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Frauscher, B.

Publications and source records attributed to Frauscher, B..

At least 19 recordsLinked to original sources

Sleep spindles stabilize human thalamocortical networks, inhibiting pathological disruptions

The thalamus coordinates sleep-dependent brain function including memory consolidation, sensory gating, and network stability through spindle oscillations. Thalamocortical circuits are also affected in many neurological and neuropsychiatric disorders. Yet how human thalamocortical circuits respond to pathological disruptions remain poorly understood. Here, we leveraged interictal epileptiform discharges (IEDs) as spontaneous perturbations to probe spindle-generating circuits and thalamocortical dynamics in vivo. Using multi-night intracranial recordings spanning multiple thalamic nuclei and cortical regions in 55 individuals with epilepsy, we investigated interactions between sleep spindles and epileptic activity across timescales from milliseconds to days. Sleep spindles were associated with IED suppression, whereas IEDs increased subsequent spindle probability, revealing bidirectional interactions between physiological and pathological activity. Nights with lower IEDs corresponded to increased spindle occurrence, longer duration, and faster frequency, reflecting a more stable thalamocortical state. These findings propose sleep spindles as potential regulators of thalamocortical networks that actively respond to and regulate pathological activity.

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The electro-MICA toolbox for integrating electrophysiology within multimodal imaging and connectomics workflows

AO_SCPLOWBSTRACTC_SCPLOWThe integration of electrophysiological recordings with multimodal neuroimaging data holds great promise for advancing our understanding of brain function and neurological disorders. To facilitate this endeavour, we present electro-MICA, an open-access Python toolbox designed to project electrophysiological features from scalp and intracranial electroencephalography (EEG) onto cortical and hippocampal surfaces generated by validated multimodal imaging ecosystems. The toolbox comprises two pipelines: one for intracranial EEG (iEEG) recorded with stereo-EEG depth electrodes, and one for scalp EEG source localization. Both pipelines are grounded in numerical solutions to the electromagnetic equations governing electric activity in the brain, solved using the Boundary Element Method. A key methodological contribution is the use of a current density double layer model for neural generators, which avoids the mathematical singularities introduced by conventional dipole-based models when electrodes are near the cortical surface, a situation that can arise in iEEG. Electrode contacts are additionally modeled with non-zero length, improving physical realism. Scalp EEG source localization is performed using eLORETA on a subject-specific three-layer head model derived from the anatomical input. Validation against empirical gamma-band iEEG data from 32 subjects demonstrates that the distributed generator model outperforms both distance-based and dipole-based alternatives. An illustrative clinical example demonstrates the toolboxs capacity to reveal associations between intracranial spike rates, cortical thickness, and anatomical connectivity in an epilepsy patient. Electro-MICA requires no parameter selection from the user, facilitating straightforward multimodal analyses in both research and clinical settings. The toolbox is available at github.com/MICA-MNI/electromica with extensive online documentation at electromica.readthedocs.io.

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Thalamic Interictal Epileptic and Non-Epileptic Events during NREM Sleep in Patients with Focal Epilepsy: a Stereo-EEG Study

BackgroundThalamic recordings are increasingly incorporated into stereo-electroencephalography (SEEG) evaluations of drug-resistant focal epilepsy to guide neuromodulation targeting. Human thalamic electrophysiology, however, is poorly defined, limiting the distinction between pathological and physiological activity. Here, we characterized interictal epileptic and non-epileptic events during non-rapid eye movement (NREM) sleep across multiple thalamic nuclei and examined their relationship to seizure outcomes. MethodsWe analyzed NREM sleep SEEG recordings from 64 patients with drug-resistant focal epilepsy. Electrodes sampled four thalamic nuclei: centromedian (CM), pulvinar (Pu), ventral lateral (VL), and ventral posterolateral (VPL). Patients were classified into three outcome groups: favorable, unfavorable, and surgically non-remediable. Rates of thalamic spikes, high-frequency oscillations (HFOs), spike-fast activity, and sleep spindles were analyzed and compared across nuclei and outcomes. FindingsRecordings of the thalamus revealed both pathological and physiological interictal events. Interictal epileptic events were infrequent. Only [~]0.2% of seizure-onset zone spikes propagated to the thalamus. Thalamic spike-fast activity was indicative of unfavorable surgical outcomes (CM: p = 0.047, d = 0.46) or surgically non-remediable epilepsy (VL: p = 0.002, d = 0.84). In contrast, thalamic sleep spindles were ubiquitous but reduced in surgically non-remediable patients (CM: p = 0.031, d = -0.58; VL: p = 0.005, d = -0.79). Finally, unique thalamic SEEG patterns were identified, including spikes concomitant with spindles, isolated spikes, and physiological fast ripples. InterpretationThis study provides a comprehensive characterization of thalamic interictal events during NREM sleep, enriching our understanding of thalamic pathophysiology and highlighting the value of thalamic recordings in presurgical evaluation.

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Sleep fragmentation drives local, network-specific epileptic activity in human epilepsy

Sleep has complex links with epileptic activity, yet the causal role of sleep instability in driving and modulating pathological discharges in the human brain remains incompletely understood. Here we directly examine this by characterising the fine-scale temporal coupling between experimentally induced sleep arousals and interictal epileptiform discharges (IEDs), using combined stereo-electroencephalography and polysomnography recordings in patients with epilepsy. Sleep arousals triggered rapid IED increases, with effects gated by anatomical region and sleep stage. Increases were confined to neocortical regions and occurred during both non-rapid eye movement stage 2 (N2) and stage 3 (N3) sleep, with a larger effect observed in N2. IED increases did not differ between the seizure-onset zone and surrounding regions. Despite elevating IED counts, arousals did not alter IED spatial propagation, indicating state-dependent enhancement of local cortical excitability without recruitment of broader epileptic networks. These findings establish a causal role for sleep instability in actively driving pathological activity on fine-grained spatiotemporal scales, and highlight sleep stabilisation as a promising therapeutic strategy to reduce epileptic burden and preserve cortical network function.

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Beyond Circadian: A Yearlong Electroencephalography Study Reveals Hidden Ultralong-term Sleep Cycles

Sleep is essential for brain function and overall health. While circadian rhythms and sleep stages across the night have been well-characterized, long-term variations in sleep remain poorly understood. We used a novel technology, subcutaneous electroencephalography, to collect yearlong sleep recordings from 20 healthy individuals. We investigated intrinsic and extrinsic drivers of sleep variability and identified recurring multi-day cycles of 8-60 days in sleep duration, latency, architecture, and stability. Additionally, sleep was modulated by external factors including season, weather, weekends and holidays. This reveals that while sleep processes are governed by internal dynamics, they remain sensitive to environmental influences. These results uncover a previously unrecognized temporal variation in human sleep and suggest new directions for understanding sleep patterns and their relevance to health and disease. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/676090v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@177393corg.highwire.dtl.DTLVardef@4ea454org.highwire.dtl.DTLVardef@106bc4corg.highwire.dtl.DTLVardef@1342321_HPS_FORMAT_FIGEXP M_FIG C_FIG

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Personalized Biomarkers of Multiscale Functional Alterations in Temporal Lobe Epilepsy

Temporal lobe epilepsy (TLE) presents with substantial inter-patient variability in clinical and neuroimaging manifestations. This multicenter study examined inter-individual differences in spatial patterns of intrinsic brain function in TLE using normative modeling at multiple spatial scales and evaluated the effectiveness of individual functional deviations for clinical diagnosis and postsurgical outcome prediction. We analyzed multimodal MRI data on 298 healthy controls, 282 TLE patients, and 45 disease controls with extratemporal epilepsy. Cortical function was profiled at local, regional, and global scales using brain signal variability, regional homogeneity, and node strength. We estimated patient-specific W-score maps to index deviations from normative metrics. Compared to healthy controls, patients with TLE showed considerable variations in patterns of functional alterations across the cortex, with the highest overlap in the ipsilateral mesiotemporal regions. Connectome-based simulation revealed the paralimbic and medial default mode regions as key disease epicenters. Functional changes were primarily underpinned by superficial white matter anomalies. Supervised pattern learning achieved classification AUCs of 0.76 for TLE versus disease controls, 0.74 for left versus right TLE, and 0.63 for seizure-free versus non-seizure-free TLE, with greater contralateral temporal functional deviations correlating with unfavorable postsurgical seizure outcome. Our findings reveal the heterogeneous impact of TLE on intrinsic cortical function. These biomarkers hold promise for clinical translation, guiding precision therapeutics and enhancing presurgical decision-making in TLE.

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Associations between epilepsy-related polygenic risk and brain morphology in childhood

AO_SCPLOWBSTRACTC_SCPLOWTemporal lobe epilepsy with hippocampal sclerosis (TLE-HS) is associated with a complex genetic architecture, but the translation from genetic risk factors to brain vulnerability remains unclear. Here, we examined associations between epilepsy-related polygenic risk scores for HS (PRS-HS) and brain structure in a large sample of neurotypical children, and correlated these signatures with case-control findings in in multicentric cohorts of patients with TLE-HS. Imaging-genetic analyses revealed PRS-related cortical thinning in temporo-parietal and fronto-central regions, strongly anchored to distinct functional and structural network epicentres. Compared to disease-related effects derived from epilepsy case-control cohorts, structural correlates of PRS-HS mirrored atrophy and epicentre patterns in patients with TLE-HS. By identifying a potential pathway between genetic vulnerability and disease mechanisms, our findings provide new insights into the genetic underpinnings of structural alterations in TLE-HS and highlight potential imaging-genetic biomarkers for early risk stratification and personalized interventions.

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Human cortical dynamics reflect graded contributions of local geometry and network topography

The brain is a physically embedded and heavily interconnected system that expresses neural rhythms across multiple time scales. While these dynamics result from the complex interplay of local and inter-regional factors, the relative contribution of such mechanisms across the cortex remains unclear. Our study explores geometric, microstructural, and connectome-level constraints on cortex-wide neural activity. We leverage intracranial electroencephalography recordings to derive a coordinate system of human cortical dynamics. Using multimodal neuroimaging, we could then demonstrate that these patterns are largely explainable by geometric properties indexed by inter-regional distance. However, dynamics in transmodal association regions are additionally explainable by incorporation of inter-regional microstructural similarity and connectivity information. Our findings are generally consistent when cross-referencing electroencephalography and imaging data from large-scale atlases and when using data obtained in the same individuals, suggesting subject-specificity and population-level generalizability. Together, our results suggest that the relative contribution of local and macroscale constraints on cortical dynamics varies systematically across the cortical sheet, specifically highlighting the role of transmodal networks in inter-regional cortical coordination.

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Rhythms and Background (RnB): The Spectroscopy of Sleep Recordings

Non-rapid eye movement (NREM) sleep is characterized by the interaction of multiple coupled oscillations essential for various functions such as memory consolidation, alongside a pervasive and dynamic arrhythmic 1/f scale-free background that may also contribute to these functions. Although recent spectral parametrization methods such as FOOOF (Fitting-One-and-Over-f) allowed to dissociate rhythmic and arrhythmic components in the spectral domain, they fail to resolve these processes in the time domain, where instantaneous measures of frequency, amplitude, and phase-amplitude coupling are still confounded by arrhythmic activity. This limitation represents a significant pitfall for studies of NREM sleep, which often rely on phase-based analyses of specific oscillations. To address this limitation, we introduce Rhythms & Background (RnB), a novel wavelet-based methodology designed to dynamically denoise time-series data by correcting for arrhythmic interference. This enables the extraction of a purely rhythmic time-series suitable for enhanced time-domain analyses of sleep rhythms. We first validate RnB through simulations, demonstrating its robust performance in accurately estimating spectral profiles of individual and multiple oscillations across a range of arrhythmic conditions. We then apply RnB to publicly available intracranial EEG sleep recordings, showing that it provides an improved spectral and time-domain representation of hallmark NREM rhythms. Finally, we demonstrate that RnB significantly enhances the assessment of phase-amplitude coupling between cardinal NREM oscillations, outperforming traditional methods that conflate rhythmic and arrhythmic components. This methodological advance offers a substantial improvement in the analysis of sleep oscillations, providing greater precision in the study of rhythmic activity critical to NREM sleep functions. SIGNIFICANCE STATEMENTThe Rhythms and Background (RnB) algorithm introduces a novel approach to signal processing in electrophysiology by isolating rhythmic activity from the arrhythmic background at the time-series level. Unlike existing spectral decomposition methods, RnB enables more precise analysis of brain rhythms in both the time and spectral domains, providing clearer insights into cerebral oscillatory processes. This breakthrough has direct applications in studying brain connectivity and oscillation dynamics during sleep. Additionally, its application in clinical populations where pathological changes in arrhythmic activity are common, such as neurodevelopmental and neurodegenerative disorders, will help to better understand abnormal oscillatory processes. By improving the accuracy of rhythmic signal analysis, RnB opens new avenues for understanding brain function and dysfunction in research and clinical settings.

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Structural compromise in spiking cortex and connected networks

INTRODUCTIONEpilepsy is increasingly conceptualized as a network disorder, and advancing methods for its diagnosis and treatment requires characterizing both the epileptic generator and related networks. We combined multimodal magnetic resonance imaging (MRI) and high-density electroencephalography (HD-EEG) to interrogate alterations in cortical microstructure, morphology, and intrinsic local function within and beyond spiking tissue in focal epilepsy. METHODSWe studied 25 patients with focal epilepsy (12F, mean {+/-} SD age = 31.28 {+/-} 9.30 years) and 55 age- and sex-matched healthy controls, subdivided into a group of 30 for imaging feature normalization (15F, 31.40 {+/-} 8.74 years) and a group of 25 for replication (12F, 31.04 {+/-} 5.65 years). The 3T MRI acquisition included T1-weighted, diffusion, quantitative T1 relaxometry, and resting-state functional imaging. Open-access MRI processing tools derived cortex-wide maps of morphology and microstructure (cortical thickness, mean diffusivity, and quantitative T1 relaxometry) and intrinsic local function and connectivity (timescales, connectivity distance, and node strength) for all participants. Multivariate approaches generated structural and functional alteration scores for each cortical location. Using HD-EEG electrical source imaging, the most prominent spike type was localized and we quantified MRI alterations within spike sources, as well as in proximal and connected networks. RESULTSRegions harboring spike sources showed increased structural MRI alterations compared to the rest of the brain in patients. Structural compromise extended to all regions with close functional coupling to spike sources, but not to anatomical neighbors of spike sources. This finding was replicated using average control functional and anatomical matrices instead of patient-specific matrices. CONCLUSIONSpiking regions contain more marked alterations in microstructure and morphology than the remaining cortex, and combining imaging with neurophysiology techniques may ultimately help identify the epileptogenic zone non-invasively. There are nevertheless broader networks effects, which may relate to a cascading of structural changes to functionally connected cortices. These results underscore the utility of combining high-definition MRI and EEG approaches for characterizing epileptogenic tissue and assessing distributed network effects.

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EEG source imaging technique to investigate sleep oscillations for simultaneous EEG-fMRI

Simultaneous recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is a widely used non-invasive neuroimaging technique in sleep studies. However, EEG data are strongly influenced by two types of MRI-related artefacts: gradient artefacts (GA) and ballistocardiogram artefacts (BCG). If artefacts correction is suboptimal, the BCG obscures the EEG signals below 20Hz and could make it difficult to investigate sleep oscillations, especially sleep spindles, sleep specific oscillations occurring within 11-16Hz frequency band. We previously demonstrated the utility of beamforming spatial filtering in correcting MRI-related artefacts on EEG. Here, we investigated the use of beamforming spatial filtering for improving the detection of EEG oscillations during sleep, in particular, 1) to accurately estimate single-event spindle EEG power changes, and 2) to demonstrate the potential improvement of fMRI general linear model (GLM) analysis when involving such additional EEG information. We analysed EEG-fMRI data acquired during a recovery nap after sleep deprivation in 20 young healthy participants (12 females, 8 males, age = 21.3 {+/-} 2.5 years). Based on spindle events (onset and duration) detected by trained sleep scorers on BCG corrected EEG signals through a conventional average artefact subtraction (AAS) method, we compared four different EEG processing steps: non-BCG corrected; AAS BCG corrected; beamforming BCG corrected; beamforming+AAS BCG corrected. These processing steps consist of non-BCG corrected and AAS BCG corrected considered either at the sensor level or at the source-level (after beamformer localization) to evaluate the impact of the BCG artefact on the detection of spindle activity. Then we further investigated four different fMRI GLM approaches using 1) the spindle onset and duration (GLM1), 2) spindle onset, duration, and parametric modulation of single-spindle power change from the Cz electrode of the AAS BCG corrected data (GLM2), 3) spindle onset, duration, and parametric modulation of single-spindle power change from the beamforming+AAS BCG corrected (GLM3) and 4) spindle onset, duration, and parametric modulation of single-spindle power change from the beamforming BCG corrected data (GLM4). We found that the beamforming approach did not only attenuate the BCG artefacts, but also recovered sleep spindle activity occurring during NREM sleep. Furthermore, this beamforming approach allowed us to accurately estimate single-event power change of each spindle in the source space when compared to the channel level analysis, and therefore to further improve the specificity of fMRI GLM analysis, better localizing the recruited brain regions during spindles. Our findings show the benefit of applying beamforming source imaging technique to EEG-fMRI acquired during sleep. We demonstrate that this approach would be beneficial especially for long EEG-fMRI data acquisitions (i.e., sleep, resting-state), when the BCG correction becomes problematic due to inherent dynamic changes of heart rates. Our findings extend previous work regarding the application of the source imaging to the sleep EEG-fMRI. Combining with this advanced methodology and analysis, sleep EEG-fMRI will help us better understand the functional roles of human sleep.

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NREM sleep brain networks modulate cognitive recovery from sleep deprivation

Decrease in cognitive performance after sleep deprivation and its recovery following sleep suggests the key role of sleep, especially non-rapid eye movement (NREM) sleep, in maintaining cognition. It remains unknown whether brain network reorganization in NREM sleep stages N2 and N3 can uniquely be mapped onto individual differences in cognitive performance after a recovery nap following sleep deprivation. Using resting state functional magnetic resonance imaging (fMRI), we quantified the integration and segregation of brain networks during N2 and N3 sleep in a 1-hour nap following 24-hour sleep deprivation, compared to well-rested wakefulness. Here, we introduce a new analytic framework called the hierarchical segregation index (HSI) to quantify network segregation across spatial scales, from whole-brain to the voxel level, by identifying spatio-temporally overlapping large-scale networks and the corresponding voxel-to-region hierarchy. We found that network segregation increased in the posterior cingulate cortex during both N2 and N3 sleep compared to wakefulness. In contrast, increased segregation in the visual cortex and decreased segregation in the posterior ventromedial prefrontal cortex during N2 returned to levels comparable to wakefulness during N3. More segregation during N3 sleep was associated with worse recovery of working memory, executive attention, and psychomotor vigilance after the nap. Sleep-related changes in network segregation emerged at different spatial scales, with regional- and voxel-level alterations being associated with different cognitive tasks. Finally, we demonstrated the sensitivity and reliability of voxel-level HSI to provide key insights into within-region variation, suggesting a mechanistic understanding of how NREM sleep replenishes cognition after sleep deprivation.

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Pharmaco-resistant temporal lobe epilepsy gradually perturbs the cortex-wide excitation-inhibition balance

AO_SCPLOWBSTRACTC_SCPLOWExcitation-inhibition (E/I) imbalance is theorized as a key mechanism in the pathophysiology of epilepsy, with a mounting body of previous research focusing on elucidating its cellular manifestations. However, there are limited studies into E/I imbalance at macroscale and its microcircuit-level mechanisms and clinical associations. In our current work, we computed the Hurst exponent--a previously validated index of the E/I ratio--from resting-state fMRI time series, and simulated microcircuit parameters using biophysical computational models. We found a broad reduction in the Hurst exponent in pharmaco-resistant temporal lobe epilepsy (TLE), indicative of a shift towards more excitable network dynamics. Connectome decoders pointed to temporolimbic and frontocentral areas as plausible network epicenters of E/I imbalance. Computational simulations further revealed that enhancing cortical excitability in patients likely reflected atypical increases in recurrent connection strength of local neuronal ensembles. Moreover, mixed cross-sectional and longitudinal analyses revealed heightened E/I elevation in patients with longer disease duration, more frequent electroclinical seizures and inter-ictal epileptic spikes, and worse cognitive functioning. Replicated in an independent dataset, our work provides compelling in-vivo evidence of a macroscale shift in E/I balance in TLE patients that undergoes progressive changes and underpins cognitive impairments, potentially informing treatment strategies targeting E/I mechanisms.

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HippoMaps: Multiscale cartography of the human hippocampal formation

The hippocampus has a unique microarchitecture, is situated at the nexus of multiple macroscale functional networks, contributes to numerous cognitive as well as affective processes, and is highly susceptible to brain pathology across common disorders. These features make the hippocampus a model to understand how brain structure covaries with function, in both health and disease. Here, we introduce HippoMaps, an open access toolbox and online data warehouse for the mapping and contextualization of subregional hippocampal data in the human brain (http://hippomaps.readthedocs.io). HippoMaps capitalizes on a unified hippocampal unfolding approach as well as shape intrinsic registration capabilities to allow for cross-subject and cross-modal data aggregation. We initialize this repository with an unprecedented combination of hippocampal data spanning 3D ex-vivo histology, ex-vivo 9.4 Tesla MRI, as well as in-vivo structural MRI and resting-state functional MRI (rsfMRI) obtained at 3 and 7 Tesla, together with intracranial encephalography (iEEG) recordings in epilepsy patients. HippoMaps also contains validated tools for spatial map association analysis in the hippocampus that correct for autocorrelation. All code and data are compliant with community standards, and comprehensive online tutorials facilitate broad adoption. Applications of this work span methodologies and modalities, spatial scales, as well as clinical and basic research contexts, and we encourage community feedback and contributions in the spirit of open and iterative scientific resource development.

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Differential reorganization of episodic and semantic memory systems in epilepsy-related mesiotemporal pathology

Declarative memory encompasses episodic and semantic divisions. Episodic memory captures singular events with specific spatiotemporal relationships, while semantic memory houses context-independent knowledge. Behavioural and functional neuroimaging studies have revealed common and distinct neural substrates of both memory systems, implicating mesiotemporal lobe (MTL) regions such as the hippocampus and distributed neocortices. Here, we explored declarative memory system reorganization in patients with unilateral temporal lobe epilepsy (TLE), as a human disease model to test the impact of variable degrees of MTL pathology on memory function. Our cohort included 31 patients with TLE as well as 60 age and sex-matched healthy controls and all participants underwent episodic and semantic retrieval tasks during a multimodal MRI session. The functional MRI tasks were closely matched in terms of stimuli and trial design. Capitalizing on non-linear connectome gradient mapping techniques, we derived task-based functional topographies during episodic and semantic memory states, both in the MTL and in neocortical networks. Comparing neocortical and hippocampal functional gradients between TLE patients and healthy controls, we observed a marked topographic reorganization of both neocortical and MTL systems during episodic memory states. In the neocortex, alterations were characterized by reduced functional differentiation in patients in lateral temporal and midline parietal cortices in both hemispheres. In the MTL, on the other hand, patients presented with a more marked functional differentiation of posterior and anterior hippocampal segments ipsilateral to the seizure focus and pathological core, indicating perturbed intrahippocampal connectivity. Semantic memory reorganization was also found in bilateral lateral temporal and ipsilateral angular regions, while hippocampal functional topographies were unaffected. Leveraging MRI proxies of MTL pathology, we furthermore observed alterations in hippocampal microstructure and morphology are associated with TLE-related functional reorganization during episodic memory. Moreover, correlation analysis and statistical mediation models revealed that these functional alterations contributed to behavioural deficits in episodic, but again not semantic memory in patients. Altogether, our findings suggest that semantic processes rely on distributed neocortical networks, while episodic processes are supported by a network involving both the hippocampus and neocortex. Alterations of such networks can provide a compact signature of state-dependent reorganization in conditions associated with MTL damage, such as TLE.

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Cerebral perfusion alterations in temporal lobe epilepsy: Structural underpinnings and network disruptions

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSOO_SCPLOWBJECTIVEC_SCPLOWC_ST_ABSNeuroimaging has been the prevailing method to study brain networks in temporal lobe epilepsy (TLE), showing widespread alterations beyond the mesiotemporal lobe. Despite the critical role of the cerebrovascular system in maintaining whole-brain structure and function, changes in cerebral blood flow (CBF) remain incompletely understood in the disease. MO_SCPLOWETHODSC_SCPLOWWe studied 24 individuals with pharmaco-resistant TLE and 38 healthy adults using multimodal 3T magnetic resonance imaging. We compared regional CBF changes in patients relative to controls and related our perfusion findings to morphological and microstructural metrics. We further probed inter-regional vascular networks in TLE, using graph theoretical CBF covariance analysis. Finally, we assessed the effects of disease duration to study progressive changes. RO_SCPLOWESULTSC_SCPLOWCompared to controls, individuals with TLE showed widespread CBF reductions, predominantly in fronto-temporal regions, with 83% of patients showing more marked decreases ipsilateral than contralateral to the seizure focus. Parallel structural profiling and network-based models showed that cerebral hypoperfusion may be partly constrained by grey and white matter changes and topologically segregated from whole-brain perfusion networks. Negative effects of progressive disease duration further targeted regional CBF profiles in patients. Findings were confirmed in a subgroup of patients who remained seizure-free after surgery. IO_SCPLOWNTERPRETATIONC_SCPLOWOur multimodal findings provide insights into vascular contributions to TLE pathophysiology and highlight their clinical potential in seizure lateralization.

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Atypical connectome topography and signal flow in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is one of the most common pharmaco-resistant epilepsies in adults. While hippocampal pathology is the hallmark of this condition, emerging evidence indicates that brain alterations extend beyond the mesiotemporal epicenter and affect macroscale brain function and cognition. We studied macroscale functional reorganization in TLE, explored structural substrates, and examined cognitive associations. We investigated a multisite cohort of 95 patients with pharmaco-resistant TLE and 95 healthy controls using state-of-the-art multimodal 3T magnetic resonance imaging (MRI). We quantified macroscale functional topographic organization using connectome dimensionality reduction techniques and estimated directional functional flow using generative models of effective connectivity. We observed atypical functional topographies in patients with TLE relative to controls, manifesting as reduced functional differentiation between sensory/motor networks and transmodal systems such as the default mode network, with peak alterations in bilateral temporal and ventromedial prefrontal cortices. TLE-related topographic changes were consistent in all three included sites and reflected reductions in hierarchical flow patterns between cortical systems. Integration of parallel multimodal MRI data indicated that these findings were independent of TLE-related cortical grey matter atrophy, but mediated by microstructural alterations in the superficial white matter immediately beneath the cortex. The magnitude of functional perturbations was robustly associated with behavioral markers of memory function. Overall, this work provides converging evidence for macroscale functional imbalances, contributing microstructural alterations, and their associations with cognitive dysfunction in TLE.

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DIFFERENTIAL MEMORY IMPAIRMENT ACROSS RELATIONAL DOMAINS IN TEMPORAL LOBE EPILEPSY

BO_SCPLOWACKGROUNDC_SCPLOWTemporal lobe epilepsy (TLE) is typically associated with pathology of the hippocampus, a key structure involved in relational memory processes, including episodic, semantic, and spatial memory. While it is widely accepted that TLE-associated hippocampal alterations may underlie global deficits in memory, it remains poorly understood whether TLE may present with shared or unique impairment across distinct relational memory domains. MO_SCPLOWETHODSC_SCPLOWWe administered a recently validated behavioral paradigm to evaluate episodic, semantic, and spatial memory in 20 pharmacoresistant TLE patients and 53 age- and sex-matched healthy controls. We implemented linear mixed effects models to identify memory deficits in individuals with TLE relative to controls, and used partial least squares analysis to identify factors contributing to overall variations in relational memory performance across both cohorts. RO_SCPLOWESULTSC_SCPLOWTLE patients showed marked impairment in episodic memory compared to controls, while spatial and semantic memory remained relatively intact. Findings were robust, with slight decreases in effect sizes after controlling for performance on executive function tests. Via partial least squares analysis, we identified group, age, and bilateral hippocampal volumes as important variables relating to relational memory impairment. CO_SCPLOWONCLUSIONC_SCPLOWOur behavioral framework provides a granular approach for assessing relational memory deficits in people with TLE and may inform future prognostic strategies in patients with hippocampal pathology. Our work warrants further investigations into the underlying neural substrates of relational memory.

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