Age-related Spike Timing Dependent Plasticity of Brain-inspired Model of Visual Information Processing with Reinforcement Learning

The paper summarizes our efforts to develop a spike timing neural network model of dynamic visual information processing and decision making inspired by the available knowledge about how the human brain performs this complicated task. It consists of multiple layers with functionality corresponding to the main visual information processing structures starting from the early level of the visual system up to the areas responsible for decision making based on accumulated sensory evidence as well as the basal ganglia modulation due to the feedback from the environment. In the present work, we investigated age-related changes in the spike timing dependent plastic synapses of the model as a result of reinforcement learning.

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1. Track 1: Artificial Intelligence

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2. Technical Session: 15th International Symposium Advances in Artificial Intelligence and Applications

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3. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).