Document Detail


Biological modeling of complex chemotaxis behaviors for C. elegans under speed regulation-a dynamic neural networks approach.
MedLine Citation:
PMID:  23334866     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
In this paper, the modeling of several complex chemotaxis behaviors of C. elegans is explored, which include food attraction, toxin avoidance, and locomotion speed regulation. We first model the chemotaxis behaviors of food attraction and toxin avoidance separately. Then, an integrated chemotaxis behavioral model is proposed, which performs the two chemotaxis behaviors simultaneously. The novelty and the uniqueness of the proposed chemotaxis behavioral models are characterized by several attributes. First, all the chemotaxis behavioral model sare on biological basis, namely, the proposed chemotaxis behavior models are constructed by extracting the neural wire diagram from sensory neurons to motor neurons, where sensory neurons are specific for chemotaxis behaviors. Second, the chemotaxis behavioral models are able to perform turning and speed regulation. Third, chemotaxis behaviors are characterized by a set of switching logic functions that decide the orientation and speed. All models are implemented using dynamic neural networks (DNN) and trained using the real time recurrent learning (RTRL) algorithm. By incorporating a speed regulation mechanism, C. elegans can stop spontaneously when approaching food source or leaving away from toxin. The testing results and the comparison with experiment results verify that the proposed chemotaxis behavioral models can well mimic the chemotaxis behaviors of C. elegans in different environments.
Authors:
Jian-Xin Xu; Xin Deng
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2013-1-19
Journal Detail:
Title:  Journal of computational neuroscience     Volume:  -     ISSN:  1573-6873     ISO Abbreviation:  J Comput Neurosci     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2013-1-21     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9439510     Medline TA:  J Comput Neurosci     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
Department of Electrical & Computer Engineering, National University of Singapore, Singapore, 117576, Singapore, elexujx@nus.edu.sg.
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