Biology subjects

Bernhardt, B.

Publications and source records attributed to Bernhardt, B..

At least 19 recordsLinked to original sources

bioRxiv2026

EigenBrain maps cortical molecular architecture from functional, geometric, and structural eigenmodes

Neurotransmitter receptor and transporter distributions shape neural communication across the cortex and underpin mechanistic interpretations of brain function. Magnetic resonance imaging (MRI)-derived eigenmodes, low-dimensional spatial patterns that capture the principal axes of cortical organization, are increasingly used to reconstruct brain maps and offer a potential route to approximating molecular topographies in large cohorts where direct measurements are unavailable. Yet whether the type of MRI data used to derive these eigenmodes determines which receptor and transporter distributions can be approximated, and which molecular systems are accessible through this approach at all, remains unknown. Using a spatial reconstruction framework applied to 23 molecular systems spanning neurotransmitter, metabolic, and pathological markers, we show that eight receptor and transporter maps, spanning serotonin, dopamine, histamine, cholinergic, and opioid markers, can be selectively approximated from functional eigenmodes but not structural or geometric ones. This selectivity also reveals that functional brain organization encodes a specific subset of neuromodulatory topographies that structural and geometric organization does not. To illustrate translational potential in clinical cohorts where molecular imaging is unavailable, we applied individual-level eigenmode decompositions of MRI data projected onto the eight validated molecular systems and detected cross-sectional differences in autism and longitudinal changes in schizophrenia. Together, these findings reveal a difference in how geometric, structural, and functional brain organization relate to molecular architecture, offering a method for approximating validated molecular profiles in population neuroimaging cohorts that lack direct molecular imaging.

neuroscience↗

bioRxiv2026

Brain-thought states during movie-watching reflect shared sensory anchors and film- and person- specific processes in association cortex

Naturalistic paradigms such as movie-watching have transformed functional neuroimaging by capturing cognitive dynamics during rich, real-world experiences. A fundamental challenge, however, is determining whether the neural signatures identified during these experiences reflect general principles of cognition or the specific contexts in which they are measured. To address this question, we combined fMRI data from participants watching eight diverse films with continuous reports of ongoing thought. We found that the generalizability of brain-thought relationships depends on the cognitive process being recruited. Neural signatures linked to sensory processing remained robust across films, whereas those involving memory-related association networks depended on how we modelled between-film variability, indicating that cognition becomes increasingly context-dependent along the cortical hierarchy from sensory to association cortex. Within default and limbic networks, we identified two contrasting memory-related states with opposite consequences for comprehension. One, reflecting the integration of prior knowledge with ongoing experience, predicted better narrative comprehension and was revealed only after accounting for between-film variability. The other, associated with stimulus-independent thought, predicted poorer comprehension and emerged only when between-film variability was not modelled. Together, these findings establish when brain-experience relationships measured during naturalistic paradigms can generalize across contexts and when they instead reflect interactions between cognition and the specific environments in which cognition unfolds. More broadly, the consistency of a given brain-experiential association may depend less on where it occurs in the brain and more on the viewer's contextual experience: perceiving the film, drawing on memory to understand it, or drifting away.

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bioRxiv2026

Assessing the Functional-Structural Reorganization of Connector Hubs in Temporal Lobe Epilepsy

Temporal lobe epilepsy (TLE) is associated with altered functional connectivity, yet its effects on connector hubs, regions supporting long-range and inter-network communication, remain poorly understood. We used SParsity-based Analysis of Reliable k-hubness to characterize connector hub reorganization in unilateral TLE compared with healthy controls. Patients exhibited significant widespread reductions in k-hubness involving the occipital, cingulate, and precuneus regions, ipsilateral hippocampus, and the bilateral pallidum. Compared to the distribution of k-hubness in healthy controls, the hub disruption index revealed rapid loss of k-hubness alongside emergence of new hubs in contralateral homologous regions. To investigate microstructural substrates of these functional changes, apparent diffusion coefficient and fractional anisotropy from diffusion magnetic resonance imaging were examined. The strongest associations with k-hubness were observed in subcortical structures and the hippocampus. These findings demonstrate that TLE is characterized by widespread, asymmetric connector hub reorganization extending beyond the epileptogenic temporal lobe, revealing distinct patterns of network disruption and reorganization across the brain.

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bioRxiv2026

The balance of local and distributed excitation shapes brain stability and reflects aging- and Alzheimer's disease-related alterations

Human brain function emerges from the interplay between recurrent local activity and distributed inter-regional interactions. However, a biologically interpretable framework for quantifying this balance between the two factors at the whole-brain level remains lacking. Here, we extended an established biophysical model to quantify inter-regional excitation and newly introduced the recurrent ratio (R-ratio), a measure of the relative balance between intra- and inter-regional excitation. Dynamical analyses showed that an optimal R-ratio supports a trade-off between network stability and flexibility. Applying this framework to healthy aging and Alzheimer's disease revealed progressively increased R-ratios with advancing age and disease severity. In healthy individuals, higher R-ratios were associated with age-related alterations in brain morphology, molecular pathology, and cognitive function, whereas Alzheimer's disease was characterized by increased R-ratios accompanied by reduced dynamical persistence. Together, these findings establish the R-ratio as a biologically interpretable marker of whole-brain excitation balance and demonstrate its utility for linking biophysical mechanisms with large-scale brain dynamics, aging, and neurodegeneration.

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bioRxiv2026

HIPPOCAMPAL TAU RELATED SIGNAL INDEXES HYPEREXCITABILITY AND NREM SLEEP MEMORY DYSFUNCTION IN TEMPORAL LOBE EPILEPSY

Background Sleep and memory disturbances are common in temporal lobe epilepsy (TLE), yet their relationship with tau-targeted neuroimaging measures remains unclear. We investigated whether in-vivo temporal 18F-MK6240 tracer retention relates to seizure burden, non-rapid eye movement (NREM) sleep microstructure, and memory performance in TLE. Methods This cross-sectional study was conducted from 2019 to 2024 at the Montreal Neurological Institute-Hospital. Eligible patients had unilateral TLE diagnosed according to International League Against Epilepsy criteria and underwent overnight electroencephalography (EEG) recordings, research-protocol 3T magnetic resonance imaging, and 18F-MK6240 positron emission tomography. Regional 18F-MK6240 standardized uptake value ratios (SUVRs), using the cerebellum as the reference region, were quantified in the ipsilateral hippocampus (defined a priori as the primary region of interest), as well as in peri-hippocampal and lateral temporal regions. Electroclinical and neuropsychological measures, including seizure burden (high vs low), N2 interictal epileptiform discharge frequency (frequent vs non-frequent), and memory performance (impaired vs intact), were classified according to predefined clinical criteria. N2 spindle rate and N3 slow-wave rate were quantified from overnight EEG recordings. Findings Of 70 eligible patients, 25 were included (eight [32%] females; mean age 35.2 years [SD 12.1]). Higher ipsilateral hippocampal 18F-MK6240 uptake was observed in participants with greater focal seizure burden (median [IQR] 0.70 [0.67-0.78] vs 0.64 [0.58-0.65], rank-biserial correlation=-0.58, 95% CI -0.82 to -0.19; p=0.02), was associated with lower N2 spindle rate (r=-0.42, 95% CI -0.70 to -0.03; p=0.04) and higher N3 slow-wave rate (r=0.47; 95% CI 0.09 to 0.73; p=0.02), and was also higher in participants with impaired than intact memory performance (n=21; mean [SD] 0.80 [0.12] vs 0.68 [0.10], Cohen's d=1.15, 95% CI 0.07 to 2.21; p=0.04). Associations outside the hippocampus were generally less consistent and less precise, with the largest non-hippocampal estimate observed in peri-hippocampal regions. Interpretation Higher hippocampal 18F-MK6240 uptake was associated with greater focal seizure burden, altered NREM sleep microstructure, and impaired memory performance in TLE. These findings suggest that hippocampal 18F-MK6240 uptake may represent a candidate marker of circuit vulnerability associated with NREM sleep-memory dysfunction in TLE, warranting validation in larger longitudinal studies.

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bioRxiv2026

Thalamocortical orchestration of human theory of mind

Reasoning about others thoughts or beliefs is central to human social behavior. This ability, known as theory of mind (ToM), has been primarily attributed to cortical regions of the default network (DN). However, whether and how subcortical structures, particularly the thalamus, contribute to this high-level computation remains unknown. Here, we investigated human thalamocortical dynamics during a naturalistic ToM movie watching condition, taking a rare dual-modality approach by combining high-field 7T fMRI and intracranial stereoelectroencephalography (sEEG). Across both modalities, ToM events reliably activated the DN, whereas the thalamus lacked canonical local activation. Despite this absence of local activation, the thalamus shared ToM-related representational structure and exhibited enhanced bidirectional interactions with the DN during mentalizing across methods. Crucially, sEEG revealed that the thalamus coordinated DN activity via cross-frequency phase-amplitude coupling (PAC), whereby thalamic low-frequency phase unidirectionally modulated DN high-frequency activity. Furthermore, the strength of thalamic-DN PAC predicted both the activity magnitude and the representational quality of ToM-related information within the dorsomedial DN subsystem. Together, these findings identify the human thalamus as a regulatory hub that gates DN computations during ToM without exhibiting observable localized activity, revealing a previously unrecognized mechanism by which thalamic dynamics coordinate high-level social cognition in humans.

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bioRxiv2026

Distinct spatial associations of adversity with hippocampal macro- and microstructure in early adolescence

Youth adversity has been associated with alterations in hippocampal structure; however, it remains unclear whether different forms of adversity relate distinctly to its organization across the anterior-posterior and proximal-distal axes. Here, we investigated the associations of different types of adversity with multiple structural properties of the hippocampus in 5,263 early adolescents from the ABCD Study. Hippocampal macrostructure was characterized using volume, thickness, and gyrification, whereas T1w/T2w ratio served as an in vivo proxy for microstructure. Adversity was assessed at the family level using questionnaires on family environment and parenting, and at the socioeconomic level using income-to-needs ratio and neighborhood disadvantage measured by the Area Deprivation Index. Associations were examined for each adversity type separately in multi-variate analyses and for cumulative adversity exposure in univariate models. Hippocampal features were obtained using HippUnfold, an advanced automatic segmentation approach that accounts for interindividual folding variability, and were analyzed globally as well as across the hippocampal anterior-posterior and proximal-distal axes. Socioeconomic measures showed widespread associations with hippocampal macrostructure across the whole hippocampus and both anatomical axes, whereas associations with T1w/T2w ratio were limited and observed only for neighborhood disadvantage along the anterior-posterior axis. Cumulative adversity exposure was consistently associated with alterations in CA1 and subiculum across volume, thickness, and gyrification, but not T1w/T2w ratio. Together, these findings suggest that different types of adversity exhibit distinct spatial associations across complementary hippocampal macro- and microstructural features, highlighting regional variation in the susceptibility of the developing hippocampus to environmental adversity.

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bioRxiv2026

FUNCTIONAL FRAGMENTATION AND STRUCTURAL DRIVERS OF THALAMO-CORTICAL CIRCUITS IN TEMPORAL LOBE EPILEPSY

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSObjectiveC_ST_ABSIn 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. MethodsWe 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. ResultsCompared 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. ConclusionOur 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.

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bioRxiv2026

Selective convergence and graded divergence of hippocampal and amygdala subregions using functional connectivity

The hippocampus and amygdala are neighboring medial temporal lobe structures linked to memory and affect, yet how their subregions are jointly embedded within distributed isocortical systems remains unclear. Using resting-state fMRI from 722 Human Connectome Project Young Adult participants, we mapped hippocampal and amygdalar subregions within a unified cortex-wide framework, quantifying subregion-to-cortex connectivity via Pearson correlation (broad co-fluctuation) and GLASSO partial correlation (relatively more direct functional association). We introduced two count-based metrics: dominance (relative hippocampal vs. amygdalar representation) and sharedness (balanced co-representation). Direct associations showed both structures sharing coupling with paralimbic areas and, more modestly, default mode regions, while broader co-fluctuations extended into somatomotor and paralimbic networks. Divergence patterns depended on the estimator: hippocampal subregions preferentially coupled with default-mode and visual networks under direct association, while amygdalar nuclei favored ventral attention and limbic networks; broader co-fluctuations additionally implicated somatomotor cortex for amygdala and visual cortex for hippocampus. These principles held at the subfield/nucleus level, varying along the hippocampal long axis and identifying the paralaminar nucleus as the most hippocampus-like amygdalar subregion. Data-driven connectivity gradients confirmed both systems separation and fine-scale interdigitation. Hippocampal and amygdalar subregions are thus embedded in cortex not as discrete systems, but through structured, spatially organized co-representation.

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bioRxiv2026

Pathology in resected areas of FDG PET hypometabolism in pediatric epilepsy patients with focal cortical dysplasia

Introduction[18F]fluorodeoxyglucose positron emission tomography (FDG-PET) frequently reveals hypometabolism extending beyond the epileptogenic zone in focal cortical dysplasia (FCD). However, it is unclear whether these peripheral hypometabolic areas harbour pathological cells potentially contributing to seizure generation. This study characterized histopathology in the lesion epicentre vs borders of the FDG-PET hypometabolism-informed resections in pediatric patients undergoing epilepsy surgery. MethodsFourteen children with intractable, extra-temporal focal epilepsy (mean age 9.0{+/-}5.0 years; 9 female) were retrospectively reviewed. FDG-PET contributed significantly to surgical planning in all cases, with the resection encompassing the visually-apparent MRI signal abnormalities as well as areas of surrounding hypometabolism when safely feasible. Multiple pathological specimens were obtained from the epicentre and surrounding hypometabolic areas. Overall, 136 specimens were analyzed: 64 epicentre (mean 4.6{+/-}3.2/patient) and 72 border (mean 5.1{+/-}3.5/patient). ResultsPathology was identified in 75% of epicentre specimens (59% with frank FCD (fFCD) IIa/b, 16% with dysmorphic neurons only (DNO)). Border specimens showed pathology in 62% (31% fFCD IIa/b, 31% DNO). We fitted a Bayesian logistic mixed model with pathology as outcome variable, location as predictor, and subject as a random effect. Compared to negative pathology, the log-odds of fFCD in the epicentre was 1.00 (confidence interval (CI) 0.32, 1.77) and -1.25 in the border (CI -2.17, -0.40). The log-odds of DNO vs negative pathology was non-significant in both locations. All patients achieved Engel Ia status at one-year follow-up with no long-term neurological deficits. ConclusionThese findings suggest a gradient of histopathology, with fFCD concentrated in the epicentre and DNO present in both the epicentre and hypometabolic borders. Thus, FDG-PET may be used to better detect the histopathological borders of FCD type II, and the high seizure-freedom rate presented here supports the inclusion of these surrounding hypometabolic regions in the surgical resection (when safe to do so), potentially improving the likelihood of removing epileptogenic cells. Key PointsO_LIPathological cells are present not only in the MRI signal abnormality in FCD but also in the periphery of the FDG-PET hypometabolism. C_LIO_LIWe observe a gradient of histopathology, with frank FCD concentrated in the epicentre and dysmorphic neurons spread throughout the area of hypometabolism. C_LIO_LIMaximal safe resection of the area of hypometabolism may increase likelihood of removing epileptogenic cells, thus improving surgical outcome. C_LI

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bioRxiv2026

Precision mapping and molecular contextualization of surgical outcome epicenters in temporal lobe epilepsy

AO_SCPLOWBSTRACTC_SCPLOWTemporal lobe epilepsy is the most common drug-resistant epilepsy, with surgical resection offering the primary path to seizure freedom. Despite standardized approaches, a substantial proportion of patients experience seizure recurrence, and the neurobiological substrates underlying these divergent outcomes remain unclear. We applied an individualized normative modeling framework to multimodal preoperative MRI data in a group that subsequently underwent surgical resection, to characterize patient-specific structural deviations and identify disease epicenters. Patients who became seizure-free exhibited spatially coherent abnormalities localized to the hippocampus and ipsilateral association regions, anchored in agranular limbic territories and enriched for genes linked to calcium-dependent signaling. Non-seizure-free patients, on the other hand, showed a more heterogeneous and distributed pattern of deviations, consistent with a "temporal-plus" network organization, and broader neuromodulatory dysregulation. Crucially, overlap between resected tissue and network-defined epicenters was closely associated with seizure freedom, independent of total resection volume. These findings provide a multiscale framework for precision surgical planning, shifting the focus from standardized tissue removal to targeted disconnection of patient-specific pathological hubs.

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bioRxiv2026

Hierarchical Signatures of Language in the Human Brain

Language relies on a hierarchy of sensory and cognitive processes, yet how different levels of this hierarchy are supported by distinct neural architectures remains unclear. Here we show that semantic processing, compared with phonological processing, is associated with higher-level brain networks, as characterized by resting-state fMRI connectivity, in vivo measures of cortical myelin, and cortical types derived from a cytoarchitecture-defined reference atlas. These relationships were established using individualized ultra-high field fMRI in both English and French speakers leveraging a multi-session, multi-modal 7T MRI protocol including a language localizer. For comparison, we developed an artificial neural network, in which a representational hierarchy spontaneously emerged where phonological information was captured in earlier layers and semantic information in later layers. By integrating individualized functional mapping, neuroanatomical characterization and artificial intelligence, this study advances understanding of the neural basis of language and provides a framework for linking biological and artificial systems of communication. Significance StatementLanguage is widely described as hierarchical, yet how this functional organization is implemented in the brains biological architecture remains unclear. By combining ultra-high field, individualized neuroimaging with in vivo measures of cortical microstructure and large-scale connectivity, this study establishes a framework for linking distinct levels of linguistic computation to the brains structural and functional organization. Integrating these findings with artificial neural network modeling further reveals shared principles between biological and machine systems. Together, this work advances a biologically grounded account of language, bridges cognitive neuroscience and artificial intelligence, and provides a roadmap for understanding how complex cognition emerges from structured brain architecture.

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bioRxiv2025

The Hemodynamic Response Function Varies Across Anatomical Location and Pathology in the Epileptic Brain

The hemodynamic response function (HRF) links neuronal activity to functional magnetic resonance imaging (fMRI) signals. While most fMRI studies use a "canonical" HRF, increasing evidence from studies of healthy subjects suggests that the HRF depends on anatomical location and disease states. Here, we investigate how HRF variability relates to anatomical location and pathology in the epileptic brain, using a large simultaneous electroencephalogram and fMRI dataset. Applying HRF deconvolution and temporal decomposition, we built the first whole-brain HRF library specific to epilepsy, identifying four distinct shape groups. We mapped HRF features across parcellations of two atlases using novel Bayesian hierarchical models. In non-epileptogenic regions, HRF shape and spatial distributions align with findings from healthy subjects. Within pathological regions, they vary significantly according to pathology. Our results indicate that HRF variability is associated with pathology, in addition to its dependence on anatomical location, motivating region- and pathology-based HRF modulation in epilepsy studies.

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bioRxiv2025

Memory network activity flow failures in temporal and frontal lobe epilepsy

Declarative memory deficits represent considerable challenges to adequate functioning and wellbeing in temporal lobe epilepsy (TLE) and frontal lobe epilepsy (FLE), two of the most common pharmaco-resistant epilepsies. TLE and FLE are impacted differently however, with TLE affecting primarily episodic, and mildly semantic memory, while FLE presenting with overall lesser declarative impairments and a greater involvement of language processes. Although functional magnetic resonance imaging (fMRI) studies are overall compatible with differential disruptions of medial temporal and fronto-limbic networks in both syndromes, direct comparisons of brain activity and connectivity remain scarce. The current study investigated how alterations in intrinsic functional brain organization, as mapped with resting-state connectivity (rsFC), shapes altered brain network activations in both episodic and semantic memory states. To this end, we acquired task- and rs-fMRI data in 28 TLE patients and 17 FLE patients and 87 age- and sex-matched healthy controls (HCs). We used activity flow mapping (AFM), a generative machine learning technique that derives plausible task activation patterns via individualized rsFC as well as normative task activation data. Previous studies in HC as well as patient populations have shown that this technique has been effective in identifying mechanisms contributing to atypical functional organization across different context. Overall, AFM reliably predicted task activations across HC, TLE, and FLE, but prediction accuracy was consistently reduced in both patient groups, indicating impaired propagation of task-relevant signals. These reductions co-occurred with abnormal episodic and semantic task activation patterns, atypical rsFC, and behavioral profiles marked by preserved semantic but impaired episodic memory performance in both patient groups. Importantly, although neither task-evoked abnormalities nor rsFC disruptions alone were associated with clinical variables, lower AFM accuracy in patients robustly tracked poorer episodic and semantic memory performance and longer disease duration. Prediction accuracy was driven more by intrinsic functional than structural network features, suggesting that altered network communication, rather than gross anatomy, constrains AFM in pharmaco-resistant epilepsy. Our work revealed syndrome-specific yet convergent disruptions in paralimbic and heteromodal association systems, linking intrinsic dysconnectivity to a shared episodic vulnerability and semantic resilience across TLE and FLE. By modelling how intrinsic connectivity shapes task-evoked responses, AFM provides a mechanistic account of imbalanced memory-state activations and isolates network-flow pathways as targets for intervention and rehabilitation.

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bioRxiv2025

The use of Artificial Intelligence in Magnetic Resonance Imaging of Epilepsy: A Systematic Review and Meta-Analysis

BackgroundThe application of artificial intelligence (AI)/machine learning (ML) to MRI can be a powerful tool to streamline clinical decision-making, yet variability amongst MRI sequences and algorithms have hindered appropriate assessment of reliability and generalizability. MethodsWe conducted a systematic review and meta-analysis of the ability of current AI/ML models operating on MRI data for: 1) epilepsy diagnosis, 2) temporal lobe epilepsy lateralization, 3) lesion localization, and 4) post-surgical outcome prediction. Searches were conducted across PubMed, Medline, and Embase databases from inception until January 1, 2025. We selected studies that employed AI/ML models trained on any MRI modality to classify at least ten patients across the four main objectives for qualitative assessment, and further included in the meta-analysis if they reported an accuracy rate. The primary outcome of the meta-analysis was the overall accuracy of AI/ML models trained on MRI data. The secondary outcome was the concomitant risk of bias evaluation using PROBAST. FindingsWe identified 158 studies for qualitative evaluation and 127 studies for inclusion in the meta-analysis. AI/ML on multimodal MRI could accurately distinguish epilepsy patients from healthy controls (overall accuracy: 88% [85-90]), lateralize temporal lobe epilepsy (90% [87-93]), localize epileptogenic lesions (82% [74-88]), and predict post-surgical seizure-freedom (83% [78-87]). Overall, a high risk of bias remains in the literature; participant bias remained high across all outcomes (64-87%), as well as predictor (88-100%) and analysis (83-100%) bias. Outcome bias was low only for AI/ML studies predicting post-surgical outcomes. InterpretationOur results support promising accuracy of AI/ML models in epilepsy diagnostics and prognostics but remain highly susceptible to bias in participants, predictors, outcome, and analysis domains which limits current translation to routine clinical practice. We encourage closer interdisciplinary collaboration between clinical and scientific groups to improve validation studies based on thorough study design, analysis, and reporting.

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bioRxiv2025

In vivo cartography of state-dependent signal flow hierarchy in the human cerebral cortex

Understanding the principle of information flow across distributed brain networks is of paramount importance in neuroscience. Here, we introduce a novel neuroimaging framework, leveraging integrated effective connectivity (iEC) and unconstrained signal flow mapping for data-driven discovery of the human cerebral functional hierarchy. Simulation and empirical validation demonstrated the high fidelity of iEC in recovering connectome directionality and its potential relationship with histologically defined feedforward and feedback pathways. Notably, the iEC-derived hierarchy revealed a monotonically increasing level along the axis where the sensorimotor, association, and paralimbic areas are sequentially ordered - a pattern supported by the Structural Model of laminar connectivity. This hierarchy was further demonstrated to flexibly reorganize across brain states: flattening during an externally oriented condition, evidenced by a reduced slope in the hierarchy, and steepening during an internally focused condition, reflecting heightened engagement of interoceptive regions. Our study highlights the unique role of macroscale directed functional connectivity in uncovering a biologically interpretable state-dependent signal flow hierarchy.

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bioRxiv2025

An open dataset of cerebral tau deposition in young healthy adults based on MK6240 positron emission tomography

Tauopathies are pathologies wherein phosphorylated insoluble tau aggregates in neurons, leading to dysfunction and degeneration. Positron emission tomography (PET) enables measurement of in vivo tau, with second-generation radiotracers such as [18F]MK6240 showing high tau affinity with minimal off-target binding. While tauopathies are commonly linked to age-related neurodegenerative diseases, notably Alzheimers disease (AD), evidence suggests pathophysiological cascades may begin long before clinical onset. Increasingly, tau is recognized in pathologies affecting younger individuals, including autosomal dominant AD, Niemann-Pick disease type C, chronic traumatic encephalopathy, and epilepsy, thus highlighting the importance of normative data in non-geriatric populations. Here, we present a dataset of 33 young to middle-age healthy adults (mean age 34.0{+/-}10.4 years, 12 female) with [18F]MK6240 PET data and T1w magnetic resonance imaging. Longitudinal data are also available in a subset of 9 participants with a minimum follow-up time of 1 year. Our dataset aims to support imaging biomarker studies on younger individuals potentially at risk for AD and to advance work in tauopathies affecting non-geriatric populations generally excluded from neurodegeneration studies.

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bioRxiv2025

In-vivo evidence for increased tau deposition in temporal lobe epilepsy

Temporal lobe epilepsy (TLE), the most common pharmaco-resistant epilepsy in adults, has been linked to structural brain changes extending beyond the mesiotemporal areas. While not traditionally viewed as a neurodegenerative disorder, recent ex-vivo studies have shown elevated levels of misfolded tau protein in TLE. This study investigated tau deposition in TLE patients using the in-vivo PET tracer [18F]MK-6240. We studied 28 TLE patients and 28 healthy controls to assess tau uptake and its relationship with brain connectivity, clinical variables, and cognitive function alongside post-surgical tissue from a subset of patients. Compared to controls, TLE patients exhibited markedly increased [18F]MK-6240 uptake in bilateral superior and medial temporal regions and the parietal cortex, with tau accumulation following regional functional and structural connectivity and cognitive impairment. Immunohistochemistry analysis confirmed variable phosphorylated tau staining in 5/6 operated cases with available specimens. These findings suggest that tau accumulation contributes to cognitive decline observed in TLE, supporting a potential role of tau in epilepsy-related neurodegeneration.

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