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Adaptive Multiscale Encoding: A Computational Function of Neuronal Synchronization

Pesenson, Meyer Z. (2013) Adaptive Multiscale Encoding: A Computational Function of Neuronal Synchronization. In: Multiscale Analysis and Nonlinear Dynamics. Wiley , Weinheim, pp. 245-256. ISBN 9783527671632.

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From the mammalian visual system to high‐dimensional artificial sensor data, the notion of scale is pivotal for information encoding and analysis. This chapter proposes a new, nonlinear mechanism based on neural synchronization that achieves the desired multiscale encoding. Entrainment of different neurons produces larger receptive fields than that of a single cell alone, leading to a multiresolution representation. In vision, the concept of the receptive field is the product of an intrinsically linear approach to visual information processing. However, recent results challenge the notion of linearity, and the idea of a stimulus‐invariant receptive field in general. It has also been suggested that the neural coding is adaptive, that sensory neurons change their responses dynamically, and moreover, that the structure of neuronal correlations changes as well. The neural network model demonstrates a new computational function of synchronization— the multiscale encoding that underlies cognitive and perceptual functions.

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Additional Information:© 2013 Wiley‐VCH Verlag GmbH & Co. KGaA. Published Online: 31 July 2013; Published Print: 14 August 2013,
Subject Keywords:computational function; multiscale encoding; neural network model; neuronal synchronization; visual information processing
Record Number:CaltechAUTHORS:20210224-145945454
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Official Citation:Z. Pesenson, M.(. (2013). Adaptive Multiscale Encoding: A Computational Function of Neuronal Synchronization. In Multiscale Analysis and Nonlinear Dynamics, M.Z. Pesenson (Ed.).
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:108184
Deposited By: Tony Diaz
Deposited On:24 Feb 2021 23:10
Last Modified:16 Nov 2021 19:09

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