Literature DB >> 25454783

Age-related declines of stability in visual perceptual learning.

Li-Hung Chang1, Kazuhisa Shibata2, George J Andersen3, Yuka Sasaki2, Takeo Watanabe4.   

Abstract

One of the biggest questions in learning is how a system can resolve the plasticity and stability dilemma. Specifically, the learning system needs to have not only a high capability of learning new items (plasticity) but also a high stability to retain important items or processing in the system by preventing unimportant or irrelevant information from being learned. This dilemma should hold true for visual perceptual learning (VPL), which is defined as a long-term increase in performance on a visual task as a result of visual experience. Although it is well known that aging influences learning, the effect of aging on the stability and plasticity of the visual system is unclear. To address the question, we asked older and younger adults to perform a task while a task-irrelevant feature was merely exposed. We found that older individuals learned the task-irrelevant features that younger individuals did not learn, both the features that were sufficiently strong for younger individuals to suppress and the features that were too weak for younger individuals to learn. At the same time, there was no plasticity reduction in older individuals within the task tested. These results suggest that the older visual system is less stable to unimportant information than the younger visual system. A learning problem with older individuals may be due to a decrease in stability rather than a decrease in plasticity, at least in VPL.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Mesh:

Year:  2014        PMID: 25454783      PMCID: PMC4269556          DOI: 10.1016/j.cub.2014.10.041

Source DB:  PubMed          Journal:  Curr Biol        ISSN: 0960-9822            Impact factor:   10.834


  40 in total

1.  Perceptual learning without perception.

Authors:  T Watanabe; J E Náñez; Y Sasaki
Journal:  Nature       Date:  2001-10-25       Impact factor: 49.962

2.  Greater disruption due to failure of inhibitory control on an ambiguous distractor.

Authors:  Yoshiaki Tsushima; Yuka Sasaki; Takeo Watanabe
Journal:  Science       Date:  2006-12-15       Impact factor: 47.728

Review 3.  A common framework for perceptual learning.

Authors:  Aaron R Seitz; Hubert R Dinse
Journal:  Curr Opin Neurobiol       Date:  2007-02-20       Impact factor: 6.627

4.  Visual motion interferes with lexical decision on motion words.

Authors:  Lotte Meteyard; Nahid Zokaei; Bahador Bahrami; Gabriella Vigliocco
Journal:  Curr Biol       Date:  2008-09-09       Impact factor: 10.834

Review 5.  Aging, training, and the brain: a review and future directions.

Authors:  Cindy Lustig; Priti Shah; Rachael Seidler; Patricia A Reuter-Lorenz
Journal:  Neuropsychol Rev       Date:  2009-10-30       Impact factor: 7.444

Review 6.  Adaptive Resonance Theory: how a brain learns to consciously attend, learn, and recognize a changing world.

Authors:  Stephen Grossberg
Journal:  Neural Netw       Date:  2012-10-04

7.  Learning mnemonics: roles of aging and subtle cognitive impairment.

Authors:  J A Yesavage; J I Sheikh; L Friedman; E Tanke
Journal:  Psychol Aging       Date:  1990-03

8.  Dichoptic training enables the adult amblyopic brain to learn.

Authors:  Jinrong Li; Benjamin Thompson; Daming Deng; Lily Y L Chan; Minbin Yu; Robert F Hess
Journal:  Curr Biol       Date:  2013-04-22       Impact factor: 10.834

9.  Perceptual learning, aging, and improved visual performance in early stages of visual processing.

Authors:  George J Andersen; Rui Ni; Jeffrey D Bower; Takeo Watanabe
Journal:  J Vis       Date:  2010-11-04       Impact factor: 2.240

10.  Improvement and impairment of visually guided behavior through LTP- and LTD-like exposure-based visual learning.

Authors:  Christian Beste; Edmund Wascher; Onur Güntürkün; Hubert R Dinse
Journal:  Curr Biol       Date:  2011-05-05       Impact factor: 10.834

View more
  6 in total

1.  A Mouse Model of Visual Perceptual Learning Reveals Alterations in Neuronal Coding and Dendritic Spine Density in the Visual Cortex.

Authors:  Yan Wang; Wei Wu; Xian Zhang; Xu Hu; Yue Li; Shihao Lou; Xiao Ma; Xu An; Hui Liu; Jing Peng; Danyi Ma; Yifeng Zhou; Yupeng Yang
Journal:  Front Behav Neurosci       Date:  2016-03-10       Impact factor: 3.558

2.  Perceptual learning of task-irrelevant features depends on the sensory context.

Authors:  Patrick Bruns; Takeo Watanabe
Journal:  Sci Rep       Date:  2019-02-07       Impact factor: 4.379

3.  Frequency-Dependent Effects of Cerebellar Repetitive Transcranial Magnetic Stimulation on Visuomotor Accuracy.

Authors:  Yun R Lien; Yi-Cheng Lin; Shang-Hua N Lin; Ching-Po Lin; Li-Hung Chang
Journal:  Front Neurosci       Date:  2022-03-18       Impact factor: 4.677

4.  Age-related differences in visual confidence are driven by individual differences in cognitive control capacities.

Authors:  Lena Klever; Pascal Mamassian; Jutta Billino
Journal:  Sci Rep       Date:  2022-04-10       Impact factor: 4.379

5.  Control of a Supernumerary Robotic Hand by Foot: An Experimental Study in Virtual Reality.

Authors:  Elahe Abdi; Etienne Burdet; Mohamed Bouri; Hannes Bleuler
Journal:  PLoS One       Date:  2015-07-30       Impact factor: 3.240

6.  Neuroimaging Evidence for 2 Types of Plasticity in Association with Visual Perceptual Learning.

Authors:  Kazuhisa Shibata; Yuka Sasaki; Mitsuo Kawato; Takeo Watanabe
Journal:  Cereb Cortex       Date:  2016-06-13       Impact factor: 5.357

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.