Capturing Multiple Timescales of Adaptation to Second-Order Statistics With Generalized Linear Models: Gain Scaling and Fractional Differentiation

Capturing Multiple Timescales of Adaptation to Second-Order Statistics With Generalized Linear Models: Gain Scaling and Fractional Differentiation

Single neurons can dynamically change the gain of their spiking responses to take into account shifts in stimulus variance. Moreover, gain adaptation can occur across multiple timescales. Here, we examine the ability of a simple statistical model of spike trains, the generalized linear model (GLM),...

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Bibliographic Details
Main Authors: Kenneth W. Latimer, Adrienne L. Fairhall
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-09-01
Series:Frontiers in Systems Neuroscience
Subjects:
adaptation
gain scaling
fractional differentiation
generalized linear model (GLM)
Hodgkin and Huxley model
Online Access:https://www.frontiersin.org/article/10.3389/fnsys.2020.00060/full

Internet

https://www.frontiersin.org/article/10.3389/fnsys.2020.00060/full

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