Literature DB >> 16421300

Spike count reliability and the Poisson hypothesis.

Asohan Amarasingham1, Ting-Li Chen, Stuart Geman, Matthew T Harrison, David L Sheinberg.   

Abstract

The variability of cortical activity in response to repeated presentations of a stimulus has been an area of controversy in the ongoing debate regarding the evidence for fine temporal structure in nervous system activity. We present a new statistical technique for assessing the significance of observed variability in the neural spike counts with respect to a minimal Poisson hypothesis, which avoids the conventional but troubling assumption that the spiking process is identically distributed across trials. We apply the method to recordings of inferotemporal cortical neurons of primates presented with complex visual stimuli. On this data, the minimal Poisson hypothesis is rejected: the neuronal responses are too reliable to be fit by a typical firing-rate model, even allowing for sudden, time-varying, and trial-dependent rate changes after stimulus onset. The statistical evidence favors a tightly regulated stimulus response in these neurons, close to stimulus onset, although not further away.

Mesh:

Year:  2006        PMID: 16421300      PMCID: PMC6675384          DOI: 10.1523/JNEUROSCI.2948-05.2006

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  24 in total

Review 1.  Conditional modeling and the jitter method of spike resampling.

Authors:  Asohan Amarasingham; Matthew T Harrison; Nicholas G Hatsopoulos; Stuart Geman
Journal:  J Neurophysiol       Date:  2011-10-26       Impact factor: 2.714

Review 2.  Neurophysiological and computational principles of cortical rhythms in cognition.

Authors:  Xiao-Jing Wang
Journal:  Physiol Rev       Date:  2010-07       Impact factor: 37.312

3.  Testing the odds of inherent vs. observed overdispersion in neural spike counts.

Authors:  Wahiba Taouali; Giacomo Benvenuti; Pascal Wallisch; Frédéric Chavane; Laurent U Perrinet
Journal:  J Neurophysiol       Date:  2015-10-07       Impact factor: 2.714

4.  Layer- and cell-type-specific suprathreshold stimulus representation in rat primary somatosensory cortex.

Authors:  C P J de Kock; R M Bruno; H Spors; B Sakmann
Journal:  J Physiol       Date:  2007-02-22       Impact factor: 5.182

5.  A rate and history-preserving resampling algorithm for neural spike trains.

Authors:  Matthew T Harrison; Stuart Geman
Journal:  Neural Comput       Date:  2009-05       Impact factor: 2.026

6.  Relating neuronal firing patterns to functional differentiation of cerebral cortex.

Authors:  Shigeru Shinomoto; Hideaki Kim; Takeaki Shimokawa; Nanae Matsuno; Shintaro Funahashi; Keisetsu Shima; Ichiro Fujita; Hiroshi Tamura; Taijiro Doi; Kenji Kawano; Naoko Inaba; Kikuro Fukushima; Sergei Kurkin; Kiyoshi Kurata; Masato Taira; Ken-Ichiro Tsutsui; Hidehiko Komatsu; Tadashi Ogawa; Kowa Koida; Jun Tanji; Keisuke Toyama
Journal:  PLoS Comput Biol       Date:  2009-07-10       Impact factor: 4.475

7.  Ambiguity and nonidentifiability in the statistical analysis of neural codes.

Authors:  Asohan Amarasingham; Stuart Geman; Matthew T Harrison
Journal:  Proc Natl Acad Sci U S A       Date:  2015-05-01       Impact factor: 11.205

8.  Monosynaptic inference via finely-timed spikes.

Authors:  Jonathan Platkiewicz; Zachary Saccomano; Sam McKenzie; Daniel English; Asohan Amarasingham
Journal:  J Comput Neurosci       Date:  2021-01-28       Impact factor: 1.621

9.  Flexible models for spike count data with both over- and under- dispersion.

Authors:  Ian H Stevenson
Journal:  J Comput Neurosci       Date:  2016-03-23       Impact factor: 1.621

10.  Beyond Poisson: increased spike-time regularity across primate parietal cortex.

Authors:  Gaby Maimon; John A Assad
Journal:  Neuron       Date:  2009-05-14       Impact factor: 17.173

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