Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
10
pubmed:dateCreated
1997-7-14
pubmed:abstractText
We present a neural network model of short-term dynamics of the human horizontal vergence system (HVS) and compare its predictions qualitatively and quantitatively with a large variety of horizontal disparity vergence data. The model consists of seven functional stages, namely: (1) computation of instantaneous disparity; (2) generation of a disparity map; (3) conversion of the disparity into a velocity signal; (4) push-pull integration of velocity to generate a position signal; (5) conversion of the position signal to motoneuron/plant activity for each eye; (6) gating of velocity overdrive signal to motoneuron/plant system; and finally (7) discharge path for position cells. Closed-loop (normal binocular viewing) symmetric step and staircase disparity vergence data were collected from three subjects and model parameters were determined to quantitatively match each subject's data. The simulated closed-loop as well as open-loop (disparity clamped viewing) symmetric step, sinusoidal, pulse, staircase, square and ramp wave responses closely resemble experimental results either recorded in our laboratory or reported in the literature. Where possible, the firing pattern of the neurons in the model have been compared to actual cellular recordings reported in the literature. The model provides insights into neural correlates underlying the dynamics of vergence eye movements. It also makes novel predictions about the human vergence system.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
0042-6989
pubmed:author
pubmed:issnType
Print
pubmed:volume
37
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1383-99
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
1997
pubmed:articleTitle
Neural network model of short-term horizontal disparity vergence dynamics.
pubmed:affiliation
Department of Electrical & Computer Engineering, University of Houston, TX 77204-4793, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't