Human midcingulate cortex encodes distributed representations of task progress

Significance Midcingulate cortex (MCC) contributes to cognitive control and decision making but its specific role in this process is highly mysterious. Here we use functional magnetic resonance imaging to test the predictions of a neural network model of MCC function. Confirming the model predictions, we find that human MCC encodes distributed, dynamically evolving representations of goal-directed action sequences. These results suggest that standard approaches for analyzing MCC function overlook the major portion of information encoded by this brain area. Rather, they indicate that MCC encodes the distances between representations of task events in task space, revealing how the MCC sustains the execution of extended behaviors. The function of midcingulate cortex (MCC) remains elusive despite decades of investigation and debate. Complicating matters, individual MCC neurons respond to highly diverse task-related events, and MCC activation is reported in most human neuroimaging studies employing a wide variety of task manipulations. Here we investigate this issue by applying a model-based cognitive neuroscience approach involving neural network simulations, functional magnetic resonance imaging, and representational similarity analysis. We demonstrate that human MCC encodes distributed, dynamically evolving representations of extended, goal-directed action sequences. These representations are uniquely sensitive to the stage and identity of each sequence, indicating that MCC sustains contextual information necessary for discriminating between task states. These results suggest that standard univariate approaches for analyzing MCC function overlook the major portion of task-related information encoded by this brain area and point to promising new avenues for investigation.