Computational Models for the Propagation of Spreading Depression Waves
Spreading Depression (SD) consists on a wave of depressed neural, electrical, activity and near complete depolarization of large neuron populations. It is believed to occur both in compromised and healthy tissue from a broad range of animal species and every structure of the gray matter. Glutamate is long been known to be involved in the ignition of SD. Therefore, despite action potentials are not necessary for the wave propagation, one would expect synaptic processes to play a role in initiating the phenomenon if they are functional. Several detailed and phenomenological computational models have been proposed to simulate the ignition and spread of SD, but few considered synaptic mechanisms. Here we briefly review them, emphasizing macroscopic models that reproduce the wave features and the lack of synaptic transmission. We also propose extensions to a popular model for the wave spread to test whether structural connectivity could aid in stopping the wave and preventing it from engulfing larger portions of the brain.
KeywordsSpreading depression Stroke Migraine Reaction-diffusion model Neural networks
This work was supported by the Instituto de Ciência e Tecnologia (INCT) grant (88887.137596/2017-00) from the INCT call MCTI/CNPq/CAPES/FAPs nr. 16/2014.
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