Titlebook: Advances in Neural Computation, Machine Learning, and Cognitive Research VII; Selected Papers from Boris Kryzhanovsky,Witali Dunin-Barkowsk

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S. Gritzalis,N. Nikitakos,P. Georgiadis and granular computations is used. The possibility of using the proposed approach for the study of cognitive processes of intelligent systems and the further development of artificial intelligence systems is shown.

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PON

https://doi.org/10.1007/978-0-387-34943-5ents to plasticity rules imposed by unsupervised learning problems and construct a novel plasticity model satisfying these requirements. This plasticity model serves as main logical component of the novel unsupervised learning algorithm called SCoBUL (Spike Correlation Based Unsupervised Learning).

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https://doi.org/10.1007/978-3-642-32805-3se time segments is highly variable, though it follows common dependence for all segments of the whole record. The brain signals during execution of a cognitive task resembled relay system switching permanently when performing computations. We intend to reveal links between remote areas in the brain which synchronize moments of abrupt switching.

GLOOM

Spinal-Tap

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GRACE

Paulo Pinto,Bernardo Patrão,Henrique Santosst to deepfakes was significantly influenced by the interaction between internal attitudes and speaker and need for cognition. The higher negative evoked brain response, alike to the N600 component, was observed for anti-vaccination group in mismatch to public opinion of the speaker.

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