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Robust sigmoidal control response of C. elegans neuronal network
Journal
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN
03029743
Date Issued
2017-01-01
Author(s)
Badhwar, Rahul
Bagler, Ganesh
Abstract
Biological systems are known to evolve mechanisms for acquiring robust response under uncertainty. Brain is a complex adaptive system characterized with system specific network features, at global as well as local level, critical for its function and control. We studied controllability response in C. elegans neuronal network with change in number of functionally important feed-forward motifs, due to synaptic rewiring. We find that this neuronal network has acquired a sigmoidal control response with a robust regime for saturation of feed-forward motifs and an extremely fragile response for their depletion. Further we show that, to maintain controllability this neuronal network must rewire following a power law distance constraint. Our results highlight distance constrained synaptic rewiring as a robust evolutionary strategy in the presence of sigmoidal control response.
Volume
10314 LNAI
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