Literature DB >> 31163197

Review: Methods of firing rate estimation.

Rimjhim Tomar1.   

Abstract

Neuronal firing rate is traditionally defined as the number of spikes per time window. The concept is essential for the rate coding hypothesis, which is still the most commonly investigated scenario in neuronal activity analysis. The estimation of dynamically changing firing rate from neural data can be challenging due to the variability of spike times, even under identical external conditions; hence a wide range of statistical measures have been employed to solve this particular problem. In this paper, we review established firing rate estimation methods, briefly summarize the technical aspects of each approach and discuss their practical applications.
Copyright © 2019 Elsevier B.V. All rights reserved.

Keywords:  Bayesian rule; Firing rate; Kernel smoothing; Spike train; Time histogram

Mesh:

Year:  2019        PMID: 31163197     DOI: 10.1016/j.biosystems.2019.103980

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  2 in total

1.  Highly Stretchable Hydrogels as Wearable and Implantable Sensors for Recording Physiological and Brain Neural Signals.

Authors:  Quanduo Liang; Xiangjiao Xia; Xiguang Sun; Dehai Yu; Xinrui Huang; Guanghong Han; Samuel M Mugo; Wei Chen; Qiang Zhang
Journal:  Adv Sci (Weinh)       Date:  2022-03-31       Impact factor: 17.521

2.  Fano Factor: A Potentially Useful Information.

Authors:  Kamil Rajdl; Petr Lansky; Lubomir Kostal
Journal:  Front Comput Neurosci       Date:  2020-11-20       Impact factor: 2.380

  2 in total

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