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The integration of negative affect, pain and cognitive control in the cingulate cortex

Nature Reviews Neuroscience volume 12, pages 154–167 (2011)Cite this article

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Key Points

  • The rostral cingulate cortex occupies a central position in models of emotion, pain and cognitive control. Work in these domains has strongly influenced recent models of social behaviour and psychopathology.

  • The segregationist view: it has been argued that the rostral cingulate cortex is functionally segregated into affective and cognitive divisions. Although this view remains influential, new data suggest that it is no longer tenable.

  • Robust links have been forged between the anterior subdivision of the midcingulate cortex (aMCC) and negative affect (as with the anticipation and delivery of pain), leading some to speculate that aMCC implements a 'domain-general' process that is integral to negative affect, pain and cognitive control.

  • Physiological evidence: a meta-analysis of activation foci from functional imaging studies of negative affect, pain and cognitive control revealed that aMCC is consistently activated by all three domains, refuting claims that cognition and emotion are strictly segregated in the cingulate.

  • Anatomical evidence: aMCC is characterized by substantial connections with subcortical regions involved in negative affect and pain (the spinothalamic system, periaqueductal grey, amygdala, nucleus accumbens and substantia nigra). Unlike other cortical 'hot spots' for emotion, aMCC harbours the rostral cingulate zone (RCZ) — a premotor area that is heavily interconnected with other motor centres (including the facial nucleus).

  • Functional evidence: measures of negative affect, pain and cognitive control exhibit convergent functional properties. These measures covary with one another and are amplified in similar ways by uncertainty about responses and outcomes.

  • The adaptive control hypothesis: the core function common to negative affect, pain and cognitive control is the need to determine an optimal course of action in the face of uncertainty — that is, to exert 'adaptive control'. We suggest that aMCC implements adaptive control by using information about punishment to bias responding in situations where the optimal course of action is uncertain or entails response competition.

  • Further evidence: pain-responsive MCC neurons are activated by the anticipation of pain, activated during instrumental escape from pain and are sensitive to manipulations of certainty and conflict. Lesions of aMCC alter how threat modulates instrumental behaviour. aMCC activity during aversively motivated learning is predicted by computational models of control and reinforcement learning.

  • These data encourage a broader perspective on the functional significance of cingulate activity, one that recognizes that aMCC did not evolve to optimize performance on laboratory measures of 'cold' cognition. The data that we have surveyed are consistent with the possibility that the contribution of aMCC to measures of cognitive control stems from its older role in regulating 'hot' behaviours.

  • The adaptive control hypothesis provides a clear roadmap to the most profitable avenues for understanding the contribution of aMCC to negative affect and pain.

Abstract

It has been argued that emotion, pain and cognitive control are functionally segregated in distinct subdivisions of the cingulate cortex. However, recent observations encourage a fundamentally different view. Imaging studies demonstrate that negative affect, pain and cognitive control activate an overlapping region of the dorsal cingulate — the anterior midcingulate cortex (aMCC). Anatomical studies reveal that the aMCC constitutes a hub where information about reinforcers can be linked to motor centres responsible for expressing affect and executing goal-directed behaviour. Computational modelling and other kinds of evidence suggest that this intimacy reflects control processes that are common to all three domains. These observations compel a reconsideration of the dorsal cingulate's contribution to negative affect and pain.

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Figure 1: Divisions of the human rostral cingulate cortex.
Figure 2: Negative affect, pain and cognitive control activate a common region within the aMCC.
Figure 3: Cingulate premotor areas in the human MCC.
Figure 4: Subcortical connnectivity of the macaque analogue to the human RCZ.

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Acknowledgements

We thank the Laboratory for Affective Neuroscience and Waisman Laboratory for Brain Imaging and Behavior staff A. Dinndorf, M. Fox, L. Friedman, L. Hinsenkamp, A. Koppenhaver, A. Laird, B. Nacewicz, D. Rebedew and J.E. Shackman for assistance; M.X. Cohen, W. Irwin, S. Nieuwenhuis, J. Oler, and T. Yarkoni for feedback; and G. Bush for providing details of the meta-analysis described in reference 14. This work was supported by the European Commission (Marie Curie Reintegration Grant to H.A.S.), the University of Toronto Centre for the Study of Pain (Clinician-Scientist award to T.V.S.), Fetzer Foundation (R.J.D.), and National Institute of Mental Health (P50-MH069315, P50-MH084051 and R01-MH43454 (R.J.D.); A.J.S. was partially supported by R01-MH064498 (B.R. Postle); A.S.F. was supported by T32-MH018931 (R.J.D.)).

Author information

Author notes

  1. Alexander J. Shackman and Tim V. Salomons: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Psychology, University of Wisconsin, Madison, 53706, Wisconsin (WI), USA

    Alexander J. Shackman, Andrew S. Fox & Richard J. Davidson

  2. Department of Psychiatry, University of Wisconsin, Madison, 53719, WI, USA

    Alexander J. Shackman & Richard J. Davidson

  3. Division of Brain, Imaging & Behaviour—Systems Neuroscience, Toronto Western Research Institute, Ontario, M5G 2M9, Canada

    Tim V. Salomons

  4. Department of Psychology, Brain and Cognition Unit, Universiteit van Amsterdam, 1018 WB, the Netherlands

    Heleen A. Slagter

  5. Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin, Madison, 53705, WI, USA

    Andrew S. Fox & Richard J. Davidson

  6. Medical School, University of Minnesota, 55455, Minnesota, USA

    Jameel J. Winter

  7. Health Emotions Research Institute, University of Wisconsin, Madison, 53 719, WI, USA

    Richard J. Davidson

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  1. Alexander J. Shackman
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  4. Andrew S. Fox
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Corresponding authors

Correspondence to Alexander J. Shackman, Tim V. Salomons or Richard J. Davidson.

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Supplementary information

Supplementary information S1 (box)

Method: Coordinate-Based Meta-Analysis (CBMA) of Functional Imaging Studies (PDF 2298 kb)

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SUPPLEMENTARY INFORMATION

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Glossary

Cognitive control

A range of elementary processes (such as attention, inhibition and learning) that are engaged when automatic or habitual responses are insufficient to sustain goal-directed behaviour. Control can be engaged proactively or reactively.

Computational model

A mathematically detailed simulation of a psychological construct that can afford quantitative predictions of trial-by-trial fluctuations in behaviour and neurophysiology.

Reinforcement learning models

(Often abbreviated to RL models.) A class of computational models describing how organisms learn to maximize reinforcement based on experience. RL models assume that organisms update reinforcer expectations on the basis of prediction errors and the current learning rate.

Stroop task

A task in which subjects rapidly respond to a colour word, such as 'blue', on the basis of the colour in which the letters are displayed. The task is easy when the colour and word are compatible ('blue' depicted in blue), but is more difficult when the two are incompatible ('blue' depicted in red).

Go/No-Go task

A task in which subjects must rapidly respond to one kind of cue ('Go') while withholding responses to another ('No-Go').

Eriksen Flanker task

A task in which subjects rapidly respond to a centrally presented visual cue, such as an arrowhead, that is neighboured (flanked) by cues that can potentially code an alternative response.

Instrumental behaviour

Behaviour that is goal-directed insofar as it increases the likelihood of obtaining rewards or avoiding punishments. Instrumental behaviour is distinguished from behaviours that are reflexively elicited independent of reinforcement, as in Pavlovian (classical) conditioning.

Reinforcer

A stimulus that is capable (intrinsically or through learning) of eliciting instrumental behaviour; reward and punishment.

Attentional set

A template, rule or goal held in memory to guide attention (for example, search for angry faces in a crowded visual scene).

Architectonic area

A region of the brain defined by its cellular and molecular neuroanatomy, including neuronal structure (cytoarchitecture), myelin structure (myeloarchitecture) and neurochemistry (chemoarchitecture).

Electrodermal activity

(Often abbreviated to EDA.) Changes in the electrical resistance of the dermis stemming from activity of the sweat glands. EDA reflects activation in the sympathetic nervous system and is used to index arousal, stress and cognitive load.

Event-related potential

(Often abbreviated to ERP.) A scalp-recorded measure of the average brain electrical activity evoked by a particular stimulus or response.

Fear-potentiated startle reflex

A reflex evoked by the sudden onset of high-intensity stimuli (for example, a loud noise) and amplified by negative affect. In humans, this is measured using electrodes overlying orbicularis oculi, the muscle responsible for eye blinks.

Response conflict

Competition elicited by stimuli associated with multiple, incompatible response tendencies — as in the Stroop task.

Prediction error

In reinforcement learning models, an explicit description of the discrepancy between reinforcer expectations and actual reinforcement.

Electromyography

(Often abbreviated to EMG.) Recordings of electrical activity generated by the skeletal musculature.

Neurofeedback

A kind of learning in which real-time neural activity is employed as feedback.

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Shackman, A., Salomons, T., Slagter, H. et al. The integration of negative affect, pain and cognitive control in the cingulate cortex. Nat Rev Neurosci 12, 154–167 (2011). https://doi.org/10.1038/nrn2994

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