Comparison of dynamical states of random networks with human EEG

Existing models of EEG have mainly focused on relations to network dynamics characterized by firing rates [L. de Arcangelis, H.J. Herrmann, C. Perrone-Capano, Activity-dependent brain model explaining EEG spectra, arXiv:q-bio.NC/0411043 v1, 23 Nov 2004; D.T. Liley, D.M. Alexander, J.J. Wright, M.D. Aldous, Alpha rhythm emerges from large-scale networks of realistically coupled multicompartmental model cortical neurons, Network 10(1) (1999) 79–92; O. David, J.K. Friston, A neural mass model for MEG/EEG: coupling and neuronal dynamics, NeuroImage 20 (2003) 1743–1755]. Generally, these models assume that there exists a linear mapping between network firing rates and EEG states. However, firing rate is only one of several descriptors for network activity states. Other relevant descriptors are synchrony and irregularity of firing patterns [N. Brunel, Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons, J. Comput. Neurosci. 8(3) (2000) 183–208]. To...

• Type: Journal
• Year: 2007
• Where: IJON
• Authors: Ralph Meier, Arvind Kumar, Andreas Schulze-Bonhage, Ad Aertsen
• Keywords: EEG States, IJON 2007, Model Cortical Neurons, Network Activity