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Neural Model for Physiological Responses to Frequency and Amplitude Transitions Uncovers Topographical Order in the Auditory Cortex

¹Department of Physiology, Northwestern University, Chicago, Illinois 60611; ²Department of Computer Science, Tel-Aviv University, Ramat-Aviv, Tel-Aviv 69978; and ³Department of Physiology, Hebrew University-Hadassah Medical School and the Interdisciplinary Center for Neural Computation, Hebrew University, Jerusalem 91120, Israel

Submitted 8 July 2003; accepted in final form 21 August 2003

We characterize primary auditory cortex (AI) units using a neural model for the detection of frequency and amplitude transitions. The model is a generalization of a model for the detection of amplitude transition. A set of neurons, tuned in the spectrotemporal domain, is created by means of neural delays and frequency filtering. The sensitivity of the model to frequency and amplitude transitions is achieved by applying a 2-dimensional rotatable receptive field to the set of spectrotemporally tuned neurons. We evaluated the model using data recorded in AI of anesthetized ferrets. We show that the model is able to fit the responses of AI units to variety of stimuli, including single tones, delayed 2-tone stimuli and various frequency-modulated tones, using only a small number of parameters. Furthermore, we show that the topographical order in maps of the model parameters is higher than in maps created from response indices extracted directly from the responses to any single stimulus. These results suggest a possible ordered organization of a simple rotatable spectrotemporal receptive field in the mammalian AI.

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