From real-time single to multicompartmental Hodgkin-Huxley neurons on FPGA for bio-hybrid systems.
Romain Beaubois, Farad Khoyratee, Pascal Branchereau, Yoshiho Ikeuchi, Timothee Levi
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2022-07-11; :
DOI: 10.1109/embc48229.2022.9871176
Lire sur PubMed
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2022-07-11; :
DOI: 10.1109/embc48229.2022.9871176
Lire sur PubMed
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.