September 2019
Volume 19, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2019
Beyond activity changes: appropriate expertise training not just drives higher activities, but also faster BOLD onset and better classifications for Greebles
Author Affiliations & Notes
  • Chun-Chia Kung
    Departments of Psychology, National Cheng Kung University, Tainan, Taiwan
    Mind Research and Imaging (MRI) center, National Cheng Kung University, Tainan, Taiwan
  • Chien-Shu Chu
    Departments of Psychology, National Cheng Kung University, Tainan, Taiwan
  • Yi Lin
    Departments of Psychology, National Cheng Kung University, Tainan, Taiwan
  • Hanshin Jo
    Institute of Medical Informatics, National Cheng Kung University, Tainan, Taiwan
  • Kuo Liu
    Departments of Psychology, National Cheng Kung University, Tainan, Taiwan
Journal of Vision September 2019, Vol.19, 137c. doi:https://doi.org/10.1167/19.10.137c
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      Chun-Chia Kung, Chien-Shu Chu, Yi Lin, Hanshin Jo, Kuo Liu; Beyond activity changes: appropriate expertise training not just drives higher activities, but also faster BOLD onset and better classifications for Greebles. Journal of Vision 2019;19(10):137c. https://doi.org/10.1167/19.10.137c.

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

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Abstract

Previous discussions about the role of FFA in face and/or expertise processing focused on whether Greebles are face-like (e.g., Brants et al., 2011 JOCN). But in our previous work (Liu et al., 2017 OHBM), we have identified that it was more likely due to the appropriate training, than on the stimulus category per se (e.g., face-likeness of Greebles), that caused the FFA activity increases. In this study, we report a companion jittered event-related fMRI experiment where participants did the same verification task that they were kept trained on. Our hypothesis is that, as the correct trial RTs for Greeble verifications became faster, their FFA BOLD responses should also rise earlier, and such earlier rise also predicts earlier and higher classification accuracy for Greebles. With previous reported training protocols and fMRI results (Liu et al., 2017), where 16 participants underwent two different Greeble training regimes (n=8 for each of Gauthier97 and Gauthier98, respectively) and scanned during and after training, we first plotted the average FFA time courses and noted that it did rise earlier in Gauthier97, but not in Gauthier98, after training (and later confirmed with estimates of BOLD rising time via BOLD Latency Mapping, or BLA), suggesting the earlier rise even before the appearance of Greebles. In addition, MVPA classifications, either ROI-based or whole-brain searchlight mapping in comparing during- vs. after-training Greebles, also reveal that these early BOLD rises help classify Greebles significantly, in response to the trained task requirements: earlier rise (Gauthier97) recruited temporal and prefrontal areas in the earlier time frame (3–8s after trial onset), whereas Gauthier98 showed classification successes much later (5–15s) and persisted comparatively in ventral temporal areas. Taken together, these results exemplify the effect of expertise training beyond single ROI (e.g., FFA) and single dimension (e.g., magnitude, time, and classification accuracy).

Acknowledgement: MOST 107-2420-H-006-007 
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