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Enhancement of a model of essential tremor using SNNAP
Author(s) -
Moran Joseph,
Watrous James
Publication year - 2013
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.27.1_supplement.933.1
Subject(s) - neuroscience , network model , focus (optics) , computer science , biological neuron model , conductance , sodium channel , neuron , artificial neural network , simulation , biological system , artificial intelligence , chemistry , physics , psychology , sodium , biology , organic chemistry , optics , condensed matter physics
Essential tremor (ET) is a disorder characterized by uncontrollable shaking in the extremities. The exact cause is unknown; thus, ET is currently the focus of several investigators. The focus of this research is the development of an improved computer model of ET. SNNAP (Simulator for Neural Networks and Action Potentials) was used to construct a model motor circuit. The initial network and neuron construction is based on work done by Shaikh et al., 2008. The model neuron is a Hodgkin‐Huxley type with additional hyperpolarizing and low threshold Calcium currents. The network contains eight neurons arranged in a simplified motor circuit. A muscle cell (20 μm × 200 μm) was inserted into the network as the output cell, providing a more physiologically realistic model. The benefits of the network have proven to be the ability to analyze the behavior of each cell and synaptic connection individually. Our results identify the hyperpolarizing channel and the conductance of synaptic connections as being most influential in controlling frequency of tremors while the sodium channel is most influential in controlling amplitude.