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Bingbing Guo, Jessica Goold, Huan Luo, Ming Meng; Neural correlates of time-resolved behavioral responses reveal theta-band oscillations in the fusiform face area and parahippocampal place area. Journal of Vision 2015;15(12):14. doi: https://doi.org/10.1167/15.12.14.
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© ARVO (1962-2015); The Authors (2016-present)
Repeated exposure to same stimuli may lead to on one hand neuronal adaption in brain areas representing the stimuli, on the other hand visual priming effect to facilitate recognition of the stimuli. To investigate dynamic relationships between these neural and behavioral effects, we measured brain activity using fMRI when participants performed a speeded response task of detecting face/house with visual priming of the same but smaller face/house. Critically, we employed time-resolved measurements, by varying stimulus onset asynchrony (SOA) between the prime and probe in a small step of 20ms, from 200ms to 1080ms. Recent behavioral studies using a similar paradigm but different stimuli to measure time-resolved response dynamics revealed theta-band oscillations in reaction times (see Huang, Chen and Luo, VSS2015). Here we chose face/house as the stimuli to examine whether activity in the known face-selective areas (e.g., the fusiform face area, FFA) and house-selective areas (e.g., the parahippocampal place area, PPA) may correlate with the rhythmic dynamics of reaction times in detecting face/house. Our behavioral results replicated previous findings, showing theta-band oscillations in priming effects. Interestingly, fMRI multivariate pattern analysis (MVPA) results also demonstrate theta-band oscillations and out-of-phase relationship between congruent and incongruent conditions in the FFA and PPA. This is the first time of using fMRI to localize time-resolved rhythmic activity, despite the relatively sluggish temporal resolution of fMRI. Our results suggest a feasible strategy that may use fMRI to localize the neural correlates of mental and behavioral oscillations in the processing of repeatedly presented stimuli. These results also provide critical constraints for developing a neural model to understand brain mechanisms underlying behavioral oscillations.
Meeting abstract presented at VSS 2015
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