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.
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Acknowledgements
Ganesh Bagler acknowledges the seed grant support from Indian Institute of Technology Jodhpur (IITJ/SEED/2014/0003), and support from Indraprastha Institute of Information Technology Delhi (IIIT-Delhi). Rahul Badhwar thanks Ministry of Human Resource Development, Government of India and Indian Institute of Technology Jodhpur for the senior research fellowship.
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Badhwar, R., Bagler, G. (2017). Robust Sigmoidal Control Response of C. elegans Neuronal Network. In: Polkowski, L., et al. Rough Sets. IJCRS 2017. Lecture Notes in Computer Science(), vol 10314. Springer, Cham. https://doi.org/10.1007/978-3-319-60840-2_29
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DOI: https://doi.org/10.1007/978-3-319-60840-2_29
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