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Abstract #2331

Decoding Subjectively Correct "Yes/No" Thoughts in the Human Brain

Zhi Yang1, 2, Javier Gonzalez-Castillo2, Zirui Huang1, Rui Dai1, Georg Northoff3, Peter A. Bandettini2

1Institute of Psychology, Chinese Academy of Sciences, Beijing, China; 2National Institute of Mental Health, Bethesda, MD, United States; 3University of Otawa, Otawa, ON, Canada

Multivariate pattern analyses were used to decode the subjectively correct "Yes/No" answers to binary questions. Using a spatiotemporal searchlight approach, a set of brain regions were identified in 10 subjects in a 3T scanner, showing group-level above-chance accuracy in decoding "Yes/No" answers regardless the subjects' intentions that were manipulated in the experimental paradigm. The results from 7T scans further verified that three of these regions can be used to robustly decode the Yes/No answers (regardless of intentions) with high accuracy, given sufficiently high TSNR, which can be achieved by means of ultra-high field scanners and trial-averaging. These findings suggest that subjectively correct answers can be accurately decoded with fMRI in the spatial-temporal patterns of prefrontal cortex, providing a basis for fMRI-based brain-computer interface.