bioRxiv Subject Collection: Neuroscience's Journal

Impact of air pollution on Neurite Orientation Dispersion and Density metrics (NODDI) in 10-13-year-old children with and without ADHD diagnosis
Air pollution is a significant risk factor for adverse neurodevelopmental outcomes in children. While studies have linked pollutants to changes in brain structure, specific effects on white matter microstructure remain inconclusive. Neurite Orientation Dispersion and Density Imaging (NODDI) provide two nuanced, separate white matter measures that serve as proxies for neurite density and cell-body organization. We used NODDI to examine potential associations between prenatal, early life and current exposure to nitrogen dioxide (NO2) and particulate matter with diameter < 10 micrometers (PM10) and white matter microstructure in school-aged children. We also explored whether ADHD diagnosis moderated these associations. We observed several negative associations between both NO2 and PM10 exposure and neurite density across various white-matter fibers and exposure windows, but none of the associations were statistically significant after correcting for multiple comparisons. In this analysis, we did not find any statistically significant associations between long-term exposure to PM10 and NO2 and white matter microstructural integrity as measured by NODDI. Our results highlight the challenge of detecting modest environmental impacts on the brain and underscore the need for larger, more targeted studies to confirm these preliminary trends.

CeDNe: A multi-scale computational framework for modeling structure-function relationships in the C. elegans nervous system
Understanding how neural circuits generate behavior requires integrating structural and functional data across scales. C. elegans with its complete connectome, genetically identifiable neurons, single-cell transcriptome, neuropeptide-receptor distribution, and an amenability to simultaneous measurement of brain-wide neural activity and behavior presents a unique opportunity for such a multiscale circuit analysis. However, the absence of a unifying framework to connect these diverse datasets limits our ability to connect network structure and attributes with function. Here we introduce CeDNe - C.elegans Dynamical Network, an open-source computational framework that integrates anatomical, molecular, and imaging datasets into a unified graph-based representation that enables multimodal data analysis by cross-referencing different omics layers in a single computational environment. Specifically, CeDNe provides modular tools for visualizing and analyzing network connectivity, motif distribution, and circuit paths. Further, it incorporates a computational framework that simulates neural dynamics and optimizes network models to bridge structural connectivity with neural activity. Thus, CeDNe establishes a scalable foundation for data-driven modeling of the nervous system. This open-source tool not only facilitates computational connectomics and multimodal analyses in C. elegans, but also serves as a generalizable framework for investigating structure-function relationships in neural networks of other organisms.

Emotional Responses to Naturalistic and AI-generated Affective Pictures: A Systematic Comparison
Pictures depicting naturalistic scenes are widely used in studies of human emotion. However, the practical use of affective pictures is limited by several factors, including the difficulty of obtaining content-diverse, high-quality, openly accessible, and standardized stimuli that are necessary for specific research questions. The use of artificially generated (AI) pictures could address this limitation, but it is unclear if AI-generated pictures evoke reliable emotional responses. The present study sought to address these challenges by comparing emotional responses to AI-generated pictures with responses to original, standardized, pictures. In two study iterations, standardized pictures containing pleasant, neutral, and unpleasant content were selected from the International Affective Picture System (IAPS) and other sources. Then, a matched AI-counterpart was created for each original picture using generative deep neural networks. A total of 109 participants viewed the picture sets while pupil diameter and electroencephalogram (EEG) were recorded. Evaluative ratings of hedonic valence and emotional arousal were also collected. For both AI and original exemplars, pictures depicting emotional content elicited stronger responses than neutral content for ratings and EEG-derived variables, with weaker effect sizes for the AI-generated pictures. Furthermore, picture-level analyses found that ratings and EEG measures were strongly correlated between matched AI and original pictures. Pupil data also showed the expected content effects in study iteration 2, but not in iteration 1. Together, this initial study suggests that AI-generated picture sets can effectively elicit well-established self-reported affect and physiological responses, presenting a promising avenue for future studies of human emotion.

Ablation of microglial estrogen receptor alpha predisposes to diet-induced obesity in male mice
Estrogen receptor alpha (ER) signaling has metabolic and anti-inflammatory properties in addition to its impact on reproductive function. In male but not female mice, inflammatory activation of microglia, the resident macrophages of the brain, has been implicated in the pathogenesis of diet-induced obesity (DIO), raising the possibility that differences in microglial estrogen signaling may account for the sexual dimorphism. In this study, we assessed metabolic and CNS histopathological properties in a mouse model with inducible microglia-specific ablation of ER (MG-ERKO). Male MG-ERKO mice developed increased weight gain and insulin resistance relative to controls during high-fat diet (HFD) feeding. Indirect calorimetry analysis revealed that reduced energy expenditure was the main driver of the obese phenotype. In contrast, female MG-ERKO mice fed HFD developed mild insulin resistance with no change in body weight gain compared to controls. Immunohistochemical analyses of the microglial activation marker IBA1 in the mediobasal hypothalamus (MBH) revealed that female MG-ERKO mice had increased number of microglia without showing morphological signs of activation. In contrast, MBH microglial number was unchanged in MG-ERKO male mice, but the cells adopted more activated morphological profiles. Finally, HFD-fed MG-ERKO male mice had increased POMC neuron-microglia interactions but fewer overall hypothalamic POMC neurons, suggesting microglia may disrupt POMC neuron integrity to promote DIO. Together, these findings indicate that sex-specific actions of estrogen in microglia limit the metabolic complications of HFD feeding.

Structured and Target-Specific Development of Cortico-Cortical Connectivity in the Mouse Visual Cortex
The mammalian cortex exhibits highly stereotyped long-range connectivity, yet the developmental principles that specify precise cortico-cortical projection patterns remain poorly defined. Two dominant models propose that target specificity arises either from early inter-regional exuberant outgrowth followed by pruning, or through initially directed axonal targeting. To resolve this, we systematically mapped the postnatal development of V1 cortico-cortical projection neurons (CCPNs) to eleven higher visual areas (HVAs) in mice using rapid and complementary retrograde, anterograde, and single-cell tracing methods. We found that V1[->]HVA connectivity develops via spatiotemporally staggered axon extension and pruning programs, aligned with target position along the medial-lateral axis. Reciprocal HVA[->]V1 feedback emerges concurrently and is refined over time, yielding gradually aligned bidirectional connectivity. Notably, both multiplexed retrograde tracing and MAPseq-based single-cell profiling revealed that individual V1 neurons initialize and retain specific projection motifs with limited variation over development, arguing against global exuberance followed by selective, inter-areal pruning. Instead, our findings support a directed guidance model, in which distinct V1 CCPN subtypes establish selective projection patterns early, followed by local, target-dependent refinement. This structured yet heterogeneous developmental strategy provides an anatomical framework for how precise long-range cortical networks emerge.

Efficient mixed representation of active and passive motion in the mouse visual thalamus during natural behaviour
During natural behaviour, changes in the visual scene are largely driven by the subject's own movements, which can be actively generated (e.g., walking) or passively imposed by external forces (e.g., riding a vehicle). How the visual system represents such active and passive motion components is poorly understood. To address these questions, we developed an assay to dissect the motion of freely moving mice into active and passive components and to study its influence upon neural activity in the dorsal lateral geniculate nucleus (dLGN) and adjacent regions. Chronically implanted mice were placed in an arena where they actively moved; at irregular intervals, the arena was tilted, resulting in passive movement. We then used 3D tracking to decompose mouse head motion into active and passive components. We observed widespread responses to tilt events in dLGN, which persisted in darkness. Light-responsive units exhibited mixed selectivity for active and passive motion, primarily encoding the speed of self-motion irrespectively of its causes. However, individual neurons varied in their relative tuning to active versus passive components, allowing partial separation at the population level. Furthermore, a decoding analysis showed that population activity decorrelated active and passive head motion signals by representing their leading principal components. Together, these results indicate that, during natural behaviour, the visual thalamus takes advantage of the coupled dynamics of active and passive movements to encode an efficient, low-dimensional representation of the subject's motion.

Influence of exoskeleton stiffness on primary afferent feedback during stretch perturbations of isolated muscle-tendon unit
Exoskeletons assist and augment human movement, but their effects on proprioceptive feedback remain poorly understood. We examined how parallel exoskeleton stiffness influences primary muscle spindle firing. In an anesthetized rat preparation, controlled stretches of the medial gastrocnemius were applied with springs (0-0.5 N/mm) attached in parallel to the muscle-tendon unit (MTU) to simulate passive exoskeleton assistance. Fascicle length was measured with sonomicrometry, force and MTU length with a servo motor, and spindle instantaneous firing rate (IFR) with dorsal root recordings. Increasing exoskeleton stiffness decreased biological muscle force (3.1 {+/-} 0.6 N to 1.6 {+/-} 0.6 N, p < 0.001) and stiffness (4.4 {+/-} 1.5 N/mm to 2.3 {+/-} 1.3 N/mm, p < 0.01), while fascicle length increased (7.9 {+/-} 1.3 mm to 8.3 {+/-} 1.5 mm, p < 0.005). Despite these altered mechanics, spindle firing did not significantly change, and showed weak correlations with muscle length, velocity, force, and yank (R2 > 0.14). These results indicate that exoskeleton stiffness modifies fascicle dynamics without altering spindle firing. Previously proposed models of primary afferent firing did not sufficiently explain these results. This is the first in situ investigation of exoskeleton effects on primary afferent feedback during active contractions.

Does wearable neurofeedback training improve memory aptitudes in healthy adults?--A systematic review and meta-analysis
Neurofeedback training (NFT) provides individuals with real-time feedback on their brain activity, enabling voluntary modulation. Interest in NFT for memory enhancement has surpassed the cumulative evidence in healthy adults, especially for modalities feasible outside of laboratory settings. To address this gap, this systematic review and meta-analysis focused on electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), both of which are portable and widely accessible. Randomized controlled trials published between January 1990 and September 2022 were retrieved from PubMed, Scopus, Web of Science, and APA PsycInfo. Of the 44 eligible studies, 24 reported sufficient data for inclusion in the meta-analysis. Using a random-effects model, we found that NFT produced a small-to-moderate improvement in memory performance (standardized mean difference = 0.28; 95% confidence interval = 0.065-0.48; t(11.9) = 2.86; p = 0.014), with moderate heterogeneity. No publication bias was detected. Subgroup meta-analyses revealed significant effects in younger adults, for EEG-based protocols, and in tasks assessing verbal and short-term memory tasks. Meta-regression identified a positive association between daily session duration and effect size, with sessions longer than 30 minutes more likely to produce positive effects. As effects also varied by targeted brain regions and EEG frequency bands used for neurofeedback, protocol differences likely contributed to the observed variability in outcomes. Long-term follow-up is warranted to determine the persistence of NFT effects.

Sickness engrams modulate anticipatory immune responses
A threat to survival in the wild is vulnerability to infection. The immune system is essential for defence against foreign species which cause sickness. During infection the brain triggers conserved behaviors, including fever, tiredness and anorexia that support immunity. The immune system stores infection information via adaptive immunity, however it remains unclear whether the brain stores immune-related information as long-term memory engrams. Here we demonstrate that mice form contextual memories for sickness events. Upon sickness-memory recall mice lower whole-body metabolism, and increase coactivation between the hippocampus and sickness regions such as the central amygdala, alongside elevated engram activation. Optogenetic reactivation of sickness engrams decreases metabolism, similar to natural recall. Finally, natural recall and artificial reactivation of a sickness-memory increased genes associated with the acute phase response in the liver. These findings suggest that sickness experiences are encoded as engrams, which upon reactivation trigger coordinated metabolic and innate immune responses.

Assessing molecular, cellular and transcriptomic bases of laminar perfusion and cytoarchitecture coupling in the human cortex
Understanding how cellular architecture organizes cortical function requires mesoscopic approaches that resolve structure-function coupling in vivo. Here we introduce cerebral blood flow (CBF) and cell-body staining intensity (CSI) similarity index (CCSI), a localized similarity index between the CBF estimates from ultra-high-field 7T arterial spin labeling images and CSI from the BigBrain histology images to serve as a quantitative marker of laminar perfusion-cytoarchitecture coupling. CCSI revealed a reproducible, region- specific alignment between laminar vascular and cellular profiles across the cortex. Going beyond CBF, CCSI selectively tracked mitochondrial respiratory capacity and colocalized with capillary endothelial and mature non-myelination oligodendrocyte populations forming neurovascular interfaces. Transcriptomic enrichment highlighted pathways related to vascular remodeling, oxidative metabolism, and lipid-myelin homeostasis, indicating that CCSI reflects integrated metabolic-structural specialization. At the systems level, CCSI strengthened structure-function gradient correspondence in transmodal cortices, such as the default mode network. Together, these findings establish CCSI as a physiologically grounded, non-invasive marker of perfusion-cytoarchitecture alignment, providing a cross-scale framework linking cortical microstructure, metabolism, and functional organization.

A chemogenetic ligand-receptor pair for voltage-gated sodium channel subtype-selective inhibition
Neuronal excitability relies on the tightly regulated expression and discrete subcellular localization of voltage-gated sodium channels (Navs). These large membrane protein complexes control the movement of sodium ions across cell membranes and are responsible for initiating and propagating action potentials. A desire to better understand the role of Nav subtypes in electrical signal conduction and the relationship between channel dysregulation and specific human pathologies (e.g., epilepsy, musculoskeletal disorders, neuropathic pain) motivates the development of high-precision pharmacological reagents to facilitate Nav studies. Investigations of Nav physiology and nerve cell conduction are limited by a lack of available methods with which to modulate acutely and reversibly the function of individual channel subtypes. Moreover, discriminating between Navs expressed in different cell types is not possible even with potent and selective ligands that target specific channel homologues. We have capitalized on both chemical design and protein engineering to advance a chemogenetic tool to inhibit a single Nav isoform. A synthetic derivative of the bis-guanidinium toxin saxitoxin (STX) is paired with two unique outer pore-forming amino acid mutations to achieve ~100:1 selectivity for the engineered channel over wild-type Nav1.1-1.4, 1.6, and 1.7. The designer ligand is nanomolar potent against the mutant channel and acts within seconds to block sodium ion conduction; washing cells with buffer solution rapidly and completely restores channel function. This technology will empower studies of Nav physiology and have additional applications for manipulating action potential signals given the requisite role of Navs in electrogenesis.

Transcriptional Profiling of D1-MSNs Reveals SIRT1-Dependent and -Independent Responses to Chronic Social Defeat Stress
SIRT1 is a critical regulator of neuronal functions and has been implicated in various neurological disorders, including depression. In a previous study, we demonstrated the pro-depressive roles of SIRT1 in the nucleus accumbens (NAc) using the chronic social defeat stress (CSDS) model, a well-validated preclinical mouse model of depression. We found that SIRT1 modulates synaptic functions and exhibits pro-susceptible effects specifically in D1-medium spiny neurons in the NAc. In this study, we extended our investigation of SIRT1 functions by employing cell-type-specific transcriptomics to compare control and susceptible groups under CSDS. Our results revealed that in wild-type mice with functional SIRT1, cellular metabolism is crucial for inducing susceptibility to depression. Conversely, in the absence of functional SIRT1 expression, circadian clock-controlled transcriptional regulation becomes a key factor. These findings suggest that SIRT1 differentially modulates key pathophysiological mechanisms of depression via its deacetylase functions, highlighting its role in both metabolic and circadian regulation in the brain. This research provides new insights into the molecular underpinnings of depression and identifies potential targets for therapeutic intervention.

Similar processing of novelty in rat dorsal and intermediate CA1 despite differences in spatial tuning
Elucidating the fundamental neural mechanisms of hippocampal information processing is necessary for understanding memory formation and related brain disorders. Differences in hippocampal genetics, anatomy, and connectivity across the longitudinal axis suggest functional heterogeneity in this structure. The dorsal pole is suggested to be primarily involved in spatial processing, whereas the ventral pole is implicated in emotional processing. Connectivity and genetic studies show this functional segregation is more prominent near their respective poles and weaker toward the intermediate region. The current study compares the firing properties of CA1 cells in the dorsal and intermediate regions of the hippocampus during spatial or social/odor novelty. We measured basic spatial properties, firing rate response, and remapping to the spatial re-configuration of a linear track or the social/odor presentation of a novel male conspecific, female bedding, or coyote urine. Behaviorally, the average rat exhibited slower maze running latencies during the novel spatial manipulation and spent more time adjacent to the chamber containing the novel social/odor stimulus. As previously shown, dorsal cells had fewer, smaller place fields, and higher spatial information content than intermediate cells in the hippocampus. Despite the differences in place field characteristics, cells in both regions responded similarly to spatial and social/odor manipulations. Taken together, these data support the differentiation of some functions, together with an overlap of other functions progressing along the longitudinal axis, which may facilitate the integration of information throughout the hippocampus.

Ephaptic-Axonal Interactions Shape Radial Biases DuringNeural Self-Organization
Communication in the brain seems to not just be mediated by axonal action potential transmission resulting in post synaptic modulations, but also by electrical field effects of depolarizing neurons, i.e. ephaptic coupling. The significant role of ephaptic coupling in synchronizing neural ensembles has been conjectured to indirectly affect ontogenetic neural circuit development through sub threshold impacts on spike timing. We therefore hypothesized synchronously firing ensembles to emerge at spatial distances where ephaptic and axonal signals were most temporally correlated. To test our model of ephaptic axonal interactions during neural self-organization, we compared its predictions to developmental outcomes of cortical rat tissue on high-density multielectrode arrays in vitro. We observed a cosinusoidal variation of synchronous activity over radial distances that can be understood to result from the joint effects of ephaptic and axonal signals during gamma-band bursts. Recurrent amplification of this theorized interaction effect during ontogenetic differentiation appears to radially bias the spectral profile of neural activity in the spatial distribution of neural ensembles. While long- term plasticity has been conventionally attributed to synaptic action alone, we show that that the interaction effects with ephaptic waves deserve further investigation.

No sex differences in predictive processing
Statistical learning, defined as the implicit extraction of environmental regularities, is recognized as a universal and evolutionarily conserved mechanism, and constitutes a fundamental aspect of predictive processing. Still, whether it is modulated by sex or hormonal influences remains an open question. The present study investigated whether statistical learning varies as a function of sex or women's hormonal status. We re-analyzed data from 473 young adults who completed an online visuomotor Alternating Serial Reaction Time (ASRT) task, comparing (i) age-matched men and women, (ii) women using or not using hormonal contraceptives, and (iii) cycling women across self-reported menstrual phases. Robust statistical learning emerged across all groups. Neither sex, hormonal contraceptive use, nor menstrual phase significantly modulated the magnitude or trajectory of statistical learning. Bayesian analyses consistently favored models excluding group effects. In addition, we observed small but noteworthy baseline differences in visuomotor performance, including faster initial responses in men and a slight premenstrual decline in accuracy. These findings suggest that while implicit statistical learning itself is largely resilient to sex-related and hormonal influences, sex and menstrual cycle may still shape aspects of visuomotor behavior, pointing to distinct levels of sensitivity within predictive cognition.

Natural variation in the oxytocin receptor gene predicts social observation in female prairie voles
Genetic variation in the oxytocin receptor gene (Oxtr) has been linked to differences in brain OXTR expression and long-term social bonds, but whether it shapes the moment-to-moment dynamics of early social interactions is unclear. Here we examined how the intronic Oxtr single nucleotide polymorphism (SNP) NT213739 in female prairie voles (Microtus ochrogaster) shapes their dynamic social interactions with an opposite-sex conspecific. Leveraging a computational pipeline to analyze the movements of freely interacting voles, we found that C/C females, which expressed higher OXTR levels in the nucleus accumbens than T/T females, spent more time socially observing novel males from a distance, especially early in interactions. This genotype-phenotype relationship persisted in multiple contexts, including the social preference test. Thus, natural Oxtr variation biases social observation in females toward unfamiliar males before bonds form, consistent with models where accumbens OXTR enhances the salience of social cues. These findings show that SNPs can shape subtle behavioral dimensions in early social encounters, with important implications for the role of oxytocin in the study of social attachment.

Reduced cerebrovascular reactivity is more pronounced in female than male youth with complex congenital heart defects
Congenital heart defects (CHD) are the most common type of neonatal malformation. Neonates with complex CHD present with cerebrovascular dysfunction, including deficits in cerebrovascular reactivity (CVR), a measure of vascular reserve. However, it is unknown whether these deficits persist beyond the perioperative period. Here, we compared CVR between 53 youth with CHD and 54 age-matched controls without CHD. We found that youth with CHD present with relative CVR deficits in the whole grey matter and in the anterior cerebral artery territory when compared to controls. Important sex differences were identified in the middle cerebral artery territory, with females having lower relative CVR than males in the CHD group. Severity of CHD also had an impact on CVR, with greater deficits in individuals with single-ventricle as compared to two-ventricle physiology. Finally, in the CHD group, a lower CVR was found to be associated with reduced performance on the Metacognitive Abilities Index. These results support that cerebrovascular deficits in CHD survivors are persistent and that CVR offers great promise as a biomarker of cognitive difficulties, which could be targeted in future interventions.

An induced pluripotent stem cell-based chemical genetic approach for studying spinal muscular atrophy
Spinal muscular atrophy (SMA) is a genetic disease characterized by degeneration of spinal cord motor neurons and neuromuscular junctions. Despite recent development in therapies for SMA, treatment efficacy largely relies on administration of drugs early in disease progression and is impacted by underlying patient genetics. Drug discovery for other diseases of the central nervous system (CNS) has also been hindered by heterogeneity in patient genetics and clinical presentations, as well as the need for early intervention. To address these hurdles, we utilized a chemical genetic-based screening approach to adapt the Connectivity Map (CMAP)/L1000 platform to study SMA. To do this, we differentiated moderate and severe SMA patient-specific induced pluripotent stem cells into neuronal cells utilizing a forward programming differentiation protocol, exposed each to 360 neuroactive or CNS disease-related compounds, and interrogated resulting changes in expression of >400 neural genes in a platform we term CMAPneuro. In doing so, we generated 4,559 transcriptional profiles identifying stimuli that modulate gene expression differences across SMA neurons. Finally, we make these data queryable, allowing the research community to 1.) identify CNS disease-related perturbagens that mimic or reverse differentially expressed genes, or 2.) explore the transcriptional response of a given perturbation in diverse SMA neuronal cells.

Functional architecture for speed tuning in primary visual cortex of carnivores
Perception of motion critically depends on detecting the speed and direction of moving stimuli. The primary visual cortex (V1) of some mammals, including primates and carnivores, exhibits functional organization for key receptive field properties such as orientation, direction, and spatial frequency; however, less is known about the organization of speed-tuned cells. While individual V1 neurons have been shown to exhibit speed selectivity, functional architecture for speed preference has been primarily reported in higher cortical areas such as primate area MT. Using multi-channel electrophysiology in anesthetized female ferrets, we investigated the joint tuning of V1 neurons for spatial frequency, temporal frequency, orientation/direction, and speed. We found significant clustering of cells tuned for speed and for speed preference within single electrode penetrations. We found that both simple and complex cells can exhibit speed tuning, and no strong variation across cortical layers. In reanalysis of intrinsic signal imaging data from cat V1, we observed repeating "hot spots" of high speed selectivity separated by "cold spots" with low tuning for speed. These findings indicate that a functional architecture for speed tuning is present within V1 itself and transmitted to downstream cortical regions.

Functionally Relevant and Reliable Brain Stimulation Targets for Enhancement of Novel Word-Learning
Linking word forms and their meanings is central to language learning. Transcranial direct current stimulation (tDCS), has shown potential to enhance this process, but with variable effects. This study aimed to (1) identify reliable and functionally relevant tDCS target brain regions to enhance novel-word learning, using a functional magnetic resonance imaging (fMRI) compatible associative picture-pseudoword learning task, and (2) assess test retest reliability (TRR) of behavioral and imaging outcomes. Twenty healthy individuals completed two fMRI sessions using parallel task versions. Participants learned picture pseudoword associations across four learning blocks. A lexical decision task served as control condition. Behavioral learning was analyzed using linear mixed models. Whole brain and region of interest analyses examined learning related activity changes and their behavioral relevance. TRR was assessed using intraclass correlation coefficients. Participants successfully acquired the novel-word forms, indexed by increased accuracy and faster latency across stages. Behavioral outcomes showed good to excellent TRR. The task elicited robust language learning related activity and activity changes across stages were correlated with learning success. The control task showed no consistent activity changes. Task-related brain activity showed substantial variability, but a subset of voxels (~30%) within significant clusters showed good consistency. In sum, we identified accessible, reliable and functionally relevant cortical targets for enhancing novel word learning by tDCS. TRR results support the usefulness of APPL task for future concurrent tDCS fMRI research. Our study also outlines a general path towards optimization of brain stimulation studies by implementing an empirically informed approach for selecting reliable and relevant target regions and implementation of reliable experimental and imaging paradigms.

Human-specific fast synaptic kinetics enable rapid detection of predictive features
Humans can discern the underlying principles in complex environments, but the cellular basis of this ability is unclear. By comparing layer 2/3 cortical pyramidal neurons in five mammals (mouse, rat, marmoset, macaque and human), we found that human neurons exhibited distinctively faster kinetics of excitatory synaptic transmissions. In a computational model, neurons with human-type synapses detected hidden patterns more quickly in noise, and this superiority was only evident in unsupervised learning. Tracking synaptic weights revealed that human synapses were potentiated sharply and persistently by the patterns, while macaque-type synapses were broadly potentiated, which were easily eroded. These data suggest that the human-specific acceleration of synaptic kinetics enables the rapid extraction of latent structures in complex environments, providing a cellular basis for our efficient cognitive abilities.

Fully Automated EEG Source Imaging Using Structured Sparsity for Single and Multiple Synchronous Epileptic Activities
Accurate localization of epileptic zones from High-Resolution ElectroEncephaloGraphy (HR-EEG) data can be challenging, especially when multiple synchronous zones are involved, and is highly dependent on the chosen EEG Source Imaging (ESI) method. Since a given scalp-level electrical pattern can result from multiple source configurations, ESI methods address this ill-posed inverse problem by imposing constraints on the structure of underlying sources. Here, we present an efficient approach that imposes sparsity on both the source-level activity and its spatial gradient. Unlike other methods that generally require a heuristic choice of a regularization parameter that balances between data fidelity and constraints, our method iteratively adjusts the parameter value based on the noise level in a fully automated way. The performance of the new method is evaluated across different scenarios of realistic synthetic HR-EEG data, including unifocal and synchronous multifocal cortical epileptic activity. Based on multiple performance indices, we demonstrate that the proposed approach outperforms traditional methods in accurately reconstructing epileptic sources. We also show that the method reduces polarity artifacts responsible for ghost sources and spatial discontinuities. Its ability to recover homogeneous, well-delineated regions of activity is further confirmed using real EEG data capturing a typical absence seizure.

Choosing the best or avoiding the worst: complementary and opponent value signals in the human brain
Whether the brain encodes the subjective value of pleasant and unpleasant situations via a single integrated circuit or through distinct pathways remains unresolved. It is also unclear how neural value signals guide choices when the context involves choosing the most favorable option or avoiding the most unfavorable one. To address these questions, we recorded intracerebral activity from 27 participants as they first rated pleasant and unpleasant scenarios and then made binary choices across all combinations of item domain (pleasant/unpleasant) and choice frame (choose best/worst). Ventromedial prefrontal cortex (vmPFC) broadband gamma activity (BGA, 50 to150 Hz) tracked the value of pleasant items during rating and pre-choice, correlating positively with the most pleasant item irrespective of choice frame. Similarly, anterior insula (aIns) BGA tracked the value of unpleasant items during rating and pre-choice, correlating negatively with the most unpleasant item irrespective of choice frame. The difference in relative value correlations between the vmPFC and aIns was larger for choices involving a conflict between item domain and choice frame, consistent with slower response times and choices less aligned with value differences in these trials. These findings reveal dissociable yet complementary neural systems for pleasant and unpleasant valuation and highlight how such signals may guide flexible decision making across contexts.

Structural and functional brain asymmetry in relation to heterogeneous causes of situs inversus totalis
Various aspects of brain organization differ between the left and right hemispheres. Clues to the developmental origins of these asymmetries may be gained through associations with situs inversus totalis (SIT), a rare condition in which visceral organs are reversed on the left-right axis. In the largest previous brain imaging analyses of SIT (38 cases, 38 controls from Belgium), typical functional asymmetries such as left-hemisphere language dominance were mostly unaltered, but various aspects of asymmetrical cerebral structure - petalia, bending, and posterior venous anatomy - were often reversed in this condition. SIT can be a monogenic trait that arises from rare genetic variants, usually affecting motile cilia which help to create the embryonic left-right body axis. However, most SIT cases do not have obvious genetic causes and may arise from environmental or random effects during embryogenesis. We sequenced the genomes of 23 SIT cases and 23 controls from the Belgian brain imaging dataset and pooled with prior data from 15 cases and 15 controls. We aimed to discover whether there are altered brain asymmetries in SIT cases with disruptive DNA variants in ciliary genes, or in other types of genes, as compared to genetically unsolved cases. In total, 19 cases had likely causal variants affecting ciliary function, while 19 cases remained genetically unsolved. Functional and structural brain asymmetries were not significantly different in genetically solved versus unsolved SIT cases. Therefore, functional brain asymmetries seem largely independent of known mechanisms of visceral situs formation, while structural brain torque is altered in SIT regardless of the presence or absence of overt genetic causes.

A Caveat Regarding the Unfolding Argument: Implications of Plasticity for Computational Theories of Consciousness
The unfolding argument in the neuroscience of consciousness posits that causal structure cannot account for consciousness because any recurrent neural network (RNN) can be "unfolded" into a functionally equivalent feedforward neural network (FNN) with identical input-output behavior. Subsequent debate has focused on dynamical properties and philosophy of science critiques. We examine a novel caveat to the unfolding argument for RNN systems with plasticity in the connection weights. We demonstrate through rigorous mathematical proofs that plasticity negates the functional equivalence between RNN and FNN. Our proofs address history-dependent plasticity, dynamical systems analysis, information-theoretic considerations, perturbational stability, complexity growth, and resource limitations. We demonstrate that neuronal systems that possess properties such as plasticity, history-dependence, and complex temporal information encoding have features that cannot be captured by a static FNN. Our findings delineate limitations of the unfolding argument that apply if consciousness arises from temporally extended dynamic neural processes rather than static input-output mappings. This work has implications for various theories of consciousness, and for the fields of computational neuroscience and philosophy of mind more generally, providing new constraints for theories of consciousness.

Neural Dynamics Underlying Repeated Learning of Visual Image Sequences
Humans possess a remarkable ability to recognize visual objects with high fidelity, supported by complex neural mechanisms underlying memory retrieval. Event-related potential (ERP) studies have identified two key neural signatures of recognition memory: the parietal old/new effect and the frontal old/new effect. Despite extensive research on these ERP components, the extent to which these components reflect distinct memory processes remains debated. In the present study, we investigated how repetitive learning modulates these ERP components. Participants repeatedly studied a fixed list of 32 real-world images across up to five study-test repetitions while EEG was recorded. Additionally, a separate set size 1 condition served as a proxy for working memory. Our results showed that with increased repetitions, the parietal old/new effect exhibited enhanced amplitude and earlier peak latency, reflecting more efficient retrieval of well-learned memories. In contrast, the frontal old/new effect remained unchanged in both amplitude and timing. These findings suggest that the parietal old/new effect is a sensitive neural marker of learning-related changes in long-term memory representations, while the frontal effect is less influenced by repetition. Additionally, despite similarly high accuracy between the well-practiced set size 32 condition and the set size 1 working memory condition, both parietal and frontal old/new effects peaked significantly earlier for set size 1, suggesting that access to working memory is substantially faster than even well-practiced long-term memory. Together, our results highlight the unique role of the parietal old/new effect, but not the frontal old/new effect, in repetitive learning, despite both components being important for successful recognition of learnt visual stimuli.

Linking Electrophysiological Metrics to Oxidative Metabolism: Implications for EEG-fMRI Association
Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to study brain function, yet its biophysiological basis remains incompletely understood. Building on our recent work, we investigated how EEG activity and cerebral metabolic rate of oxygen (CMRO2) are related to one another, and how they jointly underpin rs-fMRI metrics. Using a multimodal dataset with macrovascular correction applied to all rs-fMRI metrics, we first examined associations between EEG metrics and CMRO2, then applied mediation analysis to evaluate how CMRO2 mediates EEG-fMRI associations. We found that bandlimited EEG theta and alphafractional power was significantly associated with CMRO2. Bandlimited EEG coherence was also associated with CMRO2 across all the bands. Bandlimited EEG fractional power and coherence were also significantly associated with cerebral blood flow (CBF) and oxygen extraction fraction (OEF) in a manner that varied by frequency. EEG broadband temporal complexity was positively associated with CMRO2; and EEG coherence was negatively associated with OEF. Notably, there are pronounced sex differences in these relationships, which suggests that the biophysical underpinnings of rs-fMRI are sex dependent. Moreover, the baseline metabolic and hemodynamic variables did partially mediate EEG-fMRI associations, with CMRO2 serving as the primary mediator. However, most of the mediations are partial, highlighting the complex interplay among electrophysiological activity, oxidative metabolism, and hemodynamics. This study advances our understanding of the biophysical basis of rs-fMRI and provides a foundation for developing sex-specific diagnostic and therapeutic strategies for neurological disorders.

Feedforward representation of face information in the fusiform face area revealed by VASO 7T layer fMRI
Recognizing faces is a critical cognitive process in social interaction. Face recognition has been extensively studied with functional magnetic resonance imaging (fMRI), ranging from large coverage studies comprehensively examining the entire face pathway to high-resolution laminar-specific (layer) fMRI studies probing feedforward and feedback signals in early visual and face-selective areas during particular face processing. However, it is still unclear which brain region structures face information in the face pathway. To further elucidate this mechanism, we investigated fusiform face area (FFA) during passive face image presentation using a whole-brain vascular space occupancy (VASO) 7T layer fMRI open dataset combined with multi-voxel pattern analysis (MVPA). We analysed lateral occipital cortex (LOC) as a control region and BOLD data in the dataset as a control contrast. We trained multiple binary classification decoders with various image categories (e.g., face vs. others, house vs. others) and three cortical layer groups independently to assess information representation across cortical depths. Our results revealed that decoding accuracies in VASO data peaked in the middle layer of FFA, suggesting feedforward signature specifically during face processing. This effect was not observed in LOC or in decoders for other image categories. These findings indicate that face information is structured prior to processing in the FFA, consistent with previous reports suggesting that face-related features are partially extracted before reaching higher-level face areas. Overall, this study highlights the potential of combining high-specificity VASO layer-fMRI with high-sensitivity MVPA to dissect cortical information flow.

Limited Effects of Isolated Congenital Anosmia on Cerebral White Matter Morphology
Lack of sensory input is associated with alterations in brain morphology; mainly in or near cerebral regions normally devoted to processing of the missing sense. We have in multiple studies demonstrated that the only consistent morphological finding within the gray matter of individuals born without the sense of smell (isolated congenital anosmia; ICA), are changes in or near the olfactory sulcus. For the connecting tissue of the brain, the white matter (WM), previous studies have yielded inconsistent findings. Here, we show that individuals with ICA (n=49) exhibit alterations in WM volume as compared to age- and sex-matched controls. Consistent evidence from both voxel-based morphometry and multi-voxel pattern analysis shows that individuals with ICA show decreased WM in areas surrounding the olfactory sulcus. Importantly, no WM alterations were found in areas surrounding the olfactory (piriform) cortex. In contrast to congenital sensory loss in other systems, we show that morphological alterations due to lifelong olfactory deprivation are limited. Alterations are primarily localized around the olfactory sulcus and likely due to the absence of olfactory bulbs. A possible explanation for the lack of major morphological alterations in individuals with congenital anosmia is that the olfactory regions may be recruited for non-olfactory functions.

Inducible Calling Cards: Developing Mouse Reagents for Experimentally Controlled Transposon Insertion in vivo.
The piggyBac transposase enables robust forward genetic screens in mice. Further, fusions of piggyBac with specific transcription factors (TFs) enables recovery of recoverable transposons (Calling Cards) for recording location of DNA binding events in vitro and in vivo. Such applications would be enhanced by engineering inducible transposases, such that timing of recording could be precisely controlled in vivo, as has been previously developed in vitro. Here, we tested two approaches for applying inducible Calling Cards (iCC) in the murine brain. We engineered knock-ins of inducible versions of two TFs: Jun, an immediate early gene that serves as a proxy for neural activity, and Sp1, a promiscuous binder of CpG unmethylated regions that indicates active promoters. We fused hyperPiggyBac transposase and a tamoxifen-inducible domain (ERT2) to these TFs and tested the system for efficacy and temporal control of insertions, both in vitro and in vivo. Jun-iCC mice developed normally with no behavioral abnormalities, showed tamoxifen-dependent recording, and captured neural activity during pharmacologically induced seizures. Jun-iCC yields relatively low numbers of insertions, likely due to the transient expression of Jun. In contrast, Sp1-iCC provided substantially higher insertion numbers, but transgenic animals exhibited developmental abnormalities, including reduced viability, anophthalmia, and reduced body weight, suggesting that ERT2 domains may sequester Sp1 and thus significantly impact development. Nonetheless, these inducible Calling Cards mouse lines enable drug-inducible integration of transposon cargo into specific loci in the living mouse.