bioRxiv Subject Collection: Neuroscience's Journal

Toward Unified Biomarkers for Focal Epilepsy
Surgical resection of the epileptogenic zone (EZ) is the most effective treatment for drug-resistant focal epilepsy. However, 30[ndash]80% of patients do not attain long-term seizure freedom post-surgery, indicating that pre-surgical evaluation often falls short of fully delineating the EZ. Accurate EZ-localization is challenging because each individual EZ is a unique and complex network, often comprising multiple overlapping neuropathologies. This hypothesis is supported by studies showing that combining multiple biomarkers enhances localization accuracy. Nonetheless, combining biomarkers leads to high-dimensional features that risks overfitting classifiers and reduces the interpretability of underlying neuropathology, ultimately limiting clinical applicability. We asked whether high-dimensional neuronal features could be reduced to a low-dimensional latent space to captures essential characteristics of the epileptogenic network (EpiNet). In the latent space, each sampled brain region is assigned an EpiNet-saliency score along a 0[ndash]1 continuum, characterizing the degree of epileptogenic proneness from lowest to highest. Using 10-minute interictal recordings from 7,183 stereo-EEG (SEEG) contacts across 64 focal epilepsy patients, we extracted 260 features of local and network dynamics. Singular value decomposition revealed that ten eigenfeatures were sufficient to identify brain regions where seizures emerged (SZ). These eigenfeatures were used to train two unsupervised classifiers, which converged on a consensus model for assessing EpiNet-saliency using only the first and second eigenfeatures, reducing the dimensionality to 0.77% of the original feature set. The resulting model was tested on 7[ndash]9 hours of sleep-SEEG recordings from three patients in an independent cohort and validated using tensor component analysis. Among the 64 training subjects, SZ-classification accuracy correlated with individual position in the eigenfeature space (r2=0.5), suggesting that variability in EpiNet-saliency contributes to differences in classification performance. The model was tested on three subjects from an independent cohort, where it successfully captured time-varying EpiNet-saliency in sleep-SEEG, corroborating clinical assessments and achieving peak classification accuracies of 0.63, 0.85, and 0.94, respectively. A separate tensor component analysis verified the spatiotemporal characteristics of model-predicted EpiNet-saliency in the sleep-SEEG. These results provide compelling evidence supporting our hypothesis of a low-dimensional representation of epileptogenicity, which appears to be independent of brain state or neuropathological origin. This innovative approach enables straightforward interpretation of neuropathology and facilitates the integration of additional biomarkers and study of large cohorts, owing to its minimal computational footprint. These advancements significantly enhance the feasibility of a framework for unified epilepsy biomarkers.

Multimodal approach to characterize surgically removed epileptogenic zone from patients with focal drug-resistant epilepsy: from operating room to wet lab
Objective: We have established a comprehensive sample handling protocol designed for the multiscale assessment of epileptogenic tissue. This protocol aims to identify novel therapeutic targets and enhance the diagnosis and stratification of patients with drug-resistant epilepsy, thereby optimizing their treatment with anti-seizure medications and surgical interventions. Methods: Patients with drug-resistant focal epilepsy, recommended for surgical treatment, are recruited after detailed multidisciplinary preoperative evaluation at the Epilepsy Center at Kuopio University Hospital in Finland. A day before the resective surgery, patients undergo magnetic resonance imaging (MRI) including advanced methodologies. During the surgery, each piece of resected tissue is placed under oxygenation on ice-cold artificial cerebral spinal fluid-solution. The pieces are then immediately transported to the laboratory, assessed by a neuropathologist, and sliced for both clinical diagnosis and research. Two adjacent slices are provided for research and are sent to the University of Eastern Finland. Results: The developed sample handling protocol provides the opportunity for detailed characterization of the tissue from the same patient using emerging imaging, electrophysiology, and molecular biology technologies. We have optimized the conditions for preserving the resected tissue alive for electrophysiological measurements and simultaneously making possible ex vivo studies including multi-omics acquisition, electron microscopy, histology, and MRI. Our protocol enables the mapping of functional readouts to structural and molecular alterations in human tissue. Our goal is to integrate multimodal data and co-register the resected tissues within the whole brain's in vivo MRI space. This approach aims to enhance the characterization and localization of epileptogenic zones and refine surgical treatment targets by identifying abnormalities in global connectivity and structural patterns. Significance: We have successfully developed a systematic protocol for the collection and analysis of multimodal data. This protocol aims to elucidate the structural, functional, and molecular characteristics that render tissue epileptogenic, thereby enhancing the diagnosis and subsequent care of patients with epilepsy.

In the words of others: ERP evidence of speaker-specific phonological prediction
Prediction models usually assume that highly constraining contexts allow the pre-activation of phonological information. However, the evidence for phonological prediction is mixed and controversial. In this study, we implement a paradigm that capitalizes on the phonological errors produced by non-native speakers to investigate whether speaker-specific phonological predictions are made based on speaker identity (native-vs-foreign). EEG data was recorded from 42 healthy native Italian speakers. Participants were asked to read sentence fragments after which a final word was spoken by either a native- or a foreign-accented speaker. The spoken final word could be predictable or not, depending on the sentence context. The identity of the speaker (native-vs-foreign) may or may not be cued by an image of the face of the speaker. Our main analysis indicated that cueing the speaker identity was associated with a larger N400 predictability effect, possibly reflecting an easier processing of predictable words due to phonological preactivation. As visual inspection of the waveforms revealed a more complex pattern than initially anticipated, we used temporal EFA (Exploratory Factor Analysis) to identify and disentangle the ERP components underlying the effect observed. In the native-accent condition, predictable words elicited a posterior positivity relative to unpredictable words, possibly reflecting a P3b response, which was more pronounced when the speaker identity was cued. In the foreign-accent condition, cueing the speaker identity was associated with a smaller N1 and a larger P3a response. These results suggest that phonological prediction for native- and foreign-accented speakers likely involve different cognitive processes.

Single electrically induced epileptic afterdischarge triggers synaptic weakening, AMPA receptor endocytosis and shrinkage of dendritic spines in the hippocampus
Afterdischarge (AD) is an experimental model of electrically induced seizures. When induced in limbic structures, AD is known to induce acute behavioral alterations and flattening of local field potentials that persist for a few minutes. However, impairments in more complex cognitive processes such as learning and memory, can last for hours after the seizure. Considering the mismatch between ephemeral postictal electrophysiological changes and long-lasting cognitive impairments, synaptic plasticity emerges as a possible mechanism that integrates these findings. Therefore, we used a multilevel approach to evaluate the effects of a single seizure on synaptic plasticity. First, we showed that a single AD-eliciting stimulation at the perforant pathway-dentate gyrus (PP-DG) synapse causes long-lasting decrease of evoked postsynaptic potentials. Then, we observed that this functional alteration was accompanied by shrinkage of mushroom-shaped spines in the DG. Lastly, reduced levels of p(Ser845)-GluA1 and GluA1 subunits of AMPA receptors (AMPARs) were found in the hippocampal postsynaptic density. Together, our data suggest that a seizure induces a long-term depression (LTD)-like synaptic plasticity phenomenon, which is characterized by synaptic weakening, AMPAR endocytosis, and dendritic spines shrinkage. Furthermore, the postictal changes in synaptic plasticity observed here align with the course of cognitive impairments often reported in other studies.

D3 dopamine receptors implicate a subtype of medium spiny neuron in the aversive effects of antipsychotic medications
Second generation antipsychotics (SGAs) are widely used clinical tools, yet they often cause negative side effects and take weeks to become effective, leading to poor patient compliance. The effect/side effect profile of individual SGAs is highly variable, and the mechanisms that underlie this variability are not well understood. We found that SGA activity at D3 dopamine receptors (D3R) in the Nucleus Accumbens (NAc) mediates the aversive effects of SGAs. Using single-nucleus RNA sequencing, we found that D3R is expressed in a subpopulation of D1R neurons and defines its own distinct NAc cell type. We demonstrate that while multiple SGAs (clozapine and quetiapine) cause acute conditioned place aversion in mice, only chronic treatment with quetiapine, an arrestin-biased agonist at D3R, causes aversion to abate. We further show at both the cell and population level that quetiapine inhibits D3R-neurons in the lateral shell (LatSh) of the NAc. Selective optogenetic inhibition of D3R-neurons in the LatSh produces real time place aversion in mice, implicating this cell type in the aversive effects of SGAs. Our findings suggest a cellular and systems-level mechanism underlying aversion to SGAs and highlight the pathway to selective tolerance to this aversion, providing a framework for future therapeutic strategies in SGA development.

Temporal-orbitofrontal pathway regulates choices across physical reward and visual novelty
Perceptually novel objects have profound impacts on our daily decisions. People often pay to try novel meals over familiar ones, or to see novel visual scenes at art exhibits and travel destinations. This suggests that perceptual novelty and the value of physical rewards, such as food, interact at the level of neural circuits to guide decisions, but where and how is unknown. We designed a behavioral task to study this novelty-reward interaction in animals and to uncover its neural underpinnings. Subjects chose among familiar offers associated with different expectations of novel objects and different expectations of juice rewards. Expectation of novel objects increased the preference for expected rewards. This novelty-reward interaction was reflected by neural activity in the anterior ventral temporal cortex (AVMTC) - a region previously implicated in the detection and prediction of novelty - and in the orbitofrontal cortex (OFC) - an area that receives prominent AVMTC inputs and is known for its capacity to signal subjective value of visual objects. Neural activity patterns suggested that AVMTC was upstream of OFC in the decision process. Chemogenetic disruption of the AVMTC-OFC circuit altered the impact of expected novelty on the valuation of physical reward. Hence, the ventral visual system impacts novelty-reward interactions during decisions through direct projections to OFC.

Distinct impacts of sodium channel blockers on the strength-duration properties of human motor cortex neurones
Voltage-gated sodium channels (VGSCs) are essential for regulating axonal excitability in the human brain. While sodium channel blockers are known to modulate neuronal excitability, their in vivo effects on the human cortex remain poorly understood. Here, we employed novel transcranial magnetic stimulation (TMS) measures to investigate the effects of sodium channel blockers, carbamazepine and lacosamide, on the strength-duration behaviour of human cortical neurones, serving as an index of sodium channel function. Our data showed that single doses of both medications elevated resting motor thresholds compared to placebo, indicating reduced excitability; however, their impacts varied according to TMS pulse width. Carbamazepine raised thresholds proportionally across all pulse widths, whereas lacosamide disproportionately influenced thresholds for long-duration pulses. Crucially, lacosamide reduced the strength-duration time constant and increased rheobase, while carbamazepine had minimal effects on both. These results reveal subtle and unexpected differences in cortical neurone behaviour following VGSC-blocking medication administration. Lacosamide's response aligns with the proposed mechanism of sodium conductance blockade, while carbamazepine's effects suggest distinct VGSC interactions or potential off-target effects. Our findings advance the understanding of VGSC-blocking medication interactions in the human cortex and underscore the importance of employing specific TMS measures to gain deeper insights into medication mechanisms of action in vivo. Such measures could serve as valuable adjuncts in medication development and patient monitoring, enhancing understanding of medication action in clinical settings.

Cellular and Extracellular microRNA Dysregulation in LRRK2-Linked Parkinson's Disease
Background and objective: The discovery of cell-free micro-RNAs in body fluids has made them a promising biomarker target in the field of neurodegenerative diseases. Although they have been reported to be differentially expressed in biofluids and tissues from sporadic Parkinson's disease patients, it remains unclear whether similar observations can be made in patients with genetic forms of the disease and if miRNA profiles reflect mutation-specific pathogenic pathways. Since induced pluripotent stem cell-derived neurons represent a widely used research model for both sporadic and familial Parkinson's disease, we sought to assess the usability of this model for the identification of differentially expressed cell-free micro-RNAs in the context of the Parkinson's disease-related LRRK2 G2019S mutation in a proof-of-concept study. Materials and methods: We isolated extracellular vesicles carrying cell-free RNA from patient-derived induced pluripotent stem cells carrying the LRRK2 G2019S mutation and their gene-corrected isogenic controls. After the generation of small-RNA libraries and differential expression analysis, we quantified expression levels of fourteen micro-RNAs in an independent batch of cell-free and cellular RNA via RT-qPCR. Finally, we quantified pRab10 levels as a proxy of LRRK2 activity and correlated observable changes to the miRNA expression levels. Results: We successfully isolated extracellular vesicles from induced pluripotent stem cell-derived human dopaminergic neurons. We detected over 2000 different micro-RNAs of which 56 were differentially expressed. Dysregulation of four micro-RNAs was confirmed in an independent batch of cell-free RNA. We discovered a high correlation between changes in the cell-free and cellular micro-RNAomes. Finally, we showed poor correlation between LRRK2 expression or activity and miRNA expression levels. Conclusions: Our results suggest that patients carrying the LRRK2 G2019S mutation display alterations in cellular and cell-free micro-RNA expression levels. Notably, the miRNA changes observed in this study did not follow a linear relationship with LRRK2 expression levels or kinase activity. Validation in larger cohorts will be necessary.

Survey of hippocampal responses to sound in naive mice reveals widespread activation by broadband noise onsets
Recent studies suggest some hippocampal (HC) neurons respond to passively presented sounds in naive subjects, but the specificity and prevalence of these responses remain unclear. We used Neuropixels probes to record unit activity in HC and auditory cortex (ACtx) of awake, untrained mice during presentation of diverse sound stimuli. A subset of HC neurons exhibited reliable, short-latency responses to passive sounds, including tones and broadband noise. HC units showed evidence of tuning for tone frequency but not spectrotemporal features in continuous dynamic moving ripples. Across sound types, HC responses overwhelmingly occurred at stimulus onset; they quickly adapted to continuous sounds and did not respond at sound offset. Among all sounds tested, broadband noise was by far most effective at driving HC activity, with response prevalence scaling with increasing spectral bandwidth and density. Responses to noise were also far more common than visual flash stimuli. Sound-evoked face movements, quantified by total facial motion energy (FME), correlated with population-level HC activity, but many individual units responded regardless of movement, indicating both auditory and motor-related inputs. These results show that abrupt, acoustic events are sufficient to activate HC neurons in the absence of learning or behavioral engagement. This suggests a possible role for HC in detecting salient environmental changes and supports the idea that auditory inputs contribute directly to HC function. Given emerging links between hearing loss and dementia, these findings highlight a potential pathway by which auditory deafferentation could impact cognitive health.

Circadian-Related Dynamics of the Endocannabinoid System in Male Mouse Brain
Endocannabinoids (eCBs) and related lipids play crucial roles in brain function, including the regulation of circadian rhythms and sleep. To comprehensively map these molecules, we employed liquid chromatography high-resolution tandem mass spectrometry (LC/HRMS/MS) to quantify 78 lipids across 14 families in seven brain areas of male mice at four time points throughout the day (every six hours), and during sleep initiation. We found that most eCBs from the fatty acids (FAs) family, particularly arachidonic acid (AA), were highly abundant in the mouse brain in all brain areas and during the circadian rhythm. High eCBs abundance was shown in deeper brain areas, while temporal differences using the Cosinor analysis revealed 26 eCBs behaving in a circadian rhythm response, with linolenic acid (LnA) being the only lipid to show rhythmicity across all brain areas. Sleep initiation (ZT1) was associated with increased N-acylphosphatidylethanolamine phospholipase D (NAPE-PLD) activity and N-acylethanolamide (NAE) levels in the cortex and hippocampus, while wake extension (WEx) altered 2-monoacylglycerol (2-MAG) metabolism and increased cannabinoid receptor 1 (CB1) expression. These findings provide a detailed lipidomic map of eCBs and related lipids in the male mouse brain, highlighting their area-specific distribution, circadian regulation, and involvement in sleep/wake transitions. Given the link between sleep disruption and neurodegeneration, future studies should investigate whether the observed eCB dysregulation contributes to sleep disturbances in these conditions, and if targeting these pathways offers novel therapeutic strategies.

Electrochemical Metabolic Profiling Reveals Mitochondrial Hyperactivation and Enhanced Neural Progenitor Proliferation in MLC1-Mutant Human Cortical Organoids
Mitochondrial function is critical for neural progenitor regulation, yet its dysregulation during early human brain development remains poorly defined. Megalencephalic leukoencephalopathy with subcortical cysts (MLC) is a neurodevelopmental disorder caused by MLC1 mutations, previously attributed to postnatal astrocyte dysfunction. Using patient-derived human cortical organoids, we show that MLC1 is expressed in early neuroepithelial cells. To assess mitochondrial state in live organoids, we developed the MAGO (Matrigel-coated gold nanostructure) platform for real-time, label-free detection of redox activity. MLC1 mutant organoids showed mitochondrial hyperactivation, increased ATP and ROS, reduced membrane potential, and altered fusion protein expression. These changes were accompanied by enhanced BrdU incorporation and expansion of PAX6/SOX2 progenitors. To assess the causal role of MLC1 mutation, we generated isogenic organoids using CRISPR prime editing, which recapitulated redox hyperactivation and increased proliferation. Our findings redefine MLC as a disorder of early mitochondrial and progenitor dysregulation and establish a tractable platform to study metabolic mechanisms in neurodevelopmental disease.

The superficial tufted and mitral cell output neurons of the mouse olfactory bulb have a dual role in insulin sensing
The olfactory bulb (OB) contains multiple, parallel projection neurons to relay the nature of a stimulus. In a mouse ex vivo slice preparation, we used patch-clamp electrophysiology to measure intrinsic properties, excitability, action potential (AP) shape, voltage-activated conductances, and neuromodulation in the newly-categorized superficial tufted cells (sTCs) compared with those of mitral cells (MCs). We propose that a marked difference in voltage-dependent current represents distinct ion channel populations that affect the kinetics of action potentials, and evokes an increase in sTC firing frequency, albeit both types of projection neurons having similar AP spiking activity. Triple-colored immunofluorescence and RNA scope were used to detect co-localization of the Kv1.3 ion channel and the insulin receptor in sTCs, with ~73% of sTCs expressing both. The sTCs were modulated by bath application of insulin: increasing AP firing frequency by 97%, attributable to an 8% decrease in the intraburst interval, and a reduction of the latency to first spike by 37%. We conclude that there may be a range of neuromodulators of sTCs that may alter excitability and fine-tune olfactory information processing or metabolic balance.

A polymeric, PDMS-based large-scale skull replacement suitable for optical and mechanical access for long-term neuronal imaging, electrophysiology, and optogenetics
Many techniques to record and manipulate neuronal activity across large portions of the vertebrate brain, such as widefield and two-photon calcium imaging, electrophysiology, and optogenetics, are now available. However, few effective approaches enable both optical and mechanical access to the brain. In this work, we offer an in-depth guide for synthesizing, implanting, and using polydimethylsiloxane (PDMS) windows as skull replacements for chronic optical neuronal imaging. Furthermore, we provide instructions to perform viral injections and multi-site silicon probe implantation.

Pathological Mechanisms of Motor Dysfunction in Familial Danish Dementia: Insights from a Knock-In Rat Model
Familial Danish Dementia (FDD) is a rare autosomal dominant neurodegenerative disorder caused by a mutation in the integral membrane protein 2B (ITM2b) gene. Clinically, FDD is characterized by cerebral amyloid angiopathy (CAA), cerebellar ataxia, and dementia. Notably, FDD shares several neuropathological features with Alzheimer's disease (AD), including CAA, neuroinflammation, and neurofibrillary tangles. In this study, we investigate the pathological mechanisms linking CAA, white matter damage, and motor dysfunction using a recently developed FDD knock-in (FDD-KI) rat model. This model harbors the Danish mutation in the endogenous rat Itm2b gene, along with an App gene encoding humanized amyloid-{beta} (A{beta}). Our analysis revealed substantial vascular Danish amyloid (ADan) deposition in the cerebellar subpial and leptomeningeal vessels of FDD-KI rats, showing an age-related increase comparable to that observed in human FDD patients. Additionally, vascular A{beta} deposits (A{beta}-CAA) were present in FDD-KI rats, but A{beta}-CAA patterns showed some differences between species. Motor function assessments in FDD-KI rats demonstrated age-accelerated motor deficits and gait abnormalities, mirroring the clinical characteristics of FDD patients. To further explore the mechanisms underlying these deficits, we examined cerebellar pathology and found age-related myelin disruption and axonal fiber loss, consistent with postmortem human FDD pathology. Cerebellar demyelination appeared to be driven by neuroinflammation, marked by increased microglial/macrophage activation in response to vascular amyloid deposition. Additionally, we observed extravascular fibrinogen leakage, indicating widespread vascular permeability in both white and gray matter, with fibrinogen deposits surrounding amyloid-positive vessels in aged FDD-KI rats and postmortem FDD cerebellum. These findings suggest that this FDD-KI rat model is the first animal model to recapitulate key neuropathological features of human FDD patients, including both ADan- and A{beta}-type CAA, neuroinflammation, and white matter lesions - pathologies that may underlie the motor and gait impairments seen in the disease.

Eye movements of younger and older adults decrease during story listening in background noise
Assessments of listening effort are increasingly relevant to understanding the speech-comprehension difficulties experienced by older adults. Pupillometry is the most common tool to assess listening effort but has limitations. Recent research has shown that eye movements decrease when listening is effortful and proposed indicators of eye movements as alternative measures. However, much of the work was conducted in younger adults in trial-based sentence-listening paradigm, during concurrent visual stimulation. The extent to which eye movements index listening effort during continuous speech listening, independently of visual stimuli, and in older adults, is unknown. In the current study, younger and older adults listened to continuous stories with varying degrees of background noise under free and moving-dot viewing conditions. Eye movements decreased (as indexed by fixation duration, gaze dispersion, and saccade rate) with increasing speech masking. The reduction in eye movements did not depend on age group or viewing conditions, indicating that eye movements can be used to assess effects of speech masking in different visual situations and in people of different ages. The pupil area was only sensitive to speech masking early in the experiment. In sum, the current study suggests that eye movements are a potential tool to assess listening effort during continuous speech listening.

Development of a 24-Channel 3T Phased-Array Coil for fMRI in Awake Monkeys - Mitigating Spatiotemporal Artifacts in Ferumoxytol-Weighted Functional Connectivity Estimation
Functional magnetic resonance imaging (fMRI) of awake macaque monkeys holds promise for advancing our understanding of primate brain organization, including humans. However, estimating functional connectivity in awake animals is challenging due to the limited duration of imaging sessions and the relatively low sensitivity to neural activity. To overcome these challenges, we developed a 24-channel 3T receive radiofrequency (RF) coil optimized for parallel imaging of awake macaques. This enabled the acquisition of multiband and GRAPPA-accelerated ferumoxytol-weighted resting-state fMRI. The Human Connectome Project-style data processing pipelines were adapted to address the unique preprocessing demands of cerebral blood volume-weighted (CBVw) imaging, including motion correction, functional-to-structural image co-registration, and training a multi-run independent component analysis-based X-noiseifier (ICA-FIX) classifier for removal of structured artifacts. Our CBVw fMRI approach resulted in an elevated contrast-to-noise ratio compared to blood oxygenation level dependent (BOLD) imaging in anesthetized macaques. However, structured imaging artifacts still contributed more variance to the functional timeseries than neural activity. By applying the ICA-FIX classifier, we achieved highly reproducible parcellated functional connectivity at the single-subject level. At the group-level, we identified dense functional networks with spatial features homologous to those observed in humans. The developed RF receive coil, image acquisition protocols, and data analysis pipelines are publicly available, providing the broader scientific community with tools to leverage these advances for further research.

Neural oscillations and top-down connectivity are modulated by object-scene congruency
The knowledge we have about how the world is structured is known to influence object recognition. One way this is demonstrated is through a congruency effect, where object recognition is faster and more accurate if items are presented in expected scene contexts. However, our understanding of the dynamic neural mechanisms that underlie congruency effects are under-explored. Using MEG, we examine how the congruency between an object and a prior scene results in changes in the oscillatory activity in the brain, which regions underpin this effect, and whether congruency results arise from top-down or bottom-up modulations of connectivity. We observed that prior scene information impacts the processing of visual objects in behaviour, neural activity and connectivity. Processing objects that were incongruent with the prior scene resulted in slower reaction times, increased low frequency activity in the ventral visual pathway, and increased top-down connectivity from the anterior temporal lobe to the posterior ventral temporal cortex. Our results reveal that the recurrent dynamics within the ventral visual pathway are modulated by the prior knowledge imbued by our surrounding environment, suggesting that the way we recognise objects is fundamentally linked to their context.

Value coding by primate amygdala neurons complies with economic choice theory
Primate amygdala neurons are implicated in coding the value of choice options for decision-making. However, it remains unclear whether amygdala value signals comply with the notion that decision makers maximize the value of rewards, as formalized by key axioms of economic theory. In particular, the continuity axiom of Expected Utility Theory (EUT) postulates that reward maximization is reflected by a trade-off between reward probability and magnitude. Our experiment tested this trade-off in two male macaque monkeys who subjectively ranked three gambles in choices, thus revealing their subjective value. Axiom compliance was defined by choice indifference between the intermediate gamble and a probabilistic combination of the other two gambles. We found that the animals' choices between safe and gamble options reflected the integration of probability and magnitude into scalar values consistent with the continuity axiom. In a non-choice task, responses of individual amygdala neurons to separate probability and magnitude cues reflected the monkeys' individual preferences: neuronal responses were lower for non-preferred gambles (relative to safe options), higher for preferred gambles and equal at subjective indifference between safe and gamble options. In a choice task, amygdala neurons integrated probability and magnitude into subjective values that reflected individual preferences. In some neurons, value signals transitioned to signals coding the monkey's economic choices and chosen values. These findings identify amygdala neurons as substrates for encoding behavior-matching subjective values according to the continuity axiom of EUT, and for translating these values into economic choices.

The crosstalk between the anterior hypothalamus and the locus coeruleus during wakefulness is associated with low frequency oscillations power during sleep
Study Objectives Animal research has demonstrated that sleep regulation heavily depends on a network of subcortical nuclei. In particular, whether the crosstalk between the Locus Coeruleus (LC) and hypothalamic nuclei influences sleep variability and age-related changes in humans remains unexplored. This study investigated whether the effective connectivity between the LC and subparts of the hypothalamus is associated with the electrophysiology of rapid eye movement sleep (REMS). Methods Thirty-three healthy younger (~22y, 27 women) and 18 older (~61y, 14 women) individuals underwent 7-Tesla functional magnetic resonance imaging during wakefulness to investigate the effective connectivity between LC and distinct hypothalamus subparts encompassing several nuclei. Additionally, we recorded their sleep electroencephalogram (EEG) to explore relationships between effective connectivity measures and REMS theta energy and sigma power prior to REMS episodes. Results The effective connectivity analysis revealed robust evidence of a mutual positive influence between the LC and the anterior-superior and posterior hypothalamus, supporting the idea that the connectivity patterns observed in animal models are also present in humans. Furthermore, our results suggest that in older adults, stronger effective connectivity from the anterior-superior hypothalamus, including the preoptic area, to the LC is associated with reduced REM theta energy. Specificity analysis showed that this association was not limited to REM theta energy but also extended to specific lower-frequency bands during REMS and NREMS. Conclusions These findings highlight the complex age-dependent modulation of the LC circuitry and its role in sleep regulation. Understanding these neural interactions offers valuable insight into the mechanisms driving age-related sleep changes.

Dissociating the functional role of the para-hippocampal and the parietal cortex in human multi-step reinforcement learning
Many real-life decisions involve a tension between short-term and long-term outcomes, which requires forward-looking abilities. In reinforcement learning, this tension arises at the initial stage of multi-step learning and decision tasks, where forward-looking decisions collect smaller immediate rewards but govern the transition to more advantageous second-stage states. Here, we investigated the neural mechanisms underlying such forward-looking decisions in a cohort of healthy participants undergoing fMRI scanning (N=28). Behavioral results confirmed that participants were able to learn concurrently reward values and state-transition probabilities. By contrasting BOLD signal elicited by first-stage versus second-stage at the time of decision, we isolated a brain network, with central nodes in the bilateral parahippocampal cortex (BA37), whose activity correlate with forward-looking choices. BOLD activity in another network, including the bilateral parietal cortex, correlated with structure learning signal at the time of outcome processing. Our results shed new light on the neural bases of model-based reinforcement learning by suggesting a specific role of the parahippocampal cortex in forward planning and the parietal cortex in learning the Markovian structure of the task.

Linking neuron-axon-synapse architecture to white matter vasculature using high-resolution multimodal MRI in primate brain
Blood vessels and axons align outside the brain due to shared growth factors. However, this neuron-axon-synapse and vessel relationship within the brain white matter remains unclear, primarily due to the technical challenges of charting the complex trajectories of fiber tracts and the dense network of arteries. Consequently, the organizational logic and neurometabolic factors shaping white matter vasculature remain poorly understood. Here, we address these questions using high-resolution multimodal MRI, in vitro neuron density, and receptor autoradiography in macaque monkeys. In superficial white matter, vascularity exhibited parallel alignment with the cortical surface. This vascularity showed negligible dependence on overlying gray matter neuron density (R2 = 0.01), minimal dependence on white matter myelination (R2 = 0.10), and moderate correlation with receptor density (R2 = 0.27). These suggest an association of vascularity with energy demands and axonal branching. In deep white matter, axon geometry, density, and proximity to the cortical surface predict vascular volume with high precision (R2 = 0.62). Overall, these findings establish a relation between neuron-axon-synapse architecture and white matter vasculature in the primate brain, offering advances in understanding the organization and pathophysiology of white matter.

Cocaine-induced immediate-early gene expression in the nucleus accumbens: roles of separate cAMP sensors
Immediate-early gene (IEG) induction after administration of amphetamine or cocaine has been used to trace the signaling pathways that mediate neuronal plasticity required for the short- and long-term behavioral effects of these psychostimulants. We recently reported that a novel cyclic AMP (cAMP)-dependent Rap guanine nucleotide exchange factor-2 (RapGEF2)-ERK signaling pathway is required for Egr-1 induction in D1 medium-spiny neurons (MSNs) of the nucleus accumbens (NAc) after cocaine treatment, and that its deletion from the NAc neurons attenuates cocaine-induced locomotor sensitization and conditioned place preference (CPP). However, the cell type-specific neuronal mechanisms underlying this effect remain unclear. In this study, we used Cre-LoxP technology and a novel Cre-amplifier transgene to generate conditional RapGEF2 knockout mice targeting D1-MSNs and investigated the functional role of RapGEF2 in cocaine reward. Deletion of RapGEF2 in D1-MSNs blocked cocaine-induced ERK phosphorylation (p-ERK) and Egr-1 induction. D1-MSN-specific RapGEF2 deletion did not affect intravenous cocaine self-administration, nor did it affect Fos induction by cocaine, prompting us to examine more closely the role of metabotropic (cAMP-dependent) signaling to IEGs after cocaine administration. We used a battery of D1-MSN-specific genetic interventions targeting cAMP signaling, including Drd1-Cre::Rap1A/Bfl/fl mice, and AAV injection of a Cre-dependent catalytically active phosphodiesterase (PDE4D3-cat) or a Cre-dependent protein kinase A-inhibitor (PKI) in the NAc of Drd1-Cre mice, to explore further the underlying cAMP dependence of IEG induction by acute and chronic cocaine administration, and the cAMP sensors required. Rap1 is reported as a necessary component for both RapGEF2- and PKA-dependent ERK activation, but a requirement for Rap in Fos induction by cocaine has not been examined. Deletion of Rap1A/B in D1-MSNs blocked cocaine-induced p-ERK and Egr-1 expression, but not c-Fos, supporting the idea that the RapGEF2-Rap1-ERK pathway specifically regulates Egr-1, not c-Fos, expression. D1-specific expression of the PDE4D3-cat ablated up-regulation of both Egr-1 and Fos in NAc after cocaine administration, demonstrating that induction of both IEGs requires cAMP elevation in D1-MSNs. Notably, inhibition of PKA activity via AAV-mediated expression of PKI-alpha in D1-MSNs blocked both c-Fos and Egr-1 induction. Thus, acute or chronic cocaine administration activates at least two cAMP-dependent signaling pathways in D1-MSNs: a PKA-Fos pathway and a RapGEF2-ERK-Egr-1 pathway. The finding that PKA also activates the ERK-Egr-1 signaling pathway by convergence on Rap1, and concomitantly activates c-Fos independently of Rap1, may underlie selective effects of metabotropic activation of RapGEF2 and PKA activation by cAMP on cocaine-dependent behaviors in mice.

Improved Injury Detection Through Harmonizing Multi-Site Neuroimaging Data after Experimental TBI: A Translational Outcomes Project in NeuroTrauma (TOP-NT) Consortium Study
Multi-site neuroimaging studies have become increasingly common in order to generate larger samples of reproducible data to answer questions associated with smaller effect sizes. The data harmonization model NeuroCombat has been shown to remove site effects introduced by differences in site-related technical variance while maintaining group differences, yet its effect on improving statistical power in pre-clinical models of CNS disease is unclear. The present study examined fractional anisotropy data computed from diffusion weighted imaging data at 3 and 30 days post-controlled cortical impact injury from 184 adult rats across four sites as part of the Translational-Outcome-Project-in-Neurotrauma (TOP-NT) Consortium. Findings confirmed prior clinical reports that NeuroCombat fails to remove site effects in data containing a high proportion-of-outliers (>5%) and skewness, which introduced significant variation in non-outlier sites. After removal of one outlier site and harmonization using a global sham population, harmonization displayed an increase in effect size in data that displayed group level effects (p<0.01) in both univariate and voxel-level volumes of pathology. This was characterized by movement toward similar distributions in voxel measurements (Kolmogorov-Smirnov p<<0.001 to >0.01) and statistical power increases within the ipsilateral cortex. Harmonization improved statistical power and frequency of significant differences in areas with existing group differences, thus improving the ability to detect regions affected by injury rather than by other confounds. These findings indicate the utility of NeuroCombat in reproducible data collection, where biological differences can be accurately revealed to allow for greater reliability in multi-site neuroimaging studies.

Whole-brain EEG dynamics depending on the stimulus modality and task requirements in oddball tasks
Electroencephalography (EEG) microstates constitute temporal map configurations that reflect the whole brain electrical state. The dynamics of EEG microstates may serve as an effective discretization method for capturing spatiotemporally continuous neural dynamics with high temporal resolution. In this study, we employed polarity-sensitive microstate analysis to investigate whole-brain state transitions during audiovisual oddball tasks. Moreover, we examined how sensory modality and its coupling, types of response to target stimuli, and the physical presence or absence of target stimuli affected EEG dynamics. The results demonstrated that the abovementioned factors affected both behavioral indices and the event-related potential (ERP) components, particularly the P300. Importantly, when considering the topographical polarity of map configuration, transitions to microstate E-, which originates within 300 to 600 ms after stimulus onset and coincides with the typical latency of the P300 component potentially reflect attentional and conscious processes that are associated with the P300. These novel insights into the dynamic transitions of whole brain states during cognitive processes complement the results of traditional ERP analyses.

Identifying discriminative EEG features of Unsuccessful and Successful stopping during the Stop Signal Task
The stop-signal task is often used to study inhibitory control. When combined with electrophysiological recordings, the N2 and P3 event-related potentials (ERPs) are regularly observed. Numerous studies link both amplitude and latency differences of the N2 and P3 to failed versus successful stopping. A slower N2-P3 complex when stopping fails has repeatedly been reported across many studies and found to correlate moderately with behavioral stopping speed. However, most studies rely on averaging across trials, thereby limiting the examination of trial-by-trial dynamics. In the present study, we employed different machine learning-approaches to classify successful from failed stop trials based on time-frequency single-trial EEG data. We also tested whether attenuating the slowing effect would alter classification performance. To preserve interpretability, we first identified five group-level EEG components time-locked to stopping and then used the time-frequency representation as features in different models. Our findings suggest that regularized logistic regression can reliably classify successful from failed stopping with an AUC = 0.72. Correcting for ERP latency differences did not markedly reduce overall classification (i.e., AUC = 0.71), but the model had to compensate by leveraging subtler, broadly distributed time-frequency features. Our feature importance measure indicated that a component closely resembling the N2-P3 complex contributed largely to the classification performance, producing a sparse model. Once the slowing effect was attenuated in the data, the model still retained predictive performance but had to rely on 15 times as many time-frequency features across the five components. Thus, it is likely that multiple overlapping processes unfold during stopping that influence response inhibition in addition to the N2-P3 complex. While the N2-P3 complex is consistently evoked during stopping and carry large discriminative ability, considering additional auxiliary processes might further our understanding into mechanisms underlying response inhibition.

Real-world objects scaffold visual working memory for features: Increased neural delay activity when colors are remembered as part of meaningful objects
Visual working memory is a core cognitive function that allows active storage of task-relevant visual information. While previous studies have postulated that the capacity of this system is fixed with respect to a single feature dimension, recent research has shown that working memory performance for a simple visual feature - color - is improved when this feature is encoded as part of a real-world object relative to an unrecognizable scrambled shape. Using EEG (N = 24), we here demonstrate that this performance increase is supported by enhanced neural delay activity during the retention period (indexed by the contralateral-delay-activity of the event-related potential), suggesting that the behavioral benefit is linked to the active maintenance process of working memory. Furthermore, using time-resolved neural similarity measures, we show that the neural activity is not only increased during the delay, but also more stable over time when colors are remembered as part of real-world objects. Finally, we report a novel fronto-central event-related potential that distinguishes between real-world objects and scrambled objects during encoding and maintenance processes. Overall, our results demonstrate that active visual working memory capacity for simple features is not fixed but can expand depending on what context these features are encoded in.

Latent dimensions in neural representations predict choice context effects
Choices are often affected by the context of available alternatives, a phenomenon termed choice context effects. Current models of context effects require options to be described by two explicit numerical attributes. However, decision-makers might represent these options by additional latent attributes. We propose to use participants' neural representations to access the full attribute set they consider and predict context effects without using the explicit numerical attributes. We first estimated the context effects elicited by lotteries using a behavioral sample. Then we recruited two fMRI samples with preregistered design to estimate the neural representations of each lottery without the context of choice. We predicted the context effects using only the similarity in neural representations between the individual lotteries, improving out-of-sample predictions by 14% and explained variance by 20% compared to traditional methods. These neural representations encoded a mixture of explicit and latent attributes, previously inaccessible to researchers using only behavioral methods.

Neurologically altered brain activity may not look like aged brain activity: Implications for brain-age modeling and biomarker strategies
Background: Brain-age gap (BAG), the difference between predicted age and chronological age, is studied as a biomarker for the natural progression of neurodegeneration. The BAG captures brain atrophy as measured with structural Magnetic Resonance Imaging (MRI). Electroencephalography (EEG) has also been explored as a functional means for estimating brain age. However, EEG studies showed mixed results for BAG including a seemingly paradoxical negative BAG, i.e. younger predicted age than chronological age, in neurological populations. Objectives: This study critically examined brain age estimation from spectral EEG power as common measure brain activity in two of the largest public EEG datasets containing neurological cases alongside controls. Methods: EEG recordings were analyzed from individuals with neurological conditions (n=900, TUAB data; n=417 MCI & n=311 dementia, CAU data) and controls (n=1254, TUAB data; n=459, CAU data). Results: We found that age-prediction models trained on the reference population systematically under-predicted age in people with neurological conditions replicating a negative BAG for diseased brain activity. Inspection of age-related trends along the EEG power spectra revealed complex frequency-dependent alterations in neurological groups underlying the seemingly paradoxical negative BAG. Conclusions: The utility of brain age as an interpretable biomarker relies on the observation from structural MRI that progressive neurodegeneration often broadly resembles accelerated aging. This assumption can be violated for functional assessments such as EEG spectral power and, potentially, different neurological and psychiatric conditions or therapeutic effects. The sign of the BAG may not meaningfully be interpreted as a deviation from normal aging.

Nanobinders for Synaptotagmin 1 enable the analysis of synapticvesicle dynamics in rodent and human models.
Synaptic neurotransmission is a critical hallmark of brain activity and one of the first processes to be affected in neural diseases. Monitoring this process, and in particular synaptic vesicle recycling, in living cells has been instrumental in unraveling mechanisms responsible for neurotransmitter release. However, currently available reporters suffer from major limitations such large probe size or lack of suitability for human neurons, hampering the understanding of human synaptic pathophysiology. Here we describe the NbLumSyt1 toolkit, a panel of nanobody-based affinity probes targeting the luminal domain of the synaptic vesicle protein Synaptotagmin 1 (Syt1). These new tools enable quantitative, non-invasive imaging and functional interrogation of synaptic transmission in human neurons, with unprecedented precision, versatility and cost efficiency, in technologies ranging from fixed-and live-cell super resolution imaging to electron microscopy and mass spectrometry. Overall, NbLumSyt1 nanobinders provide a valuable platform for human synaptic physiology and pathophysiology, benefiting fundamental neuroscience and translational efforts to study and develop treatments for brain-related disorders.

In vivo MRI measurement of microstructural constraints for direct delivery of therapeutics within the brain
Brain tissue microstructure influences the efficient delivery of therapeutics within the brain. Diffusion Tensor Imaging (DTI) enables the depiction of tissue properties in vivo, and thus is potentially relevant for planning convection-enhanced delivery (CED) within the brain. We report on the quantitative assessment of the distribution of a Gadolinium solution infused by CED within the brain of a live ovine model. Infusate distributions were measured at multiple timepoints and compared to microstructural properties as depicted by DTI, thus demonstrating the impact of tissue features and catheter positioning on drug distribution in vivo. This study contributed to the clinical translation of the CED for flow-based therapy to ultimately provide new therapeutic approaches for several brain diseases, by providing essential tools and results used to develop a better prediction model and a delivery platform to reach the therapeutic target more precisely and non-invasively.

Precon_all: A species-agnostic automated pipeline for non-human cortical surface reconstruction
Cortical surface reconstruction has changed how we study brain morphology and geometry. However, extending these methods to non-human species has been limited by the lack of standardized pipelines, anatomical templates, and variability in imaging protocols. To address these challenges, we present Precon_all, an open-source, species-agnostic pipeline that automates cortical surface reconstruction for non-human neuroimaging. It runs reliably across a wide range of anatomical structures and imaging conditions and has been successfully applied to datasets from primates, carnivores, and artiodactyls. Its modular framework mirrors human neuroimaging workflows, supports manual quality control, and produces outputs compatible with FreeSurfer and Connectome Workbench. In doing so, it substantially reduces technical barriers to non-human neuroimaging. As data-sharing initiatives continue to expand access to non-human imaging datasets, Precon_all provides a scalable and standardized solution that supports the broader adoption of surface-based methods for studying cortical evolution through comparative neuroscience.

All spectral frequencies of neural activity reveal semantic representation in the human anterior ventral temporal cortex
Intracranial electrophysiology offers a unique insight into the nature of information representation in the brain - it can be used to disentangle information encoded in local neuronal activity (gamma and high gamma frequencies) from information encoded via long-range interactions (lower frequencies). We used regularised logistic regression to decode animacy from time-frequency power and phase extracted from electrocorticography (ECoG) grid electrode data recorded on the surface of human vATL. Power in gamma (30 - 60 Hz) and high gamma (42 - 200 Hz) produced reliable decoding, indicating that semantic information is indeed expressed by local populations in vATL. However, power from a wide range of frequencies (4 - 200 Hz) produced significantly higher decoding accuracy and also exhibited the same rapidly-changing dynamic code previously observed when decoding voltage. These findings support the theory that semantic information is encoded by a local vATL "hub" that interacts with distributed cortical "spokes".

Feature-dependent decorrelation of sound representations across the auditory pathway
Early studies on orientation selectivity in the visual cortex have suggested that sensory systems generate new feature representations at specific processing stages. Many observations challenge this view, but in the absence of systematic, multistage measurements, the logic of how feature tuning emerges remains elusive. Here, using a generic approach based on representational similarity analysis with a noise-corrected population metric, we demonstrate in the mouse auditory system that feature representations evolve gradually with, in some cases, major, feature-specific improvements at particular stages. We observe that single frequency tuning is already fully developed in the cochlear nucleus, the first stage of processing, while tuning to higher-order features improves up to the auditory cortex, with major steps in the inferior colliculus for amplitude modulation frequency or noise bandwidth tuning and in the cortex for frequency modulation direction and for complex sound identity or direction. Moreover, we observe that intensity tuning is established in a feature-dependent manner, earlier for pure frequencies than for more complex sounds. This indicates that auditory feature computations are a mix of stepwise and gradual processes which together contribute to decorrelate sound representations.

Flexible value coding in the mesolimbic dopamine system depending on internal water and sodium balance
Homeostatic imbalances elicit strong cravings, such as thirst and salt appetite, to restore equilibrium. Although midbrain dopaminergic neurons are known to encode the value of foods, their nutritional state-dependency remains unknown. Here, we show that the activity of the dopaminergic mesolimbic pathway flexibly expresses the positive and negative values of water and salt depending on the internal state in mice. Mice showed behavioral preference and aversion to water and salt depending on their internal water and sodium balance. Fiber photometry recordings revealed that dopamine neurons in the ventral tegmental area and dopamine release in the nucleus accumbens flexibly showed bidirectional excitatory and inhibitory responses to water and salt intake in a state-dependent manner. Furthermore, these dopaminergic and behavioral responses could be simulated by a homeostatic reinforcement learning model. Our results demonstrate the nutritional state-dependency of value coding in mesolimbic dopamine systems, providing new insights into neural circuits underlying homeostatic regulation of appetitive and avoidance behaviors.

Inharmonicity enhances brain signals of attentional capture and auditory stream segregation
Harmonicity is an important feature for auditory perception as it influences pitch processing, memory and hearing in noisy environments. However, the neural substrates of processing harmonic and inharmonic sounds remain unclear. Here, we systematically manipulated the harmonicity of synthetic sounds by introducing random jittering to the frequencies above the fundamental. Using electroencephalography, we studied the spectral uncertainty induced by inharmonic sounds and the effect on markers of auditory prediction errors - mismatch negativity (MMN) and P3a - in a roving oddball paradigm. Inharmonic sounds with a constant jittering pattern generated similar MMN and stronger P3a responses than harmonic sounds. In contrast, MMN responses became undetectable when the jittering pattern changed between consecutive sounds, suggesting that prediction errors are weighted by sequential but not spectral uncertainty. Interestingly, inharmonic sounds generated an object-related negativity, a response associated with the segregation of auditory objects. Our results suggest that inharmonicity induces the segregation of the auditory scene into different streams, captures attention, and gives rise to specific neural processes that are independent from the predictive mechanisms underlying sequential deviance detection.

Breaking the Link: Neural Dissociation of Attention and Working Memory through Inhibitory Control
Attention and working memory (WM) encoding have traditionally been considered inseparable processes with shared neural mechanisms. Here, using an innovative experimental design and a multimodal approach, we provide the first direct neural evidence that attention and WM encoding are dissociable. Functional MRI identifies the supramarginal gyrus (SMG) as the key region enabling this dissociation, while dynamic causal modeling reveals the neural circuitry through which the SMG exerts inhibitory control over attentional representations, regulating their integration into WM. Furthermore, neuromodulation via transcranial direct current stimulation (tDCS) demonstrates that enhancing SMG activity strengthens this inhibitory control, providing causal evidence for the dissociation mechanism. A second tDCS experiment with varied stimuli confirms the generalizability of this mechanism and reinforces the robustness of our results. These findings challenge the long-standing view that attention and WM encoding form a continuous process, demonstrating instead that they constitute two dissociable neural processes of information selection.

Speech markers of psychedelic-induced psychological change
5-MeO-DMT, a potent, short-acting psychedelic, induces profound shifts in cognition, affect, and self-awareness. Because language explicitly expresses these domains and voice implicitly conveys them, both may serve as potential 'biomarkers' of behavioural change. This study introduces a novel framework for analysing baseline language and vocal features, pre- to post-psychedelic changes, assessing their potential to predict subjective experiences and psychological outcomes. Daily voice journals from 29 participants were collected via 'RetreatBot' for two weeks before and after 5-MeO-DMT (1x12mg). Transcripts were analysed using NLP (bag-of-words for vocabulary; transformer model for textual affect), and acoustic features (e.g., pitch, jitter, shimmer) were extracted to assess vocal dynamics. Following 5-MeO-DMT, speech markers revealed increased cognitive language, decreased social words, and altered voice quality (increased jitter/shimmer). Baseline speech patterns predicted psychological preparedness, ego dissolution anxiety, emotional breakthrough, and post-experience well-being. This first longitudinal analysis of speech markers following psychedelic use demonstrates a shift from external focus to introspection. Speech markers predicted and tracked psychological transformation, establishing vocal journaling as a valuable framework for monitoring psychedelic-induced changes and facilitating integration.

Causal Contributions of Left Inferior and Medial Frontal Cortex to Semantic and Executive Control
Semantic control guides the targeted and context-based retrieval from semantic memory. The overlap with and dissociation from domain-general executive control in the frontal lobe remains contentious. Here, we used transcranial magnetic stimulation (TMS) to probe the functional relevance of the left inferior frontal gyrus (IFG) and pre-supplementary motor area (pre-SMA) for semantic and executive control. Across four sessions, 24 participants received 1 Hz repetitive TMS to each region individually, dual-site TMS targeting both regions sequentially (IFG followed by pre-SMA), and sham TMS. Participants then completed semantic fluency, figural fluency, and picture-naming tasks. Stimulation of either region broadly disrupted both semantic and figural fluency, suggesting shared functionality. However, electric field modeling of the induced stimulation strength revealed distinct specializations: The left IFG was primarily associated with semantic control, as evidenced by verbal fluency deficits, while the pre-SMA played a domain-general role in executive functions, affecting non-verbal fluency and cognitive flexibility (e.g., clustering and switching during semantic fluency). Notably, only dual-site TMS impaired accuracy in figural fluency, providing unique evidence for successful compensation of executive functions through either the left IFG or pre-SMA following single-site perturbation. These findings underscore the multidimensionality of cognitive control and suggest a flexible task-dependent contribution of the IFG to control processes, either as semantic-specific or general executive resource. Furthermore, they highlight the tightly interconnected network of executive control subserved by the left IFG and pre-SMA, advancing our understanding of the neural basis of semantic and executive functions.

Biophysical mechanisms of default mode network function and dysfunction
The default mode network (DMN) plays a fundamental role in internal cognitive function as well as dysfunction across numerous brain disorders. While human and rodent neuroimaging has revealed DMN suppression by salient external stimuli, the cellular mechanisms orchestrating this process remain unknown. Using whole-brain computational modeling informed by neuronal biophysics and retrograde tracer-derived directional mouse brain connectomics, we demonstrate that stimulation of the insula, involved in salience processing, suppresses DMN activity while within-DMN cingulate stimulation enhances it. Manipulating excitatory-inhibitory balance revealed how localized DMN disruptions propagate to cause distinct patterns of network dysfunction, with both reversals and paradoxical enhancements of normal suppression patterns. Brain-wide response analysis uncovered a functionally segregated frontal network and revealed a hierarchical organization with the DMN distinct from frontal regions. These findings provide a unified framework linking cellular mechanisms to large-scale network dynamics and demonstrate how region-specific disruptions might lead to the patterns of DMN dysfunction observed in brain disorders.

Plasticity of interhemispheric motor cortex connectivity induced by brain state-dependent cortico-cortical paired-associative stimulation
Transcallosal connectivity between the hand areas of the two primary motor cortices (M1) is important for coordination of unimanual and bimanual hand motor function. Effective connectivity of this M1-M1 pathway can be tested in the form of short-interval interhemispheric inhibition (SIHI) using dual-coil transcranial magnetic stimulation (TMS). Recently, we and others have demonstrated that the phase of the ongoing sensorimotor -rhythm has significant impact on corticospinal excitability as measured by motor evoked potential (MEP) amplitude, and repetitive TMS of the high-excitability state (trough of the -rhythm) but not other states resulted in long-term potentiation-like MEP increase. Here, we tested to what extent the phase of the ongoing -rhythm in the two M1 cortices affects long-term change in SIHI. In healthy subjects we applied cortico-cortical paired associative stimulation (ccPAS) in four different -phase conditions in the left conditioning M1 and right test M1 (trough-trough, trough-positive peak, positive peak-trough, random phase). We found long-term strengthening of SIHI but no differential effect of phase conditions. Findings point to a distinct regulation of plasticity of corticospinal vs. M1-M1 connectivity. The observed ccPAS-induced strengthening of effective M1-M1 connectivity (SIHI) may be utilized for therapeutic applications that potentially benefit from modification of interhemispheric excitation/inhibition balance.

Stroke Shifts Brain Dynamics Toward Criticality: Evidence from Intrinsic Neural Timescales
Stroke induces widespread disruptions to brain function, extending beyond focal lesions to alter the multiscale temporal dynamics that govern neural processing. These dynamics-operating across milliseconds to months-form a hierarchical architecture essential for communication, integration, and adaptive plasticity. While stroke is known to impair local neural activity, its effects on this temporal hierarchy and their consequences for functional recovery remain poorly understood. We conducted a comprehensive investigation of intrinsic neural timescales (INT) in 15 ischemic stroke patients using longitudinal fMRI at five time points over six months, comparing them to age-matched healthy controls. INT quantifies how long neural populations retain information, providing a quantitative measure of fundamental processing dynamics. To further elucidate the mechanistic basis of stroke-induced changes, we performed computational modelling of parsimonious excitable neuronal network dynamics, offering insights into alterations in brain activity from a dynamical systems perspective. Our analyses revealed some key findings: Stroke patients exhibited significantly prolonged INT across multiple cortical regions, indicating slowed temporal dynamics that persisted throughout recovery. The typical hierarchical organization of INT, where sensory areas have shorter timescales than higher-order association areas, was disrupted, particularly in the early post-stroke period. Recovery trajectories diverged at two months post-stroke: patients with poor outcomes maintained abnormally long INT in cognitive control networks (dorsal attention, language, and salience systems), whereas those with better recovery showed progressive normalization toward healthy INT patterns, restoring the brains dynamic balance across multiple timescales. Stroke-induced INT prolongation can be modelled as a critical slowing down driven by a shift in the distance to criticality caused by increased neuronal excitability. Within the framework of criticality, where neural systems operate near the boundary between order and disorder to optimize information processing, stroke-induced changes in neural excitability appear to push brain dynamics toward the critical regime and potentially into a supercritical state. This shift, characterized by excessive temporal persistence and reduced flexibility, may underlie both the observed INT prolongation and its association with poor recovery outcomes. Our findings highlight the importance of temporal dynamics in stroke recovery and suggest that INT may serve as a biomarker for predicting long-term functional outcomes. This perspective provides a novel way to conceptualize stroke-induced changes in brain dynamics, framing them within the broader context of brain self-organization and adaptive processes. By integrating these insights with neurorehabilitation strategies, such as non-invasive brain stimulation, INT could inform targeted interventions to restore neural excitability and intrinsic timescales, thereby improving recovery trajectories.

Updated neuronal numbers of the rat hippocampal formation: redesigning the hippocampal model.
The hippocampal formation is a functional entity that includes the hippocampus, subicular complex and the entorhinal cortex, and has an essential role in learning and memory, emotional processing and spatial coding. The well-defined structure of hippocampal fields and the segregation of the connections has made this structure a favorite candidate for functional models, that rely on fundamental information such the number of neurons populating the hippocampal fields. Existing models on the rat rely on neuronal populations obtained from single studies, so we aimed to obtain more representative estimates by analyzing all available data. We found 68 studies that overall contained 293 stereological estimates of neuronal numbers. The resulting averages for males showed 1,000,000 neurons for the granule cell layer (GCL); 50,000 for the hilus; 220,000 for CA3; 25,000 for CA2; 350,000 for CA1 and 280,000 for the Subiculum. Entorhinal cortex (EC) averages came from females: 100,000 neurons in layer II and 250,000 in layer III. Most of those estimates are significantly different from those traditionally used in hippocampal models (e.g.: 2-fold difference in EC layer II), revealing a new architecture of the rat hippocampal formation that might help build more realistic models of hippocampal connectivity and function. In addition, analysis of the data by age, sex or strain showed a trend of sexual dimorphism in the number of neurons in the GCL and EC, with higher neuronal number in males. Across strains, Wistar males showed consistently higher number of neurons than Sprague-Dawley. And, unexpectedly, adolescent animals typically showed lower numbers of neurons than adults. Although not statistically significant, those differences by sex, strain or age were consistent across fields, suggesting they might reflect actual biological features.

Association between Cortical Thickness and Functional Response to Linguistic Processing in the Occipital Cortex of Early Blind Individuals
Blindness has been shown to induce changes in the structural and functional organization of the brain. However, few studies have investigated the relationship between these structural and functional changes. In this study, we examined cortical thickness within occipital regions of interest in 38 early blind individuals and explored its relationship to functional activation during linguistic processing. Participants engaged in tactile Braille reading and auditory processing tasks involving words, pseudowords, and control conditions to assess various aspects of linguistic processing. Linear mixed models revealed a significant association between cortical thickness and functional activation in the occipital cortex during linguistic tasks. Specifically, lower cortical thickness in the middle occipital gyrus, the calcarine sulcus, and the parieto-occipital sulcus were linked to increased activation during orthographic processing in blind participants (Braille pseudowords vs. Braille nonsense-symbols). Similarly, lower cortical thickness in the calcarine sulcus and parieto-occipital sulcus was associated with greater functional activation during phonological processing (auditory pseudowords vs. auditory control). These findings align with prior research suggesting that structural and functional adaptations in the visual cortex of blind individuals may be influenced by developmental mechanisms such as pruning or myelination. This study highlights the interplay between cortical structure and functional reorganization in the blind brain.

When Melodies Cue Memories: Electrophysiological Correlates of Autobiographically Salient Music Listening in Older Adults
Autobiographical memory is essential for older adults, providing a foundation for self-identity. Healthy aging is accompanied by changes in memory retrieval. However, musical memory remains relatively preserved, suggesting it may serve as an effective cue for autobiographical memory recall. Autobiographically salient (ABS) music (i.e., deeply encoded songs associated to important people, places, and events) is posited to engage distinct memory processes than familiar (FAM) music (i.e., songs that are recognized but lack personal significance). We tested this in 36 older adults (70.6 +/- 6.6 years, 20 females) who listened to music of varying degrees of personal significance, including ABS, FAM, and unfamiliar (UFAM) music. In Experiment 1, participants pressed a button as quickly as possible when they recognized the excerpt as ABS, FAM, or UFAM. In Experiment 2, we measured event-related potentials and time-frequency responses while participants listened to the same stimuli and rated familiarity and memory at the end of each excerpt. Participants had the fastest reaction times for ABS, followed by FAM, then UFAM music. We observed a sustained evoked response from 2238 to 5000 ms post-stimulus onset that was largest in amplitude for ABS music, compared to FAM and UFAM music, over right frontal-central regions. We also observed less beta power suppression for ABS than FAM music between 1300 and 5000 ms over bilateral frontal-central-parietal areas. Our behavioral and neurophysiological findings show that ABS music is associated with faster and stronger memory-related activity distinct from FAM music.

Infralimbic prefrontal cortical projections to the autonomic brainstem: Quantification of inputs to cholinergic and adrenergic/noradrenergic nuclei
The ventromedial prefrontal cortex regulates both emotional and physiological processes. The infralimbic cortex (IL), a prefrontal subregion in rodents, integrates behavioral, neuroendocrine, and autonomic responses to stress. However, the organization of cortical inputs to brainstem nuclei that regulate homeostatic responses are not well defined. We hypothesized that IL projections differentially target pre-ganglionic parasympathetic neurons and adrenergic/noradrenergic nuclei. To quantify IL projections to autonomic brainstem nuclei in male rats, we utilized viral-mediated gene transfer to express yellow fluorescent protein (YFP) in IL glutamatergic neurons. YFP-positive projections to cholinergic and adrenergic/noradrenergic nuclei were then imaged and quantified. Cholinergic neurons were visualized by immunohistochemistry for choline acetyltransferase (ChAT), the enzyme responsible for the synthesis of acetylcholine. Adrenergic/noradrenergic neurons were visualized with immunohistochemistry for dopamine beta-hydroxylase (DBH) which converts dopamine to norepinephrine. Our results indicate that IL glutamate neurons innervated the cholinergic dorsal motor nucleus of the vagus with greater density than the nucleus ambiguus. Furthermore, numerous DBH-positive cell groups received IL inputs. The greatest density was to the C2 and A2 regions of the nucleus of the solitary tract with intermediate levels of input to A6 locus coeruleus and throughout the C1 and A1 regions of the ventrolateral medulla. Minimal input was present in the pontine A5. Additionally, IL projections targeted the local GABAergic neurons that regulate activity within preautonomic nuclei. Collectively, our results indicate that IL pyramidal neurons project to vagal preganglionic parasympathetic neurons, presympathetic neurons of the ventrolateral medulla, as well as diffuse homeostatic modulators the nucleus of the solitary tract and locus coeruleus. Ultimately, these findings provide a roadmap for determining circuit-level mechanisms for neural control of homeostasis and autonomic balance.

Reproducibility of PD patient-specific midbrain organoid data for in vitro disease modelling.
Midbrain organoids are advanced in vitro cellular models for disease modelling. They have been used successfully over the past decade for Parkinsons disease (PD) research and drug development. The three-dimensional structure and multicellular composition allow disease research under more physiological conditions than is possible with conventional 2D cellular models. However, there are concerns in the field regarding the organoid batch-to-batch variability and thus the reproducibility of the results. In this manuscript, we generate multiple independent midbrain organoid batches derived from healthy individuals or GBA-N370S mutation-carrying PD patients to evaluate the reproducibility of the GBA-N370S mutation-associated PD transcriptomic and metabolic signature as well as selected protein abundance. Our analysis shows that GBA-PD-associated phenotypes are reproducible across organoid generation batches and time points. This proves that midbrain organoids are not only suitable for PD in vitro modelling, but also represent robust and highly reproducible cellular models.

Cerebellum instructs plasticity in the mouse primary somatosensory cortex
Sensory experiences map onto distributed neural networks and may activate plasticity processes that in some brain areas are supervised by instructive signals. What remains unknown, however, is if such instructive signals influence plasticity beyond local circuits. Here, we show that optogenetic activation of climbing fibers, which provide instructive signals in cerebellar plasticity, suppresses whisker response potentiation in L2/3 pyramidal cells of the primary somatosensory cortex of mice. Using two-photon imaging and chemogenetics, we find that plasticity is controlled by modulating activity levels of VIP- and SST- positive interneurons. Transsynaptic labeling identifies zona incerta to thalamic posterior medial nucleus projections as the main pathway for cerebellar output reaching cortex. Our findings show that neocortical plasticity is not self-organized but depends on supervision by the olivo-cerebellar system.

Widespread gray and white matter microstructural alterations in dual cognitive-motor impairment
INTRODUCTION: Dual cognitive-motor impairment in aging is a strong predictor of dementia, yet its effects on vulnerable gray matter regions microstructure remain unexplored. METHODS: This study classified 582 individuals aged 36-90 into cognitive-motor impairment, isolated cognitive or motor impairment, and control groups. Microstructural differences in 27 temporal and motor-related gray matter regions and white matter tracts were assessed using DTI and mean apparent propagator (MAP-MRI), a technique well-suited for gray matter analysis. RESULTS: We found widespread microstructural alterations in gray and white matter among individuals with dual cognitive-motor impairment. These changes were not observed in isolated cognitive or motor impairment after multiple comparisons correction. DISCUSSION: Dual cognitive-motor impairment is associated with reduced cellular density in temporal gray matter, decreased fiber coherence, and potential demyelination in white matter tracts, suggesting widespread microstructural disruption. These findings could help understand brain aging and facilitate interventions to slow neurodegeneration and delay dementia onset.

How infant brains fold: Sulcal deepening is linked to development of sulcal span, thickness, curvature, and microstructure
Cortical folding begins in utero as sulci emerge and continues postnatally as sulci deepen. However, the timeline and mechanisms underlying postnatal sulcal development remain unknown. Using structural and quantitative magnetic resonance imaging in infants from birth to one year of age, we longitudinally measured macroanatomical and microstructural development in major sulci that emerge in utero between the 16th and 31st gestational weeks. We find that sulci that emerge earlier in utero are deeper at birth and deepen at a slower rate postnatally than later emerging sulci. Sulci also become wider, thicker, and microstructurally denser, while their curvature decreases. Notably, mean sulcal depth is predicted by a weighted sum of sulcal span, thickness, curvature, and tissue microstructure, with differential weights across sulci. Analysis of local depth along the sulcus also reveals that deeper portions of sulci (fundi) have higher curvature and higher microstructural density than the surrounding sulcal walls. These data reveal that postnatal sulcal deepening is nonuniform and depends on the time of emergence in utero, tissue microstructure, and multiple macroanatomical factors. Together, these findings have important ramifications for theories of cortical folding and elucidating neurodevelopmental disorders and delays.

Evidence for an active handoff between cerebral hemispheres during target tracking
The brain has somewhat separate cognitive resources for the left and right sides of our visual field. Despite this lateralization, we have a smooth and unified perception of our environment. This raises the question of how the cerebral hemispheres are coordinated to transfer information between them. We recorded neural activity in the lateral prefrontal cortex, bilaterally, as non-human primates covertly tracked a target that moved from one visual hemifield (i.e., from one hemisphere) to the other. Beta (15 to 30 Hz) power, gamma (30 to 80 Hz) power, and spiking information reflected sensory processing of the target. By contrast, alpha (10 to15 Hz) power, theta (4 to10 Hz) power, and spiking information seemed to reflect an active handoff of attention as target information was transferred between hemispheres. Specifically, alpha power and spiking information ramped up in anticipation of the hemifield cross. Theta power peaked after the cross, signaling its completion. Our results support an active hand-off of information between hemispheres. This handshaking operation may be critical for minimizing information loss, much like how mobile towers handshake when transferring calls between them.

Opponent regulation of striatal output pathways by dopamine and serotonin
Classic theories propose opponent functions for striatal dopamine (DA) and serotonin (5-hydroxytryptamine; 5HT), with DA promoting approach and 5HT promoting patience or avoidance. How these neuromodulators regulate downstream circuits to achieve such antagonistic effects remains mysterious. Here, we mapped striatal 5HT receptor expression and recorded from genetically-identified striatal neurons to demonstrate that DA and 5HT selectively activate distinct populations of striatal neurons to exert opponent control over striatal output.

Excitatory drive to the globus pallidus external segment facilitates action initiation in non-human primates
The external segment of the globus pallidus (GPe) has conventionally been regarded as a key relay in the indirect pathway of the basal ganglia, primarily mediating movement suppression; however, recent studies in rodents suggest a more complex role, including active facilitation of actions. Therefore, we investigated whether the primate GPe exhibits similar functional diversity by recording single-unit activity in two macaque monkeys performing a sequential choice task. This task separated processes of action initiation and suppression by requiring the monkeys to either accept a good object for reward or reject a bad object using one of multiple strategies. We identified three distinct neuronal clusters based on their firing patterns. Clusters 1 and 2 displayed elevated activity preceding contralateral saccades toward good objects, strongly correlating with shorter reaction times, suggesting a facilitative contribution. In contrast, Clusters 2 and 3 showed decreased activity during rejection of bad objects, reflecting proactive inhibition. Local pharmacological blockade of glutamate receptors within the caudodorsal GPe prolonged saccade latencies and reduced the frequency of rejection saccades, suggesting a causal role for excitatory drive in saccade facilitation. These findings expand the traditional view of the GPe beyond a purely inhibitory station, indicating that in primates it may simultaneously mediate both motor facilitation and proactive suppression. Our results emphasize the importance of characterizing circuit-specific and cell-type-specific roles of the GPe within basal ganglia networks, with implications for normal motor function and movement disorder pathophysiology under complex reward-based decision processes in non-human primates.

Trait reward sensitivity and behavioral motivation shape connectivity between the default mode network and the striatum during reward anticipation
Individuals vary substantially in their responses to rewarding events and their motivation to pursue rewards. The ventral striatum (VS) plays a key role in reward anticipation, and connectivity between the VS and the default mode network (DMN)-a network associated with self-referential and evaluative processes-has been implicated in reward processing. However, the relationship between these neural mechanisms and reward-related individual differences remains unclear. In the present study, we examined how trait reward sensitivity and behavioral motivation shape connectivity between the default mode network (DMN) and the ventral striatum (VS) during reward anticipation. Forty-six participants completed the Monetary Incentive Delay (MID) task while undergoing fMRI, with trial types reflecting varying levels of reward and loss salience. Behavioral measures of motivation were derived from reaction time contrasts between large and neutral trials, and self-reported anhedonia and reward sensitivity were assessed. We found that individuals with higher reward sensitivity exhibited greater striatal connectivity with DMN during reward-salient trials, highlighting the VS's role in incentive processing. However, this relationship was moderated by behavioral motivation. Specifically, in individuals with high behavioral motivation, reward sensitivity was associated with reduced DMN-VS connectivity during reward anticipation. In contrast, for those with lower behavioral motivation, the relationship between reward sensitivity and DMN-VS connectivity was attenuated. These results provide novel insights into the neural correlates of individual differences in reward processing, demonstrating that behavioral motivation is crucial in understanding DMN-striatal interactions during reward anticipation. These findings highlight the importance of considering motivational context when investigating reward-related neural mechanisms.

Thalamic Nuclei Volumes Across Psychiatric and Neurological Disorders: A Multi-Site Magnetic Resonance Imaging Study
The human thalamus is an integrative hub for multiple cortical and subcortical circuits involved in both sensory processing and higher cognitive functions. Group-level thalamic volume differences have been reported for multiple psychiatric and neurological disorders, but previous studies have relied on small samples, covered few disorders, or only investigated the whole thalamus without considering subdivisions. In this multi-site study, we compared thalamic nuclei volumes across several psychiatric and neurological disorders (N = 5 094) and healthy controls (N = 4 552). Using structural MRI scans, we segmented 25 bilateral thalamic nuclei, corresponding to six anatomical groups. We included patients covering 11 clinical conditions including mild cognitive impairment (MCI), dementia (DEM), major depressive disorder, schizophrenia spectrum disorder (SCZ), clinical high risk for schizophrenia, bipolar spectrum disorder, autism spectrum disorder, attention-deficit/hyperactivity disorder, Parkinson's disease, and multiple sclerosis (MS). Linear models revealed that some regions of the thalamus were significantly smaller in several conditions, with largest effects observed for MCI, DEM, SCZ and MS. The thalamic nuclei groups most affected across conditions were the medial and lateral thalamic groups, while the ventral and intralaminar groups were relatively spared. This pattern of effects largely corresponds with the canonical functional subdivision of the thalamus into higher-order and sensory thalamus. Clinical conditions differed when looking at the level of individual nuclei. The results highlight a role for the higher-order thalamus in common brain disorders and a differential involvement at the level of individual nuclei, contributing towards a mechanistic understanding of pathophysiological alteration in the thalamus.

Egocentric body-axis-related and allocentric clover-like tuning of object vector representations supports human spatial cognition
Vector-based spatial representation is key for navigation, mapping direction and distance between self and environment. Though observed in rodents, its neural basis in humans remains unclear. Using high-resolution imaging and a novel spatial updating task, we found vectorial representations in retrosplenial and parahippocampal cortex, extending to parietal and entorhinal areas in self- and object-centered coordinates, respectively. Egocentric directional signals peaked when the object was behind the navigator, while distance signals emerged only when the object was out of view, suggesting these signals might act as mnemonic buffers for vision-independent spatial mapping. Allocentric directional signals formed a clover-shaped four-axis pattern aligned to a common visual feature, with improved navigation accuracy along these axes, highlighting their functional relevance for human navigation. Rodent parallel single unit recordings indicated the clover pattern resulted from the average activity of neurons with allocentric vectorial properties, suggesting a shared, cross-species mechanism. Collectively, our findings demonstrate a vector-based population code detectable via fMRI, potentially serving as a neural reference axis that anchors objects to internal maps, supporting flexible navigation and perhaps broader cognition.

Nonlinear modulation of human exploration by distinct sources of uncertainty
Decision-making in uncertain environments requires balancing exploration and exploitation, with exploration typically assumed to increase monotonically with uncertainty. Challenging this prevailing assumption, we demonstrate a more complex relationship by decomposing environmental uncertainty into volatility (systematic change in reward contingencies, learnable) and stochasticity (random noise in observations, unlearnable). Across two behavioral experiments (N=1001, N=747) using a probabilistic reward task, we find a robust U-shaped relationship between the volatility-to-stochasticity (v/s) ratio and exploratory behavior, with participants exploring more when either stochasticity or volatility dominates. Remarkably, this pattern extends to real-world financial behavior, as demonstrated through analysis of five years of S&P 500 stock market data, where portfolio diversity (a proxy for exploration) shows the same U-shaped relationship with market volatility (systematic price movements driven by fundamental factors, e.g., economic shifts) relative to trading noise (random fluctuations from trading activity unrelated to fundamentals). These findings reveal how humans adaptively modulate exploration strategies based on the qualitative composition of uncertainty, with optimal performance occurring at intermediate uncertainty ratios. This nonlinear relationship has important implications for understanding decision-making across domains where uncertainty arises from multiple sources.

Whole-gut spatial genomic analysis reveals molecular regionalization of the differentiating zebrafish enteric nervous system
The enteric nervous system (ENS) is the intrinsic nervous system of the gut and controls essential functions, such as gut motility, intestinal barrier function, and water balance. The ENS displays a complex 3D architecture within the context of the gut and specific transcriptional states needed to control gut homeostasis. During development, the ENS develops from enteric neural progenitor cells (ENPs) that migrate into the gut and differentiate into functionally diverse neuron types. Incorrect ENS development can disrupt ENS function and induce various gut disorders, including the congenital disease Hirschsprung disease, or various other functional gut neurological disorders, such as esophageal achalasia. In this study, we used the zebrafish larval model and performed whole gut spatial genomic analysis (SGA) of the differentiating ENS at cellular resolution. To that end, a pipeline was developed that integrated early and late developmental ENS stages by linking various spatial and transcriptional dimensions to discover regionalized cellular groups and their co-expression similarity. We identified 3D networks of intact ENS surrounding the gut and predicted cellular connectivity properties based on the stage. Spatial variable genes, such as hoxb5b, hoxa4a, etv1, and ret, were regionalized along gut axes, suggesting they may have a precise spatiotemporal control of ENS development. The application of SGA to ENS development provides new insights into its cellular transcriptional networks and interactions, and provides a baseline data set to further advance our understanding of gut neurodevelopmental disorders such as Hirschsprung disease and congenital enteric neuropathies.

Fasting Rescues Locomotion in Neuromodulation-Deficient C. elegans via Octopamine-Gαq Signaling
Nutrient deprivation induces adaptive behavioral and physiological changes that are critical for survival. Here, we demonstrate that fasting ameliorates locomotion defects in Caenorhabditis elegans mutants lacking UNC-31/CAPS, a protein essential for dense-core vesicle (DCV)-mediated neuromodulation. Through forward genetic screening, we identified a gain-of-function mutation in egl-30, which encodes the heterotrimeric G protein subunit Gq, that suppresses the locomotion defects of unc-31 mutants under fed conditions. Transcriptomic analyses revealed that fasting induces upregulation of egl-30 and its downstream effectors in unc-31 mutants. Remarkably, exogenous octopamine treatment, which activates EGL-30/Gq signaling, mimicked the fasting response and restored locomotion in an EGL-30-dependent manner. Our findings uncover a mechanism of neuromodulatory plasticity, in which metabolic stress activates a compensatory octopamine-Gq signaling cascade to bypass impaired DCV-mediated neuromodulation, and suggest potential therapeutic strategies for CAPS-related neuropsychiatric disorders.

IL-17 sensitises sensory neurons and colonic afferents to noxious stimuli in a PI3K dependent manner
Managing visceral pain associated with gastrointestinal (GI) disease remains a significant challenge due to the gut-related side effects and contraindicated use of many commonly used painkillers in people with inflammatory bowel disease (IBD). Consequently, it is crucial to deepen our understanding of the mediators and mechanisms underlying inflammatory pain in people with IBD. To do this, we compared bulk RNA sequencing data from colonic biopsy samples from people with IBD with single-cell RNA sequencing data from colon projecting dorsal root ganglion (DRG) neurons in mice to generate an interactome of putative pro-nociceptive cytokine signalling pathways. This in silico analysis revealed a 10-fold increase in IL17A expression in samples from people with ulcerative colitis (UC) alongside marked co-expression of Il17ra with Trpv1 in colon-projecting DRG neurons in mice, highlighting a likely role for interleukin-17 (IL-17) in colonic nociceptor signalling in people with UC. In support of this, Ca2+ imaging studies demonstrated that IL-17 stimulates DRG sensory neurons co-sensitive to capsaicin with a similar proportion responding in neuron-enriched cultures generated by magnetic-activated cell sorting, thus confirming that IL-17 directly activates DRG neurons. IL-17-evoked Ca2+ signals were attenuated by TRPV1 inhibition, consistent with nociceptor activation, and blocked by inhibition of phosphoinositide 3-kinase (PI3K) activity, consistent with the known role for PI3K as a downstream effector of IL-17 receptor signalling. In keeping with these observations, IL-17 enhanced murine colonic afferent responses to colorectal distension at noxious distension pressures, an effect also blocked by PI3K inhibition. Overall, these findings demonstrate a pro-nociceptive effect of IL-17 in the GI tract, thus highlighting the potential utility of IL-17-targeting therapies to reduce pain in people with UC.

ER fusogens maintain membrane reservoir to ensure brain function
How the morphological dynamics of the endoplasmic reticulum (ER) are linked to its functions is unclear. Atlastins (ATLs), a class of GTPases, mediate ER fusion, and human mutations in ATL1 cause hereditary spastic paraplegia (HSP). Here, we show that ATL2-knockout mice are embryonic lethal with compromised development, particularly of the cerebellum. ATL2 is highly expressed in neuroglia, though ATL1 is dominant in the brain. Lack of ATL2 disorganizes the positioning of Bergmann glia, which in turn interferes with granule cell migration. These cells have significant shrinkage in the intracellular membrane area, which is associated with decreased phosphatidylcholine and cholesterol synthesis. When tested in calyx-type synapses in ATL-deleted mice, a reduced membrane reservoir, represented by fewer presynaptic vesicles, leads to defective synaptic function and deafness. Collectively, these findings suggest that ER-shaping activity by ATL is essential for sustained lipid synthesis, and boosted lipid uptake is potentially beneficial for HSP patients.

Arcuate Fasciculus: Evolutionary Convergence in Marmosets and Humans
The marmoset is a highly vocal platyrrhine monkey that shares key anatomical and functional features with humans, providing a unique opportunity to illuminate the phylogenetic origins of diverging connectivity profiles and their transformations throughout evolution. Although the similarity of vocalization features between humans has been reported, whether marmosets possess an arcuate fasciculus homolog is not known. In this study, we delineated the white matter tracts in marmosets, establishing homologies with those observed in other primates, including macaques, chimpanzees, and humans. The presence of an arcuate fasciculus homolog in marmosets was confirmed by tracer and ultra-high-resolution diffusion magnetic resonance imaging datasets. Using a connectivity blueprint approach, we compared cortical connectivity patterns across these species and found the arcuate fasciculus in marmosets terminates in the ventral frontal cortex, with a similarity to humans that exceeds that observed in macaques, something corroborated by quantitative analyses after transforming all brains into a common space. To explore arcuate fasciculus' support for species-specific vocalizations, the activation patterns of vocal communications in marmosets and humans were associated with arcuate fasciculus connectivity. Collectively, our findings suggest that a dorsal pathway, which emerged early in marmoset evolution, has evolved convergently with humans, despite their distant phylogenetic kindship.

HIF-1α/STOML2 mediated PINK1-dependent mitophagy activation against hypoxia-induced neuronal injury
Hypoxia contributes to brain disorders by causing neuronal injury. However, in the early stage of stress, neurons initiate a series of compensatory pathways to resist cell damage, but the underlying mechanisms have not been fully elucidated. In this study, we found that hypoxia transiently activates PTEN-induced kinase 1 (PINK1)-dependent mitophagy in the early stage before cell damage and neurological dysfunction. PINK1 overexpression protects neurons and it knockdown exacerbates neuronal damage, highlighting the key role of PINK1-dependent mitophagy in hypoxic adaptation. Mechanistically, hypoxia promotes HIF-1 nuclear translocation, inducing transcription of stomatin like 2 (STOML2). STOML2 relocates to the mitochondrial membrane, aiding phosphoglycerate mutase 5 (PGAM5) cleavage, which triggers PINK1-dependent mitophagy. Silencing HIF-1, STOML2, or PGAM5 inhibits PINK1-dependent mitophagy and worsens neurological function under hypoxia. Notably, intermittent hypoxia, a hypoxic conditioning strategy for improving hypoxic tolerance, enhances PINK1-dependent mitophagy by activating HIF-1/STOML2 axis, and protects neurons against hypoxia. In conclusion, our study reveals a new "self-protection" mechanism of neurons against hypoxic stress and discovers that intermittent hypoxia is a potential therapeutic strategy against hypoxia-induced injury.

Unsupervised feature computation-based feature selection robustly extracted resting-state functional connectivity patterns related to mental disorders
Research on biomarkers for predicting psychiatric disorders from resting-state functional connectivity (FC) is advancing. While the focus has primarily been on the discriminative performance of biomarkers by machine learning, identification of abnormal FCs in psychiatric disorders has often been treated as a secondary goal. However, it is crucial to investigate the effect size and robustness of the selected FCs because they can be used as potential targets of neurofeedback training or transcranial magnetic stimulation therapy. Here, we incorporated approximately 5,000 runs of resting-state functional magnetic resonance imaging from six datasets, including individuals with three different psychiatric disorders (major depressive disorder [MDD], schizophrenia [SCZ], and autism spectrum disorder [ASD]). We demonstrated that an unsupervised feature-computation-based feature selection method can robustly extract FCs related to psychiatric disorders compared to other conventional supervised feature selection methods. We found that our proposed method robustly extracted FCs with larger effect sizes from the validation dataset compared to different types of feature selection methods based on supervised learning for MDD (Cohens d = 0.40 vs. 0.25), SCZ (0.37 vs. 0.28), and ASD (0.17 vs. 0.16). We found 78, 69, and 81 essential FCs for MDD, SCZ, and ASD, respectively, and these FCs were mainly thalamic and motor network FCs. The current study showed that the unsupervised feature-computation-based feature selection method robustly identified abnormal FCs in psychiatric disorders consistently across datasets. The discovery of such robust FCs will contribute to understanding neural mechanisms as abnormal brain signatures in psychiatric disorders. Furthermore, this finding can aid in developing precise therapeutic interventions, such as neurofeedback training or transcranial magnetic stimulation therapy.

Kinocilia of Vestibular Hair Cells: Bridging Structural and Functional Traits of Primary and Motile Cilia
Vestibular hair cells (HCs) detect head motion and orientation by transducing mechanical forces generated by gravity and acceleration into neural signals. This mechanotransduction is mediated by the hair bundle, which comprises stereocilia and a kinocilium--the latter considered a specialized form of primary cilium. To investigate its characteristics, we performed single-cell RNA sequencing on 1,522 adult vestibular and cochlear HCs. Our analysis revealed an enrichment of genes associated with motile cilia in vestibular HCs, particularly those linked to the axonemal repeat complex, a defining structural feature of motile cilia. Similar axonemal-related genes were identified in zebrafish and human vestibular HCs, highlighting a conserved molecular composition of kinocilia across vertebrate species. Immunostaining confirmed the expression of key motile cilia markers--including CCDC39, CCDC40, DNAH5, and DNAH6--in vestibular kinocilia. Live imaging of bullfrog saccular and mouse crista HCs revealed spontaneous kinociliary motion that drove oscillations of the hair bundle. Together, these findings establish the kinocilium as a distinct organelle with molecular hallmarks of motile cilia and suggest it functions as an active, force-generating vestibular hair bundle component, potentially influencing mechanosensitivity of HCs.

The role of inhibitory neurons in novelty sound detection in regular and random statistical contexts.
Detecting statistical regularities in sound and responding to violations of these patterns, termed novelty detection, is a core function of the auditory system. Human studies have shown that novelty responses are enhanced in regular compared to random auditory contexts, but the underlying circuit mechanisms remain unclear. Here, we examined how inhibitory neurons contribute to context-dependent novelty responses in mouse auditory cortex. Using two-photon calcium imaging in the auditory cortex of awake head-fixed male and female mice, we recorded neuronal activity during presentation of spectro-temporally rich ripple sounds, with novel ripples embedded in either regular or random ripple sequences. AC neurons exhibited enhanced responses to novel sounds in regular contexts compared to random ones. To identify circuit mechanisms, we selectively inactivated parvalbumin (PV), somatostatin (SST), or vasoactive intestinal polypeptide (VIP) inhibitory neurons using optogenetics during imaging. Inactivation of PV and SST neurons broadly increased novelty responses in both contexts. In contrast, VIP inactivation selectively reduced responses to novel stimuli in the regular context, abolishing the context-dependent enhancement. At the population level, inactivating all three neuronal subtypes increased detectability of the novel stimulus, but with VIP inactivation, the shift was stronger for regular than random context. These findings reveal a distinct role for VIP neurons in modulating prediction error signals based on temporal structure, suggesting that VIP circuits are critical for context-sensitive auditory processing.

Control of two-pathway signal integration in a model neocortical pyramidal cell
We demonstrate how neuromodulation and spatially targetted inhibition can alter the integration of the two streams of excitatory input in a thick-tufted layer 5 pyramidal cell, using a computational reduced-compartmental cell models. Choosing suitable ranges of brief current stimulus amplitudes, applied basally to either the soma or basal dendrites (basal stimulation) and to the apical tuft (apical stimulation) results in burst firing due to either stimulus alone, if strong enough, or by a combination of the stimuli at lower amplitudes. Applying tonic inhibition to the apical tuft removes the ability of apical input alone to generate a burst over the chosen amplitude range. A similar effect is achieved by reducing the tuft calcium channel conductance as an outcome of neuromodulation. Similarly, tonic inhibition to the basal dendrites removes the ability of basal stimulation alone to generate a burst, without blocking bursts resulting from apical calcium spikes. HCN channels in the apical dendrites may amplify or reduce bursting probability, depending on other active and passive properties of dendrites. So neuromodulation that decreases the conductance of these channels may act to reduce or increase bursting probability across the across the ranges of basal and apical inputs, depending on cell properties. These effects mimic those found previously by simply limiting the range of stimulus amplitudes (Graham et al, 2025) but now show that such changes in two-stream signal integration can happen through network inhibition and neuromodulation with no change in the excitatory driving stimulus strengths. These changes in signal integration also lead to changes in information transmitted by the cell's bursting probability about the two input streams, as shown in Graham et al (2025). Changes in cell morphology are also investigated by reducing the apical trunk length and are revealed to alter this two-stream signal integration through differential effects on passive and active interaction between the soma and apical tuft.

Cannabis use in humans is associated with impaired implicit motor learning and supranormal baseline cortical activity
Chronic cannabis use is associated with cognitive impairment, but its impact on implicit motor learning is unclear. Implicit learning of movement sequences (i.e., their specific ordinal and temporal structure) is vital for performing complex motor behavior and lays the foundation for performing daily activities and interacting socially. We collected data from 32 individuals who used cannabis regularly and 30 individuals who did not use cannabis. We utilized the serial reaction time task to assess implicit motor sequence learning and the Corsi block-tapping test to assess visuospatial short-term and working memory. We also recorded resting state electroencephalography (EEG) to measure baseline cortical activity. While implicit motor learning was evident at the group level, cannabis use measures were associated with a smaller index of motor learning and increased activity in beta and gamma EEG frequencies during resting state. The cannabis group also had a significantly shorter Corsi span (in both forward and backward conditions). These findings indicate that chronic cannabis use is associated with impaired implicit motor learning that may be a function of increased baseline neural oscillatory activity, resulting in increased cortical noise, and reduced visuospatial short-term and working memory. These findings suggest that chronic cannabis use may disrupt corticostriatal pathways that underlie implicit motor sequence learning, indicating a more extensive effect of cannabis on the motor system.