A dynamical pattern recognition model of γ activity in auditory cortex

Zavaglia, M, Canolty, R T, Schofield, T M, Leff, A P, Ursino, M, Knight, R T and Penny, W D (2012) A dynamical pattern recognition model of γ activity in auditory cortex. Neural Networks, 28. pp. 1-14. ISSN 0893-6080

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Abstract

This paper describes a dynamical process which serves both as a model of temporal pattern recognition in the brain and as a forward model of neuroimaging data. This process is considered at two separate levels of analysis: the algorithmic and implementation levels. At an algorithmic level, recognition is based on the use of Occurrence Time features. Using a speech digit database we show that for noisy recognition environments, these features rival standard cepstral coefficient features. At an implementation level, the model is defined using a Weakly Coupled Oscillator (WCO) framework and uses a transient synchronization mechanism to signal a recognition event. In a second set of experiments, we use the strength of the synchronization event to predict the high gamma (75-150 Hz) activity produced by the brain in response to word versus non-word stimuli. Quantitative model fits allow us to make inferences about parameters governing pattern recognition dynamics in the brain.

Item Type: Article
Additional Information: Copyright © 2012 Elsevier Ltd. All rights reserved.
Uncontrolled Keywords: acoustic stimulation,adult,auditory cortex,brain mapping,brain waves,female,humans,neurological models,nerve net,neuronal plasticity,physiological pattern recognition,comparative study
Faculty \ School: Faculty of Social Sciences > School of Psychology
Depositing User: Pure Connector
Date Deposited: 19 Aug 2017 05:06
Last Modified: 22 Apr 2020 05:22
URI: https://ueaeprints.uea.ac.uk/id/eprint/64588
DOI: 10.1016/j.neunet.2011.12.007

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