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. 2012 Feb;16(2):106-13.
doi: 10.1016/j.tics.2011.12.010. Epub 2012 Jan 12.

The variable nature of cognitive control: a dual mechanisms framework

Todd S Braver  1
Affiliations

The variable nature of cognitive control: a dual mechanisms framework

Todd S Braver. Trends Cogn Sci. 2012 Feb.

Abstract

A core component of cognitive control - the ability to regulate thoughts and actions in accordance with internally represented behavioral goals - might be its intrinsic variability. In this article, I describe the dual mechanisms of control (DMC) framework, which postulates that this variability might arise from qualitative distinctions in temporal dynamics between proactive and reactive modes of control. Proactive control reflects the sustained and anticipatory maintenance of goal-relevant information within lateral prefrontal cortex (PFC) to enable optimal cognitive performance, whereas reactive control reflects transient stimulus-driven goal reactivation that recruits lateral PFC (plus a wider brain network) based on interference demands or episodic associations. I summarize recent research that demonstrates how the DMC framework provides a coherent explanation of three sources of cognitive control variation - intra-individual, inter-individual and between-groups - in terms of proactive versus reactive control biases.

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Figures

Figure 1
Figure 1
Conceptual distinction between reactive and proactive control, as illustrated in the classic Stroop color-naming task. Upper panel illustrates reactive control, which relies upon detection of interference (occurring in the last panel following presentation of an incongruent stimulus), to drive reactivation of task-goals and enable successful responding (albeit with slower responding). In this control mode, task goals are not actively maintained during inter-trial periods (first and third panels), and may not be triggered following presentation of congruent stimuli. Lower panel illustrates proactive control, which does involve sustained active maintenance of task goals during inter-trial intervals (first and third panels), and results in less conflict experienced during presentation of incongruent stimuli (last panel). It is important to note, that the representation of task goals is illustrated in this manner purely for ease of description. The DMC framework makes no claims about whether these involve verbal coding or are consciously accessible.
Figure 2
Figure 2
Shifts in temporal dynamics of lateral PFC activity reflecting associated with different sources of variation. A. Intra-individual (state-related) variation due to manipulation of interference expectancy during the recent probes working memory interference task. Low interference expectancy conditions were primarily associated with interference-effects at the time of the probe (blue region and blue solid bar), reflecting reactive control. However, in high expectancy conditions, probe-related activation was decreased (blue hatched bar), while in adjacent regions delay-related activation increased (orange region and bars), indicating an anticipatory and global (i.e., present on all trials) proactive control effect. Adapted from Burgess & Braver (2010). B. Inter-individual variation due to trait reward sensitivity during working memory. Task performance under reward motivation conditions was associated with an increase in sustained and early-trial early-trial transient activity (potentially reflecting across-trial maintenance of task goals and encoding/updating of working memory information), but a decrease in late-trial transient activity (potentially reflecting probe-related processing), consistent with a shift towards proactive control. The effects were observed much more prominently in highly reward sensitive individuals. Adapted from Jimura et al (2010). C. Between-groups variation and training effects observed in schizophrenia patients on the AX-CPT context processing task. Prior to cognitive training, schizophrenia patients showed reduced cue-related activity, but increased probe-related activity, indicating a differential reliance on reactive control. However, following extensive strategy training with the task, normalization of activation dynamics (and task performance) was observed. Adapted from Edwards et al (2010).
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