Overview = This project combines data, code, and documentation for Research Objective #1 of the National Science Foundation funded study (Award# BCS-173582) titled "Cognitive Control Theoretic Mechanisms of Real-time fMRI-guided Neuromodulation". Research Objective = We sought to characterize the computational model of performance monitoring encoded by the dorsal anterior cingulate cortex (dACC) during explicit affect regulation. Methods Summary = - We constructed high-accuracy affect (valence and arousal) decoding models (using SVMs) from fMRI data recorded during affect induction via IAPS image stimuli. - We independently validated affect induction using psychophysiological responses recorded concurrently with fMRI. - We then applied the models to decode affect processing during cued-recall tasks. During these tasks, IAPS stimuli are used to induce affect processing. After a prepatory period, subjects are signaled to re-imagine the cue image and try to re-experience the affect induced by the image (i.e., affect regulation). The key to this task is that we can decode a known "goal" affective state (i.e., the cue induction) as well as the affect control trajectory. By comparing the trajectory to the goal we could construct computation models of performance monitoring during explicit affect regulation. - We constructed models of error processing, predicted response outcome (PRO), expected value of control (EVC), and conflict. - We then combined these models (along with other important confounds such as age, sex, and affect processing) to predict dACC activation during affect regulation. Results = - dACC most likely encodes action-values (related to the Expected Value of Control). - dACC also likely encodes a conflict signal (concurrent with action-value) that indicates cognitive effort to overcome the prepotent response of "no control". - dACC encodes affective arousal during affect regulation.