excitability with motor-evoked potentials (MEP) and short-interval intracortical inhibition (SICI) before and after training. We found that TG tACS increased motor skill acquisition compared with sham tACS in young and older adults (P < 0.001), with greater effects for young adults (P = 0.01). The improved motor performance with TG tACS lasted at least 60 minutes after training in both age groups. Motor training was accompanied by greater MEP amplitudes with TG tACS compared to sham tACS in young and older adults (P < 0.001), but SICI did not vary between tACS sessions (P = 0.40). These findings indicate that TG tACS over M1 improves motor skill acquisition and alters training-induced changes in M1 excitability in healthy young and older adults. TG tACS may therefore be beneficial to alleviate motor deficits in the ageing population.

Fate plasticity of interneuron specification
The generation of neuronal subtypes in the mammalian central nervous system is driven by competing genetic programs. The medial ganglionic eminence (MGE) gives rise to two major cortical interneuron (cIN) populations, marked by Somatostatin (Sst) and Parvalbumin (Pvalb), which develop on different timelines. The extent to which external signals influence these identities remains poorly understood. Pvalb-positive cINs are particularly important for regulating cortical circuits through strong perisomatic inhibition, yet they have been difficult to model in vitro. Here we investigated the role of the environment in shaping and maintaining Pvalb cINs. We grafted mouse MGE progenitors into a variety of 2D and 3D co-culture models, including mouse and human cortical, MGE, and thalamic systems with dissociated cells, organoids, organotypic cultures, and conditioned media. Across models, we observed distinct proportions of Sst- and Pvalb-positive cIN descendants. Strikingly, grafting MGE progenitors into 3D human, but not mouse, corticogenesis models led to efficient, non-autonomous differentiation of Pvalb-positive cINs. This differentiation was characterized by upregulation of Pvalb maturation markers, downregulation of Sst-specific markers, and the formation of perineuronal nets. Furthermore, lineage-traced postmitotic Sst-positive cINs, when grafted onto human cortical models, also upregulated Pvalb expression. These results reveal an unexpected level of fate plasticity in MGE-derived cINs, demonstrating that their identities can be dynamically shaped by the surrounding environment.