From real-time single to multicompartmental Hodgkin-Huxley neurons on FPGA for bio-hybrid systems
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EN
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Ce document a été publié dans
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Glasgow, Scotland, United Kingdom, 2022, 2022-07-11, Glasgow. 2022-09-08p. 1602-1606
Résumé en anglais
Modeling biological neural networks has been a field opening to major advances in our understanding of the mechanisms governing the functioning of the brain in normal and pathological conditions. The emergence of real-time ...Lire la suite >
Modeling biological neural networks has been a field opening to major advances in our understanding of the mechanisms governing the functioning of the brain in normal and pathological conditions. The emergence of real-time neuromorphic platforms has been leading to a rising significance of bio-hybrid experiments as part of the development of neuromorphic biomedical devices such as neuroprosthesis. To provide a new tool for the neurological disorder characterization, we design real-time single and multicompartmental Hodgkin-Huxley neurons on FPGA. These neurons allow biological neural network emulation featuring improved accuracy through compartment modeling and show integration in bio-hybrid system thanks to its real-time dynamics.< Réduire
Mots clés
Neurological diseases
Neuromorphics
Computational modeling
Neurons
Emulation
Neuroprostheses
Real-time systems
Brain
Medical computing
Neural nets
Neurophysiology
Multicompartmental
FPGA
SNN
Bio-hybrid
Hodgkin-Huxley
Brain
Models
Neurological
Neural Networks
Computer
Neurons