Authors:
Alexey Petrushin
;
Lorenzo Ferrara
and
Axel Blau
Affiliation:
Italian Institute of Technology (IIT), Italy
Keyword(s):
Brain-Inspired Computation, Nervous System Emulation, Soft Body Simulation, Virtual Embodiment, Neurocomputational Response Models on Field-Programmable Gate Arrays (FPGAs).
Abstract:
Biological nervous systems are robust and highly adaptive information processing entities that excel current
computer architectures in almost all aspects of sensory-motor integration. While they are slow and
inefficient in the serial processing of stimuli or data chains, they outperform artificial computational systems
in seemingly ordinary pattern recognition, orientation or navigation tasks. Even one of the simplest nervous
systems in nature, that of the hermaphroditic nematode Caenorhabditis elegans with just 302 neurons and
less than 8,000 synaptic connections, gives rise to a rich behavioural repertoire that – among controlling
vital functions - encodes different locomotion modalities (crawling, swimming and jumping). It becomes
evident that both robotics and information and computation technology (ICT) would strongly benefit if the
working principles of nervous systems could be extracted and applied to the engineering of brain-mimetic
computational architectures. C. el
egans, being one of the five best-characterized animal model systems,
promises to serve as the most manageable organism to elucidate the information coding and control
mechanisms that give rise to complex behaviour. This short paper reviews past and present endeavours to
reveal and harvest the potential of nervous system function in C. elegans.
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