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Sahoo A, Tayade P, Muthukrishnan SP, Kaur S, Sharma R, Nayyar M. Effect of short-term exposure to Raag Bilawal of North Indian classical music on young Indian adults: a high-density electroencephalogram microstate study. Pan Afr Med J 2024; 48:24. [PMID: 39220561 PMCID: PMC11364891 DOI: 10.11604/pamj.2024.48.24.40977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 05/09/2024] [Indexed: 09/04/2024] Open
Abstract
Introduction the objective of the study was to find out the microstate map topographies and their parameters generated during the resting state and during listening to North Indian classical Music Raag 'the Raag Bilawal'. It was hypothesized that in the resting state and during listening to music conditions, there would be a difference in microstate parameters i.e. mean duration, global explained variance (GEV), and time coverage. Methods a 128-channel electroencephalogram (EEG) was recorded for 12 Indian subjects (average age 26.1+1.4 years) while resting and listening to music using the EEG microstate investigation. Investigation and comparison of the microstate parameters were the mean duration, global explained variance (GEV), and time coverage between both conditions were performed. Results seven microstate maps were found to represent the resting state and listening to music condition, four canonical and three novel maps. No statistically significant difference was found between the two conditions for time coverage and mean duration. The statistical significance levels of the map-1, map-2, map-3, map-4, map-5, map-6, and map-7 for the mean duration were 0.4, 0.6, 0.97, 0.34, 0.32, 0.69, and 0.29 respectively; and for time coverage were 0.92, 0.92, 0.96, 0.64, 0.78, 0.38, and 0.76 respectively. Map-1, map-4, and map-7 were the three novel maps we found in our study. Conclusion similarities regarding stability and predominance of maps with small vulnerability exist in both conditions indicating that phonological, visual, and dorsal attention networks may be activated in both resting state and listening to music condition.
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Affiliation(s)
- Abhisek Sahoo
- Department of Physiology, All India Institute of Medical Sciences, New Delhi, India
| | - Prashant Tayade
- Department of Physiology, All India Institute of Medical Sciences, New Delhi, India
| | | | - Simran Kaur
- Department of Physiology, All India Institute of Medical Sciences, New Delhi, India
| | - Ratna Sharma
- Department of Physiology, All India Institute of Medical Sciences, New Delhi, India
| | - Madhavi Nayyar
- Department of Physiology, All India Institute of Medical Sciences, New Delhi, India
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S A A, C S, P D, G A, Maniyan Lathikakumari A, V Thomas S, N Menon R. Analysis of EEG microstates as biomarkers in neuropsychological processes - Review. Comput Biol Med 2024; 173:108266. [PMID: 38531248 DOI: 10.1016/j.compbiomed.2024.108266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 02/08/2024] [Accepted: 03/06/2024] [Indexed: 03/28/2024]
Abstract
Microstate analysis is a spatiotemporal method where instantaneous scalp potential topography represents the current state of the brain. The temporal evolution of these scalp topographies gives an understanding of quasi-stable periods of long-range coherence between distant electrodes, reflecting functional coordination within large-scale cortical networks. It has been proven potential in identification and characterization of neurophysiological indicators associated with neuropsychiatric conditions. Changes in microstates connected to symptoms and cognitive impairments of neuropsychiatric conditions. It is useful in the study of cognitive processes and disorders related to memory. Researchers may probe into the relationships between microstates and other cognitive processes, such as memory retrieval and encoding. This is a tool for clinicians to enhance the precision of diagnosis and inform possibilities for treatment by acquiring information regarding individual diversity in microstates could lead to tailored medical methods. Customizing treatment according to a patient's microstate patterns could improve the efficacy of treatment. The papers selected for the review span a broad-spectrum including memory related disorders, psychiatry and neurological disorders. A section in the review article has been dedicated to source localization of EEG microstates. The selection of review papers shed light on the importance and huge potential of application of EEG microstate analysis in various neuropsychological processes. The review concludes with the need for standardization of microstate analysis. It suggests the incorporation of widely accepted machine learning techniques for increasing the accuracy, reliability and acceptability of microstate analysis as reliable biomarkers for neurological conditions in the future.
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Affiliation(s)
- Asha S A
- Health Technology Group, Centre for Development of Advanced Computing (CDAC), Thiruvananthapuram, Kerala, India.
| | - Sudalaimani C
- Health Technology Group, Centre for Development of Advanced Computing (CDAC), Thiruvananthapuram, Kerala, India.
| | - Devanand P
- Health Technology Group, Centre for Development of Advanced Computing (CDAC), Thiruvananthapuram, Kerala, India.
| | - Alexander G
- Health Technology Group, Centre for Development of Advanced Computing (CDAC), Thiruvananthapuram, Kerala, India.
| | - Arya Maniyan Lathikakumari
- R Madhavan Nayar Centre for Comprehensive Epilepsy Care, Sree Chitra Tirunal Institute of Medical Sciences & Technology (SCTIMST), Thiruvananthapuram, Kerala, India.
| | - Sanjeev V Thomas
- R Madhavan Nayar Centre for Comprehensive Epilepsy Care, Sree Chitra Tirunal Institute of Medical Sciences & Technology (SCTIMST), Thiruvananthapuram, Kerala, India.
| | - Ramshekhar N Menon
- R Madhavan Nayar Centre for Comprehensive Epilepsy Care, Sree Chitra Tirunal Institute of Medical Sciences & Technology (SCTIMST), Thiruvananthapuram, Kerala, India.
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Zhao Z, Ran X, Lv S, Wang J, Qiu M, Wang C, Xu Y, Guo X, Gao Z, Mu J, Yu Y. Causal link between prefrontal cortex and EEG microstates: evidence from patients with prefrontal lesion. Front Neurosci 2023; 17:1306120. [PMID: 38161794 PMCID: PMC10757643 DOI: 10.3389/fnins.2023.1306120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 11/24/2023] [Indexed: 01/03/2024] Open
Abstract
Introduction At present, elucidating the cortical origin of EEG microstates is a research hotspot in the field of EEG. Previous studies have suggested that the prefrontal cortex is closely related to EEG microstate C and D, but whether there is a causal link between the prefrontal cortex and microstate C or D remains unclear. Methods In this study, pretrial EEG data were collected from ten patients with prefrontal lesions (mainly located in inferior and middle frontal gyrus) and fourteen matched healthy controls, and EEG microstate analysis was applied. Results Our results showed that four classical EEG microstate topographies were obtained in both groups, but microstate C topography in patient group was obviously abnormal. Compared to healthy controls, the average coverage and occurrence of microstate C significantly reduced. In addition, the transition probability from microstate A to C and from microstate B to C in patient group was significantly lower than those of healthy controls. Discussion The above results demonstrated that the damage of prefrontal cortex especially inferior and middle frontal gyrus could lead to abnormalities in the spatial distribution and temporal dynamics of microstate C not D, showing that there is a causal link between the inferior and middle frontal gyrus and the microstate C. The significance of our findings lies in providing new evidence for elucidating the cortical origin of microstate C.
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Affiliation(s)
- Zongya Zhao
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
- Henan Engineering Research Center of Medical VR Intelligent Sensing Feedback, Xinxiang, China
- The First Affiliated Hospital of Xinxiang Medical University, Weihui, China
| | - Xiangying Ran
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
- Henan Engineering Research Center of Medical VR Intelligent Sensing Feedback, Xinxiang, China
| | - Shiyang Lv
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
- Henan Engineering Research Center of Medical VR Intelligent Sensing Feedback, Xinxiang, China
| | - Junming Wang
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
- Henan Engineering Research Center of Medical VR Intelligent Sensing Feedback, Xinxiang, China
| | - Mengyue Qiu
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
- Henan Engineering Research Center of Medical VR Intelligent Sensing Feedback, Xinxiang, China
| | - Chang Wang
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
- Henan Engineering Research Center of Medical VR Intelligent Sensing Feedback, Xinxiang, China
| | - Yongtao Xu
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
- Henan Engineering Research Center of Medical VR Intelligent Sensing Feedback, Xinxiang, China
| | - Xiao Guo
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
- Henan Engineering Research Center of Medical VR Intelligent Sensing Feedback, Xinxiang, China
| | - Zhixian Gao
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
- Henan Engineering Research Center of Medical VR Intelligent Sensing Feedback, Xinxiang, China
| | - Junlin Mu
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Yi Yu
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design, Xinxiang, China
- Henan Engineering Research Center of Medical VR Intelligent Sensing Feedback, Xinxiang, China
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