Integration of Position and Predictive Motion Signals in Aging Vision.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
29 05 2020
Historique:
received: 18 12 2018
accepted: 01 05 2020
entrez: 31 5 2020
pubmed: 31 5 2020
medline: 15 12 2020
Statut: epublish

Résumé

We examined the effect of aging on the integration of position and motion signals, which is essential for tracking visual objects, using the motion-induced position shift (MIPS) phenomenon. We first measured the MIPS and bias in speed perception at three eccentricities. Both young and older adults showed the increasing MIPS and decreasing perceived speed as the eccentricity increased, which is consistent with previous literature. More importantly, we found that the mean MIPS was 2.87 times larger in older adults, and the response variability in position tasks showed a larger difference between age groups compared with the difference in speed tasks. We then measured the MIPS across stimulus durations. Temporal changes in the MIPS showed similar patterns in young and older adults in that the MIPS initially peaked at around 60 ms and approached an asymptote. We further analyzed the changes in response variability across stimulus durations to estimate sensory noise and propagation noise separately and found that only sensory noise was significantly larger in older adults. The overall results suggest that the increased MIPS in older adults is due to the increased dependency on predictive motion signals to compensate for the relatively imprecise position signals, which in turn implies that older adults would depend more on the motion signals to track objects.

Identifiants

pubmed: 32472035
doi: 10.1038/s41598-020-65568-y
pii: 10.1038/s41598-020-65568-y
pmc: PMC7260223
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

8783

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Auteurs

Hyun-Jun Jeon (HJ)

Department of Human Factors Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea.

Yeojeong Yun (Y)

Department of Human Factors Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea.

Oh-Sang Kwon (OS)

Department of Human Factors Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea. oskwon@unist.ac.kr.

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