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      Constructing Noise-Invariant Representations of Sound in the Auditory Pathway

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          Abstract

          Along the auditory pathway from auditory nerve to midbrain to cortex, individual neurons adapt progressively to sound statistics, enabling the discernment of foreground sounds, such as speech, over background noise.

          Abstract

          Identifying behaviorally relevant sounds in the presence of background noise is one of the most important and poorly understood challenges faced by the auditory system. An elegant solution to this problem would be for the auditory system to represent sounds in a noise-invariant fashion. Since a major effect of background noise is to alter the statistics of the sounds reaching the ear, noise-invariant representations could be promoted by neurons adapting to stimulus statistics. Here we investigated the extent of neuronal adaptation to the mean and contrast of auditory stimulation as one ascends the auditory pathway. We measured these forms of adaptation by presenting complex synthetic and natural sounds, recording neuronal responses in the inferior colliculus and primary fields of the auditory cortex of anaesthetized ferrets, and comparing these responses with a sophisticated model of the auditory nerve. We find that the strength of both forms of adaptation increases as one ascends the auditory pathway. To investigate whether this adaptation to stimulus statistics contributes to the construction of noise-invariant sound representations, we also presented complex, natural sounds embedded in stationary noise, and used a decoding approach to assess the noise tolerance of the neuronal population code. We find that the code for complex sounds in the periphery is affected more by the addition of noise than the cortical code. We also find that noise tolerance is correlated with adaptation to stimulus statistics, so that populations that show the strongest adaptation to stimulus statistics are also the most noise-tolerant. This suggests that the increase in adaptation to sound statistics from auditory nerve to midbrain to cortex is an important stage in the construction of noise-invariant sound representations in the higher auditory brain.

          Author Summary

          We rarely hear sounds (such as someone talking) in isolation, but rather against a background of noise. When mixtures of sounds and background noise reach the ears, peripheral auditory neurons represent the whole sound mixture. Previous evidence suggests, however, that the higher auditory brain represents just the sounds of interest, and is less affected by the presence of background noise. The neural mechanisms underlying this transformation are poorly understood. Here, we investigate these mechanisms by studying the representation of sound by populations of neurons at three stages along the auditory pathway; we simulate the auditory nerve and record from neurons in the midbrain and primary auditory cortex of anesthetized ferrets. We find that the transformation from noise-sensitive representations of sound to noise-tolerant processing takes place gradually along the pathway from auditory nerve to midbrain to cortex. Our results suggest that this results from neurons adapting to the statistics of heard sounds.

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          Neural correlations, population coding and computation.

          How the brain encodes information in population activity, and how it combines and manipulates that activity as it carries out computations, are questions that lie at the heart of systems neuroscience. During the past decade, with the advent of multi-electrode recording and improved theoretical models, these questions have begun to yield answers. However, a complete understanding of neuronal variability, and, in particular, how it affects population codes, is missing. This is because variability in the brain is typically correlated, and although the exact effects of these correlations are not known, it is known that they can be large. Here, we review studies that address the interaction between neuronal noise and population codes, and discuss their implications for population coding in general.
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            Laminar structure of spontaneous and sensory-evoked population activity in auditory cortex.

            Spontaneous activity plays an important role in the function of neural circuits. Although many similarities between spontaneous and sensory-evoked neocortical activity have been reported, little is known about consistent differences between them. Here, using simultaneously recorded cortical populations and morphologically identified pyramidal cells, we compare the laminar structure of spontaneous and sensory-evoked population activity in rat auditory cortex. Spontaneous and evoked patterns both exhibited sparse, spatially localized activity in layer 2/3 pyramidal cells, with densely distributed activity in larger layer 5 pyramidal cells and putative interneurons. However, the propagation of spontaneous and evoked activity differed, with spontaneous activity spreading upward from deep layers and slowly across columns, but sensory responses initiating in presumptive thalamorecipient layers, spreading rapidly across columns. The similarity of sparseness patterns for both neural events and distinct spread of activity may reflect similarity of local processing and differences in the flow of information through cortical circuits, respectively.
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              A simple white noise analysis of neuronal light responses.

              A white noise technique is presented for estimating the response properties of spiking visual system neurons. The technique is simple, robust, efficient and well suited to simultaneous recordings from multiple neurons. It provides a complete and easily interpretable model of light responses even for neurons that display a common form of response nonlinearity that precludes classical linear systems analysis. A theoretical justification of the technique is presented that relies only on elementary linear algebra and statistics. Implementation is described with examples. The technique and the underlying model of neural responses are validated using recordings from retinal ganglion cells, and in principle are applicable to other neurons. Advantages and disadvantages of the technique relative to classical approaches are discussed.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Biol
                PLoS Biol
                plos
                plosbiol
                PLoS Biology
                Public Library of Science (San Francisco, USA )
                1544-9173
                1545-7885
                November 2013
                November 2013
                12 November 2013
                : 11
                : 11
                : e1001710
                Affiliations
                [1 ]Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
                [2 ]Center for Neural Science, New York University, New York, New York, United States of America
                Cold Spring Harbor Laboratory, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                The author(s) have made the following declarations about their contributions: Conceived and designed the experiments: NCR BDBW AJK JWHS. Performed the experiments: NCR BDBW. Analyzed the data: NCR BDBW. Wrote the paper: NCR BDBW AJK JWHS.

                Article
                PBIOLOGY-D-13-00972
                10.1371/journal.pbio.1001710
                3825667
                24265596
                41371b02-b5ba-4ba1-90bb-28c431fcfff5
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 12 March 2013
                : 4 October 2013
                Page count
                Pages: 18
                Funding
                The Wellcome Trust (Wellcome Principal Research Fellowship to AJK; WT076508AIA) http://www.wellcome.ac.uk/. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article

                Life sciences
                Life sciences

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