Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6172
pubmed:dateCreated
1988-7-1
pubmed:abstractText
It is not known how the visual system is organized to extract information about shape from the continuous gradations of light and dark found on shaded surfaces of three-dimensional objects. To investigate this question, we used a learning algorithm to construct a neural network model which determines surface curvatures from images of simple geometrical surfaces. The receptive fields developed by units in the network were surprisingly similar to the actual receptive fields of neurons observed in the visual cortex which are commonly believed to be 'edge' or 'bar' detectors, but have never previously been associated with shading. Thus, our study illustrates the difficulty of trying to deduce neuronal function solely from determination of their receptive fields. It is also important to consider the connections a neuron makes with other neurons in subsequent stages of processing, which we call its 'projective field'.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
0028-0836
pubmed:author
pubmed:issnType
Print
pubmed:day
2
pubmed:volume
333
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
452-4
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1988
pubmed:articleTitle
Network model of shape-from-shading: neural function arises from both receptive and projective fields.
pubmed:affiliation
Department of Biophysics, Johns Hopkins University, Baltimore, Maryland 21218.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S., Research Support, Non-U.S. Gov't