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미디어 커버리지1건1개 미디어
arXiv Q-Bio
학술
기타

Spike-frequency and h-current based adaptation are dynamically equivalent in a Wilson-Cowan field model

arXiv Q-Bio
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Abstract

During slow-wave sleep, the brain produces traveling waves of slow oscillations (SOs; $\leq 2$ Hz), characterized by the propagation of alternating high- and low-activity states.

The question of internal mechanisms that modulate traveling waves of SOs is still unanswered although it is established that it is an adaptation mechanism that mediates them.

One mechanism investigated is spike-frequency adaptation, a hyperpolarizing feedback current that is activated during periods of high-activity.

An alternative mechanism is based on hyperpolarization-activated currents, which are positive feedback currents that are activated in low-activity states.

Both adaptation mechanisms were shown to feature SO-like dynamics in neuronal populations, and the inclusion of a spatial domain seems to enhance observable differences in their effects.

To investigate this in detail, we examine a spatially extended two-population Wilson-Cowan model with local spatial coupling and the excitatory populations equipped with either one of the two adaptation mechanisms.

We describe them with the same dynamical equation and include the inverse mode of action by changing the signs of adaptation strength and gain.

We show that the dynamical systems are mathematically equivalent under a compensatory external input, which depends on the adaptation strength, leading to a shift in state space of the otherwise equivalent bifurcation structure.

Strong enough adaptation is required to induce traveling waves.

Additionally, adaptation modulates the properties of the spatio-temporal activity patterns, such as temporal and spatial frequencies, and the speed of the traveling waves, all of which increase with increasing strength.

Though being dynamically equivalent, our results also explain why location-dependent variations in feedback strength cause differences in the propagation of traveling waves between both adaptation mechanisms.

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