A neglected question regarding cognitive control is how control processes might detect situations calling for their involvement. The authors propose here that the demand for control may be evaluated in part by monitoring for conflicts in information processing. This hypothesis is supported by data concerning the anterior cingulate cortex, a brain area involved in cognitive control, which also appears to respond to the occurrence of conflict. The present article reports two computational modeling studies, serving to articulate the conflict monitoring hypothesis and examine its implications. The first study tests the sufficiency of the hypothesis to account for brain activation data, applying a measure of conflict to existing models of tasks shown to engage the anterior cingulate. The second study implements a feedback loop connecting conflict monitoring to cognitive control, using this to simulate a number of important behavioral phenomena.

A core component of cognitive control – the ability to regulate thoughts and actions in accordance with internally represented behavioral goals – might be its intrinsic variability. In this article, I describe the dual-mechanisms of control (DMC) framework, which postulates that this variability might arise from qualitative distinctions in temporal dynamics between proactive and reactive modes of control. Proactive control reflects the sustained and anticipatory maintenance of goal-relevant information within lateral prefrontal cortex (PFC) to enable optimal cognitive performance, whereas reactive control reflects transient, stimulus-driven goal reactivation that recruits lateral PFC (plus a wider brain network) based on interference demands or episodic associations. I summarize recent research that demonstrates how the DMC framework provides a coherent explanation of three sources of cognitive control variation – intra-individual, inter-individual, and between-groups – in terms of proactive vs. reactive control biases.

An unresolved question in neuroscience and psychology is how the brain monitors performance to regulate behavior. It has been proposed that the anterior cingulate cortex (ACC), on the medial surface of the frontal lobe, contributes to performance monitoring by detecting errors. In this study, event-related functional magnetic resonance imaging was used to examine ACC function. Results confirm that this region shows activity during erroneous responses. However, activity was also observed in the same region during correct responses under conditions of increased response competition. This suggests that the ACC detects conditions under which errors are likely to occur rather than errors themselves.

Extensive evidence suggests the human ability to adaptively implement a wide variety of tasks is preferentially due to the operation of a fronto-parietal brain network. We hypothesized that this network’s adaptability is made possible by ‘flexible hubs’ – brain regions that rapidly update their pattern of global functional connectivity according to task demands. We utilized recent advances in characterizing brain network organization and dynamics to identify mechanisms consistent with the flexible hub theory. We found that the fronto-parietal network’s brain-wide functional connectivity pattern shifted more than other networks’ across a variety of task states, and that these connectivity patterns could be used to identify the current task. Further, these patterns were consistent across practiced and novel tasks, suggesting reuse of flexible hub connectivity patterns facilitates adaptive (novel) task performance. Together, these findings support a central role for fronto-parietal flexible hubs in cognitive control and adaptive implementation of task demands generally.

Gamma band oscillations participate in the temporal binding needed to synchronize cortical networks, involved in early sensory and short term memory processes. In earlier studies, alterations of these neurophysiological parameters have been found in psychotic disorders. To date no study has explored the temporal dynamics and signal complexity of gamma band oscillations in first episode psychosis (FEP). To address this issue, gamma band analysis was performed in 15 FEP patients and 18 healthy controls who successfully performed an adapted 2-back working memory task. Multiple linear and logistic regression models were computed to explore the relationship between the cognitive status and gamma oscillation changes over time. Based on regression model results, phase diagrams were constructed and their complexity was estimated using fractal dimension, a mathematical tool that describes shapes as numeric values. When adjusted for gamma values at time lags-3 to-4 ms and-15 to-16 ms, FEP patients displayed significantly higher time-dependent changes than controls, independently of the nature of the task. The present results are consistent with a discoordination of the activity of cortical generators engaged by the stimulus apparition in FEP patients, leading to a global binding deficit. In addition, fractal analysis showing higher complexity of gamma signal, confirmed this deficit. Our results provide evidence for recruitment of supplementary cortical generators as compensating mechanisms and yield further understanding for the pathophysiology cognitive impairments in FEP.

People perceive and conceive of activity in terms of discrete events. Here we propose a theory according to which the perception of boundaries between events arises from ongoing perceptual processing and regulates attention and memory. Perceptual systems continuously make predictions about what will happen next. When transient errors in predictions arise, an event boundary is perceived. According to the theory, the perception of events depends on both sensory cues and knowledge structures that represent previously learned information about event parts and inferences about actors' goals and plans. Neurological and neurophysiological data suggest that representations of events may be implemented by structures in the lateral prefrontal cortex and that perceptual prediction error is calculated and evaluated by a processing pathway including the anterior cingulate cortex and subcortical neuromodulatory systems.

We used an individual-differences approach to test whether general fluid intelligence (gF) is mediated by brain regions that support attentional (executive) control, including subregions of the prefrontal cortex. Forty-eight participants first completed a standard measure of gF (Raven's Advanced Progressive Matrices). They then performed verbal and nonverbal versions of a challenging working-memory task (three-back) while their brain activity was measured using functional magnetic resonance imaging (fMRI). Trials within the three-back task varied greatly in the demand for attentional control because of differences in trial-to-trial interference. On high-interference trials specifically, participants with higher gF were more accurate and had greater event-related neural activity in several brain regions. Multiple regression analyses indicated that lateral prefrontal and parietal regions may mediate the relation between ability (gF) and performance (accuracy despite interference), providing constraints on the neural mechanisms that support gF.

The anterior cingulate cortex (ACC) and the related medial wall play a critical role in recruiting cognitive control. Although ACC exhibits selective error and conflict responses, it has been unclear how these develop and become context-specific. With use of a modified stop-signal task, we show from integrated computational neural modeling and neuroimaging studies that ACC learns to predict error likelihood in a given context, even for trials in which there is no error or response conflict. These results support a more general error-likelihood theory of ACC function based on reinforcement learning, of which conflict and error detection are special cases.