Search bioRxiv⌕ Search

Biology subjects

Weiler, M.

Publications and source records attributed to Weiler, M..

2 recordsLinked to original sources
bioRxiv2023

Early alterations of thalamo- and hippocampo-cortical functional connectivity are biomarkers of epileptogenesis after traumatic brain injury

The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) study is a prospective multicenter clinical observational study to identify early biomarkers of epileptogenesis after moderate-to-severe traumatic brain injury (TBI). In this preliminary analysis of 37 patients, using a seed-based approach applied to acute (i.e., [&le;] 14 days) functional magnetic resonance (MRI) imaging data, we directly test the hypothesis that the epileptogenic process following brain trauma is associated with functional changes within hippocampal and thalamo-cortical networks. Additionally, we hypothesize that the network connectivity involving thalamic and hippocampal circuits underlying early and late-onset epileptogenesis would differ. The three groups did not differ by sex distribution ({chi}2(2) = 1.8, p = .407), age (H(2) = 4.227, p = .121), admission Glasgow Coma Scale (H(2) = 3.850, p = .146) or postinjury day of the MRI session (H(2) = .695, p = .706). The primary finding is that patients with early seizures, a sign of early epileptogenesis, exhibited pattern 1, namely, an increased positive connectivity in thalamic and hippocampal networks, as compared to patients who had no epileptogenesis, or late epileptogenesis (p < .05, FWE-corrected at the cluster level). In contrast, this finding was absent in those patients who exhibited late seizures, with the latter group displayed pattern 2, namely, a lower positive and higher negative connectivity in the hippocampal network, as compared to patients who had no signs of epileptogenesis (p < .05, FWE-corrected at the cluster level). Patients with either pattern 1 or pattern 2 connectivity profiles in thalamic and hippocampal networks were significantly predictive of late (i.e., between 7 days and 2 years) epileptogenesis following brain trauma. A Receiver Operating Characteristic (ROC) Curve analysis model that included thalamic and hippocampal functional connectivity values presented an Area Under the Curve (AUC) 87.7, specificity 86.7, and sensitivity 84.6. Our results indicate that dysfunction in hippocampal and thalamo-cortical networks are potential biomarkers for early and late epileptogenesis following a TBI.

neuroscience↗
bioRxiv2021

Evaluating denoising strategies in resting-state fMRI in traumatic brain injury (EpiBioS4Rx)

ObjectiveResting-state functional MRI is increasingly used in the clinical setting and is now included in some diagnostic guidelines for severe brain injury patients. However, to ensure high-quality data, one should mitigate fMRI-related noise typical of this population. Therefore, we aimed to evaluate the ability of different preprocessing strategies to mitigate noise-related signal (i.e., in-scanner movement and physiological noise) in functional connectivity of traumatic brain injury patients. MethodsWe applied nine commonly used denoising strategies, combined into 17 pipelines, to 88 traumatic brain injury patients from the Epilepsy Bioinformatics Study for Anti-epileptogenic Therapy clinical trial (EpiBioS4Rx). Pipelines were evaluated by three quality control metrics across three exclusion regimes based on the participants head movement profile. ResultsWhile no pipeline eliminated noise effects on functional connectivity, some pipelines exhibited relatively high effectiveness depending on the exclusion regime. Once high-motion participants were excluded, the choice of denoising pipeline becomes secondary - although this strategy leads to substantial data loss. Pipelines combining spike regression with physiological regressors were the best performers, whereas pipelines that used automated data driven methods performed comparatively worse. ConclusionIn this study, we report the first large-scale evaluation of denoising pipelines aimed at reducing noise-related functional connectivity in a clinical population known to be highly susceptible to in-scanner motion and significant anatomical abnormalities. If resting-state functional magnetic resonance is to be a successful clinical technique, it is crucial that procedures mitigating the effect of noise be systematically evaluated in the most challenging populations, such as traumatic brain injury datasets.

neuroscience↗