Linked Life Data

9797961

Source:http://linkedlifedata.com/resource/pubmed/id/9797961

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
12
pubmed:dateCreated
1998-11-10
pubmed:abstractText
Simulations of a neural network model of retino-cortical dynamics (O?men H, Neural Netw 6 (1993) 245-273) are presented. The temporal-step response of the model to a single dot (spatial impulse) consists of three post-retinal phases: reset, feed-forward dominant and feedback dominant. In response to a single moving dot, the model predicts the perception of extensive blur. This extensive blur is proposed to be due to the relative spatial and temporal offsets between transient and sustained signals conveyed from retina to post-retinal levels. In response to a pair of horizontally separated dots moving in the horizontal direction, the model predicts extensive blur for the trailing dot irrespective of dot-to-dot separation. For the leading dot, the model predicts a decrease in perceived blur for long exposure durations when dot-to-dot separations are small. The reduction of perceived blur at long exposure durations for small dot-to-dot separations is proposed to stem from the spatio-temporal overlap between the transient activity generated by the trailing dot and the sustained activity generated by the leading dot. The model also predicts that targets moving at higher speeds generate more blur even when blur is normalized with respect to speed. The mechanism in the model generating this effect is a slow inhibition within the sustained channel. These predictions are compared with recent psychophysical data (Chen S, Bedell HE, O?men H, Vis Res 35 (1995) 2315-2328) and are found to be in excellent agreement. The model is used to offer a coherent explanation for several controversial findings published in the literature. This computational study shows that a model without any motion-compensation mechanism can give a good account of motion deblurring phenomenon and supplements our recent experimental study which provided evidence against motion-compensation type models in explaining the motion deblurring phenomenon (Chen S, Bedell HE, O?men H, Vis Res 35 (1995) 2315-2328).
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
0042-6989
pubmed:author
pubmed:issnType
Print
pubmed:volume
38
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1827-42
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
1998
pubmed:articleTitle
Motion deblurring in a neural network model of retino-cortical dynamics.
pubmed:affiliation
Department of Electrical and Computer Engineering, University of Houston, TX 77204-4793, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.