The prefrontal cortex (PFC) plays a pivotal role in goal-directed cognition, yet its representational code remains an open problem with decoding techniques ineffective in disentangling task-relevant variables from PFC. Here we applied regularized linear discriminant analysis to human scalp EEG data and were able to distinguish a mental-rotation task versus a color-perception task with 87% decoding accuracy. Dorsal and ventral areas in lateral PFC provided the dominant features dissociating the two tasks. Our findings show that EEG can reliably decode two independent task states from PFC and emphasize the PFC dorsal/ventral functional specificity in processing the where rotation task versus the what color task.
Bibliographical noteFunding Information:
We are thankful to Dr. Sung Chan Jun, Dr. Marco Congedo, Dr. Donghyeon Kim, Dr. Kwangyeol Baek, Dr. Bumhee Park, Dr. Sung Young Park, Dr. David W. Gow, and Dr. Tom Sgouros for their valuable comments and support of this study. This work was supported by the Convergent Technology R&D Program for Human Augmentation (grant number 2020M3C1B8081319 to B.-K.M.), the Information Technology Research Center (ITRC) Support Program (grant number IITP-2020-2016-0-00464 to B.-K.M.), the Institute for Information & Communications Technology Promotion (IITP) Grant (Department of Artificial Intelligence, Korea University; grant number 2019-0-00079 to H.-I.S.), and the Basic Science Research Program (grant number 2019R1I1A1A01061545 to M.-H.A.), which are funded by the Korean government (MSICT) through the National Research Foundation of Korea; and the National Institute of Health (grant number R37NS21135 to R.T.K.). The authors declare no competing interests.
- brain-machine interface
- prefrontal cortex
ASJC Scopus subject areas
- Cognitive Neuroscience