Linked Life Data

16256166

Source:http://linkedlifedata.com/resource/pubmed/id/16256166

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6-7
pubmed:dateCreated
2006-1-2
pubmed:abstractText
Glass patterns--randomly positioned coherently orientated dipoles--create a strong sensation of oriented spatial structure. On the other hand, coherently oriented dipoles comprising dots of opposite polarity ("anti-Glass" patterns) have no distinct spatial structure and are very hard to distinguish from random noise. Although anti-Glass patterns have no obvious spatial structure themselves, their presence can destroy the structure created by Glass patterns. We measured the strength of this effect for both static and dynamic Glass patterns, and showed that anti-Glass patterns can raise thresholds for Glass patterns by a factor of 2-4, increasing with density. The dependence on density suggests that the interactions occur at a local level. When the Glass and anti-Glass dipoles were confined to alternate strips (in translational and circular Glass patterns), the detrimental effect occurred for stripe widths less than about 1.5 degrees, but had little effect for larger stripe widths, reinforcing the suggestion that the interaction occurred over a limited spatial extent. The extent of spatial interaction was much less than that for spatial summation of these patterns, at least 30 degrees under matched experimental conditions. The results suggest two stages of analysis for Glass patterns, an early stage of limited spatial extent where orientation is extracted, and a later stage that sums these orientation signals.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
0042-6989
pubmed:author
pubmed:issnType
Print
pubmed:volume
46
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1139-44
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
The effects of opposite-polarity dipoles on the detection of Glass patterns.
pubmed:affiliation
Istituto di Neuroscienze del CNR, Pisa 56100, Italy. dave@in.cnr.it
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't