Institute for Systems Research

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Author: search.filters.author.Depireux, Didier A.Subject: search.filters.subject.Communications Systems

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    Analysis of Dynamic Spectra in Ferret Primary Auditory Cortex: II. Prediction of, Unit Responses to Arbitrary Dynamic Spectra
    (1995) Kowalski, Nina; Depireux, Didier A.; Shamma, S.A.; ISR
    Responses of single units and unit clusters were recorded in the ferret primary auditory cortex (AI) using broadband complex dynamic spectra. Previous work (Kowalski et al 1995) demonstrated that simpler spectra consisting of single moving ripples (i.e., sinusoidally modulated spectral profiles that travel at a constant velocity along the logarithmic frequency axis) could be used effectively to characterize the response fields and transfer functions of AI cells. An arbitrary complex dynamic spectral profile can be thought of conceptually as being composed of a weighted sum of moving ripple spectra. Such a decomposition can be computed from a two-dimensional spectro- temporal Fourier transform of the dynamic spectral profile with moving ripples as the basis function. Therefore, if AI units were essentially linear satisfying the superposition principle, then their responses to arbitrary dynamic spectra could be predicted from the responses to single moving ripples, i.e., from the units response fields and transfer functions. This conjecture was tested and confirmed with data from 293 combinations of moving ripples, involving complex spectra composed of up to 15 moving ripples of different ripple frequencies and velocities. For each case, response predictions based on the unit transfer functions were compared to measured responses. The correlation between predicted and measured responses was found to be consistently high (84% with rho > 0.6). The distribution of response parameters suggest that AI cells may encode the profile of a dynamic spectrum by performing a multiscale spectro-temporal decomposition of the dynamic spectral profile in a largely linear manner.

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    Analysis of Dynamic Spectra in Ferret Primary Auditory Cortex: I. Characteristics of Single Unit Responses to Moving Ripple Spectra
    (1995) Kowalski, Nina; Depireux, Didier A.; Shamma, S.A.; ISR
    Auditory stimuli referred to as moving ripples are used to characterize the responses of both single and multiple units in the ferret primary auditory cortex (AI). Moving ripples are broadband complex sounds with sinusoidal spectral profiles that drift along the tonotopic axis at a constant velocity. Neuronal responses to moving ripples are locked to the phase of the ripple, i.e., they exhibit the same periodicity as that of the moving ripple profile. Neural responses are characterized as a function of ripple velocity (temporal property) and ripple frequency (spectral property). Transfer functions describing the response to these temporal and spectral modulations are constructed. Temporal transfer functions are inverse Fourier transformed to obtain impulse response functions that reflect the cell's temporal characteristics. Ripple transfer functions are inverse Fourier transformed to obtain the response field, characterizing the cell's response area along the tonotopic axis. These operations assume linearity in the cell's response to moving ripples. Separability of the temporal and ripple transfer functions is established by comparing transfer functions across different test parameters. Response fields measured with either stationary ripples or moving ripples are shown to be similar. Separability implies that the neuron can be modeled as processing spatio-temporal information in two distinct stages. The assumption of linearity implies that each of these stages is a linear operation.

    The ripples parameters that characterize cortical cells are distributed somewhat evenly, with the characteristic ripple frequencies ranging from 0.2 to over 2 cycles/octave and the characteristic angular frequency typically ranging from 2 to 20 Hz. Many responses exhibit periodicities not found in the spectral envelope of the stimulus. These periodicities are of two types. Slow rebounds with a period of about 150 ms appear with various strengths in about 30 % of the cells. Fast regular firings, with interspike intervals of the order of 10 ms are much less common and may reflect the ability of certain cells to follow the fine structure of the stimulus.