Covert Intention to Answer to Self-Referential Questions Is Represented in Alpha-Band Local and Interregional Neural Synchronies

Choi, Jeong Woo; Su, Kwang; Kim, Kyung Hwan

doi:10.1155/2019/7084186

Cited by 1 publication

(5 citation statements)

References 50 publications

(84 reference statements)

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“…The higher alpha power is attributed to active inhibitory control to block incoming stimuli during WM retention, for efficient cortical information processing [38, 39, 42, 43]. Our results showed higher parietal alpha power for “no” compared to “yes,” which may imply higher cognitive load during retaining “no” in minds compared to “yes” [2]. The greater increase in alpha-band activity for “no” may reflect the increased WM load during the intention retention.…”

Section: Discussionmentioning

confidence: 82%

“…The useful features for the “yes/no” decoding in the alpha band were found to be concentrated in the parietal region at 800–1200 ms from the CSP algorithm. Recently, we showed that the alpha rhythms in the right parietal region are differentiated between the intentions to answers either “yes” or “no” in minds, presumably due to the difference in cognitive loads for the WM retention [2]. Several previous studies showed that the higher parietal alpha power reflects increased memory load [38, 39] or attentional demand [40, 41] during WM retention.…”

Section: Discussionmentioning

confidence: 99%

“…Figure 1(b) illustrates expected temporal sequence of cognitive processing following the CW onset until the “Please respond” cue appeared, which was based on our previous studies on cortical information processing of intention [1, 2], which showed that the brain activities differed between “yes” and “no” answers at both early (0∼600 ms) and late periods (600∼1300 ms) relative to the CW onset. We found that the early period was associated with semantic processing and automatic decision to answer [1] (denoted by a red box in Figure 1(b)), while the late period was involved in the retention of the answer in memory (denoted by a blue box in Figure 1(b)) until the “Respond cue” appeared (denoted by a yellow box in Figure 1(b)) [2]. Thus, the temporal period of interest for decoding the intentions to answer “yes” or “no” was the late period, corresponding to retain the intention in mind (600∼1300 ms).…”

Section: Methodsmentioning

confidence: 99%

“…As the first step toward this, here we tried to demonstrate that it is possible to decode the intentions to answer “yes” or “no” in response to self-referential questions from noninvasive electroencephalograms (EEGs) on single-trial basis. This was motivated by our recent studies which showed that the intentions to answer “yes” or “no” to self-referential questions is represented significantly differently in event-related EEGs, particularly in alpha-band activities [1, 2].…”

Section: Introductionmentioning

confidence: 99%

“…For the intention decoding, the discriminative characteristics of EEGs that we found in our previous study were utilized to find the time-frequency features for “yes/no” decoding. The decoding algorithm was developed based on the same data used in our previous study [2].…”

Section: Introductionmentioning

confidence: 99%

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Covert Intention to Answer “Yes” or “No” Can Be Decoded from Single-Trial Electroencephalograms (EEGs)

Choi

Kim

2019

Computational Intelligence and Neuroscience

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Interpersonal communication is based on questions and answers, and the most useful and simplest case is the binary “yes or no” question and answer. The purpose of this study is to show that it is possible to decode intentions on “yes” or “no” answers from multichannel single-trial electroencephalograms, which were recorded while covertly answering to self-referential questions with either “yes” or “no.” The intention decoding algorithm consists of a common spatial pattern and support vector machine, which are employed for the feature extraction and pattern classification, respectively, after dividing the overall time-frequency range into subwindows of 200 ms × 2 Hz. The decoding accuracy using the information within each subwindow was investigated to find useful temporal and spectral ranges and found to be the highest for 800–1200 ms in the alpha band or 200–400 ms in the theta band. When the features from multiple subwindows were utilized together, the accuracy was significantly increased up to ∼86%. The most useful features for the “yes/no” discrimination was found to be focused in the right frontal region in the theta band and right centroparietal region in the alpha band, which may reflect the violation of autobiographic facts and higher cognitive load for “no” compared to “yes.” Our task requires the subjects to answer self-referential questions just as in interpersonal conversation without any self-regulation of the brain signals or high cognitive efforts, and the “yes” and “no” answers are decoded directly from the brain activities. This implies that the “mind reading” in a true sense is feasible. Beyond its contribution in fundamental understanding of the neural mechanism of human intention, the decoding of “yes” or “no” from brain activities may eventually lead to a natural brain-computer interface.

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