Biology subjects

Al Harrach, M.

Publications and source records attributed to Al Harrach, M..

6 recordsLinked to original sources

bioRxiv2026

Computational Insights into the tACS Modulation in Healthy and Epileptic Brain Networks

Transcranial Electric stimulation (tES) is a safe and noninvasive technique increasingly used in treating brain disorders. Despite many studies on tES, there is still a lack of understanding of its mechanisms at the microscale network level. This is crucial for optimized parameter selection in therapy approaches such as the treatment of pharmacoresistant epilepsy. In this study, we made use of a recently published neuroinspired microscale model of the neocortex, known as NeoCoMM, and integrated a "Lambda E"-based model of tES. This updated version was used to investigate the acute effects of tES (tDCS and tACS), on the neural activity of various neuron types in both healthy and epileptic brain states. Results showed that in the case of healthy alpha and gamma rhythms, tACS induced electric field entrainment at the peak power frequency of the network oscillations as measured by the Local field Potentials (LFPs). This resonance-like entrainment was independent from the individual firing rate of cell types. For epileptic activity, tACS did not provide consistent results. Cathodal tDCS resulted in a promising decrease in hyperexcitable activity throughout simulations. These results advance our understanding of the impact of tES on network dynamics at both the extracellular and intracellular activity levels. Author summary

neuroscience↗

bioRxiv2024

NeoCoMM: Neocortical Computational Microscale Model

The Neocortical Computational Microscale model (NeoCoMM) is a unique neurophysiologically-inspired software. It offers a friendly graphical user interface that allows for the simulation of the intracellular and extracellular neural activity of a neocortical column. This software provides a realistic framework that can portray the neural activity and underlying cellular mechanisms related to different brain pathologies such as epilepsy. NeoCoMM is capable of (1) simulating the cortical tissue of three different species, (2) visualizing individual cell responses to external stimulation, (3) visualizing the corresponding local field potential, (4) studying the impact of the recording electrode features on simulated signals, and (5) testing various physiological and pathological hypotheses. While NeoCoMM was primarily developed for simulating epileptiform activity, it can also generate healthy brain rhythms or be adapted to other brain disorders.

bioengineering↗

bioRxiv2024

NeoCOMM: A Neocortical Neuroinspired Computational Model for the Reconstruction and Simulation of Epileptiform Events

Understanding the pathophysiological dynamics which underline interictal epileptiform events (IEEs) such as epileptic spikes, spike-and-waves or High-frequency oscillations (HFOs) is of major importance in the context of neocortical refractory epilepsy, as it paves the way for the development of novel therapies. Typically, these events are detected in local field potential (LFP) recordings obtained through depth electrodes during pre-surgical investigations. Although essential, the underlying pathophysiological mechanisms for the generation of these epileptic neuromarkers remain unclear. The aim of this paper is to propose a novel neurophysiologically relevant reconstruction of the neocortical microcircuitry in the context of epilepsy. This reconstruction intends to facilitate the analysis of a comprehensive set of parameters encompassing physiological, morphological, and biophysical aspects that directly impact the generation and recording of different IEEs. Accordingly, a novel microscale computational model of an epileptic neocortical column was introduced. This model incorporates the intricate multilayered structure of the cortex and allows for the simulation of realistic interictal epileptic signals. The proposed model was validated through comparisons with real IEEs recorded using intracranial stereo-electroencephalography (SEEG) signals from both humans and animals. Using the model, the user can recreate epileptiform patterns observed in different species (human, rodent, and mouse) and study the intracellular activity associated with these patterns. Our model allowed us to unravel the relationship between glutamatergic and GABAergic synaptic transmission of the epileptic neural network and the type of generated IEE. Moreover, sensitivity analyses allowed for the exploration of the pathophysiological parameters responsible for the transitions between these events. Finally, the presented modeling framework also provides an Electrode Tissue Model (ETI) that adds realism to the simulated signals and offers the possibility of studying their sensitivity to the electrode characteristics. The model (NeoCoMM) presented in this work can be of great use in different applications since it offers an in silico framework for sensitivity analysis and hypothesis testing. It can also be used as a starting point for more complex studies.

bioengineering↗

bioRxiv2023

Frequency-dependent phase entrainment of cortical cell types during tACS: Converging modeling evidence

BackgroundTranscranial alternating current stimulation (tACS) enables non-invasive modulation of brain activity, holding promise for clinical and research applications. Yet, it remains unclear how the stimulation frequency affects various neuron types. ObjectiveTo quantify the frequency-dependent behavior of key neocortical cell types. MethodsWe used both detailed (anatomical multicompartments) and simplified (three compartments) single-cell modeling approaches based on the Hodgkin-Huxley formalism to study neocortical excitatory and inhibitory cells under various-amplitude tACS frequencies within the 5-50 Hz range at rest and during basal 10 Hz activity. ResultsL5 pyramidal cells exhibited the highest polarizability at DC, ranging from 0.21 to 0.25mm and decaying exponentially with frequency. Inhibitory neurons displayed membrane resonance in the 5-15 Hz range with lower polarizability, although bipolar cells had higher polarizability. Layer 5 PC demonstrated the highest entrainment close to 10 Hz, which decayed with frequency. In contrast, inhibitory neurons entrainment increased with frequency, reaching level akin to PC. Results from simplified models could replicate the phase preferences, while amplitudes tend to follow opposite trends in PC. ConclusiontACS-induced membrane polarization is frequency-dependent, revealing observable resonance behavior. This finding motivates further experimental studies of cell-specific frequency-dependent membrane responses to weak electric stimuli. Whilst optimal phase entrainment of sustained activity is achieved in PC when tACS frequency matches the activity, inhibitory neurons tend to be entrained at higher frequencies. Consequently, this presents the potential for precise, cell-specific targeting. O_LISingle-cell models of frequency response to tACS for a wide variety of neurons C_LIO_LISimplified and morphologically accurate models were compared C_LIO_LIPyramidal cells (PC) show resonant-like response close to intrinsic firing frequency C_LIO_LIEntrainement of GABAergic neurons increases with the frequency of tACS C_LIO_LIMembrane polarization resonance in GABAergic neurons within the 5-15 Hz range C_LI

neuroscience↗

bioRxiv2022

Towards a mesoscale physical modeling framework for stereotactic-EEG recordings

ObjectiveStereotactic-EEG (SEEG) and scalp EEG recordings can be modeled using mesoscale neural mass population models (NMM). However, the relationship between those mathematical models and the physics of the measurements is unclear. In addition, it is challenging to represent SEEG data by combining NMMs and volume conductor models due to the intermediate spatial scale represented by these measurements. ApproachWe provide a framework combining the multicompartmental modeling formalism and a detailed geometrical model to simulate the transmembrane currents that appear in layer 3, 5 and 6 pyramidal cells due to a synaptic input. With this approach, it is possible to realistically simulate the current source density (CSD) depth profile inside a cortical patch due to inputs localized into a single cortical layer and the induced voltage measured by two SEEG contacts using a volume conductor model. Based on this approach, we built a framework to connect the activity of a NMM with a volume conductor model and we simulated an example of SEEG signal as a proof of concept. Main resultsCSD depends strongly on the distribution of the synaptic inputs onto the different cortical layers and the equivalent current dipole strengths display substantial differences (of up to a factor of four in magnitude in our example). Thus, the inputs coming from different neural populations do not contribute equally to the electrophysiological recordings. A direct consequence of this is that the raw output of neural mass models is not a good proxy for electrical recordings. We also show that the simplest CSD model that can accurately reproduce SEEG measurements can be constructed from discrete monopolar sources (one per cortical layer). SignificanceOur results highlight the importance of including a physical model in NMMs to represent measurements. We provide a framework connecting microscale neuron models with the neural mass formalism and with physical models of the measurement process that can improve the accuracy of predicted electrophysiological recordings.

neuroscience↗

bioRxiv2020

A Connectome-Based Approach to Assess Motor Outcome after Neonatal Arterial Ischemic Stroke

Objectivestudies of motor outcome after Neonatal Arterial Ischemic Stroke (NAIS) often rely on lesion mapping using MRI. However, clinical measurements indicate that motor deficit can be different than what would solely be anticipated by the lesion extent and location. Because this may be explained by the cortical disconnections between motor areas due to necrosis following the stroke, the investigation of the motor network can help in the understanding of visual inspection and outcome discrepancy. In this study, we propose to examine the structural connectivity between motor areas in NAIS patients compared to healthy controls in order to define the cortical and subcortical connections that can reflect the motor outcome Methods30 healthy controls and 32 NAIS patients with and without Cerebral Palsy (CP) underwent MRI acquisition and manual assessment. The connectome of all participants was obtained from T1-weighted and diffusion-weighted imaging. Resultssignificant disconnections in the lesioned and contra-lesioned hemispheres of patients were found. Furthermore, significant correlations were detected between the structural connectivity metric of specific motor areas and manuality assessed by the Box and Block Test (BBT) scores in patients. Interpretationusing the connectivity measures of these links the BBT score can be estimated using a multiple linear regression model. In addition, the presence or not of CP can also be predicted using the KNN classification algorithm. According to our results, the structural connectome can be an asset in the estimation of gross manual dexterity and can help uncover structural changes between brain regions related to NAIS.

bioengineering↗