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      Adaptation to Stimulus Statistics in the Perception and Neural Representation of Auditory Space

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          Summary

          Sensory systems are known to adapt their coding strategies to the statistics of their environment, but little is still known about the perceptual implications of such adjustments. We investigated how auditory spatial processing adapts to stimulus statistics by presenting human listeners and anesthetized ferrets with noise sequences in which interaural level differences (ILD) rapidly fluctuated according to a Gaussian distribution. The mean of the distribution biased the perceived laterality of a subsequent stimulus, whereas the distribution's variance changed the listeners' spatial sensitivity. The responses of neurons in the inferior colliculus changed in line with these perceptual phenomena. Their ILD preference adjusted to match the stimulus distribution mean, resulting in large shifts in rate-ILD functions, while their gain adapted to the stimulus variance, producing pronounced changes in neural sensitivity. Our findings suggest that processing of auditory space is geared toward emphasizing relative spatial differences rather than the accurate representation of absolute position.

          Highlights

          ► Perceptual and neural adaptation were studied using near-identical paradigms ► Changing the variance of an acoustic signal affects perception ► Close correspondence between perceptual adaptation and ILD coding in the midbrain ► Coding of spatial cues seems to be geared toward representing relative differences

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          Most cited references 60

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          Efficiency and ambiguity in an adaptive neural code.

          We examine the dynamics of a neural code in the context of stimuli whose statistical properties are themselves evolving dynamically. Adaptation to these statistics occurs over a wide range of timescales-from tens of milliseconds to minutes. Rapid components of adaptation serve to optimize the information that action potentials carry about rapid stimulus variations within the local statistical ensemble, while changes in the rate and statistics of action-potential firing encode information about the ensemble itself, thus resolving potential ambiguities. The speed with which information is optimized and ambiguities are resolved approaches the physical limit imposed by statistical sampling and noise.
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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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              Reliability of spike timing in neocortical neurons.

              It is not known whether the variability of neural activity in the cerebral cortex carries information or reflects noisy underlying mechanisms. In an examination of the reliability of spike generation using recordings from neurons in rat neocortical slices, the precision of spike timing was found to depend on stimulus transients. Constant stimuli led to imprecise spike trains, whereas stimuli with fluctuations resembling synaptic activity produced spike trains with timing reproducible to less than 1 millisecond. These data suggest a low intrinsic noise level in spike generation, which could allow cortical neurons to accurately transform synaptic input into spike sequences, supporting a possible role for spike timing in the processing of cortical information by the neocortex.
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                Author and article information

                Journal
                Neuron
                Neuron
                Neuron
                Cell Press
                0896-6273
                1097-4199
                24 June 2010
                24 June 2010
                : 66
                : 6
                : 937-948
                Affiliations
                [1 ]Department of Physiology, Anatomy and Genetics, Sherrington Building, University of Oxford, Parks Road, Oxford OX1 3PT, UK
                Author notes
                []Corresponding author johannes.dahmen@ 123456dpag.ox.ac.uk
                [∗∗ ]Corresponding author andrew.king@ 123456dpag.ox.ac.uk
                Article
                NEURON10256
                10.1016/j.neuron.2010.05.018
                2938477
                20620878
                © 2010 ELL & Excerpta Medica.

                This document may be redistributed and reused, subject to certain conditions.

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                Neurosciences

                signaling, sysneuro, sysbio

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