Precision of working memory for visual motion sequences and transparent motion surfaces.
Recent studies investigating working memory for location, color, and orientation support a dynamic resource model. We examined whether this might also apply to motion, using random dot kinematograms (RDKs) presented sequentially or simultaneously. Mean precision for motion direction declined as sequ...
| Автори: | , , , , |
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| Формат: | Journal article |
| Мова: | English |
| Опубліковано: |
2011
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| _version_ | 1826305760033767424 |
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| author | Zokaei, N Gorgoraptis, N Bahrami, B Bays, P Husain, M |
| author_facet | Zokaei, N Gorgoraptis, N Bahrami, B Bays, P Husain, M |
| author_sort | Zokaei, N |
| collection | OXFORD |
| description | Recent studies investigating working memory for location, color, and orientation support a dynamic resource model. We examined whether this might also apply to motion, using random dot kinematograms (RDKs) presented sequentially or simultaneously. Mean precision for motion direction declined as sequence length increased, with precision being lower for earlier RDKs. Two alternative models of working memory were compared specifically to distinguish between the contributions of different sources of error that corrupt memory (W. Zhang and S. J. Luck, 2008 vs. P. M. Bays, R. F. G. Catalao, and M. Husain, 2009). The latter provided a significantly better fit for the data, revealing that decrease in memory precision for earlier items is explained by an increase in interference from other items in a sequence rather than random guessing or a temporal decay of information. Misbinding feature attributes is an important source of error in working memory. Precision of memory for motion direction decreased when two RDKs were presented simultaneously as transparent surfaces, compared to sequential RDKs. However, precision was enhanced when one motion surface was prioritized, demonstrating that selective attention can improve recall precision. These results are consistent with a resource model that can be used as a general conceptual framework for understanding working memory across a range of visual features. |
| first_indexed | 2024-03-07T06:37:43Z |
| format | Journal article |
| id | oxford-uuid:f83b51c2-6f4a-424d-a3a9-879addf4b924 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T06:37:43Z |
| publishDate | 2011 |
| record_format | dspace |
| spelling | oxford-uuid:f83b51c2-6f4a-424d-a3a9-879addf4b9242022-03-27T12:48:42ZPrecision of working memory for visual motion sequences and transparent motion surfaces.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:f83b51c2-6f4a-424d-a3a9-879addf4b924EnglishSymplectic Elements at Oxford2011Zokaei, NGorgoraptis, NBahrami, BBays, PHusain, MRecent studies investigating working memory for location, color, and orientation support a dynamic resource model. We examined whether this might also apply to motion, using random dot kinematograms (RDKs) presented sequentially or simultaneously. Mean precision for motion direction declined as sequence length increased, with precision being lower for earlier RDKs. Two alternative models of working memory were compared specifically to distinguish between the contributions of different sources of error that corrupt memory (W. Zhang and S. J. Luck, 2008 vs. P. M. Bays, R. F. G. Catalao, and M. Husain, 2009). The latter provided a significantly better fit for the data, revealing that decrease in memory precision for earlier items is explained by an increase in interference from other items in a sequence rather than random guessing or a temporal decay of information. Misbinding feature attributes is an important source of error in working memory. Precision of memory for motion direction decreased when two RDKs were presented simultaneously as transparent surfaces, compared to sequential RDKs. However, precision was enhanced when one motion surface was prioritized, demonstrating that selective attention can improve recall precision. These results are consistent with a resource model that can be used as a general conceptual framework for understanding working memory across a range of visual features. |
| spellingShingle | Zokaei, N Gorgoraptis, N Bahrami, B Bays, P Husain, M Precision of working memory for visual motion sequences and transparent motion surfaces. |
| title | Precision of working memory for visual motion sequences and transparent motion surfaces. |
| title_full | Precision of working memory for visual motion sequences and transparent motion surfaces. |
| title_fullStr | Precision of working memory for visual motion sequences and transparent motion surfaces. |
| title_full_unstemmed | Precision of working memory for visual motion sequences and transparent motion surfaces. |
| title_short | Precision of working memory for visual motion sequences and transparent motion surfaces. |
| title_sort | precision of working memory for visual motion sequences and transparent motion surfaces |
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