Perceptual learning (PL) is defined as performance increase of a visual feature as a result of training or exposure to the feature and is regarded as a manifestation of plasticity in sensory/perceptual processing. While our on-going project (R01EY015980) has revealed how external factors gate PL, the current proposal will address a more fundamental but unanswered question;how do neural mechanisms change in correlation with PL? It has been found that several factors fundamentally influence the mechanism of PL. First, PL is formed as a result of training of a detection task and a discrimination task (task-relevant learning) or exposure to a task- irrelevant feature presented over time (task-irrelevant learning). Different training methods could influence the mechanisms of PL in different ways. Second, the neural processing of PL seems to greatly change as learning proceeds. Third, external feedback to subjects as to their performance of a task can facilitate PL or in some cases is necessary for PL. Nevertheless, it has yet to be clarified how these 3 factors influence the neural mechanisms of PL. We will address this question by systematically examining changes of tuning functions of a trained feature that are obtained in multiple areas of visual processing in the brain. For this purpose, we will measure blood oxygen level dependent (BOLD) signals that are regarded as reflecting neural activity. Specifically, BOLD response tuning function changes will be measured in multiple areas of visual processing in correlation with PL. We will first examine how BOLD activity changes occur by the different training methods such as training of a detection task, training of a discrimination task and exposure to a task-irrelevant feature and address the question concerning how neural changes resulting from different training methods are related to each other. Second, we will examine how BOLD activity changes occur during the time course of learning. Note that BOLD response tuning function changes can be characterized as response increases for some feature values and/or decreases for other values. We will examine how relative BOLD response increases and decreases occur in tuning functions during the time course of learning and also test whether BOLD signal increases and decreases originate from the same mechanism. Third, we will examine whether and how external feedback influences BOLD response tuning function changes reflected in multiple areas of visual processing. If feedback influences BOLD response tuning functions, we will further investigate whether it facilitates response increase only, response decrease only, or both, in response tuning functions. Overall, while the neural changes by the 3 fundamental factors appear to be highly different, the systematic investigation in 3 aims of the current proposal may clarify whether it is theoretically possible to view these changes as a result of combinations of excitatory inputs that cause response increases and inhibitory signals that cause response decreases over the time course of PL.

Public Health Relevance

The proposed research has potential for clinical applications by contributing to scientific knowledge leading to improved diagnosis of, and rehabilitative therapies for, brain disorders and lesions, in particular those related to sensory function.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
5R01EY015980-06
Application #
7904092
Study Section
Special Emphasis Panel (ZRG1-IFCN-B (04))
Program Officer
Wiggs, Cheri
Project Start
2004-08-01
Project End
2011-07-31
Budget Start
2010-08-01
Budget End
2011-07-31
Support Year
6
Fiscal Year
2010
Total Cost
$402,188
Indirect Cost
Name
Boston University
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
049435266
City
Boston
State
MA
Country
United States
Zip Code
02215
Kang, Dong-Wha; Kim, Dongho; Chang, Li-Hung et al. (2018) Structural and Functional Connectivity Changes Beyond Visual Cortex in a Later Phase of Visual Perceptual Learning. Sci Rep 8:5186
Shibata, Kazuhisa; Sasaki, Yuka; Bang, Ji Won et al. (2017) Corrigendum: Overlearning hyperstabilizes a skill by rapidly making neurochemical processing inhibitory-dominant. Nat Neurosci 20:1427
Shibata, Kazuhisa; Sasaki, Yuka; Bang, Ji Won et al. (2017) Overlearning hyperstabilizes a skill by rapidly making neurochemical processing inhibitory-dominant. Nat Neurosci 20:470-475
Shibata, Kazuhisa; Sasaki, Yuka; Kawato, Mitsuo et al. (2016) Neuroimaging Evidence for 2 Types of Plasticity in Association with Visual Perceptual Learning. Cereb Cortex 26:3681-9
Yahata, Noriaki; Morimoto, Jun; Hashimoto, Ryuichiro et al. (2016) A small number of abnormal brain connections predicts adult autism spectrum disorder. Nat Commun 7:11254
Tamaki, Masako; Bang, Ji Won; Watanabe, Takeo et al. (2016) Night Watch in One Brain Hemisphere during Sleep Associated with the First-Night Effect in Humans. Curr Biol 26:1190-4
Kim, Dongho; Seitz, Aaron R; Watanabe, Takeo (2015) Visual perceptual learning by operant conditioning training follows rules of contingency. Vis cogn 23:147-160
Chang, Li-Hung; Yotsumoto, Yuko; Salat, David H et al. (2015) Reduction in the retinotopic early visual cortex with normal aging and magnitude of perceptual learning. Neurobiol Aging 36:315-22
Kim, Dongho; Ling, Sam; Watanabe, Takeo (2015) Dual mechanisms governing reward-driven perceptual learning. F1000Res 4:764
Berard, Aaron V; Cain, Matthew S; Watanabe, Takeo et al. (2015) Frequent video game players resist perceptual interference. PLoS One 10:e0120011

Showing the most recent 10 out of 55 publications