ISSN 0869-6632 (Print)
ISSN 2542-1905 (Online)

Nonlinear Dynamics and Neuroscience

Working memory capacity: the role of parameters of spiking neural network model

Purpose of this work is to study a computational model of working memory formation based on spiking neural network with plastic connections and to study the capacity of working memory depending on the time scales of synaptic facilitation and depression and the background excitation of the network.

Ring generator of neuron-like activity with tunable frequency

The aim of the work is to build a radiophysical generator of neuron-like activity with a frequency tunable in various ways, corresponding to modern ideas about the structure of the hippocampus and the generation of pathological epileptic rhythms in it. Methods. The elements of the generator are radio engineering implementations of the complete FitzHugh– Nagumo neuron and the electronic implementation of a chemical synapse in the form of a sigmoid function with a delayed argument. The simulation was carried out in the SPICE simulator. Results.

Synchronization of excitation waves in a two-layer network of FitzHugh–Nagumo neurons with noise modulation of interlayer coupling parameters

The purpose of this work is to study the possibility of synchronization of wave processes in distributed excitable systems by means of noise modulation of the coupling strength between them. Methods. A simple model of a neural network, which consists of two coupled layers of excitable FitzHugh–Nagumo oscillators with a ring topology, is studied by numerical simulation methods. The connection between the layers has a random component, which is set for each pair of coupled oscillators by independent sources of colored Gaussian noise. Results.

Estimation of impulse action parameters using a network of neuronlike oscillators

Aim of the study is to develop a method for estimating the parameters of an external periodic impulse action using a spiking network of neuronlike oscillators. Methods. The spiking activity of a network consisting of coupled nonidentical neuronlike FitzHugh–Nagumo oscillators was studied, depending on the parameters of the periodic impulse action.

Postulates of the cognitive theory of thinking and their consequences

Purpose of the work is to create a theoretical model of the thinking process, considered as a set of operations for the formation of cognitive generalizations of the level of categories (concepts). Method for creating a theoretical model is based on the approach used in natural sciences. It involves the selection of a small number of reliable facts, which are accepted as true on the basis of their evidence. On the basis of these facts, established in various scientific disciplines, the axioms of the proposed theory are formulated.

Neurodynamic model for creative cognition of relational networks with even cyclic inhibition

The purpose of this work is study of the neurodynamic foundations of the creative activity of the brain. Modern AI systems using deep neural network training require large amounts of input data, high computational costs and long training times. On the contrary, the brain can learn from small datasets in no time and, crucially, it is fundamentally creative. Methods. The study was carried out through computational experiments with neural networks containing 5 and 7 oscillatory layers (circuits) trained to represent abstract concepts of a certain class of animals.

Clinical aspects of nonlinear dynamics of cognitive processes: features of sensorimotor activity in patients at the clinical phase of COVID-19

The mechanisms of retrograde or anterograde neuronal transport ensure the migration of SARS-CoV-2 viruses to motor and sensory terminals, which can provoke significant distortions in the processes of information pattern recognition and the formation of action programs. The purpose of this study is to experimentally determine the dynamic modes of the cognitive system in patients with COVID-19. Cognitive processes are displayed in the space of parameters of sensorimotor activity when solving problems of different levels of complexity on the COGNITOM WEB platform.

Measuring cognitive potential based on the performance of tasks of various levels of complexity

Purpose of work. The article is devoted to the topic of measuring the cognitive potential of a person on the basis of the obtained experimental data in order to identify its potential capabilities, as well as to monitor their dynamics, for example, to diagnose recovery after an illness. This goal is divided in the study into two tasks, namely, to assess the cognitive potential, it is necessary to develop two algorithms: 1. Assessment of the level of cognitive complexity of tasks. 2. Systems of levels of cognitive potential for an individual. Methods.

Compartmental spiking neuron model CSNM

The purpose of this work is to develop a compartment spiking neuron model as an element of growing neural networks. Methods. As part of the work, the CSNM is compared with the Leaky Integrate-and-Fire model by comparing the reactions of point models to a single spike. The influence of hyperparameters of the proposed model on neuron excitation is also investigated. All the described experiments were carried out in the Simulink environment using the tools of the proposed library. Results.

Construction of the fitness function depending on a set of competing strategies based on the analysis of population dynamics

The purpose of this work is to construct a fitness function that depends on the set of coexisting competing hereditary elements based on population dynamics in the “predator– prey” model with the logistic growth of prey. Materials and methods. The work uses the generalized Volterra model. The planktivorous fish plays the role of a predator. Many different species of zooplankton are considered as prey, which differ from each other in the hereditary strategies of daily vertical migrations. The model takes into account the intraspecific competition of prey.