АННОТАЦИЯ
It has been shown that various aspects of cortical activity associated with behavioral adaptation are provided by layer-specific synaptic dynamics, structural and connectional organization, as well as by layer-specific protein levels. In this study we used c-Fos immunolabeling to identify the experience-dependent mismatch specific changes in cortical activity. To determine the parameters of individuality and to assess the extent of relationship between different parameters, we analyzed the behavioral activity of rats in tests based on locomotion and anxiety levels. The results of this study demonstrated that experience-dependent mismatch induced cortical layer-specific changes in activity. Anxiety and exploratory activity were associated with selective changes in the number of Fos-activated neurons in the deep and superficial cortical layers, but were not associated with the total number of Fos-expressing cortical neurons in this area of the brain. We found a significant effect of anxiety and exploratory activity on learning rate. We argue that individual differences in learning can be predicted by the respective behavioral tests to measure exploratory and anxiety-related behavior. Although using neuroscience to develop artificial intelligence (AI) may guide neural network models toward human-like learning, at the moment artificial neural networks differ from the nervous system in many significant functional patterns. In order to create AI with human-like cognitive abilities, neuro- and cognitive sciences should participate in AI research as a part of the joint research program.
ЦИТАТА
The Influence of Anxiety and Exploratory Activity on Learning in Rats: Mismatch-Induced c-Fos Expression in Deep and Superficial Cortical Layers / A.I. Bulava, Z.A. Osipova, V.V. Arapov, A.G. Gorkin, I.O. Alexandrov, T.N. Grechenko, Y.I. Alexandrov // Advances in Neural Computation, Machine Learning, and Cognitive Research VII. : Selected Papers from the XXV International Conference on Neuroinformatics. – Zug, – 2023. – P. 323-333
