Institute for Systems Research

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Author: search.filters.author.Depireux, Didier A.Subject: search.filters.subject.auditory cortex

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    Dynamics of Neural Responses in Ferret Primary Auditory Cortex: I. Spectro-Temporal Response Field Characterization by Dynamic Ripple Spectra
    (1999) Depireux, Didier A.; Simon, J.Z.; Klein, David J.; Shamma, S.A.; ISR; CAAR
    To understand the neural representation of broadband, dynamic sounds in Primary Auditory Cortex (AI), we characterize responses using the Spectro-Temporal Response Field (STRF). The STRF describes and predicts the linear response of neurons to sounds with rich spectro-temporal envelopes. It is calculated here from the responses to elementary "ripples," a family of sounds with drifting, sinusoidal, spectral envelopes--the complex spectro-temporal envelope of any broadband, dynamic sound can expressed as the linear sum of individual ripples.

    The collection of responses to all elementary ripples is the spectro-temporal transfer function. Previous experiments using ripples with downward drifting spectra suggested that the transfer function is separable, i.e., it is reducible into a product of purely temporal and purely spectral functions.

    Here we compare the responses to upward and downward drifting ripples, assuming separability within each direction, to determine if the total bi-directional transfer function is fully separable. In general, the combined transfer function for two directions is not symmetric, and hence units in AI are not, in general, fully separable. Consequently, many AI units have complex response properties such as sensitivity to direction of motion, though most inseparable units are not strongly directionally selective.

    We show that for most neurons the lack of full separability stems from differences between the upward and downward spectral cross-sections, not from the temporal cross-sections; this places strong constraints on the neural inputs of these AI units.

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    Robust Spectro-Temporal Reverse Correlation for the Auditory System: Optimizing Stimulus Design
    (1999) Klein, David J.; Depireux, Didier A.; Simon, J.Z.; Shamma, S.A.; ISR; CAAR
    The spectro-temporal receptive field (STRF) is a functionaldescriptor of the linear processing of time-varying acoustic spectra by theauditory system. By cross-correlating sustained neuronal activity with the"dynamic spectrum" of a spectro-temporally rich stimulus ensemble, oneobtains an estimate of the STRF.

    In this paper, the relationship betweenthe spectro-temporal structure of any given stimulus and the quality ofthe STRF estimate is explored and exploited. Invoking the Fouriertheorem, arbitrary dynamic spectra are described as sums of basicsinusoidal components, i.e., "moving ripples." Accurate estimation isfound to be especially reliant on the prominence of components whosespectral and temporal characteristics are of relevance to the auditorylocus under study, and is sensitive to the phase relationships betweencomponents with identical temporal signatures.

    These and otherobservations have guided the development and use of stimuli withdeterministic dynamic spectra composed of the superposition of many"temporally orthogonal" moving ripples having a restricted, relevant rangeof spectral scales and temporal rates.

    The method, termedsum-of-ripples, is similar in spirit to the "white-noise approach," butenjoys the same practical advantages--which equate to faster and moreaccurate estimation--attributable to the time-domain sum-of-sinusoidsmethod previously employed in vision research. Application of the methodis exemplified with both modeled data and experimental data from ferretprimary auditory cortex (AI).