August 2012
Volume 12, Issue 9
Free
Vision Sciences Society Annual Meeting Abstract  |   August 2012
MEG slow activity in V1 during sleep and perceptual learning
Author Affiliations
  • Ji Won Bang
    Boston University
  • Omid Khalilzadeh
    Boston University\nMassachusetts General Hospital
  • Daniel Wakeman
    Massachusetts General Hospital
  • Masako Tamaki
    Advanced Telecommunications Research Institute International
  • Matti Hämäläinen
    Massachusetts General Hospital
  • Takeo Watanabe
    Boston University
  • Yuka Sasaki
    Massachusetts General Hospital
Journal of Vision August 2012, Vol.12, 1125. doi:https://doi.org/10.1167/12.9.1125
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      Ji Won Bang, Omid Khalilzadeh, Daniel Wakeman, Masako Tamaki, Matti Hämäläinen, Takeo Watanabe, Yuka Sasaki; MEG slow activity in V1 during sleep and perceptual learning. Journal of Vision 2012;12(9):1125. https://doi.org/10.1167/12.9.1125.

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

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Abstract

Sleep plays a key role in facilitatory effect of memory and learning. However, the underlying neural mechanism has yet to be completely understood. Here, to better clarify the mechanism for the faciliatory effect on visual perceptual learning, we measured fine-scaled spatio-temporal neural activity during sleep after training of texture discrimination task (TDT) using a multimodal neuroimaging technique that combines MEG and MRI. A leading hypothesis suggests that the slow wave activity (SWA) during the sleep period is involved in the facilitatory effect. Since the TDT is associated with changes in the region of the primary visual area (V1) that retinotopically corresponds to the trained visual field quadrant, we tested whether the strength of SWA in V1 is correlated with the facilitatory effect during sleep on TDT.

Young and healthy participants underwent an MRI session after 4 nightly MEG sessions including 2 adaptation nights, pre-training sleep, and post-training sleep. Before the post-training sleep, TDT was conducted twice; more training in one visual field quadrant and less training in another quadrant. After the post-training sleep, we conducted a re-test of TDT. Wavelet-transformed MEG during sleep was combined with high-resolution MRI to constrain the current locations to the cortical mantle individually. Based on the retinotopic mapping, we localized the 2 cortical quadrants that retinopically corresponds to the more and less trained visual field quadrants in V1 and measured the strength of SWA in those areas. The results showed that the SWA in the trained V1 was markedly stronger in the post-training sleep compared to the pre-training sleep, and the SWA strength in each cortical quadrant was correlated with the performance improvement in each visual field quadrant. The results suggest the feasibility of the hypothesis that the slow wave activity is involved in the consolidation of TDT during sleep.

Meeting abstract presented at VSS 2012

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