Journal
PSYCHIATRY RESEARCH-NEUROIMAGING
Volume 323, Issue -, Pages -Publisher
ELSEVIER IRELAND LTD
DOI: 10.1016/j.pscychresns.2022.111488
Keywords
EEG source imaging; Source localization; gRSN; SOBI; P3
Categories
Funding
- University of Hong Kong [104004683]
- Professor Anthony Edward Sweeting Memorial Fund
Ask authors/readers for more resources
Neuroimaging research provides evidence for the existence of functional networks active during rest conditions. This study investigates the similarities between a globally-distributed resting-state network (gRSN) and the neural generators underlying the widely-studied P3 component. The findings suggest that the gRSN may serve as a resting-state network for detecting and responding to novelty.
Neuroimaging research provides converging evidence in support of functional networks active under rest conditions. While these networks are typically locally-distributed, a globally-distributed resting-state network (gRSN) was recently identified. The gRSN component is characterized by a scalp topography similar to that of the widely-studied P3 component of the event related potential, thought to represent the brain's response to novelty. In this study, we investigate similarities between the neural generators underlying these two networks to test the hypothesis that the gRSN is a resting-state network for novelty. By using the second-order blind identification (SOBI) algorithm, which works with temporal information, we show that (1) a resting-state component resembling the topography of the P3 can be recovered in all participants; (2) this gRSN component can be modeled with a set of ECDs with high goodness of fit; (3) ECD locations of the gRSN correspond to a network of globally-distributed brain structures overlapping heavily with the networking underlying the P3; and, (4) structures underlying these two networks are similarly involved during task and resting-state conditions. We interpret this as evidence in support of a resting-state network for detection and response to novelty.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available