Biology subjects

Rouhl, R. P. W.

Publications and source records attributed to Rouhl, R. P. W..

3 recordsLinked to original sources

bioRxiv2026

Network analysis reveals converging molecular mechanisms in genetic epilepsies

Background: Rare genetic epilepsies are often difficult to diagnose and treat. They can arise from changes in many different genes, and the molecular basis linking these changes to epilepsy remains poorly understood. This complexity makes it difficult to select effective treatments and develop new therapies, leaving many patients with poorly controlled seizures and reduced quality of life Methods: To address this gap, we first identified epilepsy-associated genes and conducted a network-based analysis of biomolecular interactions in genetic epilepsy to identify converging pathways with high translational relevance and potential therapeutic targets. To run the analysis, we constructed a human brain-specific molecular interaction network by integrating all human pathways from the WikiPathways database. HotNet2 was then applied to identify highly perturbed clusters through evidence-based weight diffusion of EAGs in the human brain network. Results: We identified 2,496 epilepsy-associated genes (EAGs) from multiple resources. These genes encode coding for metabolite interconversion enzymes (20%), transporters (15%), and protein-modifying enzymes (11%). Furthermore, the network analysis identified 19 subnetworks with more than two nodes and 125 unique genes. Gene enrichment analysis revealed convergence of processes including action potential, synaptic function, nervous system development, TOR signaling, cilium organization, DNA repair, and cell fate specification. We identified 44 first-order neighbors connecting the subnetworks. By integrating drug-target interactions from DrugBank using CyTargetLinker, we highlighted potential therapeutic targets within the S4 subnetwork, associated with cerebral cortex development, as well as CREB1, a connector between subnetworks. Conclusion: Network analysis organized heterogeneous epilepsy-associated genes into biologically related subnetworks and generated hypotheses for further research.

bioinformatics↗

bioRxiv2022

Spatiotemporal patterns of sleep spindle activity in human anterior thalamus and cortex

Sleep spindles (8 - 16 Hz) are transient electrophysiological events during non-rapid eye movement sleep. While sleep spindles are routinely observed in the cortex using scalp electroencephalography (EEG), recordings of their thalamic counterparts have not been widely studied in humans. Based on a few existing studies, it has been hypothesized that spindles occur as largely local phenomena. We investigated intra-thalamic and thalamocortical spindle co-occurrence, which may underlie thalamocortical communication. We obtained scalp EEG and thalamic recordings from 7 patients that received bilateral deep brain stimulation (DBS) electrodes to the anterior thalamus for the treatment of drug resistant focal epilepsy. Spindles were categorized into subtypes based on their main frequency (i.e., slow (10{+/-}2 Hz) or fast (14{+/-}2 Hz)) and their level of thalamic involvement (spanning one channel, or spreading uni- or bilaterally within the thalamus). For the first time, we contrasted observed spindle patterns with permuted data to estimate random spindle co-occurrence. We found that multichannel spindle patterns were systematically coordinated at the thalamic and thalamocortical level. Importantly, distinct topographical patterns of thalamocortical spindle overlap were associated with slow and fast subtypes of spindles. These observations provide further evidence for coordinated spindle activity in thalamocortical networks. HighlightsO_LISleep spindles were measured in human anterior thalamus and on the scalp C_LIO_LIBoth fast and slow spindles occurred in the anterior thalamus C_LIO_LI> 25% of spindles spanned multiple channels in thalamus and cortex C_LIO_LIA novel statistical approach confirmed that spindle co-occurrences were not random C_LIO_LICortical spindle patterns depended on thalamic involvement and spindle frequency C_LI

neuroscience↗

bioRxiv2019

A novel approach for combining task-dependent gamma with alpha and beta power modulation for enhanced identification of eloquent cortical areas using ECoG in patients with medical-refractory epilepsy

Electrical stimulation mapping (ESM) is the gold standard for identification of \"eloquent\" areas prior to resection of epileptogenic tissue, however, it is time consuming and may cause side effects, especially stimulation-induced seizures and after-discharges. Broadband gamma activity (55 - 200 Hz) recorded with subdural electrocorticography (ECoG) during cognitive tasks has been proposed as an attractive tool for mapping cortical areas with specific function but until now has not proven definitive clinical value. Fewer studies have addressed whether the alpha (8 - 12 Hz) and beta (15 - 25 Hz) band activity could also be used to improve eloquent cortex identification. We compared alpha, beta and broadband gamma activity, and their combination for the identification of eloquent cortical areas defined by ESM. Ten patients participated in a delayed-match-to-sample task, where syllable sounds were matched to visually presented letters and responses given by keyboard. We used a generalized linear model (GLM) approach to find the optimal weighting of low frequency bands and broadband gamma power to predict the ESM categories. Broadband gamma activity increased more in eloquent areas than in non-eloquent areas and this difference had a diagnostic ability (area under (AU) the receiving operating characteristic curve - AUROC) of [~]70%. Both alpha and beta power decreased more in eloquent areas. Alpha power had lower AUROC than broadband gamma while beta had similar AUROC. AUROC was enhanced by the combination of alpha and broadband gamma (3% improvement) and by the combination of beta and broadband gamma (7% improvement) over the use of broadband gamma alone. Further analysis showed that the relative performance of broadband gamma and low frequency bands depended on multiple factors including the time period of the cognitive task, the location of the electrodes and the patients attention to the stimulus. However, the combination of beta band and broadband gamma always gave the best performance. We show how ECoG power modulation from cognitive testing periods can be used to map the probability of eloquence by ESM and how this probability can be used as an aid for optimal ESM planning. We conclude that low frequency power during cognitive testing can contribute to the identification of eloquent areas in patients with focal refractory epilepsy improving its precision but does not replace the need of ESM.\n\nHighlightsO_LIGamma, alpha and beta band activity has significant diagnostic ability to identify ESM defined eloquent cortical areas.\nC_LIO_LIWe present a novel method to combine gamma and low frequency activity for enhanced identification.\nC_LIO_LIWe quantify how identification is dependent on analysis time window, cortical function, and patients attentional engagement.\nC_LIO_LIWith further development, this approach may offer an alternative to ESM mapping with reduced burden for patients.\nC_LI

neuroscience↗