Modeling impairment of ionic regulation with extended Adaptive Exponential integrate-and-fire models.

To model the dynamics of neuron membrane excitability many models can be considered, from the most biophysically detailed to the highest level of phenomenological description. Recent works at the single neuron level have shown the importance of taking into account the evolution of slow variables such as ionic concentration. A reduction of such a model to models of the integrate-and-fire family is interesting to then go to large network models.

Symmetry breaking organizes the brain's resting state manifold.

Spontaneously fluctuating brain activity patterns that emerge at rest have been linked to the brain's health and cognition. Despite detailed descriptions of the spatio-temporal brain patterns, our understanding of their generative mechanism is still incomplete. Using a combination of computational modeling and dynamical systems analysis we provide a mechanistic description of the formation of a resting state manifold via the network connectivity.

Non-invasive Temporal Interference Stimulation of the Hippocampus Suppresses Epileptic Biomarkers in Patients with Epilepsy: Biophysical Differences between Kilohertz and Amplitude Modulated Stimulation.

Medication refractory focal epilepsy creates a significant challenge, with approximately 30% of patients ineligible for surgery due to the involvement of eloquent cortex in the epileptogenic network. For such patients with limited surgical options, electrical neuromodulation represents a promising alternative therapy. In this study, we investigate the potential of non-invasive temporal interference (TI) electrical stimulation to reduce epileptic biomarkers in patients with epilepsy by comparing intracerebral recordings obtained before, during, and after TI stimulation, to recordings during low and high kHz frequency (HF) sham stimulation.

Brain sodium MRI-derived priors support the estimation of epileptogenic zones using personalized model-based methods in epilepsy.

Patients presenting with drug-resistant epilepsy are eligible for surgery aiming to remove the regions involved in the production of seizure activities, the so-called epileptogenic zone network (EZN). Thus the accurate estimation of the EZN is crucial. Data-driven, personalized virtual brain models derived from patient-specific anatomical and functional data are used in Virtual Epileptic Patient (VEP) to estimate the EZN via optimization methods from Bayesian inference.

White matter changes after Gamma Knife Capsulotomy in patients with intractable obsessive-compulsive disorder.

Background: Anterior capsulotomy is one of the therapeutic options for refractory obsessive-compulsive disorder (OCD). Safety and efficacy of Gamma Knife Capsulotomy (GKC) have been demonstrated in the past.

Objective: To characterize changes induced by GKC using a fixel-based analysis (FBA) and possible predictors of efficacy.