STDP Plasticity in TRN Within Hierarchical Spike Timing Model of Visual Information Processing - Artificial Intelligence Applications and Innovations Access content directly
Conference Papers Year : 2020

STDP Plasticity in TRN Within Hierarchical Spike Timing Model of Visual Information Processing

Petia Koprinkova-Hristova
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Nadejda Bocheva
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Simona Nedelcheva
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Miroslava Stefanova
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Bilyana Genova
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Radoslava Kraleva
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Velin Kralev
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Abstract

We investigated age related synaptic plasticity in thalamic reticular nucleus (TRN) as a part of visual information processing system in the brain. Simulation experiments were performed using a hierarchical spike timing neural network model in NEST simulator. The model consists of multiple layers starting with retinal photoreceptors through thalamic relay, primary visual cortex layers up to the lateral intraparietal cortex (LIP) responsible for decision making and preparation of motor response. All synaptic inter- and intra-layer connections of our model are structured according to the literature information. The present work extends the model with spike timing dependent plastic (STDP) synapses within TRN as well as from visual cortex to LIP area. Synaptic strength changes were forced by teaching signal typical for three different age groups (young, middle and elderly) determined experimentally from eye movement data collected by eye tracking device from human subjects preforming a simplified simulated visual navigation task.
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hal-04050609 , version 1 (29-03-2023)

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Petia Koprinkova-Hristova, Nadejda Bocheva, Simona Nedelcheva, Miroslava Stefanova, Bilyana Genova, et al.. STDP Plasticity in TRN Within Hierarchical Spike Timing Model of Visual Information Processing. 16th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Jun 2020, Neos Marmaras, Greece. pp.279-290, ⟨10.1007/978-3-030-49161-1_24⟩. ⟨hal-04050609⟩
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