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.

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.

The neural mechanism of number representation and processing is currently under extensive investigation. In this functional magnetic resonance imaging study, we designed a number comparison task to examine how people represent and compare two-digit numbers in the brain, and whether they process the decade and unit digits in parallel. We manipulated the decade-unit-digit congruency and numerical distance between the pairs of numbers. We observed both Stroop-like interference and the distance effect in the participants' performance. People responded more slowly to incongruent pairs of numbers and pairs of a smaller distance. The inferior parietal cortex showed common and distinct patterns of activation for both attentional selection and number comparison processes, and its activity was modulated by the Stroop-like interference effect and the distance effect. Taken together, these results support both parallel and holistic comparison of two-digit numbers in the brain.