Literature DB >> 16221863

The contribution of spike threshold to acoustic feature selectivity, spike information content, and information throughput.

Monty A Escabí1, Reza Nassiri, Lee M Miller, Christoph E Schreiner, Heather L Read.   

Abstract

Hypotheses of sensory coding range from the notion of nonlinear "feature detectors" to linear rate coding strategies. Here, we report that auditory neurons exhibit a novel trade-off in the relationship between sound selectivity and the information that can be communicated to a postsynaptic cell. Recordings from the cat inferior colliculus show that neurons with the lowest spike rates reliably signal the occurrence of stereotyped stimulus features, whereas those with high response rates exhibit lower selectivity. The highest information conveyed by individual action potentials comes from neurons with low spike rate and high selectivity. Surprisingly, spike information is inversely related to spike rates, following a trend similar to that of feature selectivity. Information per time interval, however, was proportional to measured spike rates. A neuronal model based on the spike threshold of the synaptic drive accurately accounts for this trade-off: higher thresholds enhance the spiking fidelity at the expense of limiting the total communicated information. Such a constraint on the specificity and throughput creates a continuum in the neural code with two extreme forms of information transfer that likely serve complementary roles in the representation of the auditory environment.

Mesh:

Year:  2005        PMID: 16221863      PMCID: PMC6725702          DOI: 10.1523/JNEUROSCI.1804-05.2005

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


  25 in total

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Journal:  J Neurosci       Date:  2010-10-06       Impact factor: 6.167

2.  The accuracy of membrane potential reconstruction based on spiking receptive fields.

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3.  Receptive field dimensionality increases from the auditory midbrain to cortex.

Authors:  Craig A Atencio; Tatyana O Sharpee; Christoph E Schreiner
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4.  Precise feature based time scales and frequency decorrelation lead to a sparse auditory code.

Authors:  Chen Chen; Heather L Read; Monty A Escabí
Journal:  J Neurosci       Date:  2012-06-20       Impact factor: 6.167

5.  Preserving information in neural transmission.

Authors:  Lawrence C Sincich; Jonathan C Horton; Tatyana O Sharpee
Journal:  J Neurosci       Date:  2009-05-13       Impact factor: 6.167

6.  Spectrotemporal processing differences between auditory cortical fast-spiking and regular-spiking neurons.

Authors:  Craig A Atencio; Christoph E Schreiner
Journal:  J Neurosci       Date:  2008-04-09       Impact factor: 6.167

7.  Context-dependent coding in single neurons.

Authors:  Rebecca A Mease; SangWook Lee; Anna T Moritz; Randall K Powers; Marc D Binder; Adrienne L Fairhall
Journal:  J Comput Neurosci       Date:  2014-07-03       Impact factor: 1.621

8.  Spectral and temporal modulation tradeoff in the inferior colliculus.

Authors:  Francisco A Rodríguez; Heather L Read; Monty A Escabí
Journal:  J Neurophysiol       Date:  2009-12-16       Impact factor: 2.714

9.  Encoding of temporal information by timing, rate, and place in cat auditory cortex.

Authors:  Kazuo Imaizumi; Nicholas J Priebe; Tatyana O Sharpee; Steven W Cheung; Christoph E Schreiner
Journal:  PLoS One       Date:  2010-07-19       Impact factor: 3.240

10.  A threshold equation for action potential initiation.

Authors:  Jonathan Platkiewicz; Romain Brette
Journal:  PLoS Comput Biol       Date:  2010-07-08       Impact factor: 4.475

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