dc.contributor.author |
Nordberg, Hannah |
|
dc.contributor.author |
Hautus, Michael J |
|
dc.contributor.author |
Greene, Ernest |
|
dc.coverage.spatial |
United States |
|
dc.date.accessioned |
2023-08-04T03:23:10Z |
|
dc.date.available |
2023-08-04T03:23:10Z |
|
dc.date.issued |
2018-01 |
|
dc.identifier.citation |
(2018). AIMS Neuroscience, 5(2), 132-147. |
|
dc.identifier.issn |
2373-8006 |
|
dc.identifier.uri |
https://hdl.handle.net/2292/65343 |
|
dc.description.abstract |
Prior research has found that known shapes and letters can be recognized from a sparse sampling of dots that mark locations on their boundaries. Further, unknown shapes that are displayed only once can be identified by a matching protocol, and here also, above-chance performance requires very few boundary markers. The present work examines whether partial boundaries can be identified under similar low-information conditions. Several experiments were conducted that used a match-recognition task, with initial display of a target shape followed quickly by a comparison shape. The comparison shape was either derived from the target shape or was based on a different shape, and the respondent was asked for a matching judgment, i.e., did it "match" the target shape. Stimulus treatments included establishing how density affected the probability of a correct decision, followed by assessment of how much positioning of boundary dots affected this probability. Results indicate that correct judgments were possible when partial boundaries were displayed with a sparse sampling of dots. We argue for a process that quickly registers the locations of boundary markers and distills that information into a shape summary that can be used to identify the shape even when only a portion of the boundary is represented. |
|
dc.format.medium |
Electronic-eCollection |
|
dc.language |
eng |
|
dc.publisher |
American Institute of Mathematical Sciences (AIMS) |
|
dc.relation.ispartofseries |
AIMS neuroscience |
|
dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
|
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
|
dc.rights.uri |
http://creativecommons.org/licenses/by/4.0 |
|
dc.subject |
boundary marking |
|
dc.subject |
shape encoding |
|
dc.subject |
shape recognition |
|
dc.subject |
Science & Technology |
|
dc.subject |
Life Sciences & Biomedicine |
|
dc.subject |
Neurosciences |
|
dc.subject |
Neurosciences & Neurology |
|
dc.subject |
RECOGNITION |
|
dc.subject |
MODEL |
|
dc.subject |
FACE |
|
dc.subject |
3209 Neurosciences |
|
dc.title |
Visual encoding of partial unknown shape boundaries. |
|
dc.type |
Journal Article |
|
dc.identifier.doi |
10.3934/neuroscience.2018.2.132 |
|
pubs.issue |
2 |
|
pubs.begin-page |
132 |
|
pubs.volume |
5 |
|
dc.date.updated |
2023-07-26T21:49:34Z |
|
dc.rights.holder |
Copyright: The authors |
en |
dc.identifier.pmid |
32341957 (pubmed) |
|
pubs.author-url |
https://www.ncbi.nlm.nih.gov/pubmed/32341957 |
|
pubs.end-page |
147 |
|
pubs.publication-status |
Published |
|
dc.rights.accessrights |
http://purl.org/eprint/accessRights/OpenAccess |
en |
pubs.subtype |
research-article |
|
pubs.subtype |
Journal Article |
|
pubs.elements-id |
752910 |
|
pubs.org-id |
Science |
|
pubs.org-id |
Psychology |
|
dc.identifier.eissn |
2373-7972 |
|
dc.identifier.pii |
neurosci-05-02-132 |
|
pubs.record-created-at-source-date |
2023-07-27 |
|
pubs.online-publication-date |
2018-05-16 |
|