Topic: neural mass model

The neurobiological mechanisms of arousal and anesthesia remain poorly understood. Recent evidence highlights the key role of interactions between the cerebral cortex and the diffusely projecting matrix thalamic nuclei. Here, we interrogate these processes in a whole-brain corticothalamic neural mass model endowed with targeted and diffusely projecting thalamocortical nuclei inferred from empirical data. This model captures key features seen in propofol anesthesia, including diminished network integration, lowered state diversity, impaired susceptibility to perturbation, and decreased corticoc

Coherent oscillations of neural activity are ubiquitous across brain spatial and temporal scales and have been associated with the formation of sensory or behavioral representations [1]. Refined experimental techniques report today a new complexity of this oscillatory activity, especially in the gamma (30-100 Hz) band. Indeed, the frequency of these oscillations shows a large variability through time [2], questioning the classical view of γ oscillations being separated into different frequency bands. Oscillations appear instead in bursts characterised by rapid, synchronous neuronal firing. Thi

Interneurons, ubiquitous in the central nervous system, form networks connected through both inhibitory chemical synapses and gap junctions. These networks are essential for regulating neuronal activity notably by regulating temporally patterned dynamic states. We aim to understand the mechanisms that allow for synchronization to arise in networks of interneurons with both chemical synapses and electrical gap junctions (Panel 1). To this end, we use the exact mean-field reduction, often referred to as the “neural mass model” in the literature (Montbrio et al, PRX, 2015). We first analyse a sin

Dynamic Causal Modeling (DCM) is commonly used for identifying neural circuit models from neuroimaging data to deduce causal neural interactions (Penny et al., 2011). Although previous studies have applied DCM to decision-making tasks, it is unclear whether DCM can reveal multistable dynamic states associated with choices (Wong and Wang, 2006). Here, we developed a two-column cortical fully self-feedback neural mass model (FSM) comprising two excitatory and one inhibitory neural populations, and inputs to both inhibitory and excitatory populations (Roach et al., 2023) with lateral connections