Identification of MGB cells by volterra kernels - II. Towards a functional classification of cells

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Abstract

System Identification methods can be implemented in sensory physiology to formalize stimulus-response relationships. We apply the Volterra approach in order to define input-output relations of Medial Geniculate Body (MGB) cells in the awake squirrel monkey. The transfer functions (kernels) of MGB cells are computed using input output pairs. The inputs are intraspecific communication sounds, represented by their spectral components at a 1 or 1/3 octave resolution, yielding thus a multi input system. The outputs are represented by the responses of single neurons expressed as the smoothed Peri Stimulus Time Histograms (PSTHs). The kernels are computed for various combinations of the model: linear and quadratic Volterra expansions respectively 1 and 1/3 octave resolution of the input. Judging by the predictions of these models, it can be concluded that the model predictibility power is systematically improved as the order of the model and its spectral resolution are increased. An analysis of the predicted responses reveals that in certain cases, the quality of the predictions might be related primarily to either the order of the model, or alternatively to the spectral resolution of the input. The quality of the predictions, and their "Linearity", are associated with the spatial location of the cells within the MGB. Cells located at the medial aspect of the nucleus exhibit more "linear" responses, which are also better predicted, compared with most other cells.

Original languageEnglish
Pages (from-to)203-208
Number of pages6
JournalBiological Cybernetics
Volume56
Issue number2-3
DOIs
StatePublished - May 1987

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