The paper presents a hierarchical spike timing neural network model developed in NEST simulator aimed to reproduce human decision making in simplified simulated visual navigation tasks. It includes multiple layers starting from retina photoreceptors and retinal ganglion cells (RGC) via thalamic relay including lateral geniculate nucleus (LGN), thalamic reticular nucleus (TRN), and interneurons (IN) mediating connections to the higher brain areas—visual cortex (V1), middle temporal (MT), and medial superior temporal (MTS) areas, involved in dorsal pathway processing of spatial and dynamic visual information. The last layer—lateral intraparietal cortex (LIP)—is responsible for decision making and organization of the subsequent motor response (saccade generation). We simulated two possible decision options having LIP layer with two sub-regions with mutual inhibitory connections whose increased firing rate corresponds to the perceptual decision about motor response—left or right saccade. Each stage of the model was tested by appropriately chosen stimuli corresponding to its selectivity to specific stimulus characteristics (orientation for V1, direction for MT, and expansion/contraction movement templates for MST, respectively). The overall model performance was tested with stimuli simulating optic flow patterns of forward self-motion on a linear trajectory to the left or to the right from straight ahead with a gaze in the direction of heading.
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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