S. Maitra, M. Chatterjee, A. Sasidharan, S. Sinha, K. Mukhopadhyay
{"title":"Working memory, impulsivity and emotional regulation correlates with frontal asymmetry of healthy young subjects during auditory session","authors":"S. Maitra, M. Chatterjee, A. Sasidharan, S. Sinha, K. Mukhopadhyay","doi":"10.14311/NNW.2020.30.024","DOIUrl":null,"url":null,"abstract":"Background : Specific frequency oscillations provide idea about functioning of underlying brain regions. Brain oscillations and event based assessment of cognitive functions like working memory (WM), impulsivity (Imp) and emotional regulation (ER) were reported to influence each other in different ethnic groups. But how these traits are regulated in healthy Indian adults was not explored widely. Aims: We analyzed link between scalp electrical activity and different neuropsychological traits in higher education aspirants. Method: All the traits were self-assessed using standard questionnaires. QEEG was performed during an audio-sensory session. Tracings collected through BESS software were analyzed using SPSS. Results: Less impulsive individuals exhibited higher frontal theta and beta activity. Higher frontal theta activity was associated with higher ER, whereas higher theta and alpha activity showed association with WM deficit. Individuals with higher Imp and happiness exhibited higher frontal hemispheric asymmetry for theta and alpha, while those with lower asymmetry for alpha and beta activity showed higher ER. Beta asymmetry was positively related with happiness. Conclusions: We infer that variability in behaviour of healthy adults is influenced by differential frontal brain impulses and could be considered for providing individualized assistance to emotionally vulnerable individuals.","PeriodicalId":49765,"journal":{"name":"Neural Network World","volume":"93 1","pages":"365-378"},"PeriodicalIF":0.7000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neural Network World","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.14311/NNW.2020.30.024","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Background : Specific frequency oscillations provide idea about functioning of underlying brain regions. Brain oscillations and event based assessment of cognitive functions like working memory (WM), impulsivity (Imp) and emotional regulation (ER) were reported to influence each other in different ethnic groups. But how these traits are regulated in healthy Indian adults was not explored widely. Aims: We analyzed link between scalp electrical activity and different neuropsychological traits in higher education aspirants. Method: All the traits were self-assessed using standard questionnaires. QEEG was performed during an audio-sensory session. Tracings collected through BESS software were analyzed using SPSS. Results: Less impulsive individuals exhibited higher frontal theta and beta activity. Higher frontal theta activity was associated with higher ER, whereas higher theta and alpha activity showed association with WM deficit. Individuals with higher Imp and happiness exhibited higher frontal hemispheric asymmetry for theta and alpha, while those with lower asymmetry for alpha and beta activity showed higher ER. Beta asymmetry was positively related with happiness. Conclusions: We infer that variability in behaviour of healthy adults is influenced by differential frontal brain impulses and could be considered for providing individualized assistance to emotionally vulnerable individuals.
期刊介绍:
Neural Network World is a bimonthly journal providing the latest developments in the field of informatics with attention mainly devoted to the problems of:
brain science,
theory and applications of neural networks (both artificial and natural),
fuzzy-neural systems,
methods and applications of evolutionary algorithms,
methods of parallel and mass-parallel computing,
problems of soft-computing,
methods of artificial intelligence.