Subject, session and task effects on power, connectivity and network centrality: A source-based EEG study
•We studied the variability due to subject, session and task on EEG features.•Our results show a remarkable ability to identify stable subject features within a given task.•Power and connectivity features may detect stable (over-time) individual properties. Inter-subjects’ variability in functional...
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| Published in | Biomedical signal processing and control Vol. 59; p. 101891 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
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01.05.2020
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| Abstract | •We studied the variability due to subject, session and task on EEG features.•Our results show a remarkable ability to identify stable subject features within a given task.•Power and connectivity features may detect stable (over-time) individual properties.
Inter-subjects’ variability in functional brain networks has been extensively investigated in the last few years. In this context, unveiling subject-specific characteristics of EEG features may play an important role for both clinical (e.g., biomarkers) and bio-engineering purposes (e.g., biometric systems and brain computer interfaces). Nevertheless, the effects induced by multi-sessions and task-switching are not completely understood and considered. In this work, we aimed to investigate how the variability due to subject, session and task affects EEG power, connectivity and network features estimated using source-reconstructed EEG time-series. Our results point out a remarkable ability to identify stable subject features within a given task together with striking independence from the session. The results also show a relevant effect of task-switching, which is comparable to individual variability. This study suggests that power and connectivity EEG features may be adequate to detect stable (over-time) individual properties within predefined and controlled tasks and that these findings are consistent over a range of connectivity metrics, different epoch lengths and parcellation schemes. |
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| AbstractList | •We studied the variability due to subject, session and task on EEG features.•Our results show a remarkable ability to identify stable subject features within a given task.•Power and connectivity features may detect stable (over-time) individual properties.
Inter-subjects’ variability in functional brain networks has been extensively investigated in the last few years. In this context, unveiling subject-specific characteristics of EEG features may play an important role for both clinical (e.g., biomarkers) and bio-engineering purposes (e.g., biometric systems and brain computer interfaces). Nevertheless, the effects induced by multi-sessions and task-switching are not completely understood and considered. In this work, we aimed to investigate how the variability due to subject, session and task affects EEG power, connectivity and network features estimated using source-reconstructed EEG time-series. Our results point out a remarkable ability to identify stable subject features within a given task together with striking independence from the session. The results also show a relevant effect of task-switching, which is comparable to individual variability. This study suggests that power and connectivity EEG features may be adequate to detect stable (over-time) individual properties within predefined and controlled tasks and that these findings are consistent over a range of connectivity metrics, different epoch lengths and parcellation schemes. |
| ArticleNumber | 101891 |
| Author | Demuru, Matteo Pani, Sara Maria Bazzano, Giovanni D’Aloja, Ernesto Ciuffi, Marta Fraschini, Matteo La Cava, Simone Maurizio |
| Author_xml | – sequence: 1 givenname: Sara Maria surname: Pani fullname: Pani, Sara Maria organization: Department of Biomedical Sciences, PhD Program in Neuroscience, University of Cagliari, I-09042, Italy – sequence: 2 givenname: Marta surname: Ciuffi fullname: Ciuffi, Marta organization: Department of Medical Sciences and Public Health, Forensic Science Unit, University of Cagliari, Cagliari, Italy – sequence: 3 givenname: Matteo surname: Demuru fullname: Demuru, Matteo organization: Department of Electrical and Electronic Engineering, University of Cagliari, Cagliari, I-09123, Italy – sequence: 4 givenname: Simone Maurizio surname: La Cava fullname: La Cava, Simone Maurizio organization: Department of Electrical and Electronic Engineering, University of Cagliari, Cagliari, I-09123, Italy – sequence: 5 givenname: Giovanni orcidid: 0000-0002-5341-9222 surname: Bazzano fullname: Bazzano, Giovanni organization: Department of Medical Sciences and Public Health, Forensic Science Unit, University of Cagliari, Cagliari, Italy – sequence: 6 givenname: Ernesto orcidid: 0000-0003-4456-6252 surname: D’Aloja fullname: D’Aloja, Ernesto organization: Department of Medical Sciences and Public Health, Forensic Science Unit, University of Cagliari, Cagliari, Italy – sequence: 7 givenname: Matteo orcidid: 0000-0003-2784-6527 surname: Fraschini fullname: Fraschini, Matteo email: fraschin@unica.it organization: Department of Electrical and Electronic Engineering, University of Cagliari, Cagliari, I-09123, Italy |
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