Literature DB >> 9603734

Optimizing sound features for cortical neurons.

R C deCharms1, D T Blake, M M Merzenich.   

Abstract

The brain's cerebral cortex decomposes visual images into information about oriented edges, direction and velocity information, and color. How does the cortex decompose perceived sounds? A reverse correlation technique demonstrates that neurons in the primary auditory cortex of the awake primate have complex patterns of sound-feature selectivity that indicate sensitivity to stimulus edges in frequency or in time, stimulus transitions in frequency or intensity, and feature conjunctions. This allows the creation of classes of stimuli matched to the processing characteristics of auditory cortical neurons. Stimuli designed for a particular neuron's preferred feature pattern can drive that neuron with higher sustained firing rates than have typically been recorded with simple stimuli. These data suggest that the cortex decomposes an auditory scene into component parts using a feature-processing system reminiscent of that used for the cortical decomposition of visual images.

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Year:  1998        PMID: 9603734     DOI: 10.1126/science.280.5368.1439

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  132 in total

1.  Spectral-temporal receptive fields of nonlinear auditory neurons obtained using natural sounds.

Authors:  F E Theunissen; K Sen; A J Doupe
Journal:  J Neurosci       Date:  2000-03-15       Impact factor: 6.167

2.  Robust spectrotemporal reverse correlation for the auditory system: optimizing stimulus design.

Authors:  D J Klein; D A Depireux; J Z Simon; S A Shamma
Journal:  J Comput Neurosci       Date:  2000 Jul-Aug       Impact factor: 1.621

3.  The effects of temperature on vesicular supply and release in autaptic cultures of rat and mouse hippocampal neurons.

Authors:  Sonja J Pyott; Christian Rosenmund
Journal:  J Physiol       Date:  2002-03-01       Impact factor: 5.182

4.  Auditory space-time receptive field dynamics revealed by spherical white-noise analysis.

Authors:  R L Jenison; J W Schnupp; R A Reale; J F Brugge
Journal:  J Neurosci       Date:  2001-06-15       Impact factor: 6.167

5.  Nonlinear spectrotemporal sound analysis by neurons in the auditory midbrain.

Authors:  Monty A Escabi; Christoph E Schreiner
Journal:  J Neurosci       Date:  2002-05-15       Impact factor: 6.167

6.  Contrast tuning in auditory cortex.

Authors:  Dennis L Barbour; Xiaoqin Wang
Journal:  Science       Date:  2003-02-14       Impact factor: 47.728

7.  Dynamics of precise spike timing in primary auditory cortex.

Authors:  Mounya Elhilali; Jonathan B Fritz; David J Klein; Jonathan Z Simon; Shihab A Shamma
Journal:  J Neurosci       Date:  2004-02-04       Impact factor: 6.167

8.  Linearity of cortical receptive fields measured with natural sounds.

Authors:  Christian K Machens; Michael S Wehr; Anthony M Zador
Journal:  J Neurosci       Date:  2004-02-04       Impact factor: 6.167

9.  Spike correlation measures that eliminate stimulus effects in response to white noise.

Authors:  Duane Q Nykamp
Journal:  J Comput Neurosci       Date:  2003 Mar-Apr       Impact factor: 1.621

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

Authors:  Craig A Atencio; Tatyana O Sharpee; Christoph E Schreiner
Journal:  J Neurophysiol       Date:  2012-02-08       Impact factor: 2.714

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