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Communication Dans Un Congrès Année : 2017

Biomimetic neural network for modifying biological dynamics during hybrid experiments

Résumé

Electrical stimulation of nerve tissue and recording of neural electrical activity are the basis of emerging prostheses and treatments for many neurological disorders. Here we present closed-loop biohybrid experiment using in vitro Biological Neuronal Network (BNN) with an Artificial Neural Network (ANN) implemented in a neuromorphic board. We adopted a neuromorphic board which is able to perform real-time event detection and trigger an electrical stimulation of the BNN. This system embeds an ANN, based on Izhikevich neurons which can be put in uni-and bi-directional communication with the BNN. The ANN used in the following experiments was made up of 20 excitatory neurons with inhibition synapse and with synaptic plasticity to design Central Pattern Generator (CPG). Open-loop and closed-loop hybrid experiments shows that the biological dynamics can be modified. This work can be seen as the first step towards the realization of an innovative neuroprosthesis.
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Dates et versions

hal-01567497 , version 1 (27-07-2017)

Identifiants

  • HAL Id : hal-01567497 , version 1

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Matthieu Ambroise, Stefano Buccelli, Filippo Grassia, Antoine Pirog, Yannick Bornat, et al.. Biomimetic neural network for modifying biological dynamics during hybrid experiments. 22th International Symposium on Artificial Life and Robotics, Jan 2017, Beppu, Japan. ⟨hal-01567497⟩
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