Title :
Synaptic Adaptation and Sustained Generation of Waves in a Model of Turtle Visual Cortex
Author :
Freudenburg, Zachary V. ; Ghosh, Bijoy K. ; Ulinski, Philip S.
Author_Institution :
Dept. of Comput. Sci. & Eng., Washington Univ., St. Louis, MO
fDate :
5/1/2009 12:00:00 AM
Abstract :
Both single and repeated visual stimuli produce waves of activity in the visual cortex of freshwater turtles. Large-scale, biophysically realistic models of the visual cortex capture the basic features of the waves produced by single stimuli. However, these models do not respond to repetitive stimuli due to the presence of a long-lasting hyperpolarization that follows the initial wave. This paper modifies the large-scale model so that it responds to repetitive stimuli by incorporating Hebbian and anti-Hebbian learning rules in synapses in the model. The resulting adaptive model responds to repetitive stimuli with repetitive waves. However, repeated presentation of a stimulus to a restricted region of visual space produces a habituation in the model in the same way it does in the real cortex.
Keywords :
Hebbian learning; adaptive systems; biology computing; neural nets; visual evoked potentials; adaptive model; antiHebbian learning rules; hyperpolarization; synaptic adaptation; turtle visual cortex; visual stimuli; wave generation; Adaptation model; Anatomy; Brain modeling; Hebbian theory; In vivo; Information analysis; Large-scale systems; Neurons; Principal component analysis; Reflection; Spatiotemporal phenomena; Voltage; Hebbian learning; large-scale cortex model; synaptic adaptation; turtle visual cortex; Algorithms; Animals; Artificial Intelligence; Computer Simulation; Models, Neurological; Neuronal Plasticity; Photic Stimulation; Pyramidal Cells; Synapses; Turtles; Visual Cortex;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2008.2010134