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|Title:||An EEG source localization and connectivity study on deception of autobiography memories|
|Citation:||Yue, W.,Chun, N.W.,Siong, N.K.,Wu, T.,Xiaoping, L. (2013). An EEG source localization and connectivity study on deception of autobiography memories. International IEEE/EMBS Conference on Neural Engineering, NER : 468-471. ScholarBank@NUS Repository. https://doi.org/10.1109/NER.2013.6695973|
|Abstract:||Three key cognitive components involved in deception, i.e., working memory, inhibition control and task switching share a most fundamental neuropsychological process, i.e., execution control. Although dissociable neuroanatomies associated with individual cognitive component for deception have been identified by fMRI, practical application of fMRI in lie detection remains constrained by its limited accessibility and low affordability, compared with which, EEG has greater advantages. However, fewer theoretical studies have been reported from EEG community and hence leads to the lack of EEG based knowledge on deception. This study therefore aims to propose new methods to extend the current EEG researches in deception by carrying out EEG source localization method combined with connectivity analysis on EEG data collected from fifteen subjects, who participated in a deception paradigm inducing both instructed lying (IL) and instructed truth-telling (IT) conditions. The results show that: (1) significant ERS in upper alpha band (10-12 Hz) in cuneus is observed for IL compared with IT condition, (2) event related connectivity strength between neural substrates responsible for execution control in executing selectively retrieving, monitoring and scrutinizing memory information is observed increased in upper alpha band for IL compared with IT condition, (3) regional and global clustering coefficient derived in connectivity analysis have shown strong correlation to the response time, and (4) relative higher upper alpha band power founded during self-reflection period may indicate sustained alertness. © 2013 IEEE.|
|Source Title:||International IEEE/EMBS Conference on Neural Engineering, NER|
|Appears in Collections:||Staff Publications|
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