Logarithmic distributions prove that intrinsic learning is Hebbian [version 2; referees: 2 approved]
In this paper, we present data for the lognormal distributions of spike rates, synaptic weights and intrinsic excitability (gain) for neurons in various brain areas, such as auditory or visual cortex, hippocampus, cerebellum, striatum, midbrain nuclei. We find a remarkable consistency of heavy-taile...
Main Author: | Gabriele Scheler |
---|---|
Format: | Article |
Language: | English |
Published: |
F1000 Research Ltd
2017-10-01
|
Series: | F1000Research |
Subjects: | |
Online Access: | https://f1000research.com/articles/6-1222/v2 |
Similar Items
-
A multi-scale computational model of the effects of TMS on motor cortex [version 3; referees: 2 approved]
by: Hyeon Seo, et al.
Published: (2017-05-01) -
A reanalysis of “Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons” [version 1; referees: 2 approved]
by: Rainer Engelken, et al.
Published: (2016-08-01) -
Detecting variable responses in time-series using repeated measures ANOVA: Application to physiologic challenges [version 2; referees: 2 approved]
by: Paul M. Macey, et al.
Published: (2016-07-01) -
Unit testing, model validation, and biological simulation [version 1; referees: 2 approved, 1 approved with reservations]
by: Gopal P. Sarma, et al.
Published: (2016-08-01) -
Learning intrinsic excitability in medium spiny neurons [v2; ref status: indexed, http://f1000r.es/30b]
by: Gabriele Scheler
Published: (2014-02-01)