vix.ing · top · new · best · stats · spec

Selective Inhibition and Recruitment of Linear-Threshold Thalamocortical Networks

2022/01/03 by Michael McCreesh, Jorge Cortés, McCreesh, Michael +1
Computer Science · Neuroscience · #FOS: Biological sciences #FOS: Electrical engineering #Functional Brain Connectivity Studies #Neural dynamics and brain function #Neurons and Cognition (q-bio.NC) #Nonlinear Dynamics and Pattern Formation #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2201.00850

openalex publication_date 2022/01/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Neuroscientific evidence shows that for most brain networks all pathways between cortical regions either pass through the thalamus or a transthalamic parallel route exists for any direct corticocortical connection. This paper seeks to formally study the dynamical behavior of the resulting thalamocortical brain networks with a view to characterizing the inhibitory role played by the thalamus and its benefits. We employ a linear-threshold mesoscale model for individual brain subnetworks and study both hierarchical and star-connected thalamocortical networks. Using tools from singular perturbation theory and switched systems, we show that selective inhibition and recruitment can be achieved in such networks through a combination of feedback and feedforward control. Various simulations throughout the exposition illustrate the benefits resulting from the presence of the thalamus regarding failsafe mechanisms, required control magnitude, and network performance.

Related