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

semantic space

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.