| Literature DB >> 32184189 |
Joshua Gertler1, Stephanie Novotny1, Andrew Poppe1, Yu Sun Chung2, James J Gross3, Godfrey Pearlson4, Michael C Stevens5.
Abstract
Skin conductance responses (SCRs) reliably occur in the absence of external stimulation. However, the neural correlates of these non-specific SCRs have been less explored than brain activity associated with stimulus-elicited SCRs. This study modeled spontaneous skin conductance responses observed during an unstructured resting state fMRI scan in 58 adolescents. A Finite Impulse Response (FIR) fMRI model was used to detect any type of hemodynamic response shape time-locked to non-specific SCRs; the shape of these responses was then carefully characterized. The strongest evidence for signal change was found in several sub-regions of sensorimotor cortex. There also was evidence for engagement of discrete areas within the lateral surfaces of the parietal lobe, cingulate cortex, fronto-insular operculum, and both visual and auditory primary processing areas. The hemodynamic profile measured by FIR modeling clearly resembled an event-related response. However, it was a complex response, best explained by two quickly successive, but opposing neuronal impulses across all brain regions - a brief positive response that begins several seconds prior to the SCR with a much longer negative neuronal impulse beginning shortly after the SCR onset. Post hoc exploratory analyses linked these two hemodynamic response phases to different emotion-related individual differences. In conclusion, this study shows the neural correlates of non-specific SCRs are a widespread, cortical network of brain regions engaged in a complex, seemingly biphasic fashion. This bimodal response profile should be considered in replication studies that attempt to directly link brain activity to possible homeostatic mechanisms or seek evidence for alternative mechanisms.Entities:
Keywords: Electrodermal; Resting state; Skin conductance; Spontaneous fluctuations; fMRI
Mesh:
Year: 2020 PMID: 32184189 PMCID: PMC7263940 DOI: 10.1016/j.neuroimage.2020.116721
Source DB: PubMed Journal: Neuroimage ISSN: 1053-8119 Impact factor: 6.556