Literature DB >> 14714819

Modulation spectra of natural sounds and ethological theories of auditory processing.

Nandini C Singh1, Frédéric E Theunissen.   

Abstract

The modulation statistics of natural sound ensembles were analyzed by calculating the probability distributions of the amplitude envelope of the sounds and their time-frequency correlations given by the modulation spectra. These modulation spectra were obtained by calculating the two-dimensional Fourier transform of the autocorrelation matrix of the sound stimulus in its spectrographic representation. Since temporal bandwidth and spectral bandwidth are conjugate variables, it is shown that the joint modulation spectrum of sound occupies a restricted space: sounds cannot have rapid temporal and spectral modulations simultaneously. Within this restricted space, it is shown that natural sounds have a characteristic signature. Natural sounds, in general, are low-passed, showing most of their modulation energy for low temporal and spectral modulations. Animal vocalizations and human speech are further characterized by the fact that most of the spectral modulation power is found only for low temporal modulation. Similarly, the distribution of the amplitude envelopes also exhibits characteristic shapes for natural sounds, reflecting the high probability of epochs with no sound, systematic differences across frequencies, and a relatively uniform distribution for the log of the amplitudes for vocalizations. It is postulated that the auditory system as well as engineering applications may exploit these statistical properties to obtain an efficient representation of behaviorally relevant sounds. To test such a hypothesis we show how to create synthetic sounds with first and second order envelope statistics identical to those found in natural sounds.

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Year:  2003        PMID: 14714819     DOI: 10.1121/1.1624067

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  198 in total

1.  Neural response to bird's own song and tutor song in the zebra finch field L and caudal mesopallium.

Authors:  N Amin; J A Grace; F E Theunissen
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2004-04-03       Impact factor: 1.836

2.  Sound-identity processing in early areas of the auditory ventral stream in the macaque.

Authors:  Paweł Kuśmierek; Michael Ortiz; Josef P Rauschecker
Journal:  J Neurophysiol       Date:  2011-11-30       Impact factor: 2.714

3.  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

4.  Ability of primary auditory cortical neurons to detect amplitude modulation with rate and temporal codes: neurometric analysis.

Authors:  Jeffrey S Johnson; Pingbo Yin; Kevin N O'Connor; Mitchell L Sutter
Journal:  J Neurophysiol       Date:  2012-03-14       Impact factor: 2.714

5.  Sensitivity to temporal modulation rate and spectral bandwidth in the human auditory system: MEG evidence.

Authors:  Yadong Wang; Nai Ding; Nayef Ahmar; Juanjuan Xiang; David Poeppel; Jonathan Z Simon
Journal:  J Neurophysiol       Date:  2011-10-05       Impact factor: 2.714

6.  A quantitative analysis of information about past and present stimuli encoded by spikes of A1 neurons.

Authors:  Stefan Klampfl; Stephen V David; Pingbo Yin; Shihab A Shamma; Wolfgang Maass
Journal:  J Neurophysiol       Date:  2012-06-13       Impact factor: 2.714

7.  Role of the zebra finch auditory thalamus in generating complex representations for natural sounds.

Authors:  Noopur Amin; Patrick Gill; Frédéric E Theunissen
Journal:  J Neurophysiol       Date:  2010-06-16       Impact factor: 2.714

8.  Automating the design of informative sequences of sensory stimuli.

Authors:  Jeremy Lewi; David M Schneider; Sarah M N Woolley; Liam Paninski
Journal:  J Comput Neurosci       Date:  2010-06-16       Impact factor: 1.621

9.  Recovering sound sources from embedded repetition.

Authors:  Josh H McDermott; David Wrobleski; Andrew J Oxenham
Journal:  Proc Natl Acad Sci U S A       Date:  2011-01-03       Impact factor: 11.205

10.  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

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