Towards an electro-optical emulation of the C. elegans connectome

Alexey Petrushin*, Lorenzo Ferrara, Carlo Liberale, Axel Blau

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

The tiny worm Caenorhabditis elegans features one of the simplest nervous systems in nature. The hermaphrodite contains exactly 302 neurons and about 8000 connections. The Si elegans project aims at providing a reverse-engineerable model of this nematode by emulating its nervous system in hardware and embodying it in a virtual world. The hardware will consist of 302 individual FPGAs, each carrying a neuron-specific neural response model. The FPGA neurons will be interconnected by an electro-optical connectome to distribute the signal at the axonal output or gap-junction pin of an FPGA neuron onto the respective synaptic input or gap-junction pins of those target FPGA neurons that a neuron interconnects with. This technology will replicate the known connectome of the nematode to allow for an as biologically meaningful as possible and truly parallel information flow between neurons. This article focuses on the concepts and first implementation steps of such optical connectome.

Original languageEnglish (US)
Title of host publicationNEUROTECHNIX 2014 - Proceedings of the 2nd International Congress on Neurotechnology, Electronics and Informatics
EditorsAna Rita Londral, Pedro Encarnacao
PublisherINSTICC Press
Pages184-188
Number of pages5
ISBN (Electronic)9789897580567
DOIs
StatePublished - 2014
Event2nd International Congress on Neurotechnology, Electronics and Informatics, NEUROTECHNIX 2014 - Rome, Italy
Duration: Oct 25 2014Oct 26 2014

Publication series

NameNEUROTECHNIX 2014 - Proceedings of the 2nd International Congress on Neurotechnology, Electronics and Informatics

Other

Other2nd International Congress on Neurotechnology, Electronics and Informatics, NEUROTECHNIX 2014
Country/TerritoryItaly
CityRome
Period10/25/1410/26/14

Keywords

  • Brain-Inspired Computation
  • Connectome
  • Digital Mirror Device (DMD)
  • Microstructured Optical Elements
  • Nervous System Emulation
  • Parallel Information Flow
  • Structured Illumination

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • General Neuroscience

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