Classification of external signal by spiking neural network of bistable Hodgkin-Huxley neurons

We propose a classifier consisting of Hodgkin-Huxley neurons based on the activation of a different number of neurons depending on the external current amplitude. We consider a network with 2 output neurons and train the classifier for 2 external current pulses with different amplitudes by adaptation of the couplings between neurons of the main network and the output neurons.

[1]  Semen Kurkin,et al.  Machine learning approaches for classification of imaginary movement type by MEG data for neurorehabilitation , 2019, 2019 3rd School on Dynamics of Complex Networks and their Application in Intellectual Robotics (DCNAIR).

[2]  Alexander N. Pisarchik,et al.  Numerical simulation of coherent resonance in a model network of Rulkov neurons , 2018, Saratov Fall Meeting.

[3]  S. Nikitov,et al.  Spin-Wave Transport Along In-Plane Magnetized Laterally Coupled Magnonic Stripes , 2017, IEEE Magnetics Letters.

[4]  Alexander E. Hramov,et al.  Chimera state in complex networks of bistable Hodgkin-Huxley neurons. , 2019, Physical review. E.

[5]  Vladimir Maksimenko,et al.  Brain-computer interface on the basis of EEG system Encephalan , 2018, Saratov Fall Meeting.

[6]  A. Sadovnikov,et al.  Spatial dynamics of hybrid electromagnetic spin waves in a lateral multiferroic microwaveguide , 2017 .

[7]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[8]  Vladimir A. Maksimenko,et al.  Nonlinear effect of biological feedback on brain attentional state , 2018, Nonlinear Dynamics.

[9]  Vladimir A. Maksimenko,et al.  Phase-amplitude coupling between mu- and gamma-waves to carry motor commands , 2019, 2019 3rd School on Dynamics of Complex Networks and their Application in Intellectual Robotics (DCNAIR).

[10]  A. Hramov,et al.  Modeling Instabilities in Relativistic Electronic Beams in the CST Particle Studio Environment , 2018 .

[11]  Alexander E. Hramov,et al.  Multiscale interaction promotes chimera states in complex networks , 2019, Commun. Nonlinear Sci. Numer. Simul..

[12]  Alexey N. Pavlov,et al.  Perspective sub-THz powerful microwave generator "nanovircator" for T-rays biomedical diagnostics , 2016, Saratov Fall Meeting.

[13]  Olga N. Pavlova,et al.  Detrended fluctuation analysis of EEG patterns associated with real and imaginary arm movements , 2018, Physica A: Statistical Mechanics and its Applications.

[14]  Alexander E. Hramov,et al.  Stimulus classification using chimera-like states in a spiking neural network , 2020 .

[15]  Vladimir A. Maksimenko,et al.  Betweenness centrality in multiplex brain network during mental task evaluation , 2018, Physical Review E.

[16]  Vadim V. Grubov,et al.  Studying of human’s mental state during visual information processing with combined EEG and fNIRS , 2020 .

[17]  Vladimir A. Maksimenko,et al.  Neural activity during maintaining a body balance , 2020 .

[18]  Vladimir A. Maksimenko,et al.  Artificial Neural Network Classification of Motor-Related EEG: An Increase in Classification Accuracy by Reducing Signal Complexity , 2018, Complex..

[19]  A. Hodgkin,et al.  A quantitative description of membrane current and its application to conduction and excitation in nerve , 1952, The Journal of physiology.

[20]  Parth Chholak,et al.  Visual and kinesthetic modes affect motor imagery classification in untrained subjects , 2019, Scientific Reports.

[21]  N. Frolov,et al.  Virtual cathode oscillator with elliptical resonator , 2017, 2017 Eighteenth International Vacuum Electronics Conference (IVEC).

[22]  Vladimir A. Maksimenko,et al.  Coherent resonance in the distributed cortical network during sensory information processing , 2019, Scientific Reports.

[23]  A. Hramov,et al.  Simulation of the development and interaction of instabilities in a relativistic electron beam under variation of the beam wall thickness , 2017 .

[24]  Vadim Grubov,et al.  Functional Near-Infrared Spectroscopy for the Classification of Motor-Related Brain Activity on the Sensor-Level , 2020, Sensors.

[25]  Shlomo Havlin,et al.  Explosive synchronization coexists with classical synchronization in the Kuramoto model. , 2016, Chaos.

[26]  Alexander E. Hramov,et al.  Nonlinear dynamics of the complex multi-scale network , 2018, Saratov Fall Meeting.