Literature DB >> 8150740

In search of the best stimulus: an optimization procedure for finding efficient stimuli in the cat auditory cortex.

I Nelken1, Y Prut, E Vaadia, M Abeles.   

Abstract

Units in the auditory cortex of cats respond to a large variety of stimuli: pure tones, AM- and FM-modulated signals, clicks, wideband noise, natural sounds, and more. However, no single family of sounds was found to be optimal (in the sense that oriented lines are optimal in the visual cortex). The search for optimal complex sounds is hard because of the high dimensionality of the space of interesting sounds. In an effort to overcome this problem, an automatic search procedure for finding efficient stimuli in high-dimensional sound spaces was developed. This procedure chooses the stimuli to be presented according to the responses to past stimuli, trying to increase the strength of the response. The results of applying this method to recordings of population activity in the primary auditory cortex of cats are described. The search was applied to single tones, two-tone stimuli, four-tone stimuli and to a two-dimensional subset of nine-tone stimuli, parametrized by the center frequency and the fixed difference between adjacent frequencies. The method was able to find efficient stimuli, and its performance improved with the dimension of the sound spaces. Efficient stimuli, found in different optimization runs using population activity recorded from the same electrode, often shared similar frequencies and pairs of frequencies, and tended to evoke similar levels of activity. This result indicates that a global analysis of the location of spectral peaks is performed at the level of the auditory cortex.

Entities:  

Mesh:

Year:  1994        PMID: 8150740     DOI: 10.1016/0378-5955(94)90222-4

Source DB:  PubMed          Journal:  Hear Res        ISSN: 0378-5955            Impact factor:   3.208


  9 in total

1.  Searching for optimal sensory signals: iterative stimulus reconstruction in closed-loop experiments.

Authors:  Fredrik Edin; Christian K Machens; Hartmut Schütze; Andreas V M Herz
Journal:  J Comput Neurosci       Date:  2004 Jul-Aug       Impact factor: 1.621

2.  Searching for optimal stimuli: ascending a neuron's response function.

Authors:  Melinda Evrithiki Koelling; Duane Q Nykamp
Journal:  J Comput Neurosci       Date:  2012-05-13       Impact factor: 1.621

3.  Orderly cortical representation of vowels based on formant interaction.

Authors:  F W Ohl; H Scheich
Journal:  Proc Natl Acad Sci U S A       Date:  1997-08-19       Impact factor: 11.205

Review 4.  Hierarchical representations in the auditory cortex.

Authors:  Tatyana O Sharpee; Craig A Atencio; Christoph E Schreiner
Journal:  Curr Opin Neurobiol       Date:  2011-06-23       Impact factor: 6.627

5.  Online stimulus optimization rapidly reveals multidimensional selectivity in auditory cortical neurons.

Authors:  Anna R Chambers; Kenneth E Hancock; Kamal Sen; Daniel B Polley
Journal:  J Neurosci       Date:  2014-07-02       Impact factor: 6.167

6.  Complex spectral interactions encoded by auditory cortical neurons: relationship between bandwidth and pattern.

Authors:  Kevin N O'Connor; Pingbo Yin; Christopher I Petkov; Mitchell L Sutter
Journal:  Front Syst Neurosci       Date:  2010-11-05

7.  Adaptive Stimulus Design for Dynamic Recurrent Neural Network Models.

Authors:  R Ozgur Doruk; Kechen Zhang
Journal:  Front Neural Circuits       Date:  2019-01-22       Impact factor: 3.492

Review 8.  Adaptive stimulus optimization for sensory systems neuroscience.

Authors:  Christopher DiMattina; Kechen Zhang
Journal:  Front Neural Circuits       Date:  2013-06-06       Impact factor: 3.492

9.  The Automatic Neuroscientist: A framework for optimizing experimental design with closed-loop real-time fMRI.

Authors:  Romy Lorenz; Ricardo Pio Monti; Inês R Violante; Christoforos Anagnostopoulos; Aldo A Faisal; Giovanni Montana; Robert Leech
Journal:  Neuroimage       Date:  2016-01-21       Impact factor: 6.556

  9 in total

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