The influence of statistical context on the neural representation of sound

Models of stimulus-response functions have been used for decades in an attempt to understand the complex relationship between a sensory stimulus and the neural response that it elicits. A popular model for characterising auditory function is the spectrotemporal receptive field (STRF), originally due...

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Main Author: Williamson, R. S.
Published: University College London (University of London) 2012
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Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.594317
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spelling ndltd-bl.uk-oai-ethos.bl.uk-5943172015-12-03T03:31:34ZThe influence of statistical context on the neural representation of soundWilliamson, R. S.2012Models of stimulus-response functions have been used for decades in an attempt to understand the complex relationship between a sensory stimulus and the neural response that it elicits. A popular model for characterising auditory function is the spectrotemporal receptive field (STRF), originally due to Aertsen and Johannesma (1980); Aertsen et al. (1980, 1981). However, the STRF model predicts auditory cortical responses to complex sounds very poorly, presumably because the model is linear in the stimulus spectrogram and thus incapable of capturing spectrotemporal nonlinearities in auditory responses. Ahrens et al. (2008a) introduced a multilinear framework, which captures neuron-specific nonlinear effects of stimulus context on spiking responses to complex sounds. In such a framework, contextual effects are interpreted as nonlinear stimulus interactions that modulate the input to a subsequent STRF-like linear filter. We derive various extensions to this framework, and demonstrate that the nonlinear effects of stimulus context are largely inseparable, and fundamentally different for near-simultaneous and delayed non-simultaneous sound energy. In two populations of neurons, recorded from the mouse auditory cortex and thalamus, we show that simultaneous sound energy provides a nonlinear positive (amplifying) gain to the subsequent linear filter, while non-simultaneous sound energy provides a negative (dampening) gain. We demonstrate that this structure is largely responsible for providing a significant increase in the predictive capabilities of the model. Using this framework, we show that nonlinear context dependence differs between cortical fields, consistent with previous studies (Linden et al., 2003). Furthermore, we illustrate how such a model can be used to probe the nonlinear mechanisms that underly the ability of the auditory system to operate in diverse acoustic environments. These results provide a novel extension to the study of receptive fields in multiple brain areas, and extend existing understanding of the way in which stimulus context drives complex auditory responses.570University College London (University of London)http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.594317http://discovery.ucl.ac.uk/1348211/Electronic Thesis or Dissertation
collection NDLTD
sources NDLTD
topic 570
spellingShingle 570
Williamson, R. S.
The influence of statistical context on the neural representation of sound
description Models of stimulus-response functions have been used for decades in an attempt to understand the complex relationship between a sensory stimulus and the neural response that it elicits. A popular model for characterising auditory function is the spectrotemporal receptive field (STRF), originally due to Aertsen and Johannesma (1980); Aertsen et al. (1980, 1981). However, the STRF model predicts auditory cortical responses to complex sounds very poorly, presumably because the model is linear in the stimulus spectrogram and thus incapable of capturing spectrotemporal nonlinearities in auditory responses. Ahrens et al. (2008a) introduced a multilinear framework, which captures neuron-specific nonlinear effects of stimulus context on spiking responses to complex sounds. In such a framework, contextual effects are interpreted as nonlinear stimulus interactions that modulate the input to a subsequent STRF-like linear filter. We derive various extensions to this framework, and demonstrate that the nonlinear effects of stimulus context are largely inseparable, and fundamentally different for near-simultaneous and delayed non-simultaneous sound energy. In two populations of neurons, recorded from the mouse auditory cortex and thalamus, we show that simultaneous sound energy provides a nonlinear positive (amplifying) gain to the subsequent linear filter, while non-simultaneous sound energy provides a negative (dampening) gain. We demonstrate that this structure is largely responsible for providing a significant increase in the predictive capabilities of the model. Using this framework, we show that nonlinear context dependence differs between cortical fields, consistent with previous studies (Linden et al., 2003). Furthermore, we illustrate how such a model can be used to probe the nonlinear mechanisms that underly the ability of the auditory system to operate in diverse acoustic environments. These results provide a novel extension to the study of receptive fields in multiple brain areas, and extend existing understanding of the way in which stimulus context drives complex auditory responses.
author Williamson, R. S.
author_facet Williamson, R. S.
author_sort Williamson, R. S.
title The influence of statistical context on the neural representation of sound
title_short The influence of statistical context on the neural representation of sound
title_full The influence of statistical context on the neural representation of sound
title_fullStr The influence of statistical context on the neural representation of sound
title_full_unstemmed The influence of statistical context on the neural representation of sound
title_sort influence of statistical context on the neural representation of sound
publisher University College London (University of London)
publishDate 2012
url http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.594317
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