Perceptual learning (PL) is defined as long-term enhancement in a visual task or the process for the enhancement as a result of repeated visual experience and is regarded as manifestation of visual plasticity. Thus, studying PL will lead to increased clarification of visual plasticity, which is one of the most important goals in the visual sciences. Recently, there have been two important developments in studies of PL. First, reinforcement signals play an important role in PL. Second, sleep is fundamental for consolidation of PL. However, the neural mechanisms for these aspects of PL are not well clarified. In addition, these aspects have been studied totally separately (i.e., without relating to each other). Furthermore, although there are (1) task- relevant PL (TRPL) resulting from repetitive performance of a task and (2) task-irrelevant PL (TIPL) resulting from exposure to a visual feature, the roles of reinforcement signals and sleep consolidation have yet to be examined taking these two different types of PL into consideration. Using a decoding method applied to fMRI signals, we have observed how the """"""""tuning curve"""""""" in each of several brain areas changes (global tuning curve changes) under various conditions in association with PL. In this proposal, by taking advantage of using this new technique, we will investigate what the neural mechanisms are for reinforcement signal and sleep consolidation in TRPL and TIPL from the same viewpoint and aim to clarify how these mechanisms relate to each other. The goal of Aim 1 of current proposal is to clarify the neural mechanism for reinforcement signals. While it has been pointed out that reward-driven reinforcement signal plays an important role in PL, it remains unclear how the reward influences neural mechanisms in PL. We will address this question by examining how training of PL with reward leads to global tuning curve changes in brain areas. The goal of Aim 2 is to clarify neural mechanism changes during sleep consolidation. While it has been shown that sleep is fundamental for PL consolidation, it remains unclear how the neural mechanisms change during consolidation in different types of sleep (Non-REM and REM), different types of training (task-relevant and task-irrelevant PL), and with and without reward. We will address these questions by examining global tuning curve changes in these different conditions. Also, whether common neural mechanisms are involved in reward and sleep consolidation in PL will be examined by comparing global tuning curves obtained in these two aims. To date have examined reinforcement signals and sleep consolidation in PL using different paradigms and stimuli. Systematic investigation of the neural mechanisms for reinforcement signal and sleep consolidation and their interactions in each of TRPL and TIPL within the same framework will lead to significantly greater understanding of the underlying, different researchers neural mechanisms for PL.
The proposed research will investigate neural mechanisms of visual perceptual learning. The 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.
|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|
|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|
|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|
|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; Seitz, Aaron R; Watanabe, Takeo (2015) Visual perceptual learning by operant conditioning training follows rules of contingency. Vis cogn 23:147-160|
|Berard, Aaron V; Cain, Matthew S; Watanabe, Takeo et al. (2015) Frequent video game players resist perceptual interference. PLoS One 10:e0120011|
|Watanabe, Takeo; Sasaki, Yuka (2015) Perceptual learning: toward a comprehensive theory. Annu Rev Psychol 66:197-221|
|Kim, Dongho; Ling, Sam; Watanabe, Takeo (2015) Dual mechanisms governing reward-driven perceptual learning. F1000Res 4:764|
|Shibata, Kazuhisa; Sagi, Dov; Watanabe, Takeo (2014) Two-stage model in perceptual learning: toward a unified theory. Ann N Y Acad Sci 1316:18-28|
Showing the most recent 10 out of 53 publications