bioRxiv Subject Collection: Neuroscience's Journal

Sex differences distinguish performance in four object recognition-based memory tasks in the Pink1-/- rat model of Parkinson's disease
Many patients with Parkinsons disease (PD) experience early, sometimes prodromal non-motor deficits involving cognition and memory. These so-called mild cognitive impairments hold dire predictions for future risk of freezing, falls and developing PD-related dementia. Moreover, due to a dearth of effective treatments, these symptoms persist and progressively worsen. Thus, there is an urgent need to better understand and better treat these debilitating signs. Sex differences in incidence, severity and treatment sensitivities predict that the answers to these questions are sex-specific. The work presented here highlights new ways in which rats with knockout of PTEN-induced putative kinase 1 gene (Pink1-/-) emulate PDs mild cognitive deficits and their clinical sex differences. Specifically, longitudinal behavioral testing confirmed that male Pink1-/- rats developed significant deficits in Novel Object Recognition and Novel Object Location tasks by 5 months old but that female Pink1-/- were unimpaired in these and the Object-in-Place task through 12 months of age. Further, What, Where, When Episodic-like Memory testing identified enduring deficits in all three memory domains in Pink1-/- males by 3 months of age whereas in Pink1-/- females, non-significant impairments emerged at 7 months of age and progressed to significant memory deficits by 12 months of age. Together, these data show that Pink1-/- rats model the generally greater vulnerability of male PD patients to cognitive and memory deficits in PD, the growing risk for higher order deficits in female patients as they age, and features including early onset that distinguish episodic memory impairments from other at-risk processes in this disorder.

Detecting Primary Progressive Aphasia (PPA) from Text: A Benchmarking Study
Classifying subtypes of primary progressive aphasia (PPA) from connected speech presents significant diagnostic challenges due to overlapping linguistic markers. This study benchmarks the performance of traditional machine learning models with various feature extraction techniques, transformer-based models, and large language models (LLMs) for PPA classification. Our results indicate that while transformer-based models and LLMs exceed chance-level performance in terms of balanced accuracy, traditional classifiers combined with contextual embeddings remain highly competitive. Notably, SVM using RoBERTa's embeddings achieves the highest classification accuracy. These findings underscore the potential of machine learning in enhancing the automatic classification of PPA subtypes.

Adaptation of visual responses in degenerating rd10 and healthy mouse retinas during ongoing electrical stimulation.
Objective: Visual adaptation is a physiological and perceptual process by which the visual system adjusts to changes in the environment or visual stimuli. This process is fundamental to how we perceive the world around us and allows our visual system to efficiently encode and process visual information. The retina incorporates adaptaion with its dozens of functionally distinct retinal ganglion cell types. Meanwhile, the field of retinal prostheses is increasing its understanding of electrical adaptation and cell-specific stimulation. However, very little is known about the interaction of visual and electrical stimulation on the adaptation of retinal ganglion cell types. Methods/Approach: Recording with a microelectrode array (MEA), we presented an ON and OFF full-field, visual stimulus to characterize various visual response parameters in healthy and degenerating rd10 mouse retinas. We then evaluated visual response changes before and after blocks of monophasic voltage-controlled electrical pulse stimulation. Main Results: A history of electrical stimulation strengthened visual responses in WT retina, even when changes attributable to in vitro visual adaptation were taken into account. In rd10 retinas, electrical adaptation counteracted the baseline in vitro visual adaptation. In all cases, adaptation often affected the ON and OFF visual response components differentially. Consequently, the ON/OFF classification of individual cells changed as a result of adaptation. Significance: Electrical stimulation-induced changes in the retina should be considered in the encoding of visual stimuli by retinal prosthetic devices. In vitro investigations for bionic vision should strive to probe electrical responsiveness after adaptation to ongoing electrical stimulation has achieved a steady-state.

Gestational Chlorpyrifos Exposure Imparts Lasting Alterations to the Rat Somatosensory Cortex
Chlorpyrifos is an organophosphorus pesticide used extensively in agricultural and residential settings for nearly 60 years. Gestational, sub-acute exposure to chlorpyrifos is linked to increased prevalence of neurodevelopmental disorders. Animal studies have modeled these neurobehavioral detriments, however, the functional alterations in the brain induced by this exposure remain largely unknown. To address this, we used a rat model of gestational chlorpyrifos exposure to interrogate the alterations in the developing somatosensory (barrel) cortex. Rat dams were exposed to chlorpyrifos (5 mg/kg) or vehicle on gestational days 18-21 via subcutaneous injection, with no overt acute toxicity. Acetylcholinesterase was modestly inhibited but returned to baseline levels by postnatal day 12. We performed whole-cell patch clamp recordings on postnatal days 12-20 in both male and female progeny of the treated dams. A spike timing dependent plasticity protocol revealed changes to the normal development of use-dependent plasticity, including interference in long-term synaptic depression. Recording inhibitory synaptic activity revealed an increase in the frequency of spontaneous postsynaptic currents and in paired pulse ratios, in conjunction with a significant decrease in miniature postsynaptic currents. These findings suggest a presynaptic mechanism of inhibited GABA release, with potential disinhibition of inhibitory neurons. Evaluation of barrel cortex development displayed disruptions to normal barrel field patterning, with increases in both the septal area and total barrel field. We provide evidence for functional and structural alterations during brain development induced by in utero exposure to the organophosphorus pesticide chlorpyrifos that may account for the well-established behavioral outcomes.

Brain-wide mapping reveals temporal and sexually dimorphic opioid actions
While the molecular and cellular effects of opioids have been extensively studied, the precise mechanisms by which these drugs target specific brain regions over time remain unclear. Similarly, despite well-documented sex differences in opioid responses, the anatomical basis for this sexual dimorphism is not well characterized. To address these questions, we developed an automated, scalable, and unbiased approach for whole-brain anatomical mapping of the neuronal activity marker c-Fos in response to acute morphine exposure. Using ribbon scanning confocal microscopy, we imaged whole cleared brains from male and female wild-type mice at 1 hour and 4 hours post-morphine administration. Our whole-brain analysis of c-Fos expression revealed distinct patterns of morphine-induced regional brain activation across time and sex. Notably, we observed a greater number of structures with significant activity differences at 4 hours compared to 1 hour. In male mice, significant changes were primarily localized to regions within the dopamine system, whereas in female mice, they were concentrated in cortical regions. By combining high-throughput imaging with whole-brain expression analysis, particularly in the context of opioid actions, our approach provides a more comprehensive understanding of how drugs of abuse affect the brain.

Predicting High-Resolution Spatial and Spectral Features in Mass Spectrometry Imaging with Machine Learning and Multimodal Data Fusion
Recent advancements in molecular Mass Spectrometry Imaging (MSI) have sparked interest in integrating high spatial resolution methods with molecular mass-spectrometry-based chemical imaging. Fusion-based algorithms have proven effective in generating high spatial-resolution molecular mass spectra. However, a significant challenge stems from the differing physical mechanisms underlying image generation and data upsampling techniques, potentially leading to discrepancies in integrated information channels. Integrating physical constraints into data processing workflows is essential to tackle this issue. In this study, we propose an innovative approach that merges data from Fourier transform ion cyclotron resonance (FTICR), time-of-flight matrix-assisted laser desorption/ionization (MALDI-ToF), and time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging techniques. By leveraging FT-ICR's unparalleled spectral resolution and ToF-SIMS's exceptional spatial resolution, we achieve submicron spatial resolution, enabling the observation of intact molecular species with remarkable spectral precision. Canonical correlation analysis is employed to incorporate physical constraints. Through sophisticated image processing and machine learning techniques, the results of this fusion hold significant promise for advancing our comprehension of complex systems and unveiling concealed molecular intricacies.

Mouse sensorimotor cortex reflects complex kinematic details during reaching and grasping
Coordinated forelimb actions, such as reaching and grasping, rely on motor commands that span a spectrum from abstract target specification to detailed instantaneous muscle control. The sensorimotor cortex is central to controlling these complex movements, yet how the detailed command signals are distributed across its numerous subregions remains unclear. In particular, in mice it is unknown if the primary motor (M1) and somatosensory (S1) cortices represent low-level joint angle details in addition to high-level signals like movement direction. Here, we combine high quality markerless tracking and two-photon imaging during a reach-to-grasp task to quantify movement-related activity in the mouse caudal forelimb area (CFA) and forelimb S1 (fS1). Linear decoding models reveal a strong representation of proximal and distal joint angles in both areas, and both areas support joint angle decoding with comparable fidelity. Despite shared low-level encoding, the time course of high-level target-specific information varied across areas. CFA exhibited early onset and sustained encoding of target-specific signals while fS1 was more transiently modulated around lift onset. These results reveal both shared and unique contributions of CFA and fS1 to reaching and grasping, implicating a more distributed cortical circuit for mouse forelimb control than has been previously considered.

Integrated Ultrasound Neuromodulation and Optical Neuroimaging in Awake Mice using a Transparent Ultrasound Transducer Cranial Window
Ultrasound neuromodulation is a rapidly advancing, non-invasive technique with significant therapeutic potential for treating various neurological disorders. Although extensive in vitro and in vivo studies have provided valuable insights into its modulatory effects, the underlying mechanisms remain poorly understood, limiting its clinical translation. Optical neuroimaging techniques can help investigate these mechanisms; however, the opacity and bulkiness of conventional ultrasound transducers pose significant challenges for their integration with in vivo ultrasound neuromodulation studies, particularly in awake rodents. To address these limitations, we propose a straightforward solution: a miniaturized lithium niobate-based transparent ultrasound transducer (TUT) integrated as a thinned-skull cranial window for ultrasound stimulation while facilitating multimodal optical neuroimaging in awake mice brain. Using laser speckle contrast imaging and intrinsic optical signal imaging, we studied changes in brain hemodynamics in response to various ultrasound stimulation sequences. Our experiments demonstrated that TUT cranial window can robustly induce neuromodulatory effects with observed increase in both cerebral blood flow and total hemoglobin, with peak and cumulative hemodynamic changes directionally correlated with ultrasound stimulation duration and intensity. Overall, these findings highlight that TUT cranial window can seamlessly integrate ultrasound stimulation and optical neuroimaging in awake mouse brain models, offering promising prospects for uncovering the underlying mechanisms of ultrasound neuromodulation.

β-Hydroxybutyrate enhances brain metabolism in normoglycemia and hyperglycemia, providing cerebroprotection in a mouse stroke model.
Hyperglycemia in poorly controlled diabetes is widely recognized as detrimental to organ dysfunction. However, the acute effects of hyperglycemia on brain metabolism and function are not fully understood. The potential protective benefit of ketone bodies on mitochondrial function in the brain has also not been well characterized. Here, we evaluated the acute effects of hyperglycemia and {beta}-hydroxybutyrate (BHB) on brain metabolism by employing a novel approach leveraging adenosine triphosphate (ATP)-dependence of bioluminescence originating from luciferin-luciferase activity. Oxygen consumption rate was measured in ex vivo live brain punches to further evaluate mitochondrial function. Additionally, we investigated the functional relevance of BHB using an in vivo photothrombotic stroke model to assess its cerebroprotective effects. Our data demonstrate that brain metabolism in mice is affected by acute exposure to high glucose, at a level similar to consuming food or a beverage with high sucrose. This short-term effect of glucose exposure was reduced by co-administration with the ketone body BHB. Moreover, BHB significantly reduced infarct size in the brain stroke model, providing evidence for its functional protective role in the brain. These findings suggest that BHB may effectively mitigate the adverse effects of metabolic stress and ischemic events on brain metabolism and function.

Fiber photometry analysis for spontaneous dopamine signals: The z-scored data are not the data
Fluorescent sensors have revolutionized the measurement of molecules in the brain, and the dLight dopamine sensor has been used extensively to examine reward- and cue-evoked dopamine release, but only recently has the field turned its attention to spontaneous release events. Analysis of spontaneous events typically requires evaluation of hundreds of events over minutes to hours, and the most common method of analysis, z-scoring, was not designed for this purpose. Here, we compare the accuracy and reliability of three different analysis methods to identify pharmacologically induced changes in dopamine release and uptake in freely moving C57BL/6J mice. The D1-like receptor antagonist SCH23390 was used to prevent dLight sensors from interacting with dopamine in the extracellular space, while cocaine was used to inhibit uptake and raclopride to increase release of dopamine in the nucleus accumbens. We examined peak-to-peak frequency, peak amplitude, and width, the time spent above an established cutoff. The three methods were 1) the widely-used "Z-Score Method", which automatically smooths baseline drift and normalizes recordings using signal-to-noise ratios, 2) a "Manual Method", in which local baselines were adjusted manually and individual cutoffs were determined for each subject, and 3) the "Prominence Method" that combines z-scoring with prominence assessment to tag individual peaks, then returns to the preprocessed data for kinetic analysis. First, SCH23390 drastically reduced the number of signals detected as expected, but only when the Manual Method was used. Z-scoring failed to identify any changes, due to its amplification of noise when signals were diminished. Cocaine increased signal width as expected using the Manual and Prominence Methods, but not the Z-Score Method. Finally, raclopride-induced increases in amplitude were correctly identified by the Manual and Prominence Methods. The Z-Score Method failed to identify any of the changes in dopamine release and uptake kinetics. Thus, analysis of spontaneous dopamine signals requires assessment of the %{Delta}F/F values, ideally using the Manual Method, and the use of z-scoring is not appropriate.

Topologically Optimized Intrinsic Brain Networks
The estimation of brain networks is instrumental in quantifying and evaluating brain function. Nevertheless, achieving precise estimations of subject-level networks has proven to be a formidable task. In response to this challenge, researchers have developed group-inference frameworks that leverage robust group-level estimations as a common reference point to infer corresponding subject-level networks. Generally, existing approaches either leverage the common reference as a strict, voxel-wise spatial constraint (i.e., strong constraints at the voxel level) or impose no constraints. Here, we propose a targeted approach that harnesses the topological information of group-level networks to encode a high-level representation of spatial properties to be used as constraints, which we refer to as Topologically Optimized Intrinsic Brain Networks (TOIBN). Consequently, our method inherits the significant advantages of constraint-based approaches, such as enhancing estimation efficacy in noisy data or small sample sizes. On the other hand, our method provides a softer constraint than voxel-wise penalties, which can result in the loss of individual variation, increased susceptibility to model biases, and potentially missing important subject-specific information. Our analyses show that the subject maps from our method are less noisy and true to the group networks while promoting subject variability that can be lost from strict constraints. We also find that the topological properties resulting from the TOIBN maps are more expressive of differences between individuals with schizophrenia and controls in the default mode, subcortical, and visual networks.

Local variations in L/M ratio influence the detection and color naming of small spots
The distribution of long-wavelength sensitive (L) and middle-wavelength sensitive (M) cones in the retina determines how different frequencies of incident light are sampled across space, and has been hypothesized to influence spatial and color vision. We asked whether the detection and color naming of small, short-duration increment stimuli depend on the relative numbers of L and M cones illuminated. Stimuli were corrected for optical aberrations by an adaptive optics system, and targeted to locations in the parafovea where cone spectral types were known. We found that sensitivity to 680 nm light, normalized by sensitivity to 543 nm light, grew with the proportion of L cones at the stimulated locus, though intra- and intersubject variability was considerable. A similar trend was derived from a simple model of the achromatic (L+M) pathway, as well as from photoreceptor-level ideal observers, suggesting that small spot detection mainly relies on a non-opponent mechanism. Most stimuli were called achromatic, with red and green responses becoming more common as stimulus intensity and local L/M ratio symmetry increased. Our detection data confirm earlier reports that small spot psychophysics can reveal information about local cone topography, and our color naming findings suggest that chromatic sensitivity may improve when the L/M ratio approaches unity.

Single-nuclei RNA Sequencing Reveals Distinct Transcriptomic Signatures of Rat Dorsal Root Ganglia in a Chronic Discogenic Low Back Pain Model
Chronic low back pain (LBP), often correlated with intervertebral disc degeneration, is a leading source of disability worldwide yet remains poorly understood. Current treatments often fail to provide sustained relief, highlighting the need to better understand the mechanisms driving discogenic LBP. During disc degeneration, the extracellular matrix degrades, allowing nociceptive nerve fibers to innervate previously aneural disc regions. Persistent mechanical and inflammatory stimulation of nociceptors can induce plastic changes within dorsal root ganglia (DRG) neurons, characterized by altered gene expression, enhanced excitability, and lowered activation thresholds. Although these transcriptional changes have been described in other pain states, including osteoarthritis, they remain underexplored in discogenic LBP. To address this gap, this study represents the first application of comprehensive single-nuclei RNA sequencing of DRG neurons in a rat model of chronic discogenic LBP. Eighteen distinct DRG subpopulations were identified and mapped to existing mouse and cross-species atlases revealing strong similarities in neuronal populations with the mouse. Differential expression analysis revealed increased expression of pain-associated genes, including Scn9a and Piezo2, and neuroinflammatory mediators such as Fstl1 and Ngfr, in LBP animals. Axial hypersensitivity, measured using grip strength, significantly correlated with increased expression of Scn9a, Fstl1, and Ngfr, which suggests their role in maintaining axial hypersensitivity in this model. These findings establish a relationship between DRG transcriptomic changes and axial hypersensitivity in a discogenic LBP model, identifying potential molecular targets for non-opioid treatments and advancing understanding of discogenic LBP mechanisms.

Ketogenic Diet Enhances Cognitive-Behavioral Function and Hippocampal Neurogenesis While Attenuating Amyloid Pathology in Tg-SwDI Mice
The ketogenic diet (KD), characterized by high-fat, low-carbohydrate, and moderate protein intake, has gained attention for its therapeutic potential in patients with neurodegenerative diseases, including Alzheimer's disease. Studies in Alzheimer's rodent models report that KD and/or ketogenic supplements attenuate cognitive-behavioral impairments, neuroinflammation, amyloid-beta plaques and tau pathology. However, it is unknown whether KD can similarly benefit individuals with cerebral amyloid angiopathy (CAA), a prevalent condition in which amyloid accumulates in cerebral vessels. CAA is highly comorbid in patients with Alzheimer's and, on its own, increases the risk of stroke, cognitive impairment, and dementia, yet no effective treatments currently exist. The objective of this study was to determine whether KD can improve cognitive-behavioral and neuropathological outcomes in a mouse model with CAA. Male Tg-SwDI mice were fed either a standard chow or KD from 3.5 to 7.5 months of age. Following ~3 months of dietary intervention, glucose and ketone-body levels were assessed, then mice underwent a battery of behavioral tests to evaluate locomotor activity, anxiety-related behaviors, and cognition. Immunohistochemistry was performed to assess amyloid pathology, vascular density, neuroinflammation, white matter integrity, and hippocampal neurogenesis. In addition to KD inducing nutritional ketosis and achieving metabolic benefits, mice on KD exhibited increased activity, enhanced spatial learning and memory, and a trend toward improved spatial working memory. These cognitive benefits were accompanied by an attenuation of amyloid pathology and increased hippocampal neurogenesis. These findings suggest that a ketogenic diet may be safe and effective in Alzheimer's and dementia patients with CAA.

Neurometabolic signaling and control of policy complexity
Cognition and adaptive behavior emerge from neural information processing. This must operate within finite metabolic constraints, since neural information processing is metabolically expensive. While neural implementations of action selection and learning are well-studied, systems allocating the informational capacity required to encode complex behavioral policies remain unknown. We hypothesized that hypothalamic hypocretin/orexin neurons (HONs) are uniquely positioned to signal and control policy complexity, given that they are activated by metabolic depletion and influence decision-making systems. To explore this, we employed a set of cell/neurotransmitter-specific imaging and causal manipulations during a multi-armed bandit task where freely behaving mice learned probabilistic state-action-reward relationships (together ~100,000 decisions from >100 mice). Miniscope recordings of HON activity revealed that pre-choice, but not post-choice activity correlates with decision policy, dissociating decisions from feedback. Furthermore, manipulating HON signals with optogenetics and pharmacology confirmed that they causally regulate the development of complex policies. Finally, neurotransmitter-specific sensors revealed that hypocretin/orexin receptors modulate decision policy-related dopamine and noradrenaline dynamics in the nucleus accumbens and medial prefrontal cortex. These findings identify HONs as subcortical regulators of policy complexity, encoding critical signals for decision-making adjustments. This opens a new window for the development of comprehensive mechanistic models of strategic learning which account for interplay between decision-making policies and metabolic/informational constraints, and may guide the development of potential treatments for disorders with policy deficits such as autism and schizophrenia.

The pulvinar regulates plasticity in human visual cortex
In normally sighted human adults, two-hours of monocular deprivation is sufficient to transiently alter ocular dominance. Here we show that this is associated with a reduction of functional connectivity between the pulvinar and early visual cortex, selective for the pulvinar-to-V1 directionality. Our results support a revised model of adult V1 plasticity, where short-term reorganization is gated by modulatory signals relayed by the pulvinar.

Deciphering Cell-Type and Temporal-Specific Matrisome Expression Signatures in Human Cortical Development and Neurodevelopmental Disorders via scRNA-Seq Meta-Analysis
Human cortical development is a complex process involving the proliferation, differentiation, and migration of progenitor cells, all coordinated within a dynamic extracellular matrix (ECM). ECM plays a crucial role in guiding these processes, yet its specific contributions and the implications of its dysregulation in neurodevelopmental disorders (NDDs) remain underexplored. In this study, we conducted a meta-analysis of single-cell RNA sequencing (scRNA-seq) data from 37 donors, gestational weeks (GWs) 8 to 26 across six independent studies to elucidate cell type-specific matrisome gene expression signatures and their dynamics in the developing human cortex. Our analysis identified distinct matrisome gene signatures across various cell types, with significant temporal changes during cortical development. Notably, a substantial proportion of matrisome genes are associated with NDDs, exhibiting cell type, temporal and disease specificity. These findings highlight the critical role of cell type-specific matrisome regulation in cortical development and its potential involvement in NDD pathogenesis. This study provides a comprehensive map of cell type-specific matrisome signatures in the developing human cortex and highlights the importance of ECM in both normal development and the pathogenesis of NDDs.

Cell Type-Agnostic Transcriptomic Signatures Enable Uniform Comparisons of Neurodevelopment
Single-cell transcriptomics has revolutionized our understanding of neurodevelopmental cell identities, yet, predicting a cell type's developmental state from its transcriptome remains a challenge. We perform a meta-analysis of developing human brain datasets comprising over 2.8 million cells, identifying both tissue-level and cell-autonomous predictors of developmental age. While tissue composition predicts age within individual studies, it fails to generalize, whereas specific cell type proportions reliably track developmental time across datasets. Training regularized regression models to infer cell-autonomous maturation, we find that a cell type-agnostic model achieves the highest accuracy (error = 2.6 weeks), robustly capturing developmental dynamics across diverse cell types and datasets. This model generalizes to human neural organoids, accurately predicting normal developmental trajectories (R = 0.91) and disease-induced shifts in vitro. Furthermore, it extends to the developing mouse brain, revealing an accelerated developmental tempo relative to humans. Our work provides a unified framework for comparing neurodevelopment across contexts, model systems, and species.

Profiling brain morphology for autism spectrum disorder with two cross-culture large-scale consortia
We explore neurodevelopmental heterogeneity in Autism Spectrum Disorder (ASD) through normative modeling of cross-cultural cohorts. Leveraging large-scale datasets from Autism Brain Imaging Data Exchange (ABIDE) and China Autism Brain Imaging Consortium (CABIC), the model identifies two ASD subgroups with distinct brain morphological abnormalities: subgroup "L" is characterized by generally smaller brain region volumes and higher rates of abnormality, while subgroup "H" exhibits larger volumes with less pronounced deviations in specific areas. Key areas, such as the isthmus cingulate and transverse temporal gyrus, were identified as critical for subgroup differentiation and ASD trait correlations. In subgroup H, the regional volume of the isthmus cingulate cortex showed a direct correlation with individuals' autistic mannerisms, potentially corresponding to its slower post-peak volumetric declines during development. These findings offer insights into the biological mechanisms underlying ASD and support the advancement of subgroup-driven precision clinical practices.

Convergence of efficient and predictive coding in multimodal sensory processing
The existence of pathways connecting different sensory modalities in the brain challenges the traditional view of sensory systems as operating independently. However, the reasons and mechanisms underlying these interactions remain largely unknown, and no computational framework currently addresses these questions. We propose a theory of sensory processing in canonical circuits - networks of excitatory and inhibitory neurons ubiquitously found in the brain. Our theory incorporates cross-modal feedback and demonstrates that these networks can orchestrate precise mathematical computations through distinct circuit components. These computations generate neural codes that are simultaneously efficient and predictive, unifying two classical coding schemes. Our framework treats unimodal processing as a special case and accounts for olfactory-visual and auditory-somatosensory interactions observed in experiments, while offering new predictions about the role of neural feedback in optimizing multimodal codes. By bridging normative theories of sensory coding, this study provides insights into the principles governing interactions between the senses.

Head engagement during visuomotor tracking is determined by postural demands and aging
Vision is important for various tasks, from visually tracking moving objects to maintaining balance. People obtain visual information through eye movements performed either alone or in combination with head movements. Even when isolated eye movements can accommodate the amplitude of the desired gaze shift, humans still perform head movements, as they provide additional sensory signals that can be integrated with retinal input resulting in improved gaze estimates. However, head movements also create mechanical torques and attenuate vestibular processing that could disturb balance. We, therefore, here examined whether head engagement is determined by postural requirements when performing a visual tracking task. Young participants visually tracked a target moving horizontally along different amplitudes, while they were seated, standing on a firm and an unstable surface. Our results showed stronger head engagement when standing than sitting, but no systematic differences were found between firm and unstable surfaces. To further explore the interplay between head engagement and postural demands, we conducted a second experiment where young and older participants performed a similar task, but now they were either allowed to move their head or instructed to limit their head movements. Both tracking accuracy and postural sway increased when engaging the head. When asked to limit head movements, both age groups engaged their head minimally, but head movements were more pronounced in more challenging postures. When allowed to move their head naturally, younger participants engaged their head more when standing than sitting, but older adults reduced their head movements with more demanding postures. We suggest that head movements in younger adults facilitate visual tracking, while limited head movements in older adults preserve balance.

Exploiting the Angiotensin-Converting Enzyme Pathway to Augment Endogenous Opioid Signaling
Angiotensin Converting Enzyme (ACE) impacts hemodynamics by regulating the conversion of angiotensin I to the vasoconstricting angiotensin II. We recently identified a non-canonical central role of ACE in the degradation of enkephalin heptapeptide, Met-enkephalin-Arg-Phe (MERF). Enkephalins are short-lived, endogenous opioid peptides that mediate the body's intrinsic analgesic response. Here we identify chemically diverse ACE inhibitors using an optimized high throughput screening assay to boost endogenous opioid signaling. Our primary hits (thiorphan, D609, and raloxifene) were selected for dose-response characterization, in vitro enkephalin release, in vivo analgesic potency, and in silico analysis. Intracerebroventricular administration of these compounds significantly attenuated pain response, alone and in combination with MERF, which was reversed by opioid receptor antagonist naloxone. Molecular docking provided additional insight into the active site interactions of these scaffolds, which could be exploited further for creation of more potent inhibitors. These results showcase the potential of central ACE inhibitors to modulate endogenous MERF signalling.

Ultra-High Resolution TR-external EPIK with Deep Learning Image Reconstruction for Enhanced Characterisation of Cortical Depth-dependent Neural Activity
The detection of neural signals using functional MRI at the laminar or columnar level enables non-invasive exploration of fundamental brain function processing and the interconnected pathways within intracortical tissues. The growing interest in this research area is driven by advancements in fMRI acquisition techniques that enhance spatial resolution for high-fidelity mapping. However, the submillimetre voxel sizes commonly employed in layer-specific fMRI studies raise concerns about relatively low signal-to-noise ratios and increased image artefacts in reconstructed images, ultimately limiting the precise delineation of cortical depth-dependent functional activities. This work aims to address this issue by incorporating a deep learning technique for enhanced image reconstruction of the submillimetre fMRI data, acquired with echo-planar-imaging with keyhole (EPIK) combined with the repetition-time-external (TR-external) EPI phase correction scheme. Our network was trained in a self-supervised, scan-specific manner using the sampling strategy from zero-shot self-supervised learning (ZS-SSL) method, which has gained attention for high-resolution MR image reconstruction. Healthy volunteers participated in this study, and the performance of the developed method was evaluated in direct comparison to the conventional reconstruction method using datasets acquired at 7T. The deep learning reconstruction produced reconstructed images with significantly higher SNR than the conventional method, which was further quantitatively validated through histogram analysis. This enhancement was consistent across all slice locations, demonstrating the reliability of the scan-specific deep learning technique.

Boosting Hyperalignment Performance with Age-specific Templates
Hyperalignment aligns individual brain activity and functional connectivity patterns to a common, high-dimensional model space, resolving idiosyncrasies in functional-anatomical correspondence and revealing shared information encoded in fine-grained spatial patterns. Given that the brain undergoes significant developmental and functional changes over the lifespan, it is likely that certain features in brain functional organization are more prominent in certain age groups than others. In this study, we examined whether age-specific functional templates, as compared to a canonical template, could enhance alignment accuracy across diverse age groups. We used the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) dataset (18 to 87 yo) to build age-specific templates and tested their performance for analyzing data in young and old brains in both the Cam-CAN dataset and the Dallas Lifespan Brain Study (DLBS) dataset (20 to 90 yo). We found the congruent age-specific template outperforms the incongruent template for various analyses, including inter-subject correlation of hyperaligned connectivity profiles and predicting individualized connectomes using the template. The results are consistent across both datasets. This work enhances our understanding of age-related differences in brain function, highlights the benefits of creating age-specific templates to refine hyperalignment model performance, and may contribute to the development of age-sensitive diagnostic tools and interventions for neurological disorders.

Coding of the basic components of subjective value in primate dopamine neurons: subjectively weighted reward amount and probability
Behavioral choices of uncertain rewards suggest that agents construct subjective reward value by combining the basic value components of utility and weighted probability. Despite the general acceptance of this evaluation mechanism for explaining economic choice, knowledge about its neuronal implementation is fractionated and remains essentially unknown. We investigated in monkeys whether reward signals in dopamine neurons might represent subjective reward value based on these two fundamental value components. Despite some heterogeneity across individual neurons, the dopamine population signal reliably represented the axiomatically defined integration of utility and weighted probability into subjective value in a way that closely matched the animal-specific choice behavior. In particular, we identified a crucial contribution of subjectively weighted probability to the dopamine signal of subjective reward value. These data demonstrate a neuronal implementation of subjective value constructed from the two most basic subjective reward components.

Caloric restriction worsens decision-making impairments and gut dysbiosis after brain injury in male rats
Traumatic brain injury (TBI) causes long-term deficits in decision-making and disrupts the gut microbiome. Dysbiosis of the gut microbiome is a potential contributor to the development of multiple psychiatric and neurological disorders and may be a contributor to chronic symptoms from TBI. Caloric restriction is often used to assess psychiatric-related behaviors in animals, but also affects the gut microbiome. In the current study, we evaluated the effects of caloric restriction versus free feeding on a frontal controlled cortical impact TBI. Rats were trained on the rodent gambling task, an analog of the Iowa gambling task, to assess risk-based decision-making. The microbiome was sampled through the acute to subacute period post-injury and lesion size and microglia counts evaluated at 10 weeks post-injury. Caloric restriction did not affect decision-making at baseline, but did affect motivational variables. TBI impaired decision-making and this effect was exacerbated by caloric restriction. Other motivation-related variables followed a similar pattern of impairment with TBI driving impairments that were worsened by caloric restriction. The gut microbiome was initially dysbiotic, but largely recovered within 14 days post-injury. Despite this, acute gut measurements were predictive of chronic decision-making impairment. These data indicate a role for the gut microbiome in the evolution of TBI deficits and suggest that interventions targeting the gut may have a limited window of opportunity to treat long-term deficits.

Neurophysiological Correlates of Modifiable Dementia Risk Factors in Cognitively Unimpaired Older Adults
The 2024 Lancet Commission on Dementia estimates that up to 45% of dementia cases could be prevented by addressing modifiable risk factors, emphasising both prevention opportunities and the need to understand the biological mechanisms. This study investigated neurophysiological mechanisms underlying modifiable dementia risk factors in cognitively unimpaired older adults. Seventy-nine cognitively unimpaired older adults underwent MRI brain scans, with spectroscopy measurements taken from the sensorimotor cortex (SMC) and prefrontal cortex (PFC), using a Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy (HERMES) sequence, optimised for measuring GABA+. Modifiable dementia risk scores were calculated using the Assessment for Cognitive Health and Dementia Risk (CogDrisk). Hierarchical linear regression analyses revealed a significant negative relationship within the SMC, with lower GABA+ ({beta} = -0.249, p = 0.009) associated with higher risk scores. In the PFC, lower tNAA and tCho concentrations significantly predicted higher risk scores ({beta} = -0.168 and -0.170, respectively). These findings suggest that GABAergic system alterations may underlie the pathophysiology of modifiable dementia risk in healthy ageing, whilst changes in tNAA and tCho may reflect early alterations in neuronal integrity. These region-specific neurochemical findings may help identify potential early biomarkers for dementia risk, and suggest new therapeutic pathways for preventive interventions.

Glucose-dependent metabolism of hippocampal primary neurons in response to chemically induced long-term potentiation
Glucose is a predominant fuel for the brain supporting its high energy demand associated with neuronal signaling and synaptic activity. Long-term potentiation (LTP) is required for learning and memory formation by generating long lasting increase in synaptic strength and signal transmission between two neurons. While the electrophysiological bases of LTP are well established, much less is known about the metabolic demands of neurons involved in LTP. Common protocols used to examine synaptic activity rely on high glucose concentrations which are far from physiological glucose levels found in the brain. Here we used primary hippocampal neurons cultured under physiological (2.5 mM) and high (25 mM) glucose to investigate the metabolic effects of chemically induced LTP. Physiological glucose was associated with neuronal survival while high glucose promoted PAS granule accumulation. Changes in glucose altered extracellular lactate and pyruvate concentrations and affected key intracellular metabolic intermediates and neurotransmitter levels in neuronal cells without depleting the TCA cycle. LTP induction was comparable, but mitochondrial and neurotransmitter response to LTP was differentially affected physiological and high glucose conditions. Glycogen phosphorylase inhibition had minimal effects in physiological glucose but impaired synaptic responses and altered metabolite dynamics in high glucose. Our findings demonstrate that neuronal mitochondrial metabolism is closely linked to synaptic plasticity and highlight the importance of studying neurophysiological activity physiologically relevant glucose conditions.

Synthetic Diffusion Tensor Imaging Maps Generated by 2D and 3D Probabilistic Diffusion Models: Evaluation and Applications
Diffusion tensor imaging (DTI) is a key neuroimaging modality for assessing brain tissue microstructure, yet high-quality acquisitions are costly, time-intensive, and prone to artifacts. To address data scarcity and privacy concerns, and to augment the available data for training deep learning methods, synthetic DTI generation has gained interest. Specifically, denoising diffusion probabilistic models (DDPMs) have emerged as a promising approach due to their superior fidelity, diversity, controllability, and stability compared to generative adversarial networks (GANs) and variational autoencoders (VAEs). In this work, we evaluate the quality, fidelity and added value for downstream applications of synthetic DTI mean diffusivity (MD) maps generated by 2D slice-wise and 3D volume-wise DDPMs. We evaluate their computational efficiency and utility for data augmentation in two downstream tasks: sex classification and dementia classification using 2D and 3D convolutional neural networks (CNNs). Our findings show that 3D synthesis outperforms 2D slice-wise generation in downstream tasks. We present a benchmark analysis of synthetic diffusion-weighted imaging approaches, highlighting key trade-offs in image quality, diversity, efficiency, and downstream performance.

Saccadic Suppression Enhances Saliency of Prey-Like Stimuli in the Optic Tectum
Saccadic suppression, a reduction in visual sensitivity around the time of a rapid eye movement, is a robust perceptual phenomenon, extensively studied in primate psychophysics. However, the mechanisms and purpose of saccadic suppression are still debated in the field. Here, we demonstrate saccadic suppression in zebrafish, and trace its origins not only in retinal circuits, but also in downstream visual and motor-related neurons of the optic tectum. Using electrophysiology, we first established that retinal ganglion cells jumpstart saccadic suppression, in a spatial frequency dependent manner. Calcium imaging of the optic tectum, combined with 360{degrees} visual stimulation and behavioral tracking, revealed that motor signals enhance peri-saccadic suppression strength up to 0.5 s after the saccade. Notably, vision-mediated saccadic suppression lasts more than 3 s. Suppression strength depends on saccade size. Interestingly, we found much weaker saccadic suppression in the optic tectum for stimuli related to hunting behavior than for behaviorally less relevant global flashes, suggesting a selectivity of saccadic suppression aimed at increasing the salience of particular types of visual stimuli after saccades. These findings demonstrate that saccadic suppression in zebrafish integrates visual and motor signals to optimize sensory processing within neural constraints, providing insights into evolutionarily conserved visual strategies.

Simons Sleep Project (SSP): An open science resource for accelerating scalable digital health research in autism and other psychiatric conditions
Wearable and nearable devices offer a novel opportunity to measure extensive behavioral and neurophysiological data directly from participants in their home environment. The Simons Sleep Project (SSP) was designed to accelerate research into sleep and daily behaviors in individuals with autism using such techniques. This open-science resource contains raw and processed data from Dreem3 EEG headbands, multi-sensor EmbracePlus smartwatches, and Withings Sleep mats, as well as parent questionnaires and daily sleep diaries. Data were collected successfully for >3600 days/nights from 102 adolescents (10-17 years old) with idiopathic autism and 98 of their non-autistic siblings. Whole-exome sequencing data is also available for all participants and their parents. To demonstrate the utility of this extensive dataset, we first present the breadth of synchronized high-resolution data available across multiple sensors/devices. We then demonstrate that objective sleep measures (e.g., total sleep time) from the three devices are more accurate and reliable than parent reported measures and reveal that sleep onset latency (SOL) was the only objectively defined sleep measure that differed significantly between autistic children and their siblings (of those examined in the study). Moreover, SOL was reliably associated with the severity of multiple behavioral difficulties in all children, regardless of autism diagnosis. These results highlight the importance of measuring sleep directly from participants using objective measures and demonstrate the extensive opportunities afforded by the SSP to further study autism and develop new digital phenotyping techniques for multiple research domains.

Shared computational principles for mouse superior colliculus and primate population orientation selectivity
While the mouse visual system is known to differ substantially from the primate, if the two systems share computational principles, then generalization of results across species may still be possible. One prominent difference is that orientation selectivity is found in mouse superficial superior colliculus (SC), but is not commonly observed in primate SC. Nevertheless, there may be conservation of computational principles if orientation selectivity in mouse superficial SC displays similar properties to primate visual cortex (V1), such as invariance to differences in other stimulus dimensions. However, a recent calcium (Ca2+) imaging study revealed a population map for stimulus orientation in mouse superficial SC that changed with stimulus properties such as size, shape and spatial frequency, in apparent contradistinction to the computational principles for orientation selectivity in primates. To reconcile the mouse and primate mechanisms for orientation selectivity, we constructed computational models of mouse superficial SC populations with the fixed, stimulus-invariant receptive fields classically used to describe neural receptive fields in monkey lateral geniculate nucleus (LGN) and V1. We found that simulated neural responses reproduced the patterns of stimulus-dependent orientation selectivity from the imaging data. Our models provide a parsimonious explanation for stimulus-dependent orientation selectivity consistent with well-established results from sensory neurophysiology.

Endoplasmic reticulum stress protein GRP78 for ketamine's antidepressant effects
Ketamine is a fast-acting, long-lasting novel antidepressant. However, underpinning intracellular mechanisms remain unclear. We conducted an unbiased screening for genes that were less expressed in the prefrontal cortex (PFC) of mice that did not display antidepression-like effects to ketamine. GO analysis implicated endoplasmic reticulum and protein folding; in particular, GRP78, a stress-induced chaperone protein critical for protein folding, was reduced. We showed that GRP78 deficiency in PFC neurons induced depressive-like behaviors, whereas its overexpression produced anti-depression-like effects, revealing a novel function of GRP78. Prefrontal GRP78 was necessary for ketamine's antidepressant-like effects. GRP78 was also required for ketamine to increase calcium activity and glutamatergic transmission. Enhancing GRP78 by viral infection and azoramide enabled non-responsive mice to respond to ketamine. Together, our results demonstrate that GRP78 is critical for ketamine to execute antidepressant effects by potentiating glutamatergic transmission in the PFC.

Layer connective fields from ultrafast resting-state fMRI differentiate feedforward from feedback signaling
Deciphering the directionality of information flow in cortical circuits is essential for understanding brain dynamics, learning, and neuroplasticity after injury. However, current non-invasive methods cannot distinguish feedforward (FF) from feedback (FB) signals across entire networks, including deep brain regions. Here, we present a novel approach combining ultrafast fMRI with a Layer-based Connective Field (lCF) model to disentangle FF from FB signaling. Our findings reveal that lCF size, an indicator of spatial information integration, differentiates FF and FB activity through distinct layer-specific connectivity patterns during spontaneous activity, challenging the notion that FF signals are solely stimulus-driven. FF connectivity follows an inverted U-shape, peaking in layer IV, while FB exhibits a U-shaped pattern, with peaks in layers I and VI. These profiles generalize across sensory pathways (visual, somatosensory, and motor) and reveal injury-induced network reorganization, such as LGN bypassing V1 to provide direct FF input to higher visual areas.

Deep Learning to Predict Future Cognitive Decline: A Multimodal Approach Using Brain MRI and Clinical Data
Predicting the trajectory of clinical decline in aging individuals is a pressing challenge, especially for people with mild cognitive impairment, Alzheimer's disease, Parkinson's disease, or vascular dementia. Accurate predictions can guide treatment decisions, identify risk factors, and optimize clinical trials. In this study, we compared two deep learning approaches for forecasting changes, over a 2-year interval, in the Clinical Dementia Rating scale 'sum of boxes' score (sobCDR). This is a key metric in dementia research, and scores range from 0 (no impairment) to 18 (severe impairment). To predict decline, we trained a hybrid convolutional neural network that integrates 3D T1-weighted brain MRI scans with tabular clinical and demographic features (including age, sex, body mass index (BMI), and baseline sobCDR). We benchmarked its performance against AutoGluon, an automated multimodal machine learning framework that selects an appropriate neural network architecture. Our results demonstrate the importance of combining image and tabular data in predictive modeling for clinical applications. Deep learning algorithms can fuse image-based brain signatures and tabular clinical data, with potential for personalized prognostics in aging and dementia.

Astrocytic MAOB-GABA axis as a molecular brake on repair following spinal cord injury
Neuroregeneration and remyelination rarely occur in the adult mammalian brain and spinal cord following central nervous system (CNS) injury. The glial scar has been proposed as a major contributor to this failure in the regenerative process. However, its underlying molecular and cellular mechanisms remain unclear. Here, we report that monoamine oxidase B (MAOB)-dependent excessive GABA release from reactive astrocytes suppresses CNS repair system by reducing BDNF and TrkB expression in severe spinal cord injury (SCI) animal models. Genetic deletion of MAOB in a mouse SCI model promotes both functional and tissue recovery. Notably, the selective MAOB inhibitor, KDS2010, facilitates recovery and regeneration by disinhibiting the BDNF-TrkB axis in a rat SCI model. Its dose-dependent effects were further validated in a monkey SCI model. Moreover, KDS2010 demonstrates a tolerable safety profile and dose-proportional pharmacokinetics in healthy humans during a phase 1 clinical trial. Our findings identify the astrocytic MAOB-GABA axis as a crucial molecular and cellular brake on CNS repair system following SCI and highlight translational potential of KDS2010 as a promising therapeutic candidate for SCI treatment.

Episodic pain in Fabry disease is mediated by a heat shock protein-TRPA1 axis.
Two-thirds of patients with Fabry disease suffer debilitating pain attacks triggered by exercise, fever, and exposure to environmental heat. These patients face endure even greater risk of heat-related episodic pain in the face of global climate change. Almost nothing is known about the biological mechanisms underlying heat-induced pain crises in Fabry disease, and there is no preclinical model available for to study Fabry crises. Here, we established the first model of heat-induced pain attacks in Fabry disease by exposing transgenic Fabry rats to environmental heat. Heat exposure precipitated robust mechanical hypersensitivity, closely matching temporal features reported by patients with Fabry disease. At the cellular level, heat exposure sensitized Fabry dorsal root ganglia (DRG) neurons to agonists for transient receptor potential cation channel A1 (TRPA1), but not TRPV1. The heat shock response, which normally confers heat-resilience, was impaired in Fabry disease, and we demonstrated that heat shock proteins (HSP70 and HSP90) regulate TRPA1. Strikingly, pharmacologically inhibiting HSP90 completely prevented cellular and behavioral sensitization by environmental heat in Fabry disease. Together, this work establishes the first model of episodic pain in Fabry disease, implicates the heat shock response in heat-evoked pain episodes, and identifies a novel heat shock protein-TRPA1 regulatory axis.

Decoding peripheral saccade targets from foveal retinotopic cortex
Human vision is characterized by frequent eye movements. This causes continuous shifts in visual input, yet visual perception appears highly stable. A potential mechanism behind this stability is foveal prediction, involving feedback from higher cortical areas during saccade preparation. However, it remains unknown (1) whether information is fed back to early visual areas, (2) whether feedback is specific to stimulus features, and (3) which brain regions mediate this effect. To dissociate neural processes associated with stimulus presentation from those related to foveal feedback, we designed a gaze-contingent fMRI paradigm, where saccade targets are removed before they can be foveated. To determine the content of the neural representation, we used natural images as saccade targets and independently manipulated object shape and category. Multivariate analyzes revealed reliable decoding of stimuli from foveal retinotopic areas as early as V1, even though the stimulus never appeared in the fovea. Decoding was sensitive to shape but not semantic category, indicating that only low-to-mid-level information is fed back. Cross-decoding to a control condition with foveal stimulus presentation yielded reliable decoding, indicating a similar neural representation between foveal feedback and direct stimulation. Eccentricity-dependent analyzes showed a u-shaped decoding curve, confirming that these results are not explained by spillover of peripheral activity or large receptive fields. Moreover, fluctuations in foveal decodability correlated with activity in the intraparietal sulcus, a candidate region for driving this foveal feedback. These findings go beyond trans-saccadic remapping by suggesting that peripheral saccade targets are encoded in the foveal cortex in a feature-specific representation.

Initiation and maturation of the early axonal βII-spectrin membrane-associated periodic skeleton requires active cytoskeletal remodelling
The axonal membrane-associated periodic skeletal (MPS) consisting of evenly spaced F-actin rings crosslinked by spectrin heterotetramers has been observed in many neuronal subtypes across multiple species. The MPS has been implicated in a diversity of functions ranging from a load-bearing tension buffer to a periodic ruler positioning channels and signalling complexes. However, the initiation and early development of the axonal MPS are poorly understood. Using superresolution imaging of embryonic dorsal root ganglion axons, we show that the early development of the {beta}II-spectrin MPS involves recruitment and stabilisation of the {beta}II-spectrin to the axonal cortex followed by progressive establishment of long-range periodic order. Microtubule dynamics are essential for MPS formation in the early stages, while microtubules have a passive stabilizing function in the mature MPS. We show that the early subplasmalemmal recruitment and confinement of {beta}II-spectrin is dependent on cortical actin. Further, active nucleation of F-actin is required in early development but dispensable for the maintenance of the mature MPS. Finally, using a {beta}II-spectrin knockout model, we demonstrate that the actin-binding and lipid interacting domains of {beta}II-spectrin are critical for its subplasmalemmal confinement and, subsequently, MPS maturation. Our study provides insights into the mechanisms governing the development and maturation of the axonal MPS, highlighting the critical role of cytoskeletal dynamics.

Multiple Neural Modules Orchestrate Conflict Processing
Cognitive conflict is a ubiquitous aspect of our daily life, yet its underlying neural mechanisms remain debated. Competing theories propose that conflict processing is governed by either a domain-general system, multiple conflict-specific modules, or both types of systems, as evidenced by hybrid accounts. The aim of the current study was to settle this debate. We analyzed electroencephalogram (EEG) data from 507 participants (ages 20-70) who completed three conflict tasks: a change detection, a Simon, and a Stroop task. A novel decoding approach was adopted to distinguish between conflict and non-conflict trials. While within-task decoding showed robust effects, decoding across tasks yielded chance-level evidence. These findings support the idea that conflict processing relies on multiple conflict specific modules tailored to task-specific demands. By leveraging a large, diverse sample and a data-driven analysis, this study provides compelling evidence for conflict-specific neural mechanisms, offering new insights into the nature of conflict resolution and cognitive control.

Modeling Pyramidal Neurons Using Bidomain BEM and Hierarchical Matrix Approximation
Electromagnetic brain stimulation uses electrodes or coils to induce electric fields (E-fields) in the brain and affect its activity. Our understanding of the precise effects of the device-induced E-fields on neural activity is limited. In this work, we present a novel boundary integral equation that enables the modeling of fully coupled E-fields from both neurons and stimulation devices. This boundary element approach is accelerated using fast direct solvers to allow for the analysis of realistic scenarios. We present examples, indicating the ability of our solver to analyze rat L2/3 pyramidal neurons derived from the blue brain project.

β-Amyloid Induces Microglial Expression of GPC4 and APOE Leading to Increased Neuronal Tau Pathology and Toxicity
To elucidate the impact of A{beta} pathology on microglia in Alzheimer's disease pathogenesis, we profiled the microglia surfaceome following treatment with A{beta} fibrils. Our findings reveal that A{beta}-associated human microglia upregulate Glypican 4 (GPC4), a GPI-anchored heparan sulfate proteoglycan (HSPG). In a Drosophila amyloidosis model, glial GPC4 expression exacerbates motor deficits and reduces lifespan, indicating that glial GPC4 contributes to a toxic cellular program during neurodegeneration. In cell culture, GPC4 enhances microglia phagocytosis of tau aggregates, and shed GPC4 can act in trans to facilitate tau aggregate uptake and seeding in neurons. Additionally, our data demonstrate that GPC4-mediated effects are amplified in the presence of APOE. These studies offer a mechanistic framework linking A{beta} and tau pathology through microglial HSPGs and APOE.

Persistent dopamine-dependent remodeling of the neural transcriptome in response to pregnancy and postpartum
Pregnancy and postpartum experiences represent transformative physiological states that impose lasting demands on the maternal body and brain, resulting in lifelong neural adaptations. However, the precise molecular mechanisms driving these persistent alterations remain poorly understood. Here, we used brain-wide transcriptomic profiling to define the molecular landscape of parity-induced neural plasticity, identifying the dorsal hippocampus (dHpc) as a key site of transcriptional remodeling. Combining single-cell RNA sequencing with a maternal-pup separation paradigm, we additionally demonstrated that chronic postpartum stress significantly disrupts dHpc adaptations by altering dopamine dynamics, leading to dysregulated transcription, altered cellular plasticity, and impaired behavior. We further established the sufficiency of dopamine modulation in the regulation of these parity-induced adaptations via chemogenetic suppression of dopamine release into dHpc, which recapitulated key transcriptional and behavioral features of parity in virgin females. In sum, our findings establish dopamine as a central regulator of parity-induced neuroadaptations, revealing a fundamental transcriptional mechanism by which female reproductive experiences remodel the maternal brain to sustain long-term behavioral adaptations.

Social housing effects of Intermittent Access of Methamphetamine Self-administration and social behavior
Social support is a potentially protective factor against substance use disorders (SUDs). Previous studies in animal models for SUDs have shown that when females are pair housed, they have lower motivation for cocaine and methamphetamine (METH), than females who are single housed. In males, however, social housing has not had the same beneficial effect. This study investigates effects of social housing on METH self-administration in females or males when both cagemates are self-administering METH. The study also investigated how the quality of those relationships changed after METH self-administration. The results showed that singly housed females self-administered more METH than socially housed females, while males in both social housing conditions self-administered METH at the same rate. The social behavior data showed that females given saline spend more time apart, however the females given METH spend more time together, suggesting that their social behavior may play a role in the attenuation of METH self-administration. Males' social behavior remained unchanged after METH. Males METH self-administration was affected by whether they were the dominant partner, while females' self-administration was not affected by dominance. The results of this study showed that social housing provides some protective benefits to females, not males, for METH self-administration. Further, the type of relationship between cage mates affects males' self-administration and may explain why social housing with a same sex mate is not beneficial for males.

Interdigitating Modules for Visual Processing During Locomotion and Rest in Mouse V1
Layer 1 of V1 has been shown to receive locomotion-related signals from the dorsal lateral geniculate (dLGN) and lateral posterior (LP) thalamic nuclei (Roth et al., 2016). Inputs from the dLGN terminate in M2+ patches while inputs from LP target M2- interpatches (DSouza et al., 2019) suggesting that motion related signals are processed in distinct networks. Here, we investigated by calcium imaging in head-fixed awake mice whether L2/3 neurons underneath L1 M2+ and M2- modules are differentially activated by locomotion, and whether distinct networks of feedback connections from higher cortical areas to L1 may contribute to these differences. We found that strongly locomotion-modulated cell clusters during visual stimulation were aligned with M2- interpatches, while weakly modulated cells clustered under M2+ patches. Unlike M2+ patch cells, pairs of M2- interpatch cells showed increased correlated variability of calcium transients when the sites in the visuotopic map were far apart, suggesting that activity is integrated across large parts of the visual field. Pathway tracing further suggests that strong locomotion modulation in L2/3 M2- interpatch cells of V1 relies on looped, like-to-like networks between apical dendrites of MOs-, PM- and RSP-projecting neurons and feedback input from these areas to L1. M2- interpatches receive strong inputs from SST neurons, suggesting that during locomotion these interneurons influence the firing of specific subnetworks by controlling the excitability of apical dendrites in M2- interpatches.

Dynamic reconfiguration of brain coactivation states associated with active and lecture-based learning of university physics
Academic institutions are increasingly adopting active learning methods to enhance educational outcomes. Using functional magnetic resonance imaging (fMRI), we investigated neurobiological differences between active learning and traditional lecture-based approaches in university physics education. Undergraduate students enrolled in an introductory physics course underwent an fMRI session before and after a 15-week semester. Coactivation pattern (CAP) analysis was used to examine the temporal dynamics of brain states across different cognitive contexts, including physics conceptual reasoning, physics knowledge retrieval, and rest. CAP results identified seven distinct brain states, with contributions from frontoparietal, somatomotor, and visuospatial networks. Among active learning students, physics learning was associated with increased engagement of a somatomotor network, supporting an embodied cognition framework, while lecture-based students demonstrated stronger engagement of a visuospatial network, consistent with observational learning. These findings suggest significant neural restructuring over a semester of physics learning, with different instructional approaches preferentially modulating distinct patterns of brain dynamics.

Dopaminergic Modulation of Short-Term Associative Memory in Caenorhabditis elegans
Forgetting, the inability to retrieve previously encoded memories, is an active process involving neurotransmission, second messenger signalling, and cytoskeletal modifications. Forgetting is thought to be essential to remove irrelevant memories and to increase the capacity to encode new memories. Therefore, identifying key regulators of active forgetting is crucial to advance our understanding of neuroplasticity. In this study, we utilised the compact and tractable Caenorhabditis elegans model to investigate the role of the neurotransmitter dopamine in forgetting. We conducted butanone associative learning assays based on an established protocol and used mutant strains deficient in dopamine synthesis (tyrosine hydroxylase CAT-2 and dopamine transporter DAT-1) and signalling (G protein-coupled receptors DOP-1, DOP-2, and DOP-3) to assess the impact on learning and memory retention. Learning was measured immediately post-training, and memory retention was evaluated every 0.5 hours up to 2 hours. Our results show that animals lacking dopamine display a modest enhancement in learning relative to wild-type, with the learned association persisting for at least 2 hours after training. We also found that the D2-like receptors DOP-2 and DOP-3 function together to modulate the forgetting process, with D1-like receptor DOP-1 having an antagonistic effect. Furthermore, re-expression of CAT-2 tyrosine hydroxylase in ADE or CEP neurons showed that dopamine synthesis in both neuron types is essential for short-term memory retention, albeit at different time points after learning. These findings highlight the critical role of dopamine in forgetting, consistent with findings in Drosophila, and suggest potential relevance for understanding memory retention during healthy ageing and in conditions with dopamine imbalances such as Parkinson's disease.

Brain stimulation preferentially influences long-range projections in primates
Advances in brain stimulation have made it possible to target smaller and smaller regions for electromagnetic stimulation, in the hopes of producing increasingly focal neural effects. However, the brain is extensively interconnected, and the neurons comprising those connections may themselves be particularly susceptible to neurostimulation. Here, we test this hypothesis using single-unit recordings from alert non-human primates receiving transcranial electrical stimulation. We find that putative long-range projections (i.e., axons) are more strongly affected by stimulation than other cell types. These data suggest the need for alternate stimulation strategies that target the edges, rather than nodes, of neural networks.

Co-adaptive training improves performance during fMRI decoded neurofeedback
A significant challenge for neurofeedback training research and related clinical applications, is participants difficulty in learning to induce specific brain patterns during training. Here, we address this issue in the context of fMRI-based decoded neurofeedback (DecNef). Arguably, the discrepancies between the data used to construct the decoder and the data used for neurofeedback training, such as differences in data distributions and experimental contexts, are likely the cause of aforementioned participants difficulties. We developed a co-adaptation procedure using standard machine learning algorithms. First, we tested the procedure via simulations using a previous DecNef dataset. The procedure involves an adaptive decoder algorithm that is updated in real time based on its predictions across neurofeedback trials. The results showed a significant improvement in decoder performance during neurofeedback training, thereby enhancing the learning curve. We then collected real time fMRI data in a DecNef training procedure to provide proof of concept evidence that co-adaptation enhanced participants ability to induce the target state during training. Thus, personalized decoders through co-adaptation can improve the precision and reliability of DecNef training protocols to target specific brain representations, with ramifications in translational research. The tools are made openly available to the scientific community.

Dynamic fingerprinting of the human functional connectome
Resting-state functional connectivity (FC) have distinct, personalized patterns that could serve as a unique fingerprint of each individual's brain. While previous brain fingerprinting methods have used functional connectivity maps over a scanning session (static method), it has been shown that the brain is a dynamic system that switches between several metastable states, each of which having a different FC map. Taking the dynamic nature of brain connectivity into account will likely lead to more subject-specific information and better individual identification. In this paper, we derived the state-specific FCs using sliding window correlation and clustering and evaluated their performance in individual identification and cognitive score prediction. The resultant dynamic fingerprints outperformed the static fingerprints in identification accuracy. Furthermore, some of the brain states were more accurate in predicting cognitive scores, indicating that connectivity in some brain states is informative of cognition abilities, possibly useful as biomarkers for brain disorders.

The 16p11.2 microdeletion influences how early-life microbiota perturbations affect hippocampal development and behavior throughout the lifespan
Neurodevelopmental disorders result from interactions between genetic predisposition and environmental risk factors, with infancy being the most vulnerable period. We designed a longitudinal study to determine how short-term antibiotic exposure during early postnatal life impacts the gut microbiome, neurodevelopment, and behavior, and whether these alterations were exacerbated by the neurodevelopmental disorder-associated 16p11.2 microdeletion (16pDel) mutation. The cephalosporin antibiotic, cefdinir, broadly altered the gut microbiome acutely, with persistent reductions in several Lachnospiraceae genera despite overall recovery. These alterations preceded long-term behavioral changes, including reduced juvenile sociability, compromised risk assessment, and deficits in associative learning. Remarkably, only cefdinir-exposed 16pDel mice had changes in hippocampal stem cell proliferation, subsequent adolescent cell numbers, and gene expression compared to other groups, demonstrating that genetic predisposition can modulate the effects of early-life antibiotic exposure on neurodevelopment. These alterations may be mediated by gastrointestinal disturbances, as cefdinir-exposed 16pDel males had increased intestinal permeability and shifted metabolite profiles including arginine biosynthesis and glycerophospholipid metabolism. Taken together, this study highlights how early-life microbial alterations affect behavior and reveals that genetic predisposition influences antibiotic-induced changes in hippocampal development. Further, these insights identify metabolic mechanisms as potential targets for intervention and may raise concerns regarding antibiotic use during infancy.

Structured Gamma Spikes in Mouse Anterodorsal Thalamus
Gamma-frequency oscillations (~30-160 Hz) are a hallmark of neuronal synchronization, yet the fine-scale temporal arrangement of spikes within individual gamma cycles remains poorly understood. Here, we examine head direction (HD) cells in the mouse anterodorsal thalamic nucleus (ADn)---a circuit distinguished by prominent high-gamma activity---to uncover the principles governing gamma coordination. We reveal two fundamental mechanisms: (i) a stable anatomical gradient in which neurons firing earlier in the gamma cycle exhibit longer anticipatory time intervals (ATIs), and (ii) a dynamic rate-phase shift whereby spike timing advances as the animal's head aligns with a neuron's preferred direction. Together, these results delineate a spatiotemporally structured framework for gamma synchronization, advancing our understanding of the functional roles and circuit mechanisms underlying gamma rhythms in local brain networks.

Efficient Prospective Electric Field-Informed Localization of Motor Cortical Targets of Transcranial Magnetic Stimulation
Transcranial magnetic stimulation (TMS) is a versatile non-invasive tool for brain mapping and neuromodulation in both healthy individuals and patients. Effective TMS-based causal brain mapping relies on precise localization of cortical targets. Current state-of-the-art approaches use statistical methods to quantify the relationship between TMS-induced electric fields (E-fields) and motor evoked potential (MEP) amplitudes. However, this method typically relies on the random selection of coil configurations, which limits its efficacy. In this study, we present a novel optimization strategy for TMS-based motor mapping by prospectively selecting coil configurations based on their E-field characteristics using an iterative sampling algorithm called farthest point sampling (FPS). Through a combination of theoretical analysis, simulation and experimental validation including 10 healthy individuals, we systematically evaluated the performance of FPS against the random sampling approach. Our results demonstrate that FPS is twice as efficient as random sampling in reducing the number of trials required for estimating the motor map, while also being more robust across participants and less susceptible to noise. These findings highlight the potential of FPS to significantly enhance the efficiency of motor mapping, paving the way for the development of more effective TMS mapping algorithms.

Designing new natural-mimetic phosphatidic acid: aversatile and innovative synthetic strategy forglycerophospholipid research
Glycerophospholipids (GPLs) play important roles in cellular compartmentalization and signaling. Among them, phosphatidic acids (PA) exist as many distinct species depending on acyl chain composition, each one potentially displaying unique signaling function. Although the signaling functions of PA have already been demonstrated in multiple cellular processes, the specific roles of individual PA species remain obscure due to a lack of appropriate tools. Indeed, current synthetic PA analogues fail to preserve all the functions of natural PA. To circumvent these limitations, we developed a novel synthetic approach to produce PA analogues without compromising structural integrity of acyl chains. Moreover, addition of a clickable moiety allowed flexible grafting of different molecules to PA analogues for various biological applications. Hence, this innovation also provides powerful tools to investigate specific biological activities of individual PA species, with potential applications in unraveling complex GPL-mediated signaling pathways.

Sleep Resolves Competition Between Explicit and Implicit Memory Systems
Sleep supports stabilization of explicit, declarative memory and benefits implicit, procedural memory. In addition, sleep may change the quality of memory representations. Explicit and implicit learning systems, usually linked to the hippocampus and striatum, can compete during learning, but whether they continue to interact during offline periods remains unclear. Here, we investigate for feedback-driven classification learning, whether sleep integrates explicit and implicit aspects of memory. The negative relationship between implicit and explicit memory components was resolved over sleep, but not wakefulness. Additionally, sleep benefitted performance on a task that allows the cooperative use of explicit and implicit memory, and participants who slept showed superior performance in generalizing their knowledge to unseen exemplars. A reinforcement learning model relates this to better transfer of the learned exemplar value representation after sleep. This suggests that sleep integrates information learned by different routes and helps us respond optimally to everyday life contingencies.

Multimodal characterization and optogenetic potential of the bistable Gi/o-coupled vertebrate ancient opsin from the flashlight fish Anomalops katoptron
Vertebrate ancient long opsin, or VAL opsin, is a light-sensitive protein that is found within and outside the visual system in vertebrates. In accordance with its wide distribution in the retina, brain, testis and skin, VAL is suggested to play a role in light-dependent physiological processes that are beyond vision. However, many aspects of the physiological properties and specific functions of VAL remain unclear. Here we identified and characterized the VAL opsin from the flashlight fish Anomalops katoptron (AkVAL) and show that this opsin is bistable and reversibly converts between active and inactive states by responding to cycles of green and blue/UV lights. We further show that AkVAL couples to the Gi/o pathway and controls the activity of GIRK channels in a bistable manner. In line with this, we demonstrated that AkVAL modulates neu-ronal activity in cerebellar Purkinje cells, where neuronal activity is reduced by UV/blue light and increased by green/red light illumination. In addition, upon the in vivo expression of AkVAL in neurons innervating body muscles of Caenorhabditis elegans the worms body movement can be bidirectionally controlled altering blue/UV and green illuminations. These data highlight the potential of AkVAL as an optogenetic tool to control cells in vitro and in vivo, in a bistable man-ner.

Dysfunction-specific Mechanisms Critically Influence Seizure Onset and Termination in Epilepsy
Epileptic seizures arise from an abnormal synchronous firing of neurons, driven by an imbalance between excitatory and inhibitory neurotransmission. Understanding how various dysfunctions influence brain dynamics is essential for uncovering seizure mechanisms and developing effective treatments. Here, we present a neural mass model that combines an intuitive mathematical formulation with a clear biophysical interpretation to examine the role of excitatory and inhibitory dysfunctions in seizure onset and termination. We model the propagation of action potentials in the brain like the spread of an epidemic and establish a framework examining the interaction between one excitatory and one inhibitory population. Our model captures equilibria that correspond to different levels of neuronal activity: the equilibrium with maximal excitatory activity represents a seizure, and the equilibrium with minimal, non-zero neuronal activity represents normal brain activity. We then introduce various dysfunctions into the model such as an excessive drive to the excitatory population, depletion of inhibitory neurotransmitters, and depolarizing GABAergic neurotransmission and demonstrate that these dysfunctions can facilitate the transition from normal activity to seizure. Crucially, we show that interventions that only target the inhibitory neurotransmitter GABA fail to terminate a seizure when GABA is depolarising, whereas interventions targeting excitatory neurotransmission, such as levetiracetam, are more effective. Our findings highlight the importance of tailoring interventions to the specific underlying dysfunctions for effective seizure termination.

Unconscious Neural Activity Predicts Overt Attention in Visual Search
Unconscious neural activity has been shown to precede both motor and cognitive acts. In the present study, we investigated the neural antecedents of overt attention during visual search, where subjects make voluntary saccadic eye movements to search a cluttered stimulus array for a target item. Building on studies of both overt self-generated motor actions (Lau et al., 2004, Soon et al., 2008) and self-generated cognitive actions (Bengson et al., 2014, Soon et al., 2013), we hypothesized that brain activity prior to the onset of a search array would predict the direction of the first saccade during unguided visual search. Because both spatial attention and gaze are coordinated during visual search, both cognition and motor actions are coupled during visual search. A well-established finding in fMRI studies of willed action is that neural antecedents of the intention to make a motor act (e.g., reaching) can be identified seconds before the action occurs. Studies of the volitional control of covert spatial attention in EEG have shown that predictive brain activity is limited to only a few hundred milliseconds before a voluntary shift of covert spatial attention. In the present study, the visual search task and stimuli were designed so that subjects could not predict the onset of the search array. Perceptual task difficulty was high, such that they could not locate the target using covert attention alone, thus requiring overt shifts of attention (saccades) to carry out the visual search. If the first saccade to the array onset in unguided visual search shares mechanisms with willed shifts of covert attention, we expected predictive EEG alpha-band activity (8-12 Hz) immediately prior to the array onset (within 1 sec) (Bengson et al., 2014; Nadra et al., 2023). Alternatively, if they follow the principles of willed motor actions, predictive neural signals should be reflected in broadband EEG activity (Libet et al., 1983) and would likely emerge earlier (Soon et al., 2008). Applying support vector machine decoding, we found that the direction of the first saccade in an unguided visual search could be predicted up to two seconds preceding the search array's onset in the broadband but not alpha-band EEG. These findings suggest that self-directed eye movements in visual search emerge from early preparatory neural activity more akin to willed motor actions than to covert willed attention. This highlights a distinct role for unconscious neural dynamics in shaping visual search behavior.

Concurrent selection of internal goals and external sensations during visual search
Flexible goal-directed behaviour relies on the selective processing of internal goal representations and external sensations. Yet, internal and external selection processes have classically been studied in isolation, leaving us in the dark how internal and external selection processes are coordinated in time to support behaviour. To address this, we developed a novel visual-search task in which we could simultaneously track selection among internal search goals held in working memory and external search targets in the environment. Capitalising on sensitive gaze and neural markers of internal and external visual selection, we provide proof-of-principle evidence in humans that internal and external selection processes do not necessarily take turns in a strictly serial manner, but can develop concurrently. We further show how concurrent internal and external selection processes are associated with largely non-overlapping neural activity patterns in the human brain, and how these processes can be performed effectively even when engaging opposite spatial locations in working memory and perception. These findings challenge views portraying brain states as being either internally or externally focused and bring new insight into how internal and external selection processes work together to yield efficient search behaviour.

MMP-2/9 inhibition modulates sharp wave abundance, inhibitory proteoglycan sulfation, and fear memory in juvenile zebrafish: relevance to affective disorders
Sharp wave ripple (SWR) events, present in diverse species, spontaneously occur in the hippocampus during quiescent restfulness and slow-wave sleep. SWRs comprise a negative deflection, the sharp wave (SW) event with an often-superimposed ripple (R) and are the neural correlates of memory consolidation and recall. The Anterodorsolateral lobe (ADL) (zebrafish hippocampal homologue) exhibits SW and SWR events, and since SWs initiate SWRs, their abundance typically shows the same directionality. In previous work, we observed matrix metalloproteinase-9 (MMP-9)-dependent effects on depression-relevant behaviors, perineuronal net (PNN) levels, and SWR abundance in the adult rodent hippocampus. Here, we investigate MMP-2/9-dependent effects on biochemical, behavioral, and neurophysiological endpoints in juvenile zebrafish and zebrafish at the transition from the late juvenile period to early adulthood. With MMP-2/9 inhibition, juvenile zebrafish showed reduced SW amplitude and abundance together with increased fear memory retention and reduced sociability. Juvenile zebrafish also showed an increased percentage of longer-duration SW events. Except for a reduction in SW amplitude, these changes were not observed at the transition from late juvenile to early adulthood. These changes were accompanied by increased levels of chondroitin sulfate (CS) proteoglycan 4-O-sulfation, which modulates PNNs and excitatory-to-inhibitory (E/I) balance. Discontinuation of MMP-2/9 inhibition in juvenile zebrafish normalized deficits in ADL SW abundance and sociability. Together, these findings show that MMP-2/9 significantly influences E/I balance and learning and memory during the highly plastic juvenile period in zebrafish. Findings also have relevance to an emerging appreciation of PNN changes that may contribute to altered neuronal oscillations and mood or cognition.

Exploring Hippocampal Vulnerability: Diminished Angiogenic Capacity in the Hippocampus Compared to the Cortex
Abstract Background: The hippocampus is one of the first regions affected in various neurodegenerative diseases. In this study, investigated the vascular factors contributing to its susceptibility, aiming to elucidate the underlying vascular mechanisms. Method: Utilizing publicly available single-cell databases, we analyzed the differential expression of genes in blood-brain barrier (BBB)-associated cells within the hippocampus and compared them to those in the cortex. Those genes were further validated in mouse and ischemia rat models. Results: We identified differentially expressed genes (DEGs) in endothelial cells, pericytes, and astrocytes in the BBB. Subsequent gene ontology (GO) enrichment analysis and protein-protein interaction (PPI) network analysis identified key hub genes: Kdr, Fn1, Pecam1, Cd34, and Cd93, that related to angiogenesis. They differential expression was then experimentally verified using micro-vessels from mouse and rat brains: In the rat ischemia model, we observed up-regulation of angiogenesis-related genes, including Kdr, Cd34, and Cd93, in the microvasculature of both the hippocampus and cortex, with relatively lower expression in the hippocampus. Conclusion; These findings suggest that the hippocampus has a reduced angiogenic capacity compared to the cortex, which may contribute to its increased vulnerability to neurological disorders.

Data retention in awake infant fMRI: Lessons from more than 750 scanning sessions
Functional magnetic resonance imaging (fMRI) in awake infants has the potential to reveal how the early developing brain gives rise to cognition and behavior. However, awake infant fMRI poses significant methodological challenges that have hampered wider adoption. The present work takes stock after the collection of a substantial amount of awake infant fMRI data across multiple studies from two labs at different institutions. These data were leveraged to glean insights on participant recruitment, experimental design, and data acquisition that could be useful to consider for future studies. Across 766 awake infant fMRI sessions, the authors explored the factors that influenced how much usable data were obtained per session (average of 9 minutes). The age of an infant predicted whether they would successfully enter the scanner (younger was more likely) and, if they did enter, the number of minutes of functional data retained after preprocessing. The amount of functional data retained was also influenced by assigned sex (female more), experimental paradigm (movies better than blocks and events), and stimulus content (social better than abstract). In addition, the authors assessed the value of attempting to collect multiple experiments per session, an approach that yielded more than one usable experiment averaging across all sessions (including those with no data). Although any given scan is unpredictable, these findings support the feasibility of awake infant fMRI and suggest practices to optimize future research.

Marmoset Anterior Cingulate Area 32 Neurons Exhibit Responses to Presented and Produced Calls During Naturalistic Vocal Communication
Vocal communication is a complex social behavior that entails the integration of auditory perception and vocal production. Both anatomical and functional evidence have implicated the anterior cingulate cortex (ACC), including area 32, in these processes, but the dynamics of neural responses in area 32 during naturalistic vocal interactions remain poorly understood. Here, we addressed this by recording the activity of single area 32 neurons using chronically implanted ultra high density Neuropixels probes in freely moving common marmosets (Callithrix jacchus) engaged in an antiphonal calling paradigm in which they exchanged long-distance phee calls with a virtual conspecific. We found that many neurons exhibited complex modulations in discharge rates in response to presented calls, prior to and following self-generated calls, and during the interval between presented and produced vocalizations. These findings are consistent with the conceptualization of area 32 as an audiovocal interface integrating auditory information, cognitive processes, and motor outputs in the service of vocal communication.

A humanized mouse model system mimics prenatal Zika infection and reveals premature differentiation
Zika, a mosquito-borne flavivirus, has been found in 87 countries and territories. Global outbreaks peaked in 2016. Prenatal infection of Zika virus was found to be associated with microcephaly, arthrogryposis, intracranial calcifications, fetal growth restriction, and fetal demise. The most severely affected children were diagnosed with congenital Zika syndrome, which impacts thousands worldwide. With no approved treatment or preventative measures for Zika, future viral outbreaks have the potential to cause epidemic levels of prenatal brain injury, as seen over the past 70 years. Therefore, there is a great need for a reliable and clinically translational experimental system that mimics the human condition of prenatal Zika infection. To this end, we developed a humanized, immunocompetent mouse model system of virally induced brain injury from prenatal Zika infection, which ranges from mild to severe. Here, we describe the extent to which this system mirrors the human phenotypic spectrum. Using our thorough preclinical system, we find that prenatal Zika infection of mice impacts survival rate, anthropometric measurements, tissue formation, and neurological outcomes, all of which are typical of prenatal infection. Single-cell RNA sequencing of the Zika-infected cerebral cortex reveals severely disrupted transcriptome profiles and suggests that these injuries are a result of a depletion of neural stem cells. Current and future applications include the identification of genetic or environmental modifiers of brain injury, molecular or mechanistic studies of pathogenesis, and preclinical evaluation of future therapies.

Splanchnic and pelvic spinal afferent pathways relay sensory information from the mouse colorectum into distinct brainstem circuits.
This study aimed to identify where the sensory information relayed by the two spinal afferent pathways innervating the distal colon and rectum (colorectum), the splanchnic and pelvic spinal afferent pathways, integrates within the brainstem. Localised injections of transneuronal viral tracer (herpes simplex virus H129 strain expressing EGFP (H129-EGFP)) into the distal colon was used to assess the brainstem structures receiving ascending input from the colorectum. H129-EGFP positive cells were distributed in structures involved in ascending sensory relay, descending pain modulation and autonomic regulation in the medulla from 96 hours and in pontine and caudal midbrain 120 hours after inoculation. In a separate cohort of mice, in vivo noxious colorectal distension (CRD) followed by brainstem immunolabelling for phosphorylated MAP kinase ERK (pERK) showed that many of the structures in which H129-EGFP positive labelling was observed were relevant to colorectal sensory processing. Surgical removal of dorsal root ganglia (DRG) containing cell bodies of splanchnic colorectal afferent neurons, significantly reduced CRD evoked neuronal activation within the caudal ventrolateral medulla, rostral ventromedial medulla and the lateral parabrachial nuclei. Whilst, removal of DRG containing cell bodies of pelvic colorectal afferent neurons significantly reduced CRD evoked neuronal activation within the rostral ventromedial medulla, lateral parabrachial nuclei, the locus coeruleus, Barringtons nucleus and periaqueductal gray. Collectively, this study showed that the two spinal afferent pathways innervating the colorectum differentially shape colorectal processing within the brainstem and provides new insight into their unique roles to mediating visceromotor responses and defecation associated with colorectal nociception.

An integrated system for comprehensive mouse peripheral vestibular function evaluation based on Vestibulo-ocular Reflex
In the realms of both vestibular and auditory research, conducting vestibular function tests is essential. However, unlike the auditory function tests which utilize standard equipment such as the Auditory Brainstem Response (ABR) device, there is no equivalent widely adopted apparatus for vestibular tests. This is largely due to the intricate nature of the vestibular system and the challenges associated with assessing its functions. Vestibulo-ocular reflexes (VORs) are the compensatory ocular reflexes that ensure stable vision during head motion. VORs are widely used in clinics for diagnosing the vestibular deficit. In the research field, VORs, including angular VOR (aVOR) or off-vertical axis rotation (OVAR) tests, have been used by various groups to evaluate the mouse vestibular function. However, the effectiveness of VOR tests has not been systematically evaluated with proper animal models, and the lack of commercial equipment hampers its accessibility, confining vestibular testing to a select few labs. In this study, we developed an integrated instrument system with both aVOR and OVAR modes for evaluating mouse vestibular function. To demonstrate its efficacy, peripheral vestibular animal models, 1) Vestibulotoxicity drugs 3,3'-iminodiproprionitrile (IDPN, 2 mg/g and 4 mg/g) induced; 2) Critical MET-related mutant (Cdh23v2J/v2J and TMC1-/-); 3) Vestibulo-specific mutant (Zpld1-/- for semicircular canal dysfunction and Otop1tlt/tlt for otoconia deficient; 4) Unilateral vestibular lesion (UVL) model by injecting gentamicin into horizontal semicircular canal, were constructed and evaluated with the system. The results showed 1) Quantification of the vestibular deficit is achieved in a daily manner; 2) Both the otolith organ and semicircular canals can be assessed respectively; and 3) The lesion side of UVL can be identified. During an 8-week study of IDPN vestibulotoxicity, the vestibular function of 3 groups of 20 animals was evaluated at 15 test days. These test results reveal the potential of our system as a standard system for evaluating common vestibular deficits in mice.

Targeting the ferroptosis pathway: A novel compound, AZD1390, protects the brain after ischemic stroke
Background: Ferroptosis is an iron-dependent form of regulated cell death driven by lipid peroxidation. This process has been implicated in various diseases, including ischemic stroke. Ischemic stroke leads to oxidative stress, iron overload, and reactive oxygen species (ROS) accumulation, which collectively may trigger ferroptotic neuronal cell death. However, the regulatory mechanisms of ferroptosis in stroke remain poorly understood. Previous studies have identified ataxia telangiectasia mutated (ATM), a DNA damage kinase, as a critical regulator of ferroptosis. However, the therapeutic potential of this discovery remains unknown. Methods: We investigated the effect of ATM inhibitors, including the brain-penetrant AZD1390, on ferroptosis using in vitro, ex vivo, and in vivo models of ischemic stroke. Our analysis included assessments of cell viability, lipid peroxidation, ferroptosis marker expression, and infarct volume. Results: ATM inhibitors significantly alleviated ferroptosis-induced cell death in cultured cells and ex vivo murine brain slice cultures. In the oxygen-glucose deprivation (OGD) stroke model, treatment with AZD1390 reduced the expression of ferroptosis markers (xCT and PTGS2) and diminished neuronal cell death in rat and mouse brain slices. Furthermore, in a mouse model of ischemic stroke, AZD1390 decreased infarct volume confirming its therapeutic efficacy in vivo. Conclusions: This study identifies ferroptosis as a critical mechanism in ischemic stroke-induced neuronal cell death and highlights ATM inhibition, particularly with AZD1390, as a promising therapeutic candidate for mitigating stroke-associated damage. Targeting ferroptosis may provide a translationally relevant strategy to mitigate neuronal injury and improve clinical outcomes for stroke patients.

Astrocytic activation of EMMPRIN contributes to their pathological phenotype in ALS.
Amyotrophic Lateral Sclerosis (ALS) is a fatal disease characterised by the degeneration of upper and lower motoneurons. Onset and progression of the disease are determined by both cell-autonomous neuronal dysfunctions and non-cell-autonomous factors, mainly due to activation of glial cells such as astrocytes and microglia. The Extracellular Matrix Metalloproteinases INducer (EMMPRIN), a glycoprotein expressed by various cell types including neurons, is the major activator of matrix metalloproteinases (MMPs) synthesis and release. EMMPRIN activation can be induced by peptidyl-prolyl isomerase A (PPIA), a chaperone protein with cis/trans isomerase activity, that exhibits cytokine- and chemokine-like behaviour. Previous studies showed that PPIA is highly released in the cerebrospinal fluid (CSF) of ALS patients and animal models where, by activating EMMPRIN on motoneurons, induces neuronal death. Here, we show that EMMPRIN is expressed also by astrocytes, suggesting this cell type as sensitive as motoneurons to PPIA-mediated EMMPRIN activation. We observed that that PPIA-mediated EMMPRIN activation prompt astrocytes toward a pro-inflammatory profile. Interestingly, we found that this pathogenic profile can be reverted by an anti-EMMPRIN antibody. Finally, we provide evidence that the activation of EMMPRIN is relevant for mutant SOD1 and TDP-43 conditions. In conclusion, we demonstrate that EMMPRIN activation in ALS occurs also in astrocytes where it exacerbates their pathological phenotype possibly contributing to the progression of the disease. Furthermore, we suggest the potential use of an anti-EMMPRIN antibody to reduce astrocytic activation during the disease.

Caspase-dependent ablation of indirect medium spiny neurons projecting to external globus pallidus promotes compulsive ethanol-seeking and drinking behaviors
The dorsomedial striatum (DMS) is primarily recognized for regulating goal-directed reward-seeking behaviors, while the dorsolateral striatum (DLS) is predominantly associated with movement and habitual behaviors. In this study, we sought to investigate two pathways, direct medium spiny neuron (dMSN) and indirect medium spiny neuron (iMSN) in the two dorsal striatal subregions (DMS and DLS) in ethanol-seeking and drinking behaviors. Here, we selectively ablated iMSN(DMS-GPe) and iMSN(DLS-GPe) and trained mice to exhibit goal-directed and habitual reward-seeking behaviors using random ratio (RR) and random interval (RI) operant conditioning, respectively. We found that partial ablation of iMSN(DLS-GPe) exhibited increased resilience to bitter-tasting ethanol solution when subjected to quinine adulterated reward in operant conditioning paradigms, suggesting compulsive-like seeking behavior. Consistently, in a separate cohort of mice, we found that the iMSN(DLS-GPe) ablated mice show higher preference and consumption of quinine adulterated ethanol solution than control mice in two-bottle choice continuous access drinking, with increasing quinine concentration and exhibit more compulsive-like behavior. On the other hand, ablation of iMSN(DMS-GPe) resulted in insensitivity to satiety-based reward devaluation in RR-trained mice, consistent with a shift toward habitual behavior but no change in compulsive ethanol-seeking and drinking behavior. Together, our findings demonstrate that DLS iMSN function is essential in inhibiting compulsive-like behavior.

Assessing the impact of artifact correction and artifact rejection on the performance of SVM-based decoding of EEG signals
Numerous studies have demonstrated that eyeblinks and other large artifacts can decrease the signal-to-noise ratio of EEG data, resulting in decreased statistical power for conventional univariate analyses. However, it is not clear whether eliminating these artifacts during preprocessing enhances the performance of multivariate pattern analysis (MVPA; decoding), especially given that artifact rejection reduces the number of trials available for training the decoder. This study aimed to evaluate the impact of artifact-minimization approaches on the decoding performance of support vector machines. Independent component analysis (ICA) was used to correct ocular artifacts, and artifact rejection was used to discard trials with large voltage deflections from other sources (e.g., muscle artifacts). We assessed decoding performance in relatively simple binary classification tasks using data from seven commonly-used event-related potential paradigms (N170, mismatch negativity, N2pc, P3b, N400, lateralized readiness potential, and error-related negativity), as well as more challenging multi-way decoding tasks, including stimulus location and stimulus orientation. The results indicated that the combination of artifact correction and rejection did not improve decoding performance in the vast majority of cases. However, artifact correction may still be essential to minimize artifact-related confounds that might artificially inflate decoding accuracy. Researchers who are decoding EEG data from paradigms, populations, and recording setups that are similar to those examined here may benefit from our recommendations to optimize decoding performance and avoid incorrect conclusions.

Within-Individual Precision Mapping of Brain Networks Exclusively Using Task Data
Precision mapping of brain networks within individuals has become a widely used tool that prevailingly relies on functional connectivity analysis of resting-state data. Here we explored whether networks could be precisely estimated solely using data acquired during active task paradigms. The straightforward strategy involved extracting residualized data after application of a task-based general linear model (GLM) and then applying standard functional connectivity analysis. Functional correlation matrices estimated from task data were highly similar to those derived from traditional resting-state fixation data. The largest factor affecting similarity between correlation matrices was the amount of data. Networks estimated within-individual from task data displayed strong spatial overlap with those estimated from resting-state fixation data and predicted the same triple functional dissociation in independent data. The implications of these findings are that (1) existing task data can be reanalyzed to estimate within-individual network organization, (2) resting-state fixation and task data can be pooled to increase statistical power, and (3) future studies can exclusively acquire task data to both estimate networks and extract task responses. Most broadly, the present results suggest that there is an underlying, stable network architecture that is idiosyncratic to the individual and persists across task states.

Motivating Effects of Negative-hedonic Valence Encoded in Engrams
Engrams are neuronal alterations that encode associations between environmental contexts and subjectively rewarding or aversive experiences within sparsely activated neuronal assemblies that regulate behavioral responses. How positive- or negative-hedonic states are represented in brain neurocircuits is a fundamental question relevant for understanding the processing of emotionally meaningful stimuli that drive appropriate or maladaptive behavior, respectively. It is well-known that animals avoid noxious stimuli and experiences. Little is known, however, how the conditioning of environmental or contextual stimuli to behavior that leads to amelioration of dysphoric states establishes powerful associations leading to compulsive maladaptive behavior. Here we have studied engrams that encode the conditioned effects of alcohol-related stimuli associated with the reversal of the dysphoric withdrawal state in alcohol dependent rats and document the recruitment of engrams in the paraventricular nucleus of the thalamus (PVT), the central nucleus of the amygdala (CeA), and the Dorsal Striatum (DS). The findings suggest that the encoding of associations between reversal of negative hedonic states and environmental contexts in these engrams may serve as a neural mechanism for compulsive alcohol seeking and vulnerability to relapse associated with dysregulation of reward to a pathological allostatic level.

Method of loci training yields unique neural representations that support effective memory encoding
The method of loci is a technique to effectively boost memory, but its impact on the underlying neural representations is poorly understood. Here, we used functional magnetic resonance imaging and representational similarity analysis to compare the neural representations of memory athletes ranked among the world's top 50 in memory sports to those of mnemonics-naive controls. In a second study, mnemonics-naive individuals underwent a 6-week-long memory training, working memory training, or no intervention. Results showed distinct neural representations in the prefrontal cortex, inferior temporal, and posterior parietal regions as memory athletes and the memory training group studied novel content. Neural representations were also distinct between these experienced individuals, which was related to better memory performance after 4 months. Our findings highlight how extensive memory training affects neocortical memory engrams. We suggest that the method of loci may bolster memory uniqueness within one's "memory palace", setting the stage for exceptional memory performance.

Development and Characterization of a Sf-1-Flp Mouse Model
The use of genetically engineered tools, including combinations of Cre-LoxP and Flp-FRT systems, enable the interrogation of complex biology. Steroidogenic factor-1 (SF-1) is expressed in the ventromedial hypothalamic nucleus (VMH). Development of genetic tools, such as mice expressing Flp recombinase (Flp) in SF-1 neurons (Sf-1-Flp), will be useful for future studies that unravel the complex physiology regulated by the VMH. Here, we developed and characterized Sf-1-Flp mice and demonstrated its utility. Flp sequence was inserted into Sf-1 locus with P2A. This insertion did not affect Sf-1 mRNA expression levels and Sf-1-Flp mice do not have any visible phenotypes. They are fertile and metabolically comparable to wild-type littermate mice. Optogenetic stimulation using adeno-associated virus (AAV)-bearing Flp-dependent channelrhodopsin-2 (ChR2) increased blood glucose and skeletal muscle PGC-1 in Sf-1-Flp mice. This was similar to SF-1 neuronal activation using Sf-1-BAC-Cre and AAV-bearing Cre-dependent ChR2. Finally, we generated Sf-1-Flp mice that lack {beta}2-adrenergic receptors (Adr{beta}2) only in skeletal muscle with a combination of Cre/LoxP technology (Sf-1-Flp::SKM{triangleup}Adr{beta}2). Optogenetic stimulation of SF-1 neurons failed to increase skeletal muscle PGC-1 in Sf-1-Flp::SKM{triangleup}Adr{beta}2 mice, suggesting that Adr{beta}2 in skeletal muscle is required for augmented skeletal muscle PGC-1 by SF-1 neuronal activation. Our data demonstrate that Sf-1-Flp mice are useful for interrogating complex physiology.

Transfer of learned object manipulations between two- and five-digit grasps
Successful object manipulation involves integrating object properties into a motor plan and scaling fingertip forces through learning. This study investigated whether learned manipulations using a two-digit grip transfer to a five-digit grip and vice versa, focusing on the challenges posed by added degrees of freedom in force distribution. The goal of the task was to exert the necessary compensatory torque (Tcom) and vertical forces to minimize object roll on a visually symmetrical object that with an asymmetrical mass distribution. To examine this, subjects performed blocked consecutive learning trials before switching grip type. Our results support the learning transfer between two-digits and five-digit grasp configurations despite challenges in maintaining perfect stability during the grip switch. Subjects adapted their grip forces (GF), center of pressure (CoP), and Tcom to minimize object roll, with significant improvements observed from novel (1st) to transfer (11th) trials. These findings suggest high-level, effector-independent representations of object manipulation that enable generalization across grip types, though some limitations in force distribution and digit position arise during transfers.

PLXNB1 and other signaling drives a pathologic astrocyte state contributing to cognitive decline in Alzheimer's Disease
Alzheimer's disease (AD) is marked by the coordinated emergence of disease-associated cell states across multiple cell types. Here, we first performed a meta-analysis of single-nucleus transcriptomic (snRNAseq) data from 869 brains of diverse decedents, confirming the critical role of an SLC38A2highSMTNhighCACNA1Dhigh astrocyte subset, Astrocyte 10 (Ast10), in AD and aging-related cognitive decline. We then investigated the signaling drivers of Ast10's emergence in the aging brain, focusing on interactions among microglial and astrocytic subsets. Analysis of the snRNAseq data prioritized a set of ligands and receptors that are robustly predictive of Ast10 proportions across participants, and we confirm our predictions in multiple studies. Independent validation with spatial transcriptomics reveals striking colocalization of these prioritized ligands with the Ast10 signature in AD brain tissue, but not with other astrocytic states. Genetic ablation of a top receptor PLXNB1 in murine and human iPSC-derived astrocytes decreased the Ast10 signature, confirming its regulatory role. Finally, we find that Ast10 may contribute to cognitive decline through synaptic loss and is associated with cognitive decline independent of AD. Thus, Ast10 and its regulators are potential points of convergence for multiple neurodegenerative mechanisms and may be promising targets for therapeutic development to preserve cognitive function.

New insights into the 17β-hydroxysteroid dehydrogenase type 10 and amyloid-β 42 derived cytotoxicity relevant to Alzheimer's disease
The multifunctional mitochondrial enzyme 17{beta}-hydroxysteroid dehydrogenase type 10 (HSD10) plays an important role in the pathology of several diseases, of which Alzheimer's disease (AD) is the most debated. HSD10 overexpression and its interplay with amyloid-{beta} peptide (A{beta}) are considered a factor contributing to mitochondrial damage and neuronal stress observed in AD patients. This study confirms that individual overexpression of HSD10 or APP (amyloid precursor protein that gives rise to A{beta}) leads to cytotoxicity, and both pathological conditions are linked to mitochondrial damage. However, the metabolic changes caused by these two overexpressions significantly differ, particularly in their effect on the tricarboxylic acid cycle and {beta}-oxidation. Furthermore, the enzymatic activity of HSD10 is identified as the primary factor of HSD10 cytotoxicity, which is significantly exacerbated in an A{beta}-rich environment and can be partially reversed by HSD10 inhibitors. Notably, a previously published and competitive benzothiazole inhibitor was effective in restoring the viability of HSD10 overexpressing cells alone and in an A{beta}-rich environment, implying the potential benefit of HSD10 inhibitors in mitochondrial diseases and/or AD treatment.

Axially decoupled photo-stimulation and two photon readout (ADePT) for mapping functional connectivity of neural circuits
All optical physiology in vivo provides a conduit for investigating the function of neural circuits in 3-D. Here, we report a new strategy for flexible, axially-decoupled photo-stimulation and two photon readout (ADePT) of neuronal activity. To achieve axially-contained widefield optogenetic patterned stimulation, we couple a digital micro-mirror device illuminated by a solid-state laser with a motorized holographic diffuser. In parallel, we use multiphoton imaging of neural activity across different z-planes. We use ADePT to analyze the excitatory and inhibitory functional connectivity of the mouse early olfactory system. Specifically, we control the activity of individual input glomeruli on the olfactory bulb surface, and map the ensuing responses of output mitral and tufted cell bodies in deeper layers. This approach identifies cohorts of sister mitral and tufted cells, whose firing is driven by the same parent glomerulus, and also reveals their differential inhibition by other glomeruli. In addition, selective optogenetic activation of glomerular GABAergic/dopaminergic (DAT+) interneurons triggers dense, but spatially heterogeneous suppression of mitral and tufted cell baseline activity and odor responses, further demonstrating specificity in the inhibitory olfactory bulb connectivity. In summary, ADePT enables high-throughput functional connectivity mapping in optically accessible brain regions.

Apolipoprotein E abundance is elevated in the brains of individuals with Down syndrome-Alzheimer's disease
Trisomy of chromosome 21, the cause of Down syndrome (DS), is the most commonly occurring genetic cause of Alzheimer's disease (AD). Here, we compare the frontal cortex proteome of people with Down syndrome-Alzheimer's disease (DSAD) to demographically matched cases of early-onset AD and healthy ageing controls. We find wide dysregulation of the proteome, beyond proteins encoded by chromosome 21, including an increase in the abundance of the key AD-associated protein, APOE, in people with DSAD compared to matched cases of AD. To understand the cell types that may contribute to changes in protein abundance, we undertook a matched single-nuclei RNA-sequencing study, which demonstrated that APOE expression was elevated in subtypes of astrocytes, endothelial cells and pericytes in DSAD. We further investigate how trisomy 21 may cause increased APOE. Increased abundance of APOE may impact the development of, or response to, AD pathology in the brain of people with DSAD, altering disease mechanisms with clinical implications. Overall, these data highlight that trisomy 21 alters both the transcriptome and proteome of people with DS in the context of AD, and that these differences should be considered when selecting therapeutic strategies for this vulnerable group of individuals who have high-risk of early-onset dementia.

The glare illusion in individuals with schizophrenia
Individuals with schizophrenia are known to demonstrate unique reactions to visual illusions, and prior research has indicated a potential link between their increased susceptibility to geometric illusions and specific symptom profiles. While various illusory experiences have been examined among individuals with schizophrenia, their responses to brightness-related illusions remain poorly understood. In this study, we investigated how individuals with schizophrenia perceive the glare illusion, in which the apparent brightness of the central region is increased. A total of 30 patients with schizophrenia and 34 control participants were recruited. During each trial, a glare or control image (standard stimulus) was presented alongside a control image (comparison stimulus) with one of seven luminance levels. In the glare condition, the standard stimulus was a glare image; in the control condition, two control images were presented, but only the luminance of the comparison stimulus varied. The participants were asked to judge which central region appeared brighter. The results revealed that the individuals with schizophrenia exhibited greater susceptibility to the glare illusion than did the control participants. However, no significant associations were found between susceptibility to the glare illusion and scores assessing symptom severity. These findings suggest that differences in visual processing in patients with schizophrenia may increase their susceptibility to brightness illusions, although this phenomenon is independent of symptom characteristics. Understanding these perceptual alterations may aid in the development of objective measures of visual cognition for patients with schizophrenia.

Sex-differences in catecholamine transporter expression in the rodent prefrontal cortex following repetitive mild traumatic brain injury and methylphenidate treatment
Irregular catecholamine transmitter activity is theorized to underly impaired prefrontal cortex (PFC)-mediated executive functions following repetitive mild traumatic brain injury (rmTBI). The psychostimulant, methylphenidate (MPH), enhances catecholamine neurotransmission by blocking reuptake transporters and is used off-label to treat post-TBI executive dysfunction. Although rmTBI and MPH have been shown to independently alter catecholamine transporter levels, the present report evaluated the interactive effects of rmTBI and a sub-chronic therapeutic dose of MPH on expression levels of vesicular monoamine transporter-2 (VMAT2) and norepinephrine reuptake transporter (NET) within subregions of the PFC in both male and female rats. Treatment with MPH restored rmTBI-induced reductions in transporter expression in females. However, in males subjected to rmTBI, MPH exacerbated reductions in transporter expression within the PFC. These results suggest MPH treatment produces beneficial effects in females but exaggerates pathological outcomes in males when used to treat post-rmTBI symptoms.

Morphine self-administration induces region-specific brain volume changes and microglial phenotypic alterations without affecting neuronal density in male Wistar rats
Addiction to opioids, including morphine, is a major public health crisis in the U.S. It has been associated with brain volume changes in reward-related regions, neuronal death, and neuroinflammation. However, the link between structural changes and neuroinflammation is not well understood. In this study, we used operant conditioning to induce morphine self-administration in rats and examined brain volume and cellular changes, focusing on microglial phenotypes. Male Wistar rats were conditioned to morphine self-administration (0.01 mg/kg) for 20 days under a fixed-ratio 1 schedule. In vivo structural Magnetic Resonance Imaging (MRI) scans were conducted at the beginning and end of self-administration. Brains were stained for Iba1 and NeuN proteins, and confocal images were analyzed for cell counts and microglial morphology. We used Deformation-Based Morphometry for MRI volume analysis and Principal Component Analysis with K-means clustering for microglial phenotyping. Our results showed that morphine self-administration led to volume changes in addiction-related brain regions, including increased globus pallidus and decreased insular cortex volume. Additionally, morphine caused widespread neuroinflammation, evidenced by elevated microglial density in the caudate-putamen, dentate gyrus, globus pallidus, and insular cortex, without affecting neuron counts. Finally, we observed region-specific variations in microglial phenotypes, suggesting region-specific neuroinflammatory roles. In conclusion, our study shows that morphine self-administration induces structural and microglial changes in addiction-related brain regions without neuronal loss, highlighting the role of neuroinflammation in opioid-induced adaptations. The variability in microglial phenotypes underscores their complexity, emphasizing the need to study their progression in addiction and their potential as therapeutic targets.

Repetitive magnetic stimulation with iTBS600 induces persistent structural and functional plasticity in mouse organotypic slice cultures
Repetitive transcranial magnetic stimulation (rTMS) is well-established for its ability to induce synaptic plasticity. However, its impact on structural and functional remodeling within stimulated networks remains not well-understood. To bridge the gap between cellular and network-level effects, we investigated plasticity mechanisms in entorhino-hippocampal tissue cultures subjected to a clinically approved 600-pulse intermittent theta burst stimulation (iTBS600) protocol. Using a comprehensive methodological approach---including c-Fos immunostaining, whole-cell patch-clamp recordings, time-lapse imaging of dendritic spines, and calcium imaging---we conducted a 24-hour analysis of iTBS600-rMS induced plasticity. We observed long-term potentiation (LTP) of excitatory synapses in dentate granule cells, accompanied by transient c-Fos expression in the dentate gyrus, but not in hippocampal areas CA1 and CA3. Structural remodeling of dendritic spines was temporally linked to enhanced synaptic transmission, while spontaneous firing rates remained stable, reflecting the engagement of homeostatic mechanisms. Despite the widespread electric field generated by rTMS, its effects were spatially and temporally precise, driving Hebbian plasticity and region-specific spine dynamics. These findings provide critical insight into how rTMS-induced LTP mediates targeted plasticity while preserving network stability, shedding light on the mechanisms underlying the persistent effects of rTMS.

Cluster replicability in single-cell and single-nucleus atlases of the mouse brain
Single-cell RNA sequencing has advanced our understanding of cellular heterogeneity. Ensuring the replicability of identified cell clusters across studies is essential for determining their biological robustness. We assess the replicability of cell clusters identified in two large mouse brain atlases, one generated using single-cell RNA sequencing and the other with single nuclei. Both profile over 4 million cells and group them into over 5000 clusters. Using transcriptome-wide neighbor voting, we identify 2009 reciprocally matched cluster pairs with consistent spatial localization and coordinated gene expression, which were also observed in datasets from multiple species. Reciprocal clusters are enriched in the cerebellum, where lower diversity aids replicability, while the hypothalamus's heterogeneity limits agreement. Distinguishing close clusters is much more challenging than differentiating a cluster from most others, especially when using marker genes. By incorporating replicability data, we provide a stronger foundation for investigating the newly identified clusters and their biological meaning.

MuFIX - Enabling Combinations of Concurrent Optogenetics and Lock-in Amplification Fiber Photometry via Removal of Optogenetic Stimulation Crosstalk
Simultaneous fiber photometry and optogenetics is a powerful emerging technique for precisely studying the interactions of neuronal brain networks. However, spectral overlap between photometry and optogenetic components has severely limited the application of an all-optical approach. Due to spectral overlap, light from optogenetic stimulation saturates the photosensor and occludes photometry fluorescence, which is especially problematic in physically smaller model organism brains like mice. Here, we demonstrate the Multi-Frequency Interpolation X-talk removal algorithm (MuFIX) for recovering crosstalk-contaminated photometry responses recorded with lock-in amplification. MuFIX exploits multi-frequency lock-in amplification by modeling the remaining uncontaminated data to interpolate across crosstalk-affected segments (R2 ~ 1.0); we found that this approach accurately recovers the original photometry response after demodulation (Pearson's r ~ 1.0). When applied to crosstalk-contaminated data, MuFIX recovered a photometry response closely resembling the dynamics of non-crosstalk photometry recorded simultaneously. Upon further verification using simulated and empirical data, we demonstrated that MuFIX reproduces any signal that underwent simulated crosstalk contamination (r ~ 1.0). We believe adopting MuFIX will enable experimental designs using simultaneous fiber photometry and optogenetics that were previously not feasible due to crosstalk.

Lifespan Mapping of EEG Source Spectral Dynamics with Xi-AlphaNET
We formulate a new class of parametric, multivariate, and structurally informed spectral components model of the EEG, the Xi-AlphaNET, that allows us to map the Lifespan of EEG source spectral dynamics across a large data set of EEG cross spectrum at high spatial resolution. This approach accurately estimates source spectral components and effective connectivity through the use of biophysical modeling while maintaining computational efficiency, as confirmed by simulation benchmarks. We are able to analyze source dynamics with a resolution of 8,003 voxels from the HarMNqEEG dataset, which includes scalp EEG cross-spectrum tensors collected from 1965 subjects across 9 countries, using various devices and accounting for different age groups. Our findings indicate that the Bayesian Model Inversion of the Xi-AlphaNET allows to map Lifespan of conduction delays that follows a U-shaped trajectory, which contrasts with independently recorded myelin concentration measurements. Moreover, we assess the spatiotemporal distribution of spectral components, revealing that the aperiodic or fractal component has an isotropic spatial distribution on the cortical surface. While the generator's spectral peak in the alpha band, i.e., alpha-rythms, is localized on the visual areas of the brain. Using a Zero Inflated Gaussian model, our findings indicate that the mode frequency that characterizes the alpha-rythms or Peak Alpha Frequency shows an inverted U-shaped trajectory for both hemispheres across the Lifespan and a spatial gradient of zero inflation in PAF across the cortex that flattens the trajectory from posterior to frontal areas. We provide both the code of the Xi-AlphaNET and the source solution of the spectral dynamics for the HarMNqEEG.

Ketogenic interventions prevent alterations of the gut microbiome in transgenic Alzheimer Disease mice
Alterations in the gut microbiome constitute a feature of aging and therefore represent a therapeutic target for aging-related diseases. In this study, we investigated the impact of ketogenic interventions on the microbiome of mice genetically predisposed to Alzheimer disease (AD). AD mice exhibited several microbial alterations, notably increased levels of Bifidobacterium and decreased levels of Bacteroidetes. Ketogenic interventions, either a medium-chain triglyceride-enriched diet (MCT) or carbohydrate-free high-fat diet (CFHF), administered for 1 month restored the levels of more than 50% of the bacteria altered in AD mice, including a strong reduction in Bifidobacterium levels. Ketogenic interventions induced a shift in the gut microbiome associated with increased levels of short-chain fatty acid-producing bacteria, such as Lachnospiraceae and Muribaculaceae. MCT and CFHF also triggered diet-specific microbial changes, which may contribute to the distinct physiological effects of these diets. In conclusion, ketogenic interventions may influence AD pathophysiology by modulating the gut microbiome.

Activity Protects Spinal Premotor Interneurons from Microglial Phagocytosis and Transneuronal Degeneration After Corticospinal Injury
Spinal premotor circuits play a fundamental role in motor control. The corticospinal tract (CST) provides control signals to premotor circuits in the spinal cord, guiding voluntary skilled movements. Unilateral selective lesion of the CST in the medullary pyramidal tract (PTX) produces transneuronal degeneration, whereby Choline Acetyltransferase-positive (ChAT) premotor interneurons contralesionally undergo non-apoptotic degeneration by microglial phagocytosis. Evidence shows that transneuronal degeneration has an activity dependence: MCX inactivation produces transneuronal degeneration and spinal DC neuromodulation after PTX ameliorates it. This study expands our understanding of transneuronal degeneration mechanisms by examining the activity-dependence of degeneration vulnerability and the implications for motor recovery in a mouse model of a complete CST lesion model (bilateral PTX). We address four key unanswered questions: Are Chx10 (VGlut2) interneurons, the largest spinal interneuron class to receive direct synaptic connections from the CST vulnerable to transneuronal degeneration after CST loss; using DREADD neuromodulation, what are effective sources of presynaptic activation for protecting spinal premotor interneurons after CST loss; how are ameliorating transneuronal interneuron degeneration and reducing microglial activation associated; and does effective rescue of interneuron degeneration rescue grip strength after injury? Transneuronal degeneration is a pervasive pathophysiological change injury; CST lesion produces significant Chx10 interneuron loss. Multiple sources of neuronal DREADD activation--motor cortex, reticular formation, and spinal interneurons--are effective in ameliorating transneuronal degeneration. Interneuron rescue is strongly associated with ameliorating inflammation, showing potential causality between interneuron degeneration and inflammation after CST lesion. Finally, rescuing spinal interneurons was associated with restoring function. Our findings demonstrate the interplay between neuronal activity, microglia actions mediating transneuronal degeneration, and motor recovery following CNS injury.

Explainable AI techniques for dynamic functional brain imaging: validation and analysis of E/I imbalance in autism
Deep neural networks are increasingly crucial for analysing dynamic functional brain imaging data, offering unprecedented accuracy in distinguishing brain activity patterns across health and disease. However, they often function as black boxes obscuring the neurobiological features driving classifications between groups. This study systematically investigates explainable AI (xAI) methods to address this challenge, employing two complementary simulation approaches: recurrent neural networks for controlled parameter exploration, and The Virtual Brain for biophysically realistic whole-brain modelling. These simulations generate fMRI datasets with known regional alterations in excitation/inhibition (E/I) balance, mimicking mechanisms implicated in psychiatric and neurological disorders. Our comprehensive validation demonstrates that Integrated Gradients and DeepLift successfully identify ground-truth affected regions across challenging conditions, including high noise (-10dB SNR), low prevalence (1% of regions), and subtle E/I alterations. This performance remains robust across three different attribution methods and baseline choices, establishing the reliability of xAI for functional neuroimaging analysis. Critically, successful cross-species validation using both human (68-region) and mouse (426-region) connectomes demonstrates the approach's ability to detect mechanistic alterations across different scales of brain organization. Application to the multisite ABIDE resting-state fMRI dataset (N=834) reveals that regions within the default mode network, particularly the posterior cingulate cortex and precuneus, most clearly differentiated children with autism from neurotypical controls. The convergence between these empirical findings and our biophysical simulations of E/I imbalance provides computational support for mechanistic theories of E/I imbalance in autism while demonstrating how xAI can bridge cellular-level mechanisms with clinical biomarkers. This work establishes a framework for reliable interpretation of deep neural network models in functional neuroimaging, with implications for understanding brain disorders and developing targeted brain stimulation strategies.

A piece of evidence for pathogenesis of cerebral small vessel disease caused by blood-brain barrier dysfunction
Background: Blood-brain barrier (BBB) dysfunction caused by endothelial cell injury is one of the widely accepted pathogenesis of small cerebral vessel disease (CSVD). However, the early microcirculation studies were notably deficient in providing compelling imaging evidence, which has hampered a comprehensive understanding of the pathophysiological processes underlying BBB dysfunction in CSVD. The onset of CSVD is insidious and the clinical manifestations are diverse, diagnosis of CSVD relies primarily on neuroimaging information currently. These MRI imaging features mainly represent the end-stage brain parenchyma injury, rather than the vascular lesion itself. Therefore, clarifying the pathophysiological processes related to cerebral microcirculation in CSVD is of great significance for early treatment intervention of CSVD. Methods: Twenty rats were used to prepare CSVD animal model by ultrasound combined with ultrasonic microbubble contrast agent. MRI, functional ultrasound (fUS) imaging and ultrasound localization microscopy (ULM) were used to evaluate microcirculation changes in acute and chronic models. Results: Currently, our research has successfully validated that the imaging characteristics of this model align with the four established criteria outlined in the STRIVE-2 classification. FUS shows increased microflow velocity in the molding area, which can be used for initial evaluation of CSVD models in the acute phase. ULM has revealed a progressive reduction in the density of both the short cortical arteries and the long medullary arteries, along with their respective branches, over time. Concurrently, there has been a noted deviation in blood flow velocity. Conclusion: This model offers compelling evidence at the microvascular level, suggesting that blood-brain barrier (BBB) dysfunction is a central pathophysiological mechanism in the etiology of CSVD. Then it provides a straightforward, efficient, and widely applicable tool and continuous monitoring method for the further investigation of CSVD from the macroscopic to the microscopic circulation level, with significant long-term implications for CSVD diagnosis and treatment.