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The effect of a parametric change in the excitation threshold on processes of generation of the spike activity in an ensemble of FitzHugh–Nagumo neurons has been analyzed. It has been shown that the periodic change in the excitation threshold results in the existence of chaotic regimes of generation of the spike activity with various statistical properties. It has been found that chaos in the model of an individual neuron appears through Pomeau–Manneville intermittence. It has been shown that the information characteristics of the neuron can be controlled by varying the modulation depth and the frequency of parametric action. It has been found that chaotic spike sequences forming fractal-like spatiotemporal patterns appear when neurons are joined in an ensemble.

Cloning of chimera states, which is a new effect caused by the short-term interaction in a multiplex network, has been described. This effect is observed when two ring networks of linearly coupled two-frequency (bistable) oscillators are combined into the multiplex network. At certain values of the strength and duration of the inter-ring (multiplex) interaction, a copy of a chimera state with accuracy to phases in the incoherent part is formed in the ring with an initially random phase distribution. It has been shown that the effect is structurally stable and is due to the competition of self-sustained oscillations in individual rings.

Chimera states in a system with linear local connections have been studied. The system is a ring ensemble of analog bistable self-excited oscillators with a resistive coupling. It has been shown that the existence of chimera states is not due to the nonidentity of oscillators and noise, which is always present in real experiments, but is due to the nonlinear dynamics of the system on invariant tori with various dimensions.

We present a new approach for the description and analysis of sequential dynamics of excitatory neural networks. It is based on the reduction of dynamics of networks to the dynamics of cellular automata (CA) on the graph of connections. The attractors of the CA determine the different regimes of sequential dynamics of the original neural network. We illustrate our approach through Morris–Lecar and Hodgkin–Huxley neural networks.

The electronic circuit of the basic element of a neurodynamic memory system has been developed and implemented. The dynamic modes of the circuit and its responses to different external signals have been investigated experimentally. The circuit under study is shown to have all dynamic properties required for the memory system. The experimental results agree with those obtained in the previous theoretical studies of the neurodynamic memory system.

The effect of phase reset in a complex oscillatory system under the action of an external pulse is investigated. After the pulse action, the phase of oscillations in the system acquires a new value, which is virtually independent of the initial phase and is only determined by the pulse parameters (the amplitude and the duration). The phase reset is observed for pulses of different durations, including those considerably shorter than the characteristic scale of oscillations in the system. The effect occurs without any fundamental difference for the cases of regular and chaotic oscillations.