Epilepsy is characterized by widespread structural brain alterations extending beyond the epileptic zone, involving both cortical and subcortical regions. Importantly, the clinical manifestation of epilepsy, including seizure types, psychiatric comorbidities, and treatment responses, has been shown to differ between sexes. However, sex differences in structural alterations in epilepsy have been seldomly reported in neuroimaging studies, partly due to limited sample sizes and single-center designs. Here, we systematically investigated sex differences in common epilepsies and their related clinical variables using structural neuroimaging biomarkers in an international multi-center cohort of 1,253 epilepsy patients and 1,077 healthy controls. We studied cortical thickness and subcortical volume in two types of epilepsy: temporal lobe epilepsy (TLE) and genetic generalized epilepsy (GGE). Both male and female patients with TLE showed widespread cortical and subcortical thinning compared with controls. In GGE, when compared separately to controls, male patients showed only subtle structural alterations, whereas female patients exhibited more widespread structural alterations. Sex-stratified analyses revealed some variation in the extent and distribution of cortical thickness and subcortical volume alterations between male and female patients in both epilepsy cohorts. Yet, we did not find significant sex-by-diagnosis interaction effects in TLE and GGE. Similarly, no significant interaction effects were observed between sex and age of onset or disease duration in either patient group. Overall, although we observed some differences in regional cortical thickness and subcortical volume between male and female patients with epilepsy, we did not find significant sex-by-diagnosis interactions. Our findings indicate that sex differences in behavioral and clinical outcomes of epilepsy may involve biological or functional processes that require further investigation.

Diagnostic MRI evaluation of temporal lobe epilepsy (TLE) depends on the subjective visual interpretation of MRI images. These interpretations could be enhanced by quantitative artificial intelligence (AI) support tools. Humans often make sequential and conditional decisions during their radiological interpretations, such as whether an abnormality is present and, if present, characterizing the abnormality. It is not known whether it is superior to train AI to treat every decision separately in a similar step-wise manner or to train a model holistically on all decisions simultaneously. Here, we analysed three large epilepsy MRI datasets [n = 3676, 2320 people with epilepsy and 1356 healthy controls (HC)] to perform two tasks: (i) establish the presence of a TLE pattern on MRI and (ii) determine TLE pattern lateralization. We compared Step-wise models that independently classify TLE versus HC and lateralize patients as left TLE (L-TLE) or right TLE (R-TLE), against a simultaneous model trained to distinguish all three classes in a single step. To do this, 3D volumetric T1-weighted images were input into an EfficientNetV2 model multiple times to ensure reproducibility of results. Class prediction, model classification confidence and saliency maps were output for interpretability. Step-wise models outperformed the Simultaneous model on both tasks (both Ps < 0.001), with an average ∼2.8% accuracy increase for discriminating HC from TLE and an average 12.7% accuracy increase for distinguishing L-TLE from R-TLE. For both the Step-wise and Simultaneous models, important features discriminating TLE from HC included the known TLE limbic pattern involving the hippocampus, parahippocampal cortical regions, cingulate cortex and lateral temporal regions. However, there was less concordance between the Step-wise and Simultaneous models for the L-TLE versus R-TLE task (all Fisher's Zs > 10.5, Ps < 0.001); the Step-wise model focused less on subcortical regions such as the thalamus and hippocampus and focused more on distributed cortical pathology. Across the two Step-wise models, 95.1% of TLE patients had accurate classifications in either HC versus TLE and/or L-TLE versus R-TLE tasks. These results included 69.6% of patients being both correctly labelled as TLE and lateralized, 13.9% being correctly labelled TLE but lateralized incorrectly and 11.6% being lateralized correctly but not detected as TLE. These findings provide evidence that diagnostic tasks with simpler, Step-wise AI models may enhance diagnostic performance and interpretability in clinical workflows. Future AI clinical support tools can leverage this step-wise approach in the early identification of TLE-related structural patterns, supporting timely diagnosis and treatment decisions.

Dogs can distinguish human facial expressions, particularly happiness, yet brain processes remain unclear. Using fMRI, we conducted two experiments in awake pet dogs. In Experiment 1 (n = 8), happy faces elicited a stronger response than neutral faces in a right temporal cluster extending to the caudate nucleus, including the rostral Sylvian gyrus. In Experiment 2 (n = 12), dogs viewed faces expressing happiness, anger, fear, or sadness. Using the Experiment 1 cluster as a region of interest, a machine-learning classifier distinguished happiness from each negative facial expression, but not between negative pairs, showing differential BOLD responsiveness to happy faces. Whole-brain representational similarity analyses revealed activity patterns differentiating angry vs. fearful faces (right mid ectosylvian and left splenial gyri) and sad vs. fearful faces (right rostral suprasylvian gyrus) but not angry vs. sad faces. This provides direct evidence that dog brains can distinguish between two negative facial expressions. Video abstract

Extensive neuroimaging research in temporal lobe epilepsy with hippocampal sclerosis (TLE-HS) has identified brain atrophy as a disease phenotype. While it is also related to a complex genetic architecture, the transition from genetic risk factors to brain vulnerabilities remains unclear. Using a population-based approach, we examined the associations between epilepsy-related polygenic risk for HS (PRS-HS) and brain structure in healthy developing children, assessed their relation to brain network architecture, and evaluated its correspondence with case-control findings in TLE-HS diagnosed patients relative to healthy individuals. We used genome-wide genotyping and structural T1-weighted MRI of 3826 neurotypical children from the Adolescent Brain Cognitive Development (ABCD) study. Surface-based linear models related PRS-HS to cortical thickness measures, and subsequently contextualized findings with structural and functional network architecture based on epicentre mapping approaches. Imaging-genetic associations were then correlated to atrophy and disease epicentres in 785 patients with TLE-HS relative to 1512 healthy controls aggregated across multiple sites. Higher PRS-HS was associated with decreases in cortical thickness across temporo-parietal as well as fronto-central regions of neurotypical children. These imaging-genetic effects were anchored to the connectivity profiles of distinct functional and structural epicentres. Compared with disease-related alterations from a separate epilepsy cohort, regional and network correlates of PRS-HS strongly mirrored cortical atrophy and disease epicentres observed in patients with TLE-HS and were highly replicable across different studies. Findings were consistent when using statistical models controlling for spatial autocorrelations and robust to variations in analytic methods. Capitalizing on recent imaging-genetic initiatives, our study provides novel insights into the genetic underpinnings of structural alterations in TLE-HS, revealing common morphological and network pathways between genetic vulnerability and disease mechanisms. These signatures offer a foundation for early risk stratification and personalized interventions targeting genetic profiles in epilepsy.

Reading is a fundamental human skill that has been widely studied. While substantial progress has been made in identifying the white matter pathways supporting reading in adults, less is known about the neural substrates underlying reading acquisition in children. Moreover, existing evidence primarily focuses on a small set of languages, thereby raising questions about the generalizability of these findings. In this study, we address this gap by examining the white matter correlates of phonological awareness-a well-established precursor of reading development-in a cohort of monolingual Mexican Spanish-speaking children. Contrary to the classical view that left-lateralized dorsal pathways support phonological awareness, our results reveal that fractional anisotropy in bilateral ventral tracts, but not dorsal tracts, correlates with phonological awareness in this population. These findings challenge the traditional dichotomy between dorsal and ventral stream functions, instead highlighting the flexible and language-dependent nature of the neural mechanisms that support early reading development in children.

Focal cortical dysplasia (FCD) is a leading cause of pharmacoresistant epilepsy in pediatric populations, yet its role in epileptogenesis remains incompletely understood. Recent findings suggest that hyperexcitability may originate in non-dysplastic peripheral areas rather than the malformation itself. However, given the significant variability across FCD cases, clarifying whether cytoarchitectural disorganization drives activity changes remains challenging. Using the carmustine-induced animal model, we investigated how varying degrees of cortical malformation influence neural dynamics. Local field potentials were recorded via multielectrode arrays during spontaneous activity and external perturbation. We introduced a novel metric to quantify spatial heterogeneity in signal organization and assessed its association with excitation-inhibition balance. Results show that alterations in signal structure correlate with the extent and distribution of cortical abnormalities, highlighting the functional relevance of cytoarchitectural variability. This work advances understanding of FCD-related network dysfunction and offers analytical tools with potential translational value for pre-surgical evaluation.

A bstract Objective In temporal lobe epilepsy (TLE), the thalamus acts as a nexus in a pathophysiological network that implicates mesiotemporal, subcortical, and neocortical regions. Studying a large multimodal and multicentre dataset, we profiled thalamic, hippocampal, and neocortical functional connectivity (FC), assessed structural mediators, and examined clinical associations. Methods We studied resting-state FC alongside structural and diffusion MRI data in 250 unilateral TLE patients and 259 healthy controls, with measures aggregated across four independent datasets. Data were processed using open-access neuroinformatics workflows and analyzed at a subregional level to maximize anatomical precision. Statistical analysis and mediation models assessed between-group FC changes, structural contributors, and clinical correlations. Results Compared to controls, TLE patients presented with reduced thalamo-cortical FC, which was most marked in mesiotemporal, fronto-central, and occipital regions. Thalamo-hippocampal FC was also reduced, with effects seen in all CA subfields. In the thalamus, FC reductions peaked in the ventral posterior nucleus when considering neocortical target regions and in the mediodorsal nucleus when considering hippocampal target regions. While ipsilateral hippocampal volume and diffusion changes mediated thalamo-hippocampal FC, thalamo-cortical FC appeared decoupled from structural alterations. Findings were consistent in left and right TLE patients, in patients with short and long disease duration, and across imaging sites, suggesting that thalamo-cortical FC imbalances are a consistent signature of TLE. Conversely, thalamo-hippocampal FC was elevated in patients with focal-to-bilateral-tonic-clonic seizures and FC alterations were more marked in the subgroup of operated patients that became seizure-free after surgery. Conclusion Our multi-site findings demonstrate marked thalamic circuit fragmentation in TLE. Ipsilateral findings robustly showed subdivision-specific effects, which point to both mesiotemporal co-lateralization as well as broader system-level involvement. Mediation analyses furthermore confirmed a key role of hippocampal pathology in disrupted thalamo-hippocampal connectivity in TLE, while broader thalamo-cortical fragmentation becomes increasingly independent of mesiotemporal compromise. Critically, thalamic FC represents a network substrate for seizure generalization and can serve as a prognostic indicator for surgical outcome. These results underscore the contribution of the thalamus as a hub in macroscale dysfunction in TLE.

Objectives Temporal lobe epilepsy (TLE) impacts multiple brain networks. Aberrant functional connectivity has been demonstrated in resting-state networks (RSNs) that mediate higher brain functions in TLE. This study aimed to identify the reproducible patterns of altered functional connectivity in TLE in a large, international cohort through ENIGMA-Epilepsy.Methods Resting-state functional MRI datasets from nine centers across North America, South America, Europe and South Africa, including 442 people with TLE and 387 healthy adults, were analyzed. We examined group differences in whole-brain connectivity in patients compared to controls in seven major RSNs. We also investigated whole-brain connectivity maps for key nodes within the default mode network (DMN). Furthermore, the associations between connectivity patterns and clinical variables were assessed.Results We found lower within-network connectivity scores (13.6% on average) and higher between-network connectivity scores (129% on average) in non-limbic RSN in TLE. This pattern was reproducible across all seven sites and most robust for DMN and visual networks. Patterns of connectivity were not associated with age of seizure onset or disease duration and were mostly similar in patients with left and right TLE with a few exceptions; isolated regions of high connectivity in left TLE and lower connectivity in right TLE compared to controls.Significance We show strong evidence of lower connectivity within most RSNs and higher connectivity outside of these networks that was highly consistent across geographically diverse sites, demonstrating the robustness and generalizability of our findings. The findings demonstrate a consistent disruption of network organization in TLE that may underlie cognitive co-morbidities and seizure propagation patterns observed in this patient population.Plain Language Summary In this international ENIGMA-Epilepsy study, resting-state fMRI data from 442 individuals with TLE showed reduced connectivity within major resting-state networks (about 14% lower) and markedly increased connectivity between networks (about 129% higher), compared to 387 healthy controls. These patterns were highly reproducible across sites. Connectivity alterations were not related to age of onset or disease duration and were largely similar across left and right TLE, aside from small, region-specific differences. Overall, the study demonstrates a robust, widespread reorganization of brain network connectivity in TLE, which may help explain associated cognitive difficulties and seizure spread.

Ferroptosis is a form of non-apoptotic cell death in which iron catalyzes the formation of reactive oxygen species, leading to lipid peroxidation. Experimentally, this process has recently been associated with seizures based on the increased levels of specific markers (4-hydroxynonenal and malondialdehyde) in the brain and plasma. Clinically, iron deposits have been identified in resected tissue from patients with refractory temporal lobe epilepsy. Quantitative susceptibility mapping (QSM) offers an opportunity to detect these accumulations in vivo . In this study, we investigated how pilocarpine-induced status epilepticus contributes to the generation of iron deposits in diverse cerebral regions and whether QSM can detect these deposits longitudinally. We scanned 14 animals (n = 10 experimental; n = 4 control) at five different time points (pre- status epilepticus induction and 1, 7, 14, 21 days post-induction) using QSM. We identified iron deposits in the caudate putamen, hippocampus, thalamus, and primary somatosensory cortex of experimental animals, which is consistent with histological findings. The initial size of the hippocampal iron deposits significantly increased over the following weeks. None of these effects was observed in the control animals. The presence of cerebral iron depositions in an animal model of pilocarpine-induced status epilepticus suggests that ferroptosis may be involved in the onset, development, and progression of spontaneous recurrent seizures. Furthermore, non-invasive, longitudinal in vivo mapping of brain iron deposits could be a potential imaging marker in neurological disorders such as epilepsy. Future experiments will be required to determine the origin of the iron and avoid its progressive accumulation.

Introduction Brain structural differences consistent with an older-appearing brain have been reported in people with epilepsy, but the extent to which these differences reflect clinical characteristics vs broader socioeconomic context is unclear. We investigated whether country-level socioeconomic factors are associated with neuroanatomical differences in adults with epilepsy using MRI-based age prediction, along with epilepsy subtype, sex, and clinical factors. Methods Structural MRI and clinical data were collected from 26 epilepsy centres across 12 countries in the Americas, Australia, Europe, Asia and Africa. MRI-based age estimates were estimated using a previously developed prediction model trained on 29,175 healthy subjects. Brain predicted age difference (BrainPAD) was calculated as the difference between MRI-predicted brain age and chronological age. National gross domestic product (GDP) per capita and income inequality (Gini index) were obtained from the World Bank. Associations between BrainPAD and epilepsy subtype (temporal lobe epilepsy, extratemporal epilepsy, and genetic generalised epilepsy), national socioeconomic context (GDP per capita and Gini index), age and sex were assessed using regression models. Results We analyzed 2,109 individuals with epilepsy and 1,041 healthy non-epilepsy controls (57% female; median age = 35; range 17-83). BrainPAD was higher in epilepsy than controls (β 4.2 years, SE 0.4; t=10.6), with increases ranging from 2.5 to 6 years across subtypes. Male sex was associated with 1 year higher BrainPAD relative to females (SE 0.33, t=3.12). There were no main effects of GDP or Gini index; however, significant interactions between were observed. The effect of epilepsy on BrainPAD was greater in countries with lower GDP per capita (t=-2.74) and higher income inequality (t=2.72). Conclusions Clinical factors and socioeconomic context both influence brain structural ageing in epilepsy. These findings highlight the importance of geographic and economic diversity in neuroimaging research and underscore the relevance of global socioeconomic context when interpreting brain health measures.

Diffusion magnetic resonance imaging (dMRI) is a non-invasive neuroimaging technique that enables in vivo assessment of white matter microstructure and is highly sensitive to tissue alterations associated with disease. Although substantial evidence links diffusion-derived metrics to underlying white matter tissue properties, the presence of complex within-voxel axonal configurations complicates their biological interpretation. Several methods have been proposed to assess diffusion properties of individual crossing axonal populations, but their validation and clinical applicability remain limited. Glaucoma, the second leading cause of blindness worldwide, is characterized by progressive loss of retinal ganglion cells and axonal damage in the optic nerve, leading to degeneration along the entire visual pathway. This degeneration includes secondary effects on fiber crossings within the optic chiasm, which are challenging to characterize with conventional diffusion methods. Here, we evaluated whether advanced diffusion metrics can detect microstructural alterations in these complex white matter configurations and whether these measures correlate with clinical markers of glaucoma severity. In this study, we evaluated 31 patients with asymmetric glaucoma and 31 healthy controls using advanced diffusion magnetic resonance imaging methods, including Diffusion Tensor Imaging, Constrained Spherical Deconvolution, multi-tensor fit via Multi-Resolution Discrete Search method, and Fixel-Based Analysis. We found significant differences of diffusion metrics in white matter tracts of the visual system, including the optic nerve, optic chiasm, optic tracts, and optic radiations. Moreover, diffusion metrics correlated with clinical ophthalmological parameters such as cup-to-disc ratio, visual field mean deviation, and retinal nerve fiber layer thickness. These findings support the use of advanced diffusion magnetic resonance imaging models as sensitive tools for detecting Wallerian degeneration and resolving complex white matter architecture in the human visual pathway, and demonstrate their utility to study other fiber-crossing regions throughout the brain.

Abstract Resting-state functional magnetic resonance imaging (MRI) studies have reported abnormal intrinsic functional connectivity (FC) across distributed circuits in patients with temporal lobe epilepsy (TLE), indicating a system-level impact of the disorder. However, findings remain inconsistent due to limited sample sizes and methodological heterogeneity, leaving the structural determinants and clinical relevance of FC alterations unresolved. To identify a robust and reproducible FC signature, we conducted a data-driven, connectome-wide mega-analysis in a large multicentre cohort of 652 participants (297 TLE, 73 disease controls, and 282 healthy controls) with multimodal 3T MRI and deep clinical phenotyping. We identified convergent FC reconfigurations at both group and individual levels that preferentially involved densely connected hubs, manifesting as hyperconnectivity in frontoparietal association systems and hypoconnectivity in temporal and paralimbic systems. Integrating structural cortical wiring features further revealed that these extensive alterations were constrained by corticocortical proximity, microstructural similarity, and white matter connectivity. Clinically, the FC phenotype tracked symptom burden and disease progression, informed postsurgical seizure outcome, and distinguished TLE from other focal epilepsies. Collectively, these findings systematically delineate a neurobiologically grounded, hub-centric pattern of intrinsic network disruption in TLE, anchored in temporolimbic and adjacent transmodal systems, with potential utility for individualized phenotypic stratification and outcome prognostication.

The superficial white matter (SWM), immediately beneath the cortical mantle, is thought to play a major role in cortico-cortical connectivity as well as large-scale brain function. Yet, this compartment remains rarely studied due to its complex organization. Our objectives were to develop and disseminate a robust computational framework to study SWM organization based on 3D histology and high-field 7T MRI. Using data from the BigBrain and Ahead 3D histology initiatives, we first interrogated variations in cell staining intensities across different cortical regions and different SWM depths. These findings were then translated to in vivo 7T quantitative myelin-sensitive MRI, including T1 relaxometry (T1 map) and magnetization transfer saturation (MTsat). As indicated by the statistical moments of the SWM intensity profiles, the first 2 mm below the cortico-subcortical boundary were characterized by high structural complexity. We quantified SWM microstructural variation using a nonlinear dimensionality reduction method and examined the relationship of the resulting microstructural gradients with indices of cortical geometry, as well as structural and functional connectivity. Our results showed correlations between SWM microstructural gradients, as well as curvature and cortico-cortical functional connectivity. Our study provides novel insights into the organization of SWM in the human brain and underscores the potential of SWM mapping to advance fundamental and applied neuroscience research.

Cortical dysplasias are malformations of cortical development characterized by disorganization of the cyto- and myeloarchitecture of the neocortex. They are a common cause of epilepsy and their diagnosis through conventional imaging can often be challenging, hindering surgical treatments. Diffusion-weighted magnetic resonance imaging (dMRI) has the ability to infer tissue properties at the microscopic scale, making it a promising technique for detection of cortical dysplasias. This study aims to assess the microarchitecture of the cerebral cortex in a murine model of cortical dysplasia using dMRI acquired with b-tensor encoding. Pregnant Sprague-Dawley rats were administered either carmustine (BCNU) or saline solution on day 15 of gestation. Their offspring were imaged at 120 days of age using a 7 tesla scanner, acquiring diffusion-sensitive images with b-tensor encoding. Images were processed with Q-space trajectory imaging with positivity constraints (QTI+) to derive various metrics along a curvilinear coordinate system across the neocortex. After scanning, the brains were processed for immunofluorescence and histological examinations. Experimental animals exhibited a significant reduction of microscopic fractional anisotropy (µFA) and anisotropic kurtosis (Kshear) in the middle and lateral cortical layers compared to the control animals. Immunofluorescence and histological analysis showed decreased and dysorganized myelinated fibers, and an increase of glial processes in BCNU-treated animals. Given the applicability of b-tensor encoding in clinical scanners, this approach holds promise for improving detection of focal cortical dysplasias in patients with epilepsy.

Iron accumulations have been identified in resected tissue from patients with refractory temporal lobe epilepsy. These deposits are linked to ferroptosis, a form of nonapoptotic cell death in which iron catalyzes the formation of reactive oxygen species, leading to lipid peroxidation. Experimentally, this process has recently been associated with seizures based on the increased levels of specific markers (4-hydroxynonenal and malondialdehyde) in the brain and plasma. Quantitative susceptibility mapping (QSM) offers an opportunity to detect the iron accumulations in vivo. In this study, we investigated how pilocarpine-induced status epilepticus contributes to the generation of iron deposits in diverse cerebral regions and whether QSM can detect these deposits longitudinally. We scanned 14 animals (n = 10 experimental and n = 4 control) at five different time points (pre-status epilepticus induction and 1, 7, 14, 21 days postinduction) using QSM. We identified iron deposits in the caudate putamen, hippocampus, thalamus, and primary somatosensory cortex of experimental animals, which is consistent with histological findings. The initial size of the hippocampal iron deposits significantly increased over the following weeks. None of these effects was observed in the control animals. The presence of cerebral iron depositions in epilepsy-related brain structures suggests that they could be involved in the onset, development, and progression of spontaneous recurrent seizures. Furthermore, noninvasive, longitudinal in vivo mapping of brain iron deposits could be a potential imaging marker in neurological disorders such as epilepsy. Future experiments will be required to determine the origin of the iron and avoid its progressive accumulation.

The neocortex is a highly organized structure, with region-specific spatial patterns of cells and fibers constituting cyto- and myelo-architecture, respectively. These architectural features are modulated during neurodevelopment, aging, and disease. While invasive techniques have contributed significantly to our understanding of cortical patterning, the task remains challenging through non-invasive methods. Structural magnetic resonance imaging (MRI) has advanced to improve sensitivity in identifying cortical features, yet most methods focus on capturing macrostructural characteristics, often overlooking critical microscale components. Diffusion-weighted MRI (dMRI) offers an opportunity to extract quantitative information reflecting microstructural changes. Here we investigate how different dMRI modalities contribute to the detection of microstructural characteristics and whether per-bundle approaches can disentangle characteristics related to the orientational organization of the myelo- and cyto-architecture in an animal model of cortical dysplasia, a malformation of cortical development. We scanned 32 animals (n=16 experimental; n=16 control) at four different time points (30, 60, 120, and 150 post-natal days) using both structural and multi-shell dMRI. All dMRI metrics were sampled using a 2D curvilinear system of coordinates as a common anatomical descriptor across animals. Per-bundle metrics were labeled according to their orientation with respect to the cortical surface, and analyzed separately. Experimental animals showed diffusion abnormalities of the tangential and radial fiber components in deeper cortical areas, consistent with histological findings of neuronal and fiber disorganization. The ability of dMRI to detect abnormalities in an animal model of cortical dysplasia is indicative of the clinical potential of advanced dMRI methods to study cortical microstructure in neurological disorders.

PURPOSE:We aimed to evaluate longitudinal structural and metabolic changes after induced status epilepticus (SE) in the pilocarpine model of TLE, over the three phases of epileptogenesis. METHODS:We analyzed 48 male eight-week-old Wistar rats assigned to sham-control and SE-induced groups. T2-weighted images and 1H-MR spectra were acquired using a 3 T MRI clinical scanner (Philips Achieva) equipped with an animal coil. We measured hippocampal volumes (dorsal-HVol) and total N-acetylaspartate ratios to total creatine (tNAA/tCr) in four points in time (MRI-scan): baseline (before pilocarpine or sham treatments), 48 h (acute phase), 15 days (silent period), and 30 days (beginning of the chronic phase) after experimental treatment. To test differences in dorsal-HVol and hippocampal tNAA/tCr we built generalized linear mixed effects models including groups (pilo-SE and control) and MRI-scan as main effects and a group*MRI-scan interaction. RESULTS:Pilo-SE and control animals showed similar baseline dorsal-HVol and hippocampal tNAA/tCr (both p > 0.1). Pilo-SE showed reduced dorsal-HVol and tNAA/tCr at all MRI-scans (all p < 0.001) when compared to controls. Intragroup analysis revealed that dorsal-HVol and tNAA/tCr significantly increased at 15- and 30-days (all p < 0.001) when compared to 48 h, although remaining lower than the baseline scan. There were no changes over time in sham-controls (all p > 0.4). CONCLUSIONS:The novelty of our study was to analyze non-invasively structural and metabolic markers of hippocampal dysfunction across the three main phases of pilocarpine-induced epileptogenesis in comparison to the typical brain development over the same period. Acute dorsal hippocampal volume loss and hippocampal neuronal dysfunction are present as early as 48 h post-pilocarpine-induced SE, dynamically changing over time. This acute damage is followed by a pattern of gradual recovery throughout the silent and chronic phases of epileptogenesis, though with an offset for the pilo-SE group. A better understanding of the course of noninvasive markers of epileptogenesis and HS may contribute to stablish surrogate endpoints in interventions to treat or prevent focal epilepsy.

Cocaine use disorder (CUD) detrimentally impacts personal health, social relationships, and economic opportunity. Here, we assess CUD-associated shifts in brain dynamics using Network Control Theory and examine how they align with previously identified changes in neurological systems and behavioral profiles of people with CUD. The SUDMEX CONN dataset consists of multi-modal MRI, cocaine use metrics, behavioral measures, and demographics of individuals with CUD (N=132, 71 CUD). We identified recurring brain activity states and used NCT to calculate the transition energy (TE) between pairs of states. ANCOVAs examined global and regional TE associations with drug use group (CUD vs controls (NC)), years of CUD, and risk-taking behaviors. We identified potential mechanisms driving the differences by correlating CUD-related regional TE effects with neurotransmitter/receptor systems. People with CUD had significantly lower global TE and default mode, dorsal attention and limbic network TE compared to non-user controls, particularly in regions enriched for noradrenaline and mu opioid receptors. Longer duration of CUD was associated with more decreased global TE, top-down TE, default mode, control and ventral attention network TE, and regional TE enriched for excitatory neurotransmitters and receptors. People with CUD needed to expend more global and top-down TE to perform better on a risk-taking task (the Iowa Gambling task), an effect which was not found in NCs. Our analysis of whole-brain activity dynamics provides a link between the effects of upstream glutamatergic excitotoxicity and/or opioid receptor dysfunction, and downstream weakening of inhibitory control that is central to CUD. ### Competing Interest Statement The authors have declared no competing interest.

Current treatments fail to prevent long-term consequences induced by a severe traumatic brain injury (TBI). This study aimed to evaluate the efficacy of repetitive intranasal administration of NeuroEPO (a derivative of erythropoietin) on long-term alterations after a severe TBI induced by the application of a lateral fluid percussion in male rats. A otal of 30-31 days after the trauma, TBI+vehicle group showed sensorimotor dysfunction (Neuroscore, p < 0.0009; beam walking test, p < 0.0001 vs. Sham+vehicle group) and depressive-like behavior suggested by increased immobility (p = 0.0009 vs. baseline) during the forced swim test. Rats also showed increased production of malondialdehyde (a marker of oxidative damage), increased catalase activity (an antioxidant enzyme), and atrophy of brain areas evaluated with Magnetic Resonance Imaging 31 days after the trauma. TBI+NeuroEPO group received intranasal administration of NeuroEPO (0.136 mg/kg) starting 3 h post-TBI and continued every 8 h for four days. This group showed less sensorimotor dysfunction (Neuroscore, p = 0.020; beam walking test, p = 0.001, vs. TBI+vehicle group) and normal immobility behavior (p = 0.998 vs. Sham+vehicle group). Levels of malondialdehyde and catalase as well as the volume of brain structures of this group were like the Sham+vehicle group. These findings support the potential of NeuroEPO as a therapeutic agent to reduce long-term consequences of TBI.

The superficial white matter (SWM), immediately beneath the cortical mantle, is thought to play a major role in cortico-cortical connectivity as well as large-scale brain function. Yet, this compartment remains rarely studied due to its complex organization. Our objectives were to develop and disseminate a robust computational framework to study SWM organization based on 3D histology and high-field 7T MRI. Using data from the BigBrain and Ahead 3D histology initiatives, we first interrogated variations in cell staining intensities across different cortical regions and different SWM depths. These findings were then translated to in-vivo 7T quantitative myelin-sensitive MRI, including T1 relaxometry (T1 map) and magnetization transfer saturation (MTsat). As indicated by the statistical moments of the SWM intensity profiles, the first 2 mm below the cortico-subcortical boundary were characterized by high structural complexity. We quantified SWM microstructural variation using a non-linear dimensionality reduction method and examined the relationship of the resulting microstructural gradients with indices of cortical geometry, as well as structural and functional connectivity. Our results showed correlations between SWM microstructural gradients, as well as curvature and cortico-cortical functional connectivity. Our study provides novel insights into the organization of SWM in the human brain and underscores the potential of SWM mapping to advance fundamental and applied neuroscience research. Highlights ### Competing Interest Statement The authors have declared no competing interest. * SWM : Superficial white matter MRI : Magnetic resonance imaging T1 map : T1 relaxometry MTsat : Magnetization transfer saturation GM : Gray matter WM : White matter