Work

eCOALIA: Neocortical neural mass model for simulating electroencephalographic signals

Year: 2024

Type: software-paper

Abstract: This paper introduces eCOALIA, a Python-based environment for simulating intracranial local field potentials and scalp electroencephalography (EEG) signals with neural mass models. The source activity is modeled by a novel neural mass model respecting the layered structure of the neocortex. The whole-brain model is composed of coupled neural masses, each representing a brain region at the mesoscale and connected through the human connectome matrix. The forward solution on the electrode contracts is computed using biophysical modeling. eCOALIA allows parameter evolution during a simulation time course and visualizes the local field potential at the level of cortex and EEG electrodes. Advantaged with the neurophysiological modeling, eCOALIA advances the in silico modeling of physiological and pathological brain activity.

Source: SoftwareX

DOI: 10.1016/j.softx.2024.101924

Authors: Elif Köksal-Ersöz, Maxime Yochum, Pascal Benquet, Fabrice Wendling

Institutions: Inserm, Laboratoire Traitement du Signal et de l'Image, Université de Rennes

Language: English

Topic: Neural dynamics and brain function

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $970