December 2022
Volume 22, Issue 14
Open Access
Vision Sciences Society Annual Meeting Abstract  |   December 2022
The stabilization of visual perceptual learning during REM sleep involves reward-processing circuits
Author Affiliations & Notes
  • Takashi Yamada
    Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI
  • Tyler Barnes-diana
    Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI
  • Shazain Khan
    Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI
  • Luke Rosedahl
    Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI
  • Sebastian Frank
    Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI
  • Antoinette Burger
    Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI
  • Takeo Watanabe
    Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI
  • Yuka Sasaki
    Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI
  • Footnotes
    Acknowledgements  NIH (R01EY031705, R01EY019466, R01EY027841, P20GM13974), KAKENHI (JP20KK0268).
Journal of Vision December 2022, Vol.22, 3262. doi:https://doi.org/10.1167/jov.22.14.3262
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      Takashi Yamada, Tyler Barnes-diana, Shazain Khan, Luke Rosedahl, Sebastian Frank, Antoinette Burger, Takeo Watanabe, Yuka Sasaki; The stabilization of visual perceptual learning during REM sleep involves reward-processing circuits. Journal of Vision 2022;22(14):3262. https://doi.org/10.1167/jov.22.14.3262.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

It is well-known that sleep facilitates visual perceptual learning (VPL), but which circuits are involved in the facilitation is unclear. Early visual areas are implicated in the facilitation. For example, non-rapid eye movement (non-REM) sleep plays a role in performance enhancement by increasing plasticity in early visual areas, while REM sleep stabilizes learning by decreasing plasticity in early visual areas. However, we recently found that reward provided during training prolongs subsequent REM sleep and strengthens VPL after sleep, suggesting that reward-processing circuits also play a role in some aspects of the facilitation. Here, we investigated how the reward-processing circuits are involved in VPL facilitation during sleep. Subjects were trained on different texture discrimination tasks (TDTs) before and after sleep. The TDTs were designed to interfere with each other unless pre-sleep learning was stabilized during sleep. We measured the balance between excitatory and inhibitory neurotransmitter concentrations (E/I balance) in the ventromedial prefrontal cortex (vmPFC), part of reward-processing circuits during non-REM sleep and REM sleep and wakefulness as baselines by magnetic resonance spectroscopy. This was based on our previous finding that the E/I balance is associated with the degree of brain plasticity. Sleep stages were determined by polysomnogram simultaneously measured with E/I balances. We found that the performance of both pre-sleep and post-sleep TDTs improved, indicating that pre-sleep learning was stabilized during sleep. Additionally, the E/I balance in the vmPFC during REM sleep decreased relative to baselines, and the amount of decrease was correlated with the degree of stabilization of pre-sleep learning. However, no such changes occurred during non-REM sleep. These results suggest that the stabilization of VPL during REM sleep involves the vmPFC as part of reward-processing circuits as well as early visual areas. Future research will investigate how the vmPFC interacts with early visual areas during sleep and facilitates VPL.

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