Neural mass models for mimicking brain signals – impact of extrinsic inputs on interneurons and dendritic time constants
© Spiegler and Knösche; licensee BioMed Central Ltd. 2009
Published: 13 July 2009
In order to reproduce brain signals like electroencephalography (EEG), one has to consider biological inspired and plausible models like neural mass models. The neuronal currents underlying the generation of EEG are assumed to be generated by the postsynaptic potentials (PSPs) of pyramidal cells. A cortical area can be described by three neural masses: pyramidal cells, excitatory and inhibitory interneurons, strongly interacting by positive and negative feedback loops . Due to the cortical organization, short- and long-range connections establish afferent pathways on interneurons, which are of major importance for top-down and lateral connections . To date, there is no systematic analysis of the impact of extrinsic inputs on pyramidal cells and interneurons.
In our model we consider extrinsic inputs on all three neural masses. With the bifurcation theory  we analyzed the impact of extrinsic inputs and dendritic parameters. We produced bifurcation diagrams, which are suitable compact representations of system states. They allow for far reaching predictions concerning the possible dynamic behavior.
A whole range of new dynamic phenomena could be described, which potentially form the basis for important phenomena in brain function and the associated features in brain signals. We found various biologically interesting branches of limit cycles, providing sudden entering into orbits by small variation of inputs for instance. Extrinsic inputs on interneurons can change the behavior of the system dramatically, e.g. forcing the system to produce various oscillatory activities. The impact of afferents on inhibitory interneurons is greater than on excitatory interneurons. Activities like alpha rhythms can be changed but not suppressed by inputs on inhibitory interneurons.
- Jansen BH, Rit VG: Electroencephalogram and visual evoked potential generation in a mathematical model of coupled cortical columns. Biol Cybern. 1995, 73: 357-366. 10.1007/BF00199471.PubMedView ArticleGoogle Scholar
- Felleman DJ, van Essen DC: Distributed Hierarchical Processing in the Primate Cerebral Cortex. Cereb Cortex. 1991, 1: 1-47. 10.1093/cercor/1.1.1-a.PubMedView ArticleGoogle Scholar
- Kuznetsov YA: Elements of Applied Bifurcation Theory. 1998, Berlin: Springer-Verlag, 2Google Scholar
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