TY - JOUR
T1 - Synaptic adaptation and sustained generation of waves in a model of turtle visual cortex
AU - Freudenburg, Zachary V.
AU - Ghosh, Bijoy K.
AU - Ulinski, Philip S.
N1 - Funding Information:
Thus, Gitman M.B., Danilov A. N., Stolbov, V. Yu., and Yuzhakov A. A., when considering the models of network interaction between universities and institutes of the Russian Academy of Sciences in the implementation of educational programs for the preparation of masters and graduate students, identify a model of network interaction in the framework of university cooperation; regional model of network interaction of universities based on the Scientific and Educational Center of the National Research University; model of networking of universities based on the Scientific and Educational Center network in the framework of the integration of science and education and intercollegiate cooperation [20].
PY - 2009/5
Y1 - 2009/5
N2 - Both single and repeated visual stimuli producewaves 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 papermodifies 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.
AB - Both single and repeated visual stimuli producewaves 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 papermodifies 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.
KW - Hebbian learning
KW - Large-scale cortex model
KW - Synaptic adaptation
KW - Turtle visual cortex
UR - http://www.scopus.com/inward/record.url?scp=67649221680&partnerID=8YFLogxK
U2 - 10.1109/TBME.2008.2010134
DO - 10.1109/TBME.2008.2010134
M3 - Article
C2 - 19150779
AN - SCOPUS:67649221680
SN - 0018-9294
VL - 56
SP - 1277
EP - 1286
JO - IEEE Transactions on Biomedical Engineering
JF - IEEE Transactions on Biomedical Engineering
IS - 5
M1 - 4749354
ER -