bioRxiv Subject Collection: Neuroscience's Journal

Reconstructing the Ischemic Cerebrum by Transplanted Human Neurons
Neural transplantation holds the potential to repair damaged neural circuits in neurological diseases. However, it remains unknown how the grafted neurons project axons to and make functional connections with the appropriate targets to repair the damaged circuit at the adult stage. Here we report that human cortical progenitors, transplanted into the ischemic mouse motor cortex, matured and integrated into cortical and subcortical neural circuits including the corticospinal tract. Neuronal tracing combined with single-nuclei RNA sequencing revealed the close relationship between the transcription profiles of a cortical neuronal subtype, especially those of axon guidance and synapse assembly, with the specific target projection and synapse organization. Machine learning-based regression further identified the transcriptional codes for the targeted projection and circuit integration to reconstruct the damaged circuits. Our finding opens a promising strategy for treating neurological diseases through promoting regeneration and neural transplantation.

Replicating the Gold Standard: A Novel Female Chronic Social Defeat Stress Model (femCSDS) for Studying Sex Differences in Depression
Depression shows significant sex differences in prevalence and neurobiological underpinnings, yet preclinical research investigating the pathophysiology of depression and the efficacy of antidepressants has predominantly relied on male models. Here, we establish a novel female chronic social defeat stress paradigm by leveraging the natural aggression of parous CD1 females, co-housed with castrated males to induce aggression while eliminating confounding sexual behaviors and without hormonal or surgical manipulations. Selected aggressive females reliably displayed offensive behaviors toward C57BL/6NCrl intruders across repeated encounters. Defeated female mice exhibited pronounced depression-like behaviors, including social withdrawal, anhedonia, behavioral despair, and elevated anxiety-like responses. Biochemical analysis revealed elevated glutamate levels in Nucleus Accumbens (NAc) and caudate putamen (CPu). Alterations in EAAT1, GRIN2B, and Neurabin expression were observed in CPu, indicating excitotoxic stress and compromised synaptic integrity. Label free Quantitative MS-MS analysis of NAc revealed 1194 significantly dysregulated proteins. Ingenuity Pathway Analysis highlighted canonical pathway disruptions in synaptogenesis signaling pathway and glutamate signaling pathway. Disease and function analysis revealed enrichment in neuroinflammation, synaptic dysfunction, and mitochondrial dysfunction. Given the extensive literature on male CSDS and its established pathophysiology, we aimed and successfully developed female-specific replica model of traditional male CSDS, enabling direct comparison and elucidation of sex differences in depression pathophysiology.

Low-intensity focused ultrasound to human amygdala reveals a causal role in ambiguous emotion processing and alters local and network-level activity
The amygdala is a core region changed in depression, a disorder characterized by compromised emotion, motivation and learning processes. However, lesion studies in humans examining amygdala function have largely focused on its role in processing fear. It currently remains unclear what causal role the human amygdala plays in more complex emotion, motivation and learning processes in daily life. This is because it has not been possible to reversibly modulate amygdala activity non-invasively in humans. Here, we used transcranial focused ultrasound stimulation (TUS) to bilaterally perturb neural activity in the basolateral amygdala (BLA). In separate sessions (n = 87), 29 healthy volunteers received offline-TUS to bilateral BLA, mid-insula or sham before playing a novel emotional learning task validated in an independent large cohort online (n = 210). 7T-resting-state and metabolite signals clearly demonstrated target engagement. BLA-TUS reduced the BLA's connectivity fingerprint and decreased its excitation/inhibition balance, suggesting an inhibitory effect of our TUS protocol on BLA activity. In behaviour, BLA-TUS caused a stimulation volume-dependent increase in the tendency to approach neutral, emotionally ambiguous faces, treating them more similarly to happy faces, and a slowing of reaction times for those two emotion categories. These effects were functionally and regionally specific and suggest a causal role for the amygdala in resolving emotional ambiguity. Our results provide important insights for future studies into mood disorders where ambiguous situations might be harder to resolve, which could contribute to existing emotional and learning biases.

Neural representation of emotional valence in human amygdala
The amygdala is a core structure for encoding the affective value of external stimuli. Animal studies suggest that positive and negative emotions are separately encoded by distinct neuronal populations within the amygdala; however, this hypothesis has rarely been tested in humans. The current study examined this hypothesis by comparing the distributed emotion encoding model, as proposed in animal studies, with the univariate emotion encoding model using functional magnetic resonance (fMRI) imaging. More specifically, we applied univariate regression, using average amygdala activation to represent global activation level, and multivariate regression, using distributed voxel-level pattern within the amygdala, to predict normative valence of affective images from the IAPS library. In the core amygdala, the multivariate model prediction performance was not better than that of the univariate model, with weight map analysis revealing an overwhelming predominance of voxels selectively responsive to negative stimuli. When the region of interest was expanded to include voxels with lower anatomical probability of belonging to the amygdala as well as voxels from adjacent areas, the multivariate model significantly outperformed the univariate model, with the voxels selectively responsive to positive valence primarily located in regions surrounding the core amygdala. These findings suggest that in the human amygdala, the core region encodes emotional valence primarily through a global activation signal, rather than distributed patterns consisting of separate clusters of positive and negative voxels, and a more distributed valence representation emerges when voxels surrounding the amygdala are taken into consideration.

Depression symptoms enhance goal-directed behavior underuncertainty
Achieving goals in uncertain environments requires integrating expected benefits, costs, and the likelihood of outcomes - processes that may be disrupted in depression. Although depression is characterized by affective and motivational biases, the computational mechanisms by which these symptoms shape goal-directed decision-making remain poorly understood. We investigated these mechanisms using a novel goal-directed decision task. After learning the structure of the environments, participants (n = 384) chose between certain rewards and risky goals varying in both reward magnitude and distance, where greater goal distance led to higher compounded risk of failure. Using transdiagnostic symptom factors derived from clinical questionnaires, we found that individuals with higher apathy-anhedonia symptoms reported lower expectations of goal success yet showed enhanced performance across multiple aspects of goal-directed behavior. These results reveal a dissociation between perceived risk and its influence on choice in individuals with motivational symptoms, and uncover a novel positive link between these symptoms and adaptive behavior.

Neuroinflammation in Olfactory Circuits Underlies Odor Hypersensitivity in a Rodent Model of Depression
Depression can affect quality of life in several ways, including reduced concentration, motivation, and energy. Olfactory anhedonia in depressed patients results in a decreased attraction to pleasant smells and increased aversion to unpleasant odors. We used the Unpredictable Chronic Mild Stress (UCMS) as an induced-depression model to study olfactory perception and avoidance in mice of both sexes. After inducing a depression-like state, we observed an increased sensitivity to aversive odorants as well as an associated increase in escape behavior in an odorized environment. Previous studies using a similar model of induced depression have demonstrated increased neuroinflammation in brain areas, including the medial prefrontal cortex, but few have explored the effects in olfactory processing centers. We used immunohistochemistry to measure changes in astrocytic activation and microglia in multiple olfactory regions of the brain to further investigate the connection between neuroinflammation and odor hypersensitivity. We found an increase in the number of astrocytes in the medial amygdala, which receives direct input from the accessory olfactory bulb, and more complex microglial morphology in the olfactory bulb and piriform cortex. Additional analysis revealed a relationship between the extent of neuroinflammation and odor aversion. Our findings indicate that glial cells in sensory processing centers are sensitive to stress-induced depression and contribute to altered olfactory perception.

Choroid plexus sex differences in secretory signalling and immune compartments
The choroid plexus (ChP)- cerebrospinal fluid (CSF) axis is emerging as a key regulator of the brain environment. The ChP is a multi-functional structure, which forms the blood-CSF barrier, and acts as a sensor of inputs from the periphery and the brain, dynamically responding by modulating its secretome into the CSF. However, sex differences in the ChP have been little explored. Molecular profiling of the adult mouse ChP at the transcriptomic and proteomic levels revealed sex differences across multiple cell types, with immune signatures enriched in females. Interestingly, border associated macrophages showed distinct sex differences in the stromal and epiplexus compartments. We further uncovered sex differences in ChP secretory signalling, with functional differences between males and females. Finally, the human LVChP showed largely similar sex differences. Together, our findings highlight that sex differences may play an important role in ChP function in both health and disease.

Large vision model framework for automated C. elegans analysis: From static morphometry to dynamic neural activity
Quantitative phenotyping of Caenorhabditis elegans is essential across numerous fields, yet data extraction remains a significant analytical bottleneck. Traditional segmentation methods, typically reliant on pixel-intensity thresholding, are highly sensitive to variations in imaging conditions and often fail in the presence of noise, overlaps, or uneven illumination. These failures necessitate meticulous experimental setups, expensive hardware, or extensive manual curation, which reduces throughput and introduces bias. Here, we introduce TWARDIS (Tools for Worm Automated Recognition & Dynamic Imaging System), a modular, Python-based analysis suite that leverages large foundation vision models, specifically the Segment Anything Models (SAM and SAM2) and a fine-tuned vision transformer classifier, to overcome these limitations. We demonstrate the versatility and robustness of our AI compound system across diverse modalities. For static morphological analysis, TWARDIS successfully resolved overlapping worms in noisy images without human intervention, showing a 0.999 correlation with manual segmentation. In behavioral assays (swimming and crawling), the pipeline enabled high-definition postural analysis even in low-resolution, wide-field recordings where the worm occupied only ~0.25% of the field of view, accurately resolving complex postures without frame rejection. Finally, when applied to calcium imaging of semi-restricted animals, TWARDIS provided precise, frame-by-frame segmentation of neural compartments, reducing the artificial signal flattening common in traditional region-of-interest-based approaches and enabling the extraction of biologically accurate, absolute head positions. The system's hardware-scalable architecture and modular design ensure both current accessibility and future improvements without restructuring. By automating the most time-consuming aspects of image analysis, TWARDIS removes critical bottlenecks and tradeoffs in C. elegans research, enabling researchers to focus on biological questions rather than technical image processing challenges.

Cis-regulatory fragments from the dissatisfaction gene identify novel mating behavior neurons in female Drosophila
During Drosophila courtship, males chase and sing to females, while females perform abdominal behaviors to indicate their willingness to mate. The nerve cord circuits in females that produce their abdominal behaviors are poorly characterized. We recently identified an anatomically diverse population of abdominal interneurons, the DDAG neurons, which express the Tlx-like nuclear receptor dissatisfaction (dsf) and influence several female mating behaviors. Here, we searched the dsf locus for cis-regulatory enhancer fragments that regulate its spatial expression in the adult and larval central nervous system. We found several enhancers, most located within two introns, that drove reporter expression in subsets of dsf-expressing neurons throughout the brain and nerve cord. Using one of these enhancers, we genetically isolated a single subtype of female-specific DDAG local interneurons. Optogenetic activation of these neurons triggered vaginal plate opening in both unmated and mated females, a behavior used by Drosophila females to signal receptivity to courting males. Our findings offer new reagents to target dsf-expressing cells and new insights into the neural substrates in Drosophila females that express their mating decisions during courtship.

An Anterior Cingulate Cortex Neuronal Ensemble Controls Contextual Opioid Analgesic Tolerance
Despite well-established cellular and molecular adaptations, opioid analgesic tolerance can be rapidly reversed in settings where these drugs are not expected. The specific neuronal populations that orchestrate this expectation-based tolerance remain poorly defined. In this study, we used a contextual tolerance training method alongside whole-brain clearing and immunostaining to identify brain regions involved in contextual tolerance and to pinpoint a specific neuronal ensemble in the ACC activated by this process. We observed that calcium activity in principal neurons of the ACC is suppressed by fentanyl in opioid-naive mice or during contextual reversal but not during contextual tolerance. Chemogenetic silencing of the ACC induced tolerance reversal in the opioid-associated context without affecting thermal nociception in opioid-free mice. Furthermore, chemogenetic activation of the ACC contextual tolerance-active neuronal ensemble triggered analgesic tolerance in an unassociated context. This research highlights a role for ACC neuronal ensembles in mediating expectation-driven, contextual opioid analgesic tolerance without affecting basal nociception. Therefore, modulating the ACC could provide a promising strategy to improve pain relief while maintaining the essential ability to detect harmful stimuli.

Deep transcriptome profiling of human hypothalamic agouti-related protein and proopiomelanocortin neurons regulating energy homeostasis
We have developed and validated a pioneering 'IHC/LCM-Seq' method for transcriptome profiling of spatially defined neuronal cell types detected with immunohistochemistry in sections of formaldehyde-fixed human brains. IHC/LCM-Seq provided unprecedented insight, with 14,000-16,000 transcripts identified, into the gene expression landscape of human agouti-related peptide (AgRP) neurons, which drive appetite and energy storage, and proopiomelanocortin (POMC) neurons, which suppress feeding and promote energy expenditure. These cells differed from each other, and from fertility-regulating kisspeptin neurons, in their distinct enrichments of co-transmitters, transcription factors, and receptors. The AgRP neuron transcriptome was rich in receptors for proinflammatory cytokines, metabolic hormones and growth hormone, whereas POMC neurons expressed reproductive hormone-, glucagon-like peptide- and endocannabinoid receptors. IHC/LCM-Seq, a versatile spatial transcriptomic approach for characterizing cell types in postmortem brains, opened a new window onto molecular mechanisms regulating energy homeostasis in the human hypothalamus and highlighted possible pharmacological targets for weight management.

Strain variation identifies a neural substrate for behavioral evolution in Drosophila
Sexual selection acts on heritable differences within species, driving the parallel diversification of signal production in one sex and behavioral responses in the other. This coevolution implies that sensory preferences are themselves variable traits, yet the neural basis of such variation remains unclear. Here, we identify striking strain-specific differences in Drosophila melanogaster male mate preferences that arise from differential sensitivity to heterospecific female pheromones. We map this variation to an ascending inhibitory pathway targeting a central circuit node known to dynamically pattern courtship. Inhibitory circuits thus emerge as a key locus for shaping mate discrimination via transient suppression of a males pursuit. Our findings highlight how variation within sensory circuitry serves as a substrate for selection, fueling the evolution of reproductive barriers between species.

Proteo-transcriptomic reprogramming and resource reallocation define the aging mammalian brain
Brain aging is a major risk for neurodegeneration, yet the underlying molecular mechanisms remain poorly understood. Here we performed an integrative proteo-transcriptomic analysis of the aging mouse brain, uncovering molecular signatures of aging through the assessment of protein aggregation, mRNA relocalization, and comparative proteomics across eight models of premature aging and neurodegeneration. We identified dynamic changes in physiological aging highlighting differences in synaptic maintenance and energy-allocation. These were linked to changes associated with fundamental protein biochemical properties such as size and net charge. Network analysis highlighted a decrease in mitochondrial complex I proteins not compensated at the mRNA level. Aggregation of 60S ribosome subunits indicated deteriorating translation efficiency and was accompanied by mitochondrial and proteasomal imbalance. The analysis of the nine models revealed key similarities and differences between physiological aging and pathology. Overall, our study provides an extensive resource on molecular aging, and offers insights into mechanisms predisposing to neurodegeneration, easily accessible at our Brain Aging and Molecular Atlas Project (BrainAging-MAP) website.

Systemic neonatal AAV9 gene therapy delivery improves behavioral and phenotypic outcomes comparable to intracerebroventricular delivery in a mouse model of Niemann-Pick disease, type C1
Niemann-Pick disease, type C (NPC), is an inherited fatal lysosomal storage disorder caused by a mutation in the NPC1 or NPC2 genes and characterized by impaired lysosomal cholesterol export. Previous studies have demonstrated that delivery of the NPC1 gene to the central nervous system (CNS) via an adeno-associated virus (AAV) can substantially improve lifespan and mitigate signs of disease in Npc1-deficient mouse models of NPC. To determine the optimal parameters for an efficacious AAV-based gene therapy for NPC, we measured the survival and disease phenotypes of mice treated systemically as neonates or at weaning age, along with neonatal mice treated via intracerebroventricular (ICV) delivery, with a construct containing either a ubiquitous truncated EF1 promoter or a truncated Mecp2 promoter. While all constructs and delivery methods resulted in improvement compared with baseline, mice treated as neonates survived significantly longer and experienced slower disease progression compared with those treated systemically at weaning age. Systemic delivery to neonates was capable of increasing survival and phenotypic improvement comparable to that of ICV delivery, and neonatal systemic and ICV delivery were both similarly capable of near-total Purkinje cell rescue. We also found no difference between a ubiquitous EF1-derived promoter and an Mecp2-derived promoter. Ultimately, early treatment with maximal access to the CNS, whether via systemic or direct CNS delivery, is key to the efficacy of gene therapy in treating NPC.

Distinct roles of hippocampus and neocortex in symbolic compositional generalization
Humans can combine symbols to generate new meanings. Here, we studied the regional neural mechanisms that might make this possible. We asked participants to combine two discrete, symbolic features (a shape and a colour) to make a novel spatial inference. BOLD data suggested that the hippocampus encoded elementary visual attributes in a high-dimensional, parallel format that permitted flexible individuation. In ventromedial prefrontal cortex (vmPFC), posterior parietal cortex (PPC) and primary visual cortex (V1), neural patterns for novel stimuli (composites) could be predicted as a linear combination of signals for familiar stimuli (elements). In vmPFC, this composition occurred in a high-dimensional format, but in PPC and V1, it took place in a low-dimensional, spatial, response-consistent frame of reference. These data offer new insights into the neural circuit underlying compositional generalization.

Functional organization of multisensory integration network in children and youth with neurodevelopmental disorders predicts clinical sensory issues
Differences in sensory processing in neurodevelopmental conditions, including Autism Spectrum Disorder (ASD) and Attention-deficit/Hyperactivity Disorder (ADHD), cascade into downstream clinical symptomatology. This includes differences in combining sensory information from multiple modalities into a unified percept, known as multisensory integration. Little is known about the functional organization of multisensory network (MSN) in these groups, its relation to clinical sensory issues, or its interaction with other higher-order cortical networks. We examined resting-state fMRI data from 417 participants in the Province of Ontario Neurodevelopmental Network (ASD=174, ADHD=130, Typical Development=113; Mean age=11.96, SD = 4.10). Timeseries data were extracted from the MSN and seven additional resting-state cortical networks (RSNs). Undirected and directed functional connectivity (FC) metrics were computed within the MSN and between the MSN and other RSNs. FC was compared across diagnoses and related to clinical sensory characteristics. The thalamus emerged as a hub region in both undirected and directed FC within the MSN and between the MSN-RSNs. Some diagnosis-related differences were observed, with increased MSN-RSN FC particularly in ADHD; however, associations with sensory characteristics were stronger in both undirected and directed FC within the MSN and between the MSN-RSNs, regardless of diagnosis. Converging evidence was seen in data-driven clusters based on FC metrics, which did not align with diagnosis, but instead mapped on to the overall level of sensory issues reported. That the data-driven clusters sorted not by diagnosis but by sensory characteristics suggests that these sensory characteristics and their underlying neurobiology are transdiagnostic in nature as opposed to specific to ASD or ADHD.

Discrete Subfields and Continuous Gradients Coexist: A Multi-Scale View of Hippocampal Organization
The human hippocampus is studied via two competing frameworks: one dividing it into discrete anatomical subfields with distinct computational processes, and another describing it as a continuous, functional gradients along the anterior-posterior and medial-lateral axes. How these organizational principles relate to one another, particularly regarding intrinsic neural timescales of the hippocampus, remains unknown. Here, we used high-resolution resting-state fMRI to investigate how single-voxel autocorrelation, a measure of intrinsic neural timescale, maps onto hippocampal subfields. We found evidence for a hybrid organization. First, consistent with our predictions, we observed significantly higher autocorrelation (longer timescales) in the subiculum compared to the other subfields. Contrary to our hypotheses, we found that CA1, which is implicated in integration, had low autocorrelation whereas CA2/3 and CA4DG, which are linked to pattern separation, had intermediate autocorrelation. Second, we discovered that the overarching anterior-posterior and medial-lateral gradients of autocorrelation were recapitulated within each individual subfield. Finally, data-driven clusters of autocorrelation values aligned more strongly with the continuous gradients than with the discrete anatomical boundaries, particularly in the right hemisphere. These results suggest that the discrete and continuous views of hippocampal organization are not mutually exclusive but coexist across different spatial scales. We therefore propose a new comprehensive model of hippocampal function that integrates both its modular, subfield-specific properties and its graded, large-scale organization.

Dynamic representation of sound locations during task engagement in marmoset auditory cortex
In auditory cortex, neural responses to stimuli inside receptive fields (RFs) can be further facilitated by behavioral demands, such as attending to a spatial location. It is less clear how off-RF stimuli modulate neural responses and contribute to behavioral tasks. Our recent study revealed a particular form of location-specific facilitation evoked by repeated stimulation from an off-RF location, suggesting behavioral modulation of spatial RFs. To further explore this question, we trained marmosets to attend to sound locations that were either inside or outside the RFs of auditory cortical neurons. The majority of neurons showed increased firing rates at target locations inside their RFs. Interestingly, this increase also occurred outside the RFs, sometimes exceeding the responses at the RF center during passive listening. These task-related off-RF facilitation were much more common in the caudal area than in the rostral area and the primary auditory cortex. A normalization model reproduced the off-RF facilitation using widespread suppression. The models prediction was confirmed by experimental observations of widespread reductions in firing rate and hyperpolarized membrane potentials for off-RF stimuli. These results suggest that behavioral task demands recruit a broader range of neurons than those that are responsive to a target sound in the passive state.

Deterministic versus Probabilistic Tractography: Impact on White Matter Bundle Shape
In diffusion MRI-based tractography, deterministic and probabilistic algorithms reconstruct white matter using distinct strategies, yet their impact on bundle morphology remains uncertain. Using bundle shape similarity analysis, we compared both methods for the left arcuate fasciculus (AF_L) (The left arcuate fasciculus is a critical white matter tract that connects language comprehension and production areas in the human brain, enabling fluent language processing) across four datasets: Alzheimer's Disease Neuroimaging Initiative (ADNI), Human Connectome Project-Aging (HCP-A), National Institute of Mental Health and Neurosciences (NIMHANS), and Pediatric Imaging, Neurocognition, and Genetics (PING). Probabilistic tractography consistently produced higher inter-subject shape similarity, by capturing broader anatomical trajectories and enhancing reproducibility. However, this extensive coverage may obscure subtle pathological variations critical for clinical detection. Bundle shape similarity analysis with atlas corroborated these findings, showing stronger alignment for probabilistic tracking and highlighting its utility in quantitative quality control. These results emphasize the need to balance morphological consistency with sensitivity to neuroanatomical variation when selecting tractography methods for research and clinical applications.

Ongoing thoughts at rest reflect functional brain organization and behavior
Resting-state functional connectivity (rsFC)-brain connectivity observed when people rest with no external tasks-predicts individual differences in behavior. Yet, rest is not idle; it involves streams of thoughts. Are these ongoing thoughts reflected in rsFC? To test this question, we developed a novel annotated rest paradigm where participants rated and verbally described their thoughts after each rest period during functional MRI (N = 60). Our findings revealed rich and idiosyncratic thoughts across individuals. Similarity in thoughts was associated with more similar rsFC patterns within and across individuals. In addition, both thought ratings and topics could be decoded from rsFC. Furthermore, neuromarkers of these thoughts generalized to unseen individuals in the Human Connectome Project dataset (N = 908), where decoded thought patterns during rest predicted positive vs. negative trait-level individual differences. Together, our findings reveal that ongoing thoughts at rest are reflected in brain dynamics and these network patterns predict everyday cognition and experiences. Understanding subjective in-scanner experiences is thus crucial in characterizing the relationship between individual differences in functional brain organization and behavior.

EEG-decodability of facial expressions and their stereoscopic depth cues in immersive virtual reality
Face perception typically occurs in three-dimensional space, where stereoscopic depth cues enrich the perception of facial features. Yet, most neurophysiological research on face processing relies on two-dimensional displays, potentially overlooking the role of stereoscopic depth information. Here, we combine immersive virtual reality (VR), electroencephalography (EEG), and eye tracking to examine the neural representation of faces under controlled manipulations of stereoscopic depth. Thirty-four participants viewed computer-generated faces with neutral, happy, angry, and surprised expressions in frontal view under monoscopic and stereoscopic viewing conditions. Using time-resolved multivariate decoding, we show that EEG signals in immersive VR conditions can reliably differentiate facial expressions. Stereoscopic depth cues elicited a distinct and decodable neural signature, confirming the sensitivity of our approach to depth-related processing. Yet, expression decoding remained robust across depth conditions, indicating that under controlled frontal viewing, the neural encoding of facial expressions is invariant to binocular depth cues. Eye tracking showed that expression-related gaze patterns contained comparable information but did not account for neural representations, while depth information was absent in gaze patterns--consistent with dissociable representational processes. Our findings demonstrate the feasibility of EEG-based neural decoding in fully immersive VR as a tool for investigating face perception in naturalistic settings and provide new evidence for the stability of expression representations across depth variations in three-dimensional viewing conditions.

Neuromodulator control of energy reserves in dopaminergic neurons
The brain is a metabolically vulnerable organ as neurons have both high resting metabolic rates and the need for local rapid conversion of carbon sources to ATP during activity. Midbrain dopamine neurons are thought to be particularly vulnerable to metabolic perturbations, as a subset of these are the first to undergo degeneration in Parkinsons disease (PD), a neurodegenerative disorder long suspected to be in part driven by deficits in mid-brain bioenergetics (1). In skeletal muscle, energy homeostasis under varying demands is achieved in part by its ability to rely on glycogen as a fuel store, whose conversion to ATP is under hormonal regulatory control. In neurons however the absence of easily observable glycogen granules has cast doubt on whether this fuel store is operational, even though brain neurons express the key regulatory enzymes associated with building or burning glycogen (2). We show here that that in primary mid brain dopaminergic neurons, glycogen availability is under the control of dopamine auto receptors (D2R), such that dopamine itself provides a signal to store glycogen. We find that when glycogen stores are present, they provide remarkable resilience to dopamine nerve terminal function under extreme hypometabolic conditions, but loss of this dopamine derived signal, or impairment of access to glycogen, makes them hypersensitive to fuel deprivation. These data show that neurons can use an extracellular cue to regulate local metabolism and suggest that loss of dopamine secretion might make dopamine neurons particularly subject to neurodegeneration driven by metabolic stress.

Significance StatementThis work demonstrates that a neurons metabolic resilience is actively shaped by local neuromodulation, providing a potential explanation for why different neuronal subtypes exhibit unequal vulnerability to metabolic stressors and why dopamine neurons become more vulnerable when they lose the capacity to release dopamine.

Postnatal plasticity in the olfactory system of the juvenile swine brain
Swine have an excellent sense of smell and highly complex olfactory brain structures, which play a crucial role in their complex social interactions. In other mammals the olfactory system is known to exhibit significant plasticity, even during adulthood. The aim of this study was to investigate postnatal plasticity in olfactory areas of juvenile swine brains by studying immature cells immunoreactive for the microtubule-associated protein doublecortin (DCX). Using immunofluorescence, we studied DCX coexpression with the cell proliferation marker Ki-67, and different neuronal markers. Our results show the existence of numerous DCX+ cells throughout the olfactory pallial areas. In some of them, we found DCX+/Ki-67+ coexpressing cells, suggesting that they were proliferating. Some of these proliferating cells were grouped in tangentially-oriented migratory-like chains, forming the rostral migratory stream to anterior olfactory area and olfactory bulb. Moreover, chains of DCX+ cells were found in the external capsule and white matter adjacent to the temporal horn of the ventricle. Chains of DCX+ cells were observed crossing the internal layers of the piriform and entorhinal cortices. In layer II of these cortices, DCX+ cells of varying maturity degrees and neuronal phenotypes (including NeuN expression) were present. This suggests the existence of multiple migratory streams along the anteroposterior axis. Most DCX+ immature cells in the migratory chains and in the anterior olfactory area, piriform and entorhinal cortices expressed the transcription factor Brn2 (Pou3f2), suggesting the incorporation of new glutamatergic neurons in these areas. Together, these results highlight the interest of swine to study the role of postnatal brain plasticity and their potential for regeneration in large, gyrencephalic brains.

Sleep Renormalizes Negative Emotional Generalization
Overgeneralization of negative experiences, in which aversive responses spread to otherwise safe stimuli, often co-occurs with sleep disruption, and both are central features of anxiety and posttraumatic stress disorder (PTSD). Here, we show that sleep shifts emotional generalization away from the negative and toward the positive. Across three experiments combining behavior, fMRI, and sleep electrophysiology, participants learned to associate three faces with positive, negative, or neutral outcomes. Participants were tested using morphed faces that blended the original stimuli in varying proportions. Immediate generalization was assessed post-learning, and delayed generalization was assessed after overnight sleep or daytime wakefulness. Behaviorally, we found that sleep selectively promotes positive generalization, whereas prolonged daytime wakefulness favors generalization of the negative face. In the fMRI scanner, amygdala and limbic activity during outcome processing predicted stronger immediate generalization of the negative face, and subsequent shift from negative to positive face generalization that occurred only after sleep. Overnight sleep spindle activity, extracted from high-density sleep EEG, positively correlated both with positive face generalization and with the shift from negative to positive generalization following sleep. These findings reveal a potential neural mechanism by which sleep attenuates negative bias and enhances positive representations, suggesting a potential method to buffer against maladaptive generalization in anxiety and PTSD.

Developmental plasticity facilitates the structural maturation of cochlear inner hair cell ribbon synapses
Sound detection occurs in the cochlea, where sensory inner hair cells (IHC) accurately convert auditory stimuli into neurochemical signals. Presynaptically, IHCs harbor synaptic ribbons, specialized scaffolds that facilitate ultrafast and indefatigable exocytosis. During synapse assembly and subsequent maturation, IHC ribbons increase in volume and synaptic vesicle tethering capacity. This development is thought to result from progressive precursor aggregation. However, the underlying mechanisms of ribbon synapse formation have remained elusive thus far. In this study, we established a novel triple-color live-cell imaging approach to monitor IHC presynaptogenesis in situ. We found that ribbon precursors are highly dynamic and undergo bidirectional plasticity. The presynaptic active zone (AZ) forms a focal point for dramatic structural remodeling of precursors, which the AZ recruits, confines and redistributes. Furthermore, silencing spontaneous synaptic activity decreased precursor mobility and plasticity at the AZ. This suggests a fundamental role for activity-dependent Ca2+ influx in the plastic development shaping the unique properties of auditory ribbon synapses.

White matter microstructure predicts effort and reward sensitivity
From rodents to humans, animals constantly face a central question: is the reward worth the effort? Effort and reward sensitivity in such situations vary substantially across individuals and ultimately shape goal-directed behavior. Yet, the brain mechanisms underlying this variability across individuals remain unclear. Here, we combined computational modeling of effort and reward sensitivity during decision-making with whole-brain diffusion MRI in 45 healthy participants to identify white matter substrates of individual sensitivity. A data-driven, cluster-based analysis of fractional anisotropy and mean diffusivity revealed 12 clusters: five linked to effort sensitivity, all within tracts connected to major frontal valuation nodes (e.g., supplementary motor area [SMA], dorsal anterior cingulate cortex [dACC], orbitofrontal cortex [OFC]), and seven linked to reward sensitivity, spanning frontal valuation, fronto-parietal, and sensorimotor networks. The strongest associations involved two SMA-connected clusters, one shared across effort and reward sensitivity and another consistent across both microstructural metrics. Critically, microstructural features from the five effort-related and seven reward-related clusters reliably predicted individual effort and reward sensitivity in out-of-sample machine learning analyses, respectively, whereas randomly sampled clusters did not. SMA-connected tracts were the dominant predictors in these decoding analyses, with additional contributions from fronto-parietal and sensorimotor pathways for reward sensitivity. These findings reveal a distributed white matter architecture underlying inter-individual differences in effort and reward sensitivity, with SMA pathways emerging as central hubs. They demonstrate that localized white matter microstructure can robustly predict these individual differences, offering a framework to forecast the impact of lesions or interventions on goal-directed behavior, including apathy and impulsivity.

SIGNIFICANCE STATEMENTWhy do some people give up easily when faced with high effort demands, while others persist even when rewards are small? Such differences in effort and reward sensitivity shape goal-directed behavior, yet their neural basis is unclear. Using diffusion MRI and computational modeling, we show that white matter microstructure in specific pathways reliably predicts individual differences in these sensitivities. Tracts connected to the supplementary motor area emerged as central hubs, with additional contributions from fronto-parietal and sensorimotor networks. These results demonstrate that variability in effort and reward sensitivity is rooted not only in brain activity but also in structural connectivity, providing a framework to anticipate how white matter lesions or interventions may alter goal-directed behavior, including apathy and impulsivity.

White Matter Tract Vulnerability to Amyloid Pathology on the Alzheimer's Disease Continuum
Alzheimer's disease (AD) is marked by progressive cognitive decline and memory loss, due to the abnormal accumulation of amyloid-beta (A{beta}) plaques, followed by tau pathology, and a gradually spreading pattern of neuronal loss. Understanding how amyloid positivity affects the brain's neural pathways is critical for understanding how the brain changes with AD pathology. Tractometry offers a powerful approach for the in vivo, 3D quantitative assessment of white matter tracts, enabling the localization of microstructural abnormalities in diseased populations and those at risk. In this study, we applied BUAN (Bundle Analytics) tractometry to multi-cohort diffusion MRI data from a total of 1,908 participants: 606 participants in ADNI3 (Alzheimer's Disease Neuroimaging Initiative Phase 3) and 1,302 participants from the HABS-HD (Health and Aging Brain Study - Healthy Diversity). Using BUAN and along-tract statistical analysis, we assessed the localized effects of amyloid positivity, potentially mediated by tau, on white matter pathways, with amyloid positivity quantified via amyloid-sensitive positron emission tomography (PET). BUAN enables tract-specific quantification of white matter microstructure and supports statistical testing along the full length of fiber bundles to detect subtle, spatially localized associations. We present 3D visualizations of tract-wise amyloid associations, highlighting distinct patterns of white matter degeneration in AD.

Phenotypic characterization of a mouse model of Rett syndrome reveals pubertal dysregulation and hypothalamic-gonadal dysfunction
Background: Mutations in the MECP2 gene, encoding the epigenetic reader Methyl-CpG binding protein 2, are the main cause of Rett syndrome, a rare neurodevelopmental disorder. Besides severe symptoms such as profound intellectual disability, loss of speech and motor skills and epilepsy, loss of function of MECP2 has been associated with pubertal dysregulation, but the biological mechanisms leading to this remain unclear. Methods: We first carried out a patient survey to assess pubertal timing in a sample of Spanish patients with Rett syndrome. Second, using a mouse model of Rett, in which males are hemizygous and females heterozygous for Mecp2 loss of function mutation, we assessed the onset and progression of puberty, together with increase in body weight and onset of neurological symptoms in post-weaning mice until puberty. In brain samples of young adult mice, we analysed hypothalamic Gonadotropin releasing hormone (GnRH) neurons by immunofluorescent labelling, and in plasma samples measured circulating GnRH and testosterone concentrations. Finally, we analysed testosterone dependent arginine-vasopressin circuits. Results: Our data in patients are in agreement with previous reports showing that a subset of female patients with Rett syndrome experience a delayed timing of menarche. Further, in our mouse model we found delayed puberty in Mecp2CD1-null males, associated with a reduced rate of weight gain, but with puberty onset occurring at a lower body weight than in wildtype controls. Despite later puberty onset, Mecp2CD1-null male mice were found to have an increased number of GnRH neurons, but displayed lower levels of circulating reproductive hormones. Consequently, Mecp2CD1-null males have deficient testosterone-dependent arginine-vasopressin innervation. In female Mecp2CD1-heterozygous mice, we found no overall significant differences in pubertal development or GnRH neurons, albeit in a subset of mice with early neurological symptoms, we found lower body weight, and a trend to delayed vaginal opening but precocious first oestrous, attributable to variable phenotypic penetrance. Conclusions: Our data supports that MECP2 is essential for typical pubertal development, with complete loss of Mecp2 in a male murine model resulting in abnormalities of pubertal timing with an observed increase in hypothalamic GnRH neurons.

Interpretable EEG Biomarkers for Neurological Disease Models in Mice Using Bag-of-Waves Classifiers
Electroencephalograms (EEGs) are time-series records of the electrical potential from collective neural activity in the brain. EEG waveform patterns--rhythmic and irregular oscillations and transient patterns of sharp waves or spikes--are potential phenotypical biomarkers, reflecting genotype-specific neural activity. This is especially relevant to diagnosing epilepsy without direct seizure observations, which is common in clinical settings, as well as in animal models, which often have subtle neurological phenotypes without overt epilepsy. Herein, we investigate genotypic prediction from long-term EEG signals of freely behaving mice belonging to six groups defined by the presence or absence of a neurological disease-genotype (TSC1 gene knockout) in three different inbred strains with distinct genetic backgrounds. The potential complexity of genotype-related EEG patterns motivates a machine learning approach to automatically extract time-series descriptors, such as waveforms or spectral content, as biomarkers. We propose a machine learning approach to predict the genotypes of individual mice from the occurrence counts of waveforms that approximate short windows of the EEG. That is, a dictionary of waveforms is optimized to approximate windows from each genotype, and the vectors of waveform occurrence counts are the features for predicting genotypes via logistic regression models. Across two-fold cross-validation of the waveform dictionary learning, and leave-one-individual-out genotype prediction, we find that waveform counts pooled over multiple hour segments enable reliable prediction of mouse strain with an accuracy of 70% (chance rate of 38%), and for two of the three strains, DBA2 and C57B6, strain-specific classifiers reliably determined the epilepsy-genotype (TSC1 gene knockout) at a 67% sensitivity with a 100% specificity for DBA2 and 67% specificity for C57B6. None of the mice of these strains had evidence of overt seizures or EEG-based seizure detection. The methodologies and results show the potential of EEG waveform as phenotypes and bag-of-waves as a feature representation for identifying epilepsy genotypes.

Cortical thickness changes precede high levels of amyloid by at least seven years
Alzheimer's disease (AD) is now defined based on its underlying brain pathology, with the presence of amyloid (A{beta}) plaques at high enough levels sufficient to warrant a diagnosis in the absence of cognitive symptoms. High levels of PET-detectable A{beta} are widely thought to be the first imaging marker, with structural brain changes detectable on MRI scans thought to occur later. We combined 4570 longitudinal MRIs and 1684 A{beta} PET scans from three cognitively healthy cohorts to test the difference in cortical thickness and its change between those that subsequently converted to be A{beta}-positive or stayed A{beta}-negative, using MRIs acquired exclusively in the years before conversion. We found those that subsequently developed elevated A{beta} levels show both thicker cortex and less cortical thinning, even when the last MRI used to estimate their thickness trajectories was acquired at least seven years before conversion. Many effects remained when accounting for quantitative A{beta} levels, suggesting some cortical thickness effects may be partly independent of A{beta}. Differences in cortical thickness and its change between converters and A{beta}-negative individuals showed moderate alignment with patterns of A{beta} deposition, and the timing of thickness changes tracked the temporal progression of A{beta} accumulation. Thus, if amyloid is AD, we show that high levels of PET-detectable amyloid are not the first imaging marker of AD, as cortical thickness changes can be traced years before pathological amyloid. This has implications for understanding the sequence of events leading up to the earliest stages of AD.

Rapid Invisible Frequency Tagging (RIFT) with a consumer monitor: A proof-of-concept
Rapid Invisible Frequency Tagging (RIFT) enables neural frequency tagging at rates above the flicker fusion threshold, eliciting steady-state responses to flicker that is almost imperceptible. While RIFT has proven valuable for studying visuospatial attention, it has so far relied on costly projector systems, typically in combination with magnetoencephalography (MEG). The recent emergence of high-speed organic light-emitting diode (OLED) monitors for consumers suggests that RIFT may also be feasible with much more accessible hardware. Here, we provide a proof-of-concept demonstrating successful RIFT using a consumer-grade 480 Hz OLED monitor in combination with electroencephalography (EEG). We also share practical recommendations for achieving precise stimulus timing at 480 Hz with minimal frame drops. In a central fixation task, participants viewed a tapered disc stimulus flickering either centrally or peripherally. Luminance was modulated sinusoidally at 60 Hz or 64 Hz, frequencies at which the flicker was barely visible. Photodiode recordings confirmed that the monitor delivered accurate frame timing with few dropped frames. Cross-coherence analysis between occipital EEG channels and a photodiode revealed robust, frequency-specific neural tagging responses for central stimuli at both frequencies. In comparison, weaker coherence was observed for 60 Hz peripheral flicker. Our findings demonstrate that RIFT can be reliably implemented using affordable stimulation hardware, a low-density EEG montage, and a minimal processing pipeline. We hope that this lowers barriers to entry, facilitating broader use of RIFT in basic research and in applied settings where cost and portability matter.

White matter microstructure changes across the lifespan: a meta-analysis of longitudinal diffusion MRI studies
White matter in the human brain is known to play a critical role in facilitating communication between different brain regions. White matter microstructure is often quantified using fractional anisotropy (FA) derived from diffusion-weighted MRI, and is often considered a key measure of neural efficiency that is positively associated with motor and cognitive functioning. While lifespan trajectories of FA have been well studied in cross-sectional designs, it remains less clear how FA changes longitudinally with age across the lifespan, and whether the rates of change are influenced by genetic variation. We systematically reviewed the evidence of white matter changes, as measured by fractional anisotropy (FA) with diffusion magnetic resonance imaging longitudinally across the lifespan, and the genetic influences on this change. Searches were conducted in Medline, PsycInfo, and EMBASE up to August 2023 with terms related to DTI/FA and longitudinal/change. Following this, genetic-related search terms were applied to the results and the search was broadened to include other measures of white matter change. Our systematic search resulted in 29 studies that met our criteria. In addition, 14 studies investigated genetic influences on FA change rates across the lifespan. A meta-regression using a thin-plate spline model was conducted to examine annual whole-brain FA change as a function of age. Across childhood and adolescence, FA increased, and the rate of increase slowed into early adulthood. Between ages 20 and 35, changes in FA were not statistically significant. This was followed by a significant decline in FA between ages 36 and 50. The decreases plateaued between ages 51 and 61, and then continued at a slightly slower rate towards the upper end of the age range assessed (77 years). Average FA change per year relative to baseline assessment reached a maximum of +1.1% during development, and -0.6% per year, during ageing. Significant heritability was found for change in local but not global FA during development. During ageing, common variants in genes that have been related to increased risk for neuropsychiatric disorders (APOE, HTT, MAPT) were associated in some studies with accelerated local FA decreases over time. In conclusion, there are changes in white matter microstructure within individuals across the lifespan, with increases during childhood, adolescence and early adulthood, followed by a period of relative stability during early to mid-adulthood, and subsequent gradual declines from midlife onwards. Evidence is emerging for genetic influences on white matter changes over time, shaping individual trajectories.

Retrieval-mediated and sleep-based memory consolidation provoke different neural and behavioural markers of memory generalisation.
Across sleep-based and retrieval-mediated consolidation, memories typically become generalised and less dependent on their episodic components for their recollection. However, memory transformations across sleep and retrieval training have not been directly compared. The current study aims to compare how sleep and retrieval training impact the endorsement of semantically similar and different lures, as well as their episodic recollection using the parietal old/new effect on the late positive component (LPC) in subjects' EEG. Thirty subjects (27F, 18-34, M=22.17) attended four sessions where they learnt different sets of 104 object-word pairs and completed one of four 120-minute memory interventions: retrieval training (i.e., cued recall practice), restudy (i.e., pair re-exposure), a nap opportunity, or a wakeful rest. EEG was recorded while subjects were tested on their recognition accuracy in an old/new paradigm with similar- and different-object lures. Our results revealed that retrieval training, but not sleep, lead to greater accuracy for identifying old pairs, but worse similar-lure discrimination. Whilst the parietal old/new effect did not differ between conditions, retrieval had lower LPC amplitudes for similar- than different-object false alarms, whilst restudy demonstrated the opposite. Sleep and wake demonstrated no differences in LPC amplitudes between hits and different false alarm types. Together, our study demonstrates evidence for gist-abstraction across retrieval training, and a task-relevant selective maintenance of episodic details across sleep. These results challenge theories that retrieval training replicates sleep-based consolidation mechanisms, instead acting as a fast route to semanticization regardless of the context.

Symptomatic treatment by a BBB-permeable AAV engineered to restore TDP-43 function slows motor neuron disease and prevents paralysis
TAR DNA-binding protein 43kDa (TDP-43) dysfunction is an early pathogenic mechanism that underlies amyotrophic lateral sclerosis (ALS), a devastating neurodegenerative disorder that lacks disease modifying therapies. We previously developed a mouse model in which TDP-43 is selectively deleted from motor neurons (ChAT-Cre;Tardbpf/f) that mimics the early stages of ALS. Here, we demonstrate that intravenous delivery of a blood-brain-barrier (BBB) permeable AAV capsid expressing our rationally designed splicing repressor CTR (AAV-PHP.eB-CTR) in symptomatic ChAT-Cre;Tardbpf/f mice markedly slowed disease progression and prevented paralysis. Systemic delivery of AAV-PHP.eB-CTR led to transduction of ~80% of spinal motor neurons, repression of TDP-43-associated cryptic exons within motor neurons expressing CTR, and attenuation of motor neuron loss. Notably, the addition of the TARDBP 3UTR autoregulatory element to CTR maintained its expression within a physiological range. In control littermates that received AAV-PHP.eB-CTR and were monitored for >20 months, grip strength and body weight remained normal, and no histopathological abnormalities were observed, underscoring a favorable safety profile for this gene therapy. These results provide preclinical proof-of-concept that BBB-crossing AAV delivery of CTR can rescue motor neuron disease through the restoration of TDP-43 function, offering a promising mechanism-based therapeutic strategy for ALS.

A Comparison of Sleep-Based and Retrieval-Mediated Memory Consolidation Using Sigma-Band Activity
Sleep and retrieval training both promote memory consolidation, likely via similar neural mechanisms, but they have not yet been directly compared in a counterbalanced design that accounts for potential masking of nap effects by prior retrieval training. The current study aimed to see if we could replicate sleep spindles enhancement of weakly encoded memories, across both sleep-based and retrieval-mediated memory consolidation, using EEG sigma power (~11-16 Hz) as a proxy for sleep spindles (i.e., sigma-band activity). Thirty subjects (27F, 18-34, M=22.17) participated in four separate sessions where they learnt different sets of 104 object-word pairs. Subjects were then tested on their recognition accuracy of the pairs before and after one of four 120 min memory interventions where EEG was recorded: retrieval training (i.e., cued recall practice), restudy (i.e., pair re-exposure), a nap opportunity, or a wakeful rest. Our results did not replicate an enhancement of weakly encoded memories, moderated by either sleep spindles of sigma power. Contrary to expectations, sigma power demonstrated a negative impact on memory outcomes. We also detected a prioritisation to enhance memory outcomes for strongly encoded memories and greater memory outcomes following retrieval training and restudy compared to sleep and wake interventions. These results challenge the assumptions of encoding-strength-dependent enhancements across consolidation. Importantly, our study provides a methodological approach to comparing sleep-based and retrieval-mediated memory consolidation that should be explored across different memory paradigms in future studies.

Lifespan Variation in Perceptual Style Along an Autism-Schizotypy Continuum Explains Individual Responses to External Uncertainty
Individuals differ in how they weigh prior knowledge against sensory evidence. This cognitive-perceptual style has been proposed to vary along a continuum from autism-spectrum-like (ASD) to schizophrenia-spectrum-like (SSD) processing. In the present study, we first introduce a refined method for estimating individuals' positions on this continuum by re-combining subscales of established autism and schizotypy questionnaires with a newly validated five-factor model for the autism questionnaire (AQ). Second, using a large, age-diverse adult sample (N = 340, age 18-82), we show that cognitive-perceptual style shifts systematically across the lifespan, with older adults exhibiting more sensory-driven, ASD-like profiles. Third, a total of over 160,000 self-paced reading times reveal that individuals with more sensory-driven styles show heightened sensitivity to lexical predictability, particularly in older age. Fourth, individuals' intrinsic response dynamics, indexed by autocorrelations of reading times, did not covary with cognitive-perceptual style, suggesting a dissociation between linguistic prediction and non-linguistic temporal dynamics. Finally, in a separate experiment (N = 28, age 21-41), individuals with more ASD-like profiles showed reduced adaptation to latent-state volatility in a voice detection task, especially with increasing age. These findings demonstrate the ASD-SSD continuum to provide a dynamic, lifespan-sensitive framework for understanding individual differences in perceptual inference and predictive processing.

Low-dimensional brain-symptom associations delineate depression phenotypes with distinct connectivity biomarkers and symptom profiles
Depression is neurobiologically and clinically heterogeneous. New approaches using resting-state functional MRI (rs-fMRI) functional connectivity (FC) data have modeled the neural basis of depression heterogeneity and revealed unique neural phenotypes. Yet, no studies have identified depression phenotypes from electrophysiological magnetoencephalography (MEG) data although MEG measures human brain dynamics at millisecond precision. We demonstrate here unique depression phenotypes based on MEG-oscillation FC. We collected resting-state MEG, MRI, and clinical symptom data from 263 patients with unipolar depression and 75 healthy controls. We assessed MEG-FC with two oscillatory coupling-mode measures that are fundamental for information processing. To define normative phenotypes, we computed their latent-space low-dimensional brain-symptom associations, and used these components to identify phenotypes using unsupervised machine learning. We identified five stable depression phenotypes that were characterized by unique symptom profiles and distinct spectral patterns. Our results demonstrate new neural underpinnings of depression heterogeneity and reveal unique neural phenotypes with potential personalized diagnostic value.