Development and validation of an unsupervised scoring system (Autonomate) for skin conductance response analysis.

The skin conductance response (SCR) is increasingly being used as a measure of sympathetic activation concurrent with neuroscience measurements. We present a method of automated analysis of SCR data in the contexts of event-related cognitive tasks and nonspecific responding to complex stimuli. The primary goal of the method is to accurately measure the classical trough-to-peak amplitude of SCR in a fashion closely matching manual scoring. To validate the effectiveness of the method in event-related paradigms, three archived datasets were analyzed by two manual raters, the fully-automated method (Autonomate), and three alternative software packages. Further, the ability of the method to score non-specific responses to complex stimuli was validated against manual scoring. Results indicate high concordance between fully-automated and computer-assisted manual scoring methods. Given that manual scoring is error prone, subject to bias, and time consuming, the automated method may increase the efficiency and accuracy of SCR data analysis.

Duke Scholars

Author Kevin S. LaBar Psychology & Neuroscience