Elsevier

Biological Psychiatry

Volume 69, Issue 12, 15 June 2011, Pages e55-e68
Biological Psychiatry

Review
From Reactive to Proactive and Selective Control: Developing a Richer Model for Stopping Inappropriate Responses

https://doi.org/10.1016/j.biopsych.2010.07.024Get rights and content

A better understanding of the neural systems underlying impulse control is important for psychiatry. Although most impulses are motivational or emotional rather than motoric per se, it is research into the neural architecture of motor response control that has made the greatest strides. This article reviews recent developments in the cognitive neuroscience of stopping responses. Most research of this kind has focused on reactive control—that is, how subjects stop a response outright when instructed by a signal. It is argued that reactive paradigms are limited as models of control relevant to psychiatry. Instead, a set of paradigms is advocated that begins to model proactive inhibitory control—that is, how a subject prepares to stop an upcoming response tendency. Proactive inhibitory control is generated according to the goals of the subject rather than by an external signal, and it can be selectively targeted at a particular response tendency. This may have wider validity than reactive control as an experimental model for stopping inappropriate responses.

Section snippets

Behavioral Paradigms

Many experimental paradigms exist for studying how people—and, in some cases, experimental animals—control their response tendencies. These include stop signal, go/no-go, antisaccade, Eriksen flanker, Stroop, Simon, Wisconsin card sort, continuous performance, reversal learning, and many others. All require control over a prepotent response tendency. Here we consider the first three in brief detail.

The stop signal test requires people to stop an already initiated response (7). On each trial,

Reactive Stopping Is a Useful Endophenotype for Psychiatry

Clearly, much has been learned about the neural architecture of reactive stopping. The convergent findings from different methods and species have motivated the stop signal task and related paradigms as endophenotypes for psychiatric disorders, as reviewed by various authors (21, 23, 97, 98, 99). To take some examples, many studies in patients have shown case–control increases in SSRT, as well as functional activation or structural integrity differences within regions such as the rIFC and

Proactive Inhibitory Control—Preparing to Stop

Reactive stopping requires completely countermanding the initiated response. By contrast, hold-your-horses is a hypothesized mechanism through which subjects put a “brake” on response tendencies when conflict is detected. Another type of control is referred to here as “proactive inhibitory control.” This involves a preparatory step before the response tendency is triggered. This can occur trial-by-trial in response to control cues (109), at the level of blocks of trials (110), or in a strategic

Distinguishing Selective from Global Mechanisms for Stopping

We saw that the STN is involved in both stop signal and no-go paradigms. We also saw that the STN may lead to widespread pulses that could inhibit basal ganglia output generally. Behavioral studies and TMS studies with the stop signal paradigm are consistent with the idea that such global suppression has functional consequences in the motor system. Other evidence, reviewed earlier, points to a role for the STN in “hold your horses” and also in proactive inhibitory control. However, a widespread

Conclusions and Further Questions

Cognitive neuroscience has made progress with behavioral paradigms that require reactive stopping. Accumulating evidence from many research groups clearly points to the critical importance of right IFC, the dorsomedial frontal cortex (esp. preSMA), and the basal ganglia, with downstream effects on M1 (16, 21, 22, 23, 24). The identification of this network is leading to efforts that characterize its subcomponents. For example, what are the relative roles of different nodes in the network such

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