Title
The generation of rhythms within a cortical region: Analysis of a neural mass model.
Abstract
Rhythms in brain electrical activity are assumed to play a significant role in many cognitive and perceptual processes. It is thus of great value to analyze these rhythms and their mutual relationships in large scale models of cortical regions. In the present work, we modified the neural mass model by Wendling et al. (Eur. J. Neurosci. 15 (2002) 1499–1508) by including a new inhibitory self-loop among GABAA,fast interneurons. A theoretical analysis was performed to demonstrate that, thanks to this loop, GABAA,fast interneurons can produce a γ rhythm in the power spectral density (PSD) even without the participation of the other neural populations. Then, the model of a whole cortical region, built upon four interconnected neural populations (pyramidal cells, excitatory, GABAA,slow and GABAA,fast interneurons) was investigated by changing the internal connectivity parameters. Results show that different rhythm combinations (β and γ, α and γ, or a wide spectrum) can be obtained within the same region by simply altering connectivity values, without the need to change synaptic kinetics. Finally, two or three cortical regions were connected by using different topologies of long range connections. Results show that long-range connections directed from pyramidal neurons to GABAA,fast interneurons are the most efficient to transmit rhythms from one region to another. In this way, PSD with three or four peaks can be obtained using simple connectivity patterns. The model can be of value to gain a deeper insight into the mechanisms involved in the generation of γ rhythms and provide a better understanding of cortical EEG spectra.
Year
DOI
Venue
2010
10.1016/j.neuroimage.2009.12.084
NeuroImage
Keywords
Field
DocType
EEG rhythms,Connectivity,Neural mass models,GABAA,fast inhibitory interneurons,Power spectral density
Developmental psychology,Neuroscience,Psychology,Excitatory postsynaptic potential,GABAA receptor,Inhibitory postsynaptic potential,Brain electrical activity,Spectral density,Region analysis,Rhythm,Electroencephalography
Journal
Volume
Issue
ISSN
52
3
1053-8119
Citations 
PageRank 
References 
26
1.21
18
Authors
3
Name
Order
Citations
PageRank
M. Ursino111113.13
Filippo Cona2585.89
Melissa Zavaglia3796.83