Adaptive goal-directed behavior involves monitoring of ongoing actions and performance outcomes, and subsequent adjustments of behavior and learning. We evaluate new findings in cognitive neuroscience concerning cortical interactions that subserve the recruitment and implementation of such cognitive control. A review of primate and human studies, along with a meta-analysis of the human functional neuroimaging literature, suggest that the detection of unfavorable outcomes, response errors, response conflict, and decision uncertainty elicits largely overlapping clusters of activation foci in an extensive part of the posterior medial frontal cortex (pMFC). A direct link is delineated between activity in this area and subsequent adjustments in performance. Emerging evidence points to functional interactions between the pMFC and the lateral prefrontal cortex (LPFC), so that monitoring-related pMFC activity serves as a signal that engages regulatory processes in the LPFC to implement performance adjustments.

Psychologists and neuroscientists have had a long-standing interest in the P3, a prominent component of the event-related brain potential. This review aims to integrate knowledge regarding the neural basis of the P3 and to elucidate its functional role in information processing. The authors review evidence suggesting that the P3 reflects phasic activity of the neuromodulatory locus coeruleus-norepinephrine (LC-NE) system. They discuss the P3 literature in the light of empirical findings and a recent theory regarding the information-processing function of the LC-NE phasic response. The theoretical framework emerging from this research synthesis suggests that the P3 reflects the response of the LC-NE system to the outcome of internal decision-making processes and the consequent effects of noradrenergic potentiation of information processing.

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An important dimension of cognitive control is the adaptive regulation of the balance between exploitation (pursuing known sources of reward) and exploration (seeking new ones) in response to changes in task utility. Recent studies have suggested that the locus coeruleus–norepinephrine system may play an important role in this function and that pupil diameter can be used to index locus coeruleus activity. On the basis of this, we reasoned that pupil diameter may correlate closely with control state and associated changes in behavior. Specifically, we predicted that increases in baseline pupil diameter would be associated with decreases in task utility and disengagement from the task (exploration), whereas reduced baseline diameter (but increases in task-evoked dilations) would be associated with task engagement (exploitation). Findings in three experiments were consistent with these predictions, suggesting that pupillometry may be useful as an index of both control state and, indirectly, locus coeruleus function.

The error negativity (Ne/ERN) and error positivity (Pe) are two components of the event-related brain potential (ERP) that are associated with action monitoring and error detection. To investigate the relation between error processing and conscious self-monitoring of behavior, the present experiment examined whether an Ne and Pe are observed after response errors of which participants are unaware. Ne and Pe measures, behavioral accuracy, and trial-to-trial subjective accuracy judgments were obtained from participants performing an antisaccade task, which elicits many unperceived, incorrect reflex-like saccades. Consistent with previous research, subjectively unperceived saccade errors were almost always immediately corrected, and were associated with faster correction times and smaller saccade sizes than perceived errors. Importantly, irrespective of whether the participant was aware of the error or not, erroneous saccades were followed by a sizable Ne. In contrast, the Pe was much more pronounced for perceived than for unperceived errors. Unperceived errors were characterized by the absence of posterror slowing. These and other results are consistent with the view that the Ne and Pe reflect the activity of two separate error monitoring processes, of which only the later process, reflected by the Pe, is associated with conscious error recognition and remedial action.

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The information processing capacity of the human mind is limited, as is evidenced by the so-called “attentional-blink” deficit: When two targets (T1 and T2) embedded in a rapid stream of events are presented in close temporal proximity, the second target is often not seen. This deficit is believed to result from competition between the two targets for limited attentional resources. Here we show, using performance in an attentional-blink task and scalp-recorded brain potentials, that meditation, or mental training, affects the distribution of limited brain resources. Three months of intensive mental training resulted in a smaller attentional blink and reduced brain-resource allocation to the first target, as reflected by a smaller T1-elicited P3b, a brain-potential index of resource allocation. Furthermore, those individuals that showed the largest decrease in brain-resource allocation to T1 generally showed the greatest reduction in attentional-blink size. These observations provide novel support for the view that the ability to accurately identify T2 depends upon the efficient deployment of resources to T1. The results also demonstrate that mental training can result in increased control over the distribution of limited brain resources. Our study supports the idea that plasticity in brain and mental function exists throughout life and illustrates the usefulness of systematic mental training in the study of the human mind.

In theory, a comparison of two experimental effects requires a statistical test on their difference. In practice, this comparison is often based on an incorrect procedure involving two separate tests in which researchers conclude that effects differ when one effect is significant (P < 0.05) but the other is not (P > 0.05). We reviewed 513 behavioral, systems and cognitive neuroscience articles in five top-ranking journals (Science, Nature, Nature Neuroscience, Neuron and The Journal of Neuroscience) and found that 78 used the correct procedure and 79 used the incorrect procedure. An additional analysis suggests that incorrect analyses of interactions are even more common in cellular and molecular neuroscience. We discuss scenarios in which the erroneous procedure is particularly beguiling."The percentage of neurons showing cue-related activity increased with training in the mutant mice (P < 0.05), but not in the control mice (P > 0.05)." "Animals receiving vehicle (control) infusions into the amygdala showed increased freezing to the conditioned stimulus compared with a control stimulus (P < 0.01); in animals receiving muscimol infusions into the amygdala, this difference was abolished (F < 1)."These two fictive, but representative, statements illustrate a statistical error that is common in the neuroscience literature. The researchers who made these statements wanted to claim that one effect (for example, the training effect on neuronal activity in mutant mice) was larger or smaller than the other effect (the training effect in control mice). To support this claim, they needed to report a statistically significant interaction (between amount of training and type of mice), but instead they reported that one effect was statistically significant, whereas the other effect was not. Although superficially compelling, the latter type of statistical reasoning is erroneous because the difference between significant and not significant need not itself be statistically significant 1 . Consider an extreme scenario in which traininginduced activity barely reaches significance in mutant mice (for example, P = 0.049) and barely fails to reach significance for control mice (for example, P = 0.051). Despite the fact that these two P values lie on opposite sides of 0.05, one cannot conclude that the training effect for mutant mice differs statistically from that for control mice.That is, as famously noted by Rosnow and Rosenthal 2 , "surely, God loves the 0.06 nearly as much as the 0.05". Thus, when making a comparison between two effects, researchers should report the statistical significance of their difference rather than the difference between their significance levels.Our impression was that this error of comparing significance levels is widespread in the neuroscience literature, but until now there were no aggregate data to support this impression. We therefore examined all of the behavioral, systems and cognitive neuroscience studies published in four prestigious journals (Nature, Science, Nature Neuroscience and Neuron) ...