The switching and learning behavior of an octopus cell implemented on FPGA

Autor: Alexej Tschumak, Frank Feldhoff, Frank Klefenz
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Mathematical Biosciences and Engineering, Vol 21, Iss 4, Pp 5762-5781 (2024)
Druh dokumentu: article
ISSN: 1551-0018
DOI: 10.3934/mbe.2024254?viewType=HTML
Popis: A dendrocentric backpropagation spike timing-dependent plasticity learning rule has been derived based on temporal logic for a single octopus neuron. It receives parallel spike trains and collectively adjusts its synaptic weights in the range [0, 1] during training. After the training phase, it spikes in reaction to event signaling input patterns in sensory streams. The learning and switching behavior of the octopus cell has been implemented in field-programmable gate array (FPGA) hardware. The application in an FPGA is described and the proof of concept for its application in hardware that was obtained by feeding it with spike cochleagrams is given; also, it is verified by performing a comparison with the pre-computed standard software simulation results.
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