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Abstract #3172

MVPA using the hyperaligned 7T-BOLD signals revealed that the initial decrease contains finer information to decode facial expressions

Toshiko Tanaka1, Naohiro Okamoto2, Ikuhiro Kida1,2, and Masahiko Haruno1,2
1National Institute of Information and Communications Technology, Suita Osaka, Japan, 2Osaka Universitiy, Suita Osaka, Japan


Previous studies suggested that the initial decrease in the BOLD signal reflects primary neuronal activity more than the later hemodynamic positive peak responses. We applied the hyper-alignment algorithm to 7T-BOLD timeseries during the facial expression discrimination task. and conducted the MVPA using the aligned data. We found decoding accuracies in the amygdala and superior temporal sulcus at 2 s after the face onset were significantly beyond baseline and the voxels contributing to the decoding accuracy displayed decreasing pattern in hemodynamics response, revealing that the initial decrease in 7T-BOLD signals contains finer information than thought previously.

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