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Sahlas, E.

Publications and source records attributed to Sahlas, E..

5 recordsLinked to original sources

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.

neuroscience↗

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.

neuroscience↗

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.

neuroscience↗

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.

neuroscience↗

Stability of Neural Oscillations Supports Auditory-Motor Synchronization

Previous findings suggest that musical training leads to increased coactivation of auditory and motor brain networks, as well as enhanced auditory-motor synchronization. Less is known about the temporal dynamics of auditory-motor network interactions and how these temporal dynamics are shaped by musical training. The current study applied Recurrence Quantification Analysis, a nonlinear technique for characterizing the temporal dynamics of complex systems, to participants neurophysiological activity recorded via electroencephalography (EEG) during an auditory-motor synchronization task. We investigated changes in neural predictability and stability with musical training, and how these changes were related to synchronization accuracy and consistency. EEG was recorded while musicians and nonmusicians first tapped a familiar melody at a comfortable rate, called Spontaneous Production Rate (SPR). Then participants synchronized their taps with an auditory metronome presented at each participants SPR and at rates 15% and 30% slower than their SPR. EEG-based outcomes of determinism (predictability) and meanline (stability) were compared with behavioral synchronization measures. Musicians synchronized more consistently overall than nonmusicians. Both groups of participants showed decreased synchronization accuracy at slower rates, and higher EEG-based determinism (predictability) at slower rates. Furthermore, neural meanline (stability) measures correlated with synchronization consistency across all participants and stimulus rates; as neural stability increased, so did synchronization consistency. Neural stability may be a general mechanism supporting the maintenance of synchronization across rates, which may improve with musical training.

neuroscience↗