ML Anthology

Linearization of F-I Curves by Adaptation

Bard Ermentrout
NeCo 1998 pp. 1721-1729
doi:10.1162/089976698300017106 /neco/1998/ermentrout1998neco-linearization/

Abstract

We show that negative feedback to highly nonlinear frequency-current (F-I) curves results in an effective linearization. (By highly nonlinear we mean that the slope at threshold is infinite or very steep.) We then apply this to a specific model for spiking neurons and show that the details of the adaptation mechanism do not affect the results. The crucial points are that the adaptation is slow compared to other processes and the unadapted F-I curve is highly nonlinear.

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Cite

Text

Ermentrout. "Linearization of F-I Curves by Adaptation." Neural Computation, 1998. doi:10.1162/089976698300017106

Markdown

[Ermentrout. "Linearization of F-I Curves by Adaptation." Neural Computation, 1998.](https://mlanthology.org/neco/1998/ermentrout1998neco-linearization/) doi:10.1162/089976698300017106

BibTeX

@article{ermentrout1998neco-linearization,
  title     = {{Linearization of F-I Curves by Adaptation}},
  author    = {Ermentrout, Bard},
  journal   = {Neural Computation},
  year      = {1998},
  pages     = {1721-1729},
  doi       = {10.1162/089976698300017106},
  volume    = {10},
  url       = {https://mlanthology.org/neco/1998/ermentrout1998neco-linearization/}
}