Differences in brain information transmission between gifted and normal children during scientific hypothesis generation

Neural correlates of creative thinking and schizotypy

“…This may also be related with the concept of 'neural efficiency' (Haier et al, 1988), where lower cortical activation is observed in brighter individuals when engaged in a demanding cognitive task, compared to less intelligent individuals (Jin, Kwon, Jeong, Kwon, & Shin, 2006;Neubauer & Fink, 2009). Relating this back to the role of the left hemispheric inhibitory control, it could be that the disinhibition of such supervisory regulation could result in the release of more holistic functions and ideas mediated by the right prefrontal regions.…”

Linear and nonlinear information flow based on time-delayed mutual information method and its application to corticomuscular interaction

“…Previous studies have examined the function or information transmission between brain areas during object and emotional recognition tasks (Ioannides, 2001, Ioannides et al, 2000), odor stimulation in subjects classified by occupation (Min et al, 2003), and the scientific hypothesis generation process in gifted or normal children (Jin et al, 2006a, b). Hinrichs et al (2006, 2008) used directed information flow (DIF) as a model free approach of information flow to measure causal interactions in event related fMRI, EEG, and MEG experiments.…”

Differences in Neural Current Sources of Science Gifted and Normal Children in Creative Reasoning

“…In addition, as estimation of current source being induced from deep cerebral structures such as hippocampal and subgenual cingulate foci is enabled, a study on both cognitive and sensory area is enabled as well. Contrary to existing study of frequency analysis through potential being represented in scalp (Kwon et al, 2007;Jin et al, 2006a;2006b) …”

“…In order to solve this problem, a process of dividing independent sources in brain inside is required. Contrary to the fact that Principal Component Analysis (PCA) considers even secondary correlation, as independent component analysis considers even high-order correlation, separation into most independent sources is enabled (Jin et al, 2006a;Lee, 1998). At the time of EEG analysis, ICA is used for internal source localization or artifacts removal and in this study, it was used for artifacts removal of EOG, EMG or EKG.…”