Although much evidence indicates that RT increases as a function of computational load in many cognitive tasks, quantification of changes in neural activity related to increasing demand of cognitive control has rarely been attempted. In this fMRI study, we used a majority function task to quantify the effect of computational load on brain activation, reflecting the mental processes instantiated by cognitive control under conditions of uncertainty. We found that the activation of the frontoparieto-cingulate system as well as the deactivation of the anticorrelated default mode network varied parametrically as a function of information uncertainty, estimated as entropy with an information theoretic model. The current findings suggest that activity changes in the dynamic networks of the brain (especially the frontoparieto-cingulate system) track with information uncertainty, rather than only conflict or other commonly proposed targets of cognitive control.

The ACC, the dorsolateral prefrontal cortex (DLPFC), and the parietal cortex near/along the intraparietal sulcus (IPS) are members of a network subserving attentional control. Our recent study revealed that these regions participate in both response anticipation and conflict processing. However, little is known about the relative contribution of these regions in attentional control and how the dynamic interactions among these regions are modulated by detection of predicted versus unpredicted targets and conflict processing. Here, we examined effective connectivity using dynamic causal modeling among these three regions during a flanker task with or without a target onset cue. We compared various models in which different connections among ACC, DLPFC, and IPS were modulated by bottom–up stimulus-driven surprise and top–down conflict processing using Bayesian model selection procedures. The most optimal of these models incorporated contextual modulation that allowed processing of unexpected (surprising) targets to mediate the influence of the IPS over ACC and DLPFC and conflict processing to mediate the influence of ACC and DLPFC over the IPS. This result suggests that the IPS plays an initiative role in this network in the processing of surprise targets, whereas ACC and DLPFC interact with each other to resolve conflict through attentional modulation implemented via the IPS.

Recent evidence in cognitive neuroscience has suggested that attention is a complex organ system subserved by at least three attentional networks in the brain, for alerting, orienting, and executive control functions. However, how these different networks work together to give rise to the seemingly unitary mental faculty of attention remains unclear. We describe a connectionist model of human attentional networks to explore the possible interplays among the networks from a computational perspective. This model is developed in the framework of leabra (local, error-driven, and associative, biologically realistic algorithm) and simultaneously involves these attentional networks connected in a biologically inspired way. We evaluate the model by simulating the empirical data collected on normal human subjects using the Attentional Network Test (ANT). The simulation results fit the experimental data well. In addition, we show that the same model, with a single parameter change that affects executive control, is able to simulate the empirical data collected from patients with schizophrenia. This model represents a plausible connectionist explanation for the functional structure and interaction of human attentional networks.

In recent years, three attentional networks have been defined in anatomical and functional terms. These functions involve alerting, orienting, and executive attention. Reaction time measures can be used to quantify the processing efficiency within each of these three networks. The Attention Network Test (ANT) is designed to evaluate alerting, orienting, and executive attention within a single 30-min testing session that can be easily performed by children, patients, and monkeys. A study with 40 normal adult subjects indicates that the ANT produces reliable single subject estimates of alerting, orienting, and executive function, and further suggests that the efficiencies of these three networks are uncorrelated. There are, however, some interactions in which alerting and orienting can modulate the degree of interference from flankers. This procedure may prove to be convenient and useful in evaluating attentional abnormalities associated with cases of brain injury, stroke, schizophrenia, and attention-deficit disorder. The ANT may also serve as an activation task for neuroimaging studies and as a phenotype for the study of the influence of genes on attentional networks.