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Cerebral correlates of skin conductance responses in a cognitive task.

ABSTRACT: Changes in physiological arousal frequently accompany cognitive performance. Many studies sought to identify the neural correlates of heightened arousal as indexed by skin conductance responses (SCR). However, the observed regional activations may be confounded by task events. We addressed this issue by recording SCR in 25 adults performing a stop signal task (SST) during functional magnetic resonance imaging. We compared only go trials with high and low SCR in order to isolate the event-independent processes. Furthermore, we distinguished go trials that followed another go, a stop success, or a stop error trial to examine whether the neural activities are contingent on the local context in which changes in SCR occurred. The results showed that the supplementary motor area responded to increased SCR irrespective of the preceding trial. The dorsal anterior cingulate cortex increased activation to heightened arousal most significantly in response to stop errors. The medial prefrontal cortex increased activation to SCR following a stop error but decreased activation following a go or stop success trial. These new findings specify the regional activations that accompany changes in physiological arousal during the SST and support distinct processes for the changes that occur under different local contexts. In particular, the MPFC shows opposing responses by increasing activation to changes in arousal evoked by salient stimuli and decreasing activation to the control of arousal.

SUBMITTER: Zhang S

PROVIDER: S-EPMC3408848 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature

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Cerebral correlates of skin conductance responses in a cognitive task.

Zhang Sheng S Hu Sien S Chao Herta H HH Luo Xi X Farr Olivia M OM Li Chiang-shan R CS

NeuroImage 20120524 3

Changes in physiological arousal frequently accompany cognitive performance. Many studies sought to identify the neural correlates of heightened arousal as indexed by skin conductance responses (SCR). However, the observed regional activations may be confounded by task events. We addressed this issue by recording SCR in 25 adults performing a stop signal task (SST) during functional magnetic resonance imaging. We compared only go trials with high and low SCR in order to isolate the event-indepen ...[more]

PMID: 22634217

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Project description:Depressive symptoms are related to abnormalities in the autonomic nervous system (ANS), and physiological signals that can be used to measure and evaluate such abnormalities have previously been used as indicators for diagnosing mental disorder, such as major depressive disorder (MDD). In this study, we investigate the feasibility of developing an objective measure of depressive symptoms that is based on examining physiological abnormalities in individuals when they are experiencing mental stress. To perform this, we recruited 30 patients with MDD and 31 healthy controls. Then, skin conductance (SC) was measured during five 5-min experimental phases, comprising baseline, mental stress, recovery from the stress, relaxation, and recovery from the relaxation, respectively. For each phase, the mean amplitude of the skin conductance level (MSCL), standard deviations of the SCL (SDSCL), slope of the SCL (SSCL), mean amplitude of the non-specific skin conductance responses (MSCR), number of non-specific skin conductance responses (NSCR), and power spectral density (PSD) were evaluated from the SC signals, producing 30 parameters overall (six features for each phase). These features were used as input data for a support vector machine (SVM) algorithm designed to distinguish MDD patients from healthy controls based on their physiological responses. Statistical tests showed that the main effect of task was significant in all SC features, and the main effect of group was significant in MSCL, SDSCL, SSCL, and PSD. In addition, the proposed algorithm achieved 70% accuracy, 70% sensitivity, 71% specificity, 70% positive predictive value, 71% negative predictive value in classifying MDD patients and healthy controls. These results demonstrated that it is possible to extract meaningful features that reflect changes in ANS responses to various stimuli. Using these features, detection of MDD was feasible, suggesting that SC analysis has great potential for future diagnostics and prediction of depression based on objective interpretation of depressive states.

Project description:Psychosocial stressors induce autonomic nervous system (ANS) responses in multiple body systems that are linked to health risks. Much work has focused on the common effects of stress, but ANS responses in different body systems are dissociable and may result from distinct patterns of cortical-subcortical interactions. Here, we used machine learning to develop multivariate patterns of fMRI activity predictive of heart rate (HR) and skin conductance level (SCL) responses during social threat in humans (N = 18). Overall, brain patterns predicted both HR and SCL in cross-validated analyses successfully (rHR = 0.54, rSCL = 0.58, both p < 0.0001). These patterns partly reflected central stress mechanisms common to both responses because each pattern predicted the other signal to some degree (rHR?SCL = 0.21 and rSCL?HR = 0.22, both p < 0.01), but they were largely physiological response specific. Both patterns included positive predictive weights in dorsal anterior cingulate and cerebellum and negative weights in ventromedial PFC and local pattern similarity analyses within these regions suggested that they encode common central stress mechanisms. However, the predictive maps and searchlight analysis suggested that the patterns predictive of HR and SCL were substantially different across most of the brain, including significant differences in ventromedial PFC, insula, lateral PFC, pre-SMA, and dmPFC. Overall, the results indicate that specific patterns of cerebral activity track threat-induced autonomic responses in specific body systems. Physiological measures of threat are not interchangeable, but rather reflect specific interactions among brain systems. SIGNIFICANCE STATEMENT:We show that threat-induced increases in heart rate and skin conductance share some common representations in the brain, located mainly in the vmPFC, temporal and parahippocampal cortices, thalamus, and brainstem. However, despite these similarities, the brain patterns that predict these two autonomic responses are largely distinct. This evidence for largely output-measure-specific regulation of autonomic responses argues against a common system hypothesis and provides evidence that different autonomic measures reflect distinct, measurable patterns of cortical-subcortical interactions.

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Cerebral correlates of skin conductance responses in a cognitive task.

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Cerebral correlates of skin conductance responses in a cognitive task.

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