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Cortical patterns and gamma genesis are modulated by reversal potentials and gap-junction diffusion

Abstract
In this chapter we describe a continuum model for the cortex that includes both axon-to-dendrite chemical synapses and direct neuron-to-neuron gap-junction diffusive synapses. The effectiveness of chemical synapses is determined by the voltage of the receiving dendrite V relative to its Nernst reversal potential Vrev. Here we explore two alternative strategies for incorporating dendritic reversal potentials, and uncover surprising differences in their stability properties and model dynamics. In the “slow-soma” variant, the (Vrev - V) weighting is applied after the input flux has been integrated at the dendrite, while for “fast-soma”, the weighting is applied directly to the input flux, prior to dendritic integration. For the slow-soma case, we find that–-provided the inhibitory diffusion (via gap-junctions) is sufficiently strong–-the cortex generates stationary Turing patterns of cortical activity. In contrast, the fast-soma destabilizes in favor of standing-wave spatial structures that oscillate at low-gamma frequency ( 30-Hz); these spatial patterns broaden and weaken as diffusive coupling increases, and disappear altogether at moderate levels of diffusion. We speculate that the slow- and fast-soma models might correspond respectively to the idling and active modes of the cortex, with slow-soma patterns providing the default background state, and emergence of gamma oscillations in the fast-soma case signaling the transition into the cognitive state.
Type
Chapter in Book
Type of thesis
Series
Citation
Steyn-Ross, D. A., Steyn-Ross, M. L., Wilson, M. T. & Sleigh, J. W. (2010). Cortical patterns and gamma genesis are modulated by reversal potentials and gap-junction diffusion. In D. A. Steyn-Ross & M. Steyn-Ross (Eds), Modeling Phase Transitions in the Brain. (pp. 271-299). New York, USA: Springer.
Date
2010
Publisher
Springer
Degree
Supervisors
Rights
This is an author’s accepted version of an article published in the book: Modeling Phase Transitions in the Brain. © 2010 Springer Science+Business Media, LLC.