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Neural correlates of non-specific skin conductance responses during resting state fMRI.

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.

SUBMITTER: Gertler J

PROVIDER: S-EPMC7263940 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:There exists growing interest in understanding the dynamics of resting state functional magnetic resonance imaging (rs-fMRI) to establish mechanistic links between individual patterns of spontaneous neural activation and corresponding behavioral measures in both normative and clinical populations. Here we propose and validate a novel approach in which whole-brain rs-fMRI data are mapped to a specific low-dimensional representation-affective valence and arousal processing-prior to dynamic analysis. This mapping process constrains the state space such that both independent validation and visualization of the system's dynamics become tractable. To test this approach, we constructed neural decoding models of affective valence and arousal processing from brain states induced by International Affective Picture Set image stimuli during task-related fMRI in (n = 97) healthy control subjects. We applied these models to decode moment-to-moment affect processing in out-of-sample subjects' rs-fMRI data and computed first and second temporal derivatives of the resultant valence and arousal time-series. Finally, we fit a second set of neural decoding models to these derivatives, which function as neurally constrained ordinary differential equations (ODE) underlying affect processing dynamics. To validate these decodings, we simulated affect processing by numerical integration of the true temporal sequence of neurally decoded derivatives for each subject and demonstrated that these decodings generate significantly less (p < 0.05) group-level simulation error than integration based upon decoded derivatives sampled uniformly randomly from the true temporal sequence. Indeed, simulations of valence and arousal processing were significant for up to four steps of closed-loop simulation (Δt = 2.0 s) for both valence and arousal, respectively. Moreover, neural encoding representations of the ODE decodings include significant clusters of activation within brain regions associated with affective reactivity and regulation. Our work has methodological implications for efforts to identify unique and actionable biomarkers of possible future or current psychopathology, particularly those related to mood and emotional instability.

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Neural correlates of non-specific skin conductance responses during resting state fMRI.

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