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When asked to perform the same task, different individuals exhibit markedly different patterns of brain activity. This variability is often attributed to volatile factors, such as task strategy or compliance. We propose that individual differences in brain responses are, to a large degree, inherent to the brain and can be predicted from task-independent measurements collected at rest. Using a large set of task conditions, spanning several behavioral domains, we train a simple model that relates task-independent measurements to task activity and evaluate the model by predicting task activation maps for unseen subjects using magnetic resonance imaging. Our model can accurately predict individual differences in brain activity and highlights a coupling between brain connectivity and function that can be captured at the level of individual subjects.

It has been suggested that variation in brain structure correlates with the sizes of individuals' social networks. Whether variation in social network size causes variation in brain structure, however, is unknown. To address this question, we neuroimaged 23 monkeys that had been living in social groups set to different sizes. Subject comparison revealed that living in larger groups caused increases in gray matter in mid-superior temporal sulcus and rostral prefrontal cortex and increased coupling of activity in frontal and temporal cortex. Social network size, therefore, contributes to changes both in brain structure and function. The changes have potential implications for an animal's success in a social context; gray matter differences in similar areas were also correlated with each animal's dominance within its social network.

In our event-related functional magnetic resonance imaging (fMRI) experiment, participants learned to select between two response options by trial-and-error, using feedback stimuli that indicated monetary gains and losses. The results of the experiment indicate that error responses and error feedback activate the same region of dorsal anterior cingulate cortex, suggesting that this region is sensitive to both internal and external sources of error information.

We used measures of the human event-related brain potential (ERP) to investigate the neural mechanisms underlying error processing during action observation. Participants took part in two conditions, a task execution condition and a task observation condition. We found that activity in both the medial frontal cortex and the motor cortices, as measured via the error-related negativity and the lateralized readiness potential, respectively, was modulated by the correctness of observed behavior. These data suggest that similar neural mechanisms are involved in monitoring one's own actions and the actions of others.

Previous research has identified the anterior cingulate cortex (ACC) as an important node in the neural network underlying decision making in primates. Decision making can, however, be studied under a large variety of circumstances, ranging from the standard well-controlled lab situation to more natural, stochastic settings, in which multiple agents interact. Here, we illustrate how these different varieties of decision making studied can influence theories ofACC function in monkeys. Converging evidence from unit recordings and lesion studies now suggest that the ACC is important for interpreting outcome information according to the current task context to guide future action selection. We then apply this framework to the study of human ACC function and discuss its potential implications.

Doubts have been cast on the strict dissociation between short- and long-term memory systems. Specifically, several neuroimaging studies have shown that the medial temporal lobe, a region almost invariably associated with long-term memory, is involved in active short-term memory maintenance. Furthermore, a recent study in hippocampally lesioned patients has shown that the hippocampus is critically involved in associating objects and their locations, even when the delay period lasts only 8 s. However, the critical feature that causes the medial temporal lobe, and in particular the hippocampus, to participate in active maintenance is still unknown. This study was designed in order to explore hippocampal involvement in active maintenance of spatial and non-spatial associations. Eighteen participants performed a delayed-match-to-sample task in which they had to maintain either object–location associations, color–number association, single colors, or single locations. Whole-brain activity was measured using event-related functional magnetic resonance imaging and analyzed using a random effects model. Right lateralized hippocampal activity was evident when participants had to maintain object–location associations, but not when they had to maintain object–color associations or single items. The present results suggest a hippocampal involvement in active maintenance when feature combinations that include spatial information have to be maintained online.

Functional neuroimaging research in humans has identified a number of brain areas that are activated by the delivery of primary and secondary reinforcers. The present study investigated how activity in these reward-sensitive regions is modulated by the context in which rewards and punishments are experienced. Fourteen healthy volunteers were scanned during the performance of a simple monetary gambling task that involved a “win” condition (in which the possible outcomes were a large monetary gain, a small gain, or no gain of money) and a “lose” condition (in which the possible outcomes were a large monetary loss, a small loss, or no loss of money). We observed reward-sensitive activity in a number of brain areas previously implicated in reward processing, including the striatum, prefrontal cortex, posterior cingulate, and inferior parietal lobule. Critically, activity in these reward-sensitive areas was highly sensitive to the range of possible outcomes from which an outcome was selected. In particular, these regions were activated to a comparable degree by the best outcomes in each condition–a large gain in the win condition and no loss of money in the lose condition–despite the large difference in the objective value of these outcomes. In addition, some reward-sensitive brain areas showed a binary instead of graded sensitivity to the magnitude of the outcomes from each distribution. These results provide important evidence regarding the way in which the brain scales the motivational value of events by the context in which these events occur.

Adaptive behavior requires an organism to evaluate the outcome of its actions, such that future behavior can be adjusted accordingly and the appropriate response selected. During associative learning, the time at which such evaluative information is available changes as learning progresses, from the delivery of performance feedback early in learning to the execution of the response itself during learned performance. Here, we report a learning-dependent shift in the timing of activation in the rostral cingulate zone of the anterior cingulate cortex from external error feedback to internal error detection. This pattern of activity is seen only in the anterior cingulate, not in the pre-supplementary motor area. The dynamics of these reciprocal changes are consistent with the claim that the rostral cingulate zone is involved in response selection on the basis of the expected outcome of an action. Specifically, these data illustrate how the anterior cingulate receives evaluative information, indicating that an action has not produced the desired result.

Anterior cingulate cortex (ACC) carries a wealth of value-related information necessary for regulating behavioral flexibility and persistence. It signals error and reward events informing decisions about switching or staying with current behavior. During decisions it encodes the average value of exploring alternative choices (search value), even after controlling for response selection difficulty, and, during learning, the degree to which internal models of the environment and current task must be updated. ACC value signals are in part derived from the history of recent reward simultaneously integrated over multiple time scales thereby enabling comparison of experience over the recent and more extended past. Such ACC signals may instigate attentionally demanding and difficult processes such as behavioral change via interactions with prefrontal cortex. However, the signal in ACC instigating behavioral change need not itself be a conflict/difficulty signal.