Summary Many functional network properties of the human brain have been identified during rest and task states, yet it remains unclear how the two relate. We identified a whole-brain network architecture present across dozens of task states that was highly similar to the resting-state network architecture. The most frequent functional connectivity strengths across tasks closely matched the strengths observed at rest, suggesting this is an “intrinsic”, standard architecture of functional brain organization. Further, a set of small but consistent changes common across tasks suggests the existence of a task-general network architecture distinguishing task states from rest. These results indicate the brain’s functional network architecture during task performance is shaped primarily by an intrinsic network architecture that is also present during rest, and secondarily by evoked task-general and task-specific network changes. This establishes a strong relationship between resting-state functional connectivity and task-evoked functional connectivity – areas of neuroscientific inquiry typically considered separately.

OverviewVirtually all working memory (WM) theorists agree that control processes are a critical component of WM function. Some set of internal mechanisms must be responsible for: 1) selecting information for active maintenance in WM; 2) ensuring that it can be stored for an appropriate length of time; 3) protecting it against sources of interference; 4) updating it at appropriate junctures; and 5) utilizing it to influence other cognitive systems (i.e., perception, attention, memory and action). Yet, equally clear to most theorists is the observation that the ability to exert control over WM varies substantially, both within individuals (across time and task situations) and across individuals. In some sense, this observation poses perhaps the core paradox regarding cognitive control: Why is cognitive control so important, yet simultaneously so fragile and vulnerable to disruption? Why does it appear that our ability to exert control is so strong in some cases, but so weak in others? If exerting cognitive control seems to be the optimal response in many situations, why does it seem as if behavior is sub-optimally controlled much of the time in many individuals, and at least some of the time in all individuals?In this chapter, we put forth a theory of cognitive control in WM that attempts to explain this variability. Our central hypothesis is that cognitive control operates via two distinct operating modes -proactive control and reactive control. We will present arguments suggesting that these two modes are dissociable on a number of dimensions, such as computational properties, neural substrates, temporal dynamics, and consequences for information processing. We will suggest that although most formulations of cognitive control in WM only consider proactive control, reactive control 3 mechanisms may be more dominant. We will further suggest that by distinguishing between these two modes we will be able to: 1) resolve some of the apparent inconsistencies in the existing WM literature; 2) understand how and why the impact of cognitive control processes in WM can vary so strongly within individuals across time and task situations; 3) gain insight into the nature of cognitive control impairments found in healthy aging (and possibly in other populations suffering from neuropsychiatric disorders); 4) understand some of the critical underlying mechanisms related to individual differences in WM function; and 5) account for potentially surprising data indicating that putatively "non-cognitive" variables such as mood states and personality traits (e.g., extraversion, neuroticism) may also influence WM function.The general theoretical framework that we advance here for understanding the sources of variation that affect WM and cognitive control is termed the D u a l Mechanisms of Control, or DMC account. It is worth noting that, although we have been developing this framework for several years now, this chapter marks the first comprehensive treatment of the theory and its empirical support. As such, we combine discussion of b...

Research on cognitive control and executive function has long recognized the relevance of motivational factors. Recently, however, the topic has come increasingly to center stage, with a surge of new studies examining the interface of motivation and cognitive control. In the present article we survey research situated at this interface, considering work from cognitive and social psychology and behavioral economics, but with a particular focus on neuroscience research. We organize existing findings into three core areas, considering them in the light of currently vying theoretical perspectives. Based on the accumulated evidence, we advocate for a view of control function that treats it as a domain of reward-based decision making. More broadly, we argue that neuroscientific evidence plays a critical role in understanding the mechanisms by which motivation and cognitive control interact. Opportunities for further cross-fertilization between behavioral and neuroscientific research are highlighted.

Anterior cingulate cortex (ACC) may play a key role in cognitive control by monitoring for the occurrence of response conflict (i.e. simultaneous activation of incompatible response tendencies). Low-frequency responding might provide a minimal condition for eliciting such conflict, as a result of the need to overcome a prepotent response tendency. We predicted that ACC would be selectively engaged during low-frequency responding, irrespective of the specific task situation. To test this hypothesis, we examined ACC activity during the performance of simple choice-discrimination tasks, using rapid event-related functional magnetic resonance imaging. Subjects were scanned while performing three tasks thought to tap different cognitive processes: 'Go/No-go' (response inhibition), 'oddball' (target detection), and two-alternative forced- choice (response selection). Separate conditions manipulated the frequency of relevant task events. Consistent with our hypothesis, the same ACC region was equally responsive to low-frequency events across all three tasks, but did not show differential responding when events occurred with equal frequency. Subregions of the ACC were also identified that showed heightened activity during the response inhibition condition, and on trials in which errors were committed. Task-sensitive activity was also found in right prefrontal and parietal cortex (response inhibition), left superior temporal and tempoparietal cortex (target detection), and supplementary motor area (response selection). Taken together, the results are consistent with the hypothesis that the ACC serves as a generic detector of processing conflict arising when low-frequency responses must be executed, but also leave open the possibility that further functional specialization may occur within ACC subregions.

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