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We propose to use the chimera-like state for stimulus classification in a spiking neural network of bistable HH neurons. As a stimulus, we use an external pulsed current applied to the network. Additive noise makes the neurons nonidentical so that the external pulse switches only a part of the neurons from the resting to the oscillatory state depending on the pulse amplitude. For classification, we use the neural network and two output neurons. The network is trained on two external pulses with different amplitudes to adjust coupling strengths between neurons in the main network and output neurons. We investigate influence of inhibitory coupling between output neurons on classification of input signal with different amplitudes.
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Andrey V. Andreev, Alexander N. Pisarchik, "External stimulus classification by Hodgkin-Huxley neural network," Proc. SPIE 11847, Saratov Fall Meeting 2020: Computations and Data Analysis: from Molecular Processes to Brain Functions, 118470H (4 May 2021); https://doi.org/10.1117/12.2591339