Biology subjects

Menchaca, M.

Publications and source records attributed to Menchaca, M..

4 recordsLinked to original sources

bioRxiv2026

Language Dysfunction Associated with Pathological Brain Connectivity in Children with Epilepsy

Language impairment is common in childhood epilepsy and may arise in part from disruption of the distributed brain networks that support language. In self-limited epilepsy with centrotemporal spikes (SeLECTS)--the most common focal epilepsy of childhood--hyperconnectivity has been linked to poor language outcomes, but the specific network patterns associated with language dysfunction remain unclear, limiting the ability to target neurostimulation rationally. We recorded high-density EEG from 27 children with SeLECTS and 29 age-matched controls during verb generation and rest, and quantified functional connectivity across multiple frequency bands and bilateral frontal, temporal, occipital, and motor regions. Using multivariate pattern analysis, we identified connectivity patterns that predicted language ability, distinguished patterns shared across groups from those specific to SeLECTS and tested whether spatially specific connectivity provided information beyond whole-brain or hemispheric averages and conventional clinical variables. Frontal and occipitotemporal connectivity, particularly within the left hemisphere, predicted language ability across groups, whereas motor-network connectivity emerged as the dominant SeLECTS-specific predictor, linking the epileptogenic network to language dysfunction. Connectivity between specific regions outperformed averaged connectivity measures and predicted language beyond epilepsy diagnosis and antiseizure medication use. Task-based connectivity also outperformed resting-state connectivity. These findings show that language ability is associated with distributed yet spatially specific patterns of brain connectivity, while epilepsy introduces distinct alterations centered on the epileptogenic network. Identifying these disease-specific network patterns provides mechanistic insight into language dysfunction and a rational basis for spatially targeted neuromodulation.

neuroscience↗

bioRxiv2026

TMS timed to interictal epileptiform discharges

Interictal epileptiform discharges (IEDs) are pathological hypersynchronous bursts of electrical brain activity that occur between seizures in patients with epilepsy. IEDs are caused by transient brain states that are difficult to predict, making them a challenging neurophysiological and technological case for brain-state-dependent stimulation. Administering stimulation at IED onset may provide insight into the epileptic network and optimize neurostimulation therapies. Here, we assessed the feasibility of IED-triggered transcranial magnetic stimulation (TMS) in two children with self-limited epilepsy with centrotemporal spikes (SeLECTS), a common pediatric epilepsy in which IEDs emerge from the motor cortex. A convolutional neural network (CNN) was trained on the participants pre-recorded electroencephalography (EEG) data with IEDs annotated by an epileptologist. The CNN was integrated into an EEG-processing pipeline that classified EEG segments as "IED" or "non-IED" in real time. With this pipeline, TMS pulses were administered during IED or non-IED periods in an interleaved, randomized design. We stimulated both the motor cortex generating the IEDs and the contralateral motor cortex and tested the impact of IEDs on TMS-evoked potentials (TEPs). Our study demonstrated that TMS can be timed to IEDs and that there is a site-specific increase in TEP amplitude when stimulating during IEDs. Out of the TMS pulses aimed at an IED, 39% and 19% were successfully delivered during an IED for the two participants, respectively. For future research, we propose ways to address the methodological challenges of IED-timed TMS, enabling brain-state-dependent TMS for epilepsy research and treatment.

neuroscience↗

bioRxiv2025

Functional Connectivity in Self-limited Epilepsy with Centrotemporal Spikes (SeLECTS) Increases with Epilepsy Duration and Interictal Spike Exposure.

ObjectiveTo determine the impact of epilepsy duration and interictal spikes on functional connectivity in children with Self-Limited Epilepsy with Centrotemporal Spikes (SeLECTS). MethodsConnectivity was calculated from electroencephalograms (EEGs) of 68 children with SeLECTS and 65 age and sex-matched controls using the weighted phase lag index. SeLECTS EEGs were categorized by epilepsy duration (shorter or longer than 6 months) to assess progressive connectivity changes. To investigate the impact of spikes on connectivity, 19 SeLECTS patients who underwent two EEGs were analyzed longitudinally, comparing those whose spikes persisted versus resolved over time. Analyses focused on connectivity during sleep. ResultsConnectivity increased with epilepsy duration, being lowest in controls, intermediate in patients with shorter epilepsy duration, and highest in those with longer duration. Changes were initially greatest within the right occipital region and became more widespread with longer epilepsy duration. Longitudinally, patients with persistent spikes showed increasing connectivity over time, while those with spike resolution demonstrated decreasing connectivity, resulting in significant between-group differences. ConclusionsFunctional connectivity in SeLECTS increases progressively with epilepsy duration and spike exposure, suggesting that ongoing spikes drive neural network alterations. SignificanceSpikes are a potential treatment target to prevent progressive brain network disruption and preserve cognitive outcomes.

neuroscience↗

bioRxiv2025

Abnormal Elevated Connectivity During Language Processing is Associated with Poor Cognitive Performance in Children with Self-limited Epilepsy with Centrotemporal Spikes

Self-Limited Epilepsy with Centrotemporal Spikes (SeLECTS) is associated with language impairments despite seizures originating in the motor cortex, suggesting aberrant cross-network interactions. Here we tested whether functional connectivity in SeLECTS during language tasks predicts language performance. We recorded high-density EEG from right-handed children with SeLECTS (n=31) and age-matched controls (n=32) during verb generation, repetition, and resting tasks. Phonological awareness was assessed using the Comprehensive Test of Phonological Processing-2. Connectivity between bilateral motor cortices and language regions (the left inferior frontal and superior temporal cortices and their right hemisphere homologues) was measured using weighted Phase Lag Index (wPLI). Children with SeLECTS demonstrated significantly elevated connectivity between motor and language regions during language processing. Motor-to-frontal connectivity was higher in SeLECTS during both verb generation and repetition tasks. Frontal-to-temporal connectivity was elevated specifically during verb generation. Higher interhemispheric connectivity (between the left and right hemispheres) during language tasks strongly predicted worse phonological awareness in children with SeLECTS ({beta}= -40 to -61, all p<0.005), but not controls. Together, we found that children with SeLECTS exhibited pathologically elevated connectivity between motor and language networks that was strongly associated with impaired phonological awareness. These findings identify aberrant interhemispheric connectivity as a pathophysiological mechanism underlying language dysfunction and establish EEG-based connectivity measures as a potential biomarker for guiding targeted neuromodulation therapies to treat cognitive impairments in pediatric epilepsy.

neuroscience↗