STDP Training of Hierarchical Spike Timing Model of Visual Information Processing

Koprinkova–Hristova, Petia; Nedelcheva, Simona; Bocheva, Nadejda; Kraleva, Radoslava; Kralev, Velin; Stefanova, Miroslava; Genova, Bilyana

doi:10.1109/ijcnn48605.2020.9207598

Cited by 1 publication

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“…Our preliminary attempt to tune the synaptic connections between the last two layers (MST and LIP) using final outcome from experiments on visual information perception and decision making, i.e. recorded motor reaction (saccade generation) revealed that spike timing dependent plasticity (STDP) led to age-related changes in these synaptic weights [12]. Training data was collected from the human decisions during experiment with visual stimuli simulating optic flow patterns of forward self-motion on a linear trajectory to the left or to the right of the center of the visual field with a gaze in the direction of heading.…”

Section: Introductionmentioning

confidence: 99%

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

Koprinkova–Hristova

Bocheva

Nedelcheva

et al. 2020

IFIP Advances in Information and Communication Technology

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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. Keywords: Spike timing neural model • Spike timing dependent plasticity • Visual system • Decision making • Saccade generation This work was financially supported by the Bulgarian Science Fund, grant No DN02-3-2016 "Modeling of voluntary saccadic eye movements during decision making".

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Section: Introductionmentioning

confidence: 99%