Neuronal identification of acoustic signal periodicity |
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Authors: | Paul Friedel Moritz Bürck J Leo van Hemmen |
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Institution: | 1. Physik Department T35, Technische Universit?t München, 85748, Garching bei München, Germany 2. Bernstein Center for Computational Neuroscience-Munich, München, Germany
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Abstract: | Acoustic signals transmit information by temporal characteristics and envelope periodicity as well as by their frequency content.
Many animals can extract the frequency content of a signal by means of specialized organs such as the cochlea but for the
detection and identification of higher-order periodicity, e.g., amplitude modulations, this type of organ is useless. In addition,
many animals do not have a cochlea but still depend on a reliable identification of different frequencies in the vast variety
of acoustic signals they perceive in their natural environment. Hence, neural mechanisms to decode periodicity information
must exist. We present a detailed mathematical analysis of a recurrent and a feedforward model of neuronal periodicity extraction
and discuss basic constraints for neuronal circuitry performing such a task in a biological system. Both the recurrent and
the feedforward model perform well using neuronal parameters typical for the auditory system. Performance is limited mainly
by the temporal precision of the connections between the neurons. |
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Keywords: | Periodicity detection Auditory signal processing Neuronal modeling |
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