Population Coding and Decoding in a Neural Field: A Computational Study

Wu, Si, Amari, Shun-ichi and Nakahara, Hiroyuki (2002) Population Coding and Decoding in a Neural Field: A Computational Study. Neural Computation, 14 (5). pp. 999-1026. ISSN 0899-7667

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Item Type: Article
Additional Information: Originality: This work investigated the performances of neural population coding under different correlation structures, and for the first time, it systematically clarified the conditions under which a population decoding strategy is efficient. Rigor: This work applied a combination of methods, including Information Theory, Statistical Inference and the Theory of Dynamical Systems, to analyze the performance of neural population decoding. It found that when the neuronal correlation is strong, population decoding is not as efficient as many people thought before. Significance: This work developed a new mathematical method to analyze the efficiency of neural population decoding. The results on the efficiency of population decoding have important guidance on data analysis in neurophysiology experiments. Impact: This work has important impact on our understanding of population coding, an important feature of neural information processing. It has citations: Web of Knowledge=11, Google Scholar=18.
Schools and Departments: School of Engineering and Informatics > Informatics
Depositing User: Si Wu
Date Deposited: 06 Feb 2012 20:14
Last Modified: 27 Mar 2012 07:43
URI: http://sro.sussex.ac.uk/id/eprint/24919
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