We report on the experimental observation and study of dynamic attractors in chaotic neural networks, probed by timed current stimuli. We observed multistability in chaotic networks and demonstrate how systematically controlling the timing of stimulation selects the spa-tiotemporal sequences of voltage oscillations of neurons. We have developed a network of N neurons interconnected with mutually inhibitory gap junctions, using silicon chips. This neural network is based on the Hodgkin-Huxley model. We then generated phase-lag maps of neuronal oscillators by varying the timing of current stimulation to individual neurons . We observed multiple attractors that consists of N-phasic sequences of unevenly spaced pulses, propagating clockwise and anti-clockwise. Our results validate the command neuron hypothesis and the control of adaptation of motor patterns to stimulation. The proposed approach may find application for modulating heart rate and providing therapy for heart failure.
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