Advertisement

Looking for Greener Pastures

Humans, like other animals, have evolved to forage. Brain-imaging studies by Kolling et al. (p. 95) suggest that activity in the dorsal anterior cingulate cortex supplies a continuous signal of environmental richness predicted by foraging theory. The signal exhibits a frame of reference that is tied to the key foraging decision of whether to engage with the current choice or to search for alternatives. The same strategy is used when humans are making other types of decisions. In contrast, the ventromedial prefrontal cortex, a brain region that lacks any signals pertinent to foraging, encodes choice values in a manner uninfluenced by environmental richness.

Abstract

Behavioral economic studies involving limited numbers of choices have provided key insights into neural decision-making mechanisms. By contrast, animals’ foraging choices arise in the context of sequences of encounters with prey or food. On each encounter, the animal chooses whether to engage or, if the environment is sufficiently rich, to search elsewhere. The cost of foraging is also critical. We demonstrate that humans can alternate between two modes of choice, comparative decision-making and foraging, depending on distinct neural mechanisms in ventromedial prefrontal cortex (vmPFC) and anterior cingulate cortex (ACC) using distinct reference frames; in ACC, choice variables are represented in invariant reference to foraging or searching for alternatives. Whereas vmPFC encodes values of specific well-defined options, ACC encodes the average value of the foraging environment and cost of foraging.

Get full access to this article

View all available purchase options and get full access to this article.

Already a subscriber or AAAS Member? Log In

Supplementary Material

Summary

Materials and Methods
Supplementary Text
Figs. S1 to S9
Table S1
References (3137)

Resources

File (1216930.kolling.sm.pdf)

References and Notes

1
Platt M. L., Huettel S. A., Risky business: The neuroeconomics of decision making under uncertainty. Nat. Neurosci.11, 398 (2008).
2
Charnov E. L., Optimal foraging, the marginal value theorem. Theor. Popul. Biol.9, 129 (1976).
3
D. W. Stephens, J. R. Krebs, Foraging Theory (Princeton Univ. Press, Princeton, NJ, 1986).
4
Hayden B. Y., Pearson J. M., Platt M. L., Neuronal basis of sequential foraging decisions in a patchy environment. Nat. Neurosci.14, 933 (2011).
5
Freidin E., Kacelnik A., Rational choice, context dependence, and the value of information in European starlings (Sturnus vulgaris). Science334, 1000 (2011).
6
Hare T. A., Schultz W., Camerer C. F., O’Doherty J. P., Rangel A., Transformation of stimulus value signals into motor commands during simple choice.Proc. Natl. Acad. Sci. U.S.A.108, 18120 (2011).
7
Basten U., Biele G., Heekeren H. R., Fiebach C. J., How the brain integrates costs and benefits during decision making. Proc. Natl. Acad. Sci. U.S.A.107, 21767 (2010).
8
Botvinick M. M., Conflict monitoring and decision making: Reconciling two perspectives on anterior cingulate function. Cogn. Affect. Behav. Neurosci.7, 356 (2007).
9
Boorman E. D., Behrens T. E., Woolrich M. W., Rushworth M. F., How green is the grass on the other side? Frontopolar cortex and the evidence in favor of alternative courses of action. Neuron62, 733 (2009).
10
Lim S. L., O’Doherty J. P., Rangel A., The decision value computations in the vmPFC and striatum use a relative value code that is guided by visual attention. J. Neurosci.31, 13214 (2011).
11
Mansouri F. A., Buckley M. J., Tanaka K., Mnemonic function of the dorsolateral prefrontal cortex in conflict-induced behavioral adjustment.Science318, 987 (2007).
12
Rushworth M. F., Noonan M. P., Boorman E. D., Walton M. E., Behrens T. E., Frontal cortex and reward-guided learning and decision-making. Neuron70, 1054 (2011).
13
Noonan M. P., et al., Separate value comparison and learning mechanisms in macaque medial and lateral orbitofrontal cortex. Proc. Natl. Acad. Sci. U.S.A.107, 20547 (2010).
14
Wunderlich K., Dayan P., Dolan R. J., Nat. Neurosci.,10.1038/nn.3068 (2012).
15
Fellows L. K., Deciding how to decide: Ventromedial frontal lobe damage affects information acquisition in multi-attribute decision making. Brain129, 944 (2006).
16
Noonan M. P., Mars R. B., Rushworth M. F., Distinct roles of three frontal cortical areas in reward-guided behavior. J. Neurosci.31, 14399 (2011).
17
Hare T. A., O’Doherty J., Camerer C. F., Schultz W., Rangel A., Dissociating the role of the orbitofrontal cortex and the striatum in the computation of goal values and prediction errors. J. Neurosci.28, 5623 (2008).
18
Seo H., Lee D., Temporal filtering of reward signals in the dorsal anterior cingulate cortex during a mixed-strategy game. J. Neurosci.27, 8366 (2007).
19
Vickery T. J., Chun M. M., Lee D., Ubiquity and specificity of reinforcement signals throughout the human brain.Neuron72, 166 (2011).
20
Croxson P. L., Walton M. E., O’Reilly J. X., Behrens T. E., Rushworth M. F., Effort-based cost-benefit valuation and the human brain. J. Neurosci.29, 4531 (2009).
21
Rudebeck P. H., Walton M. E., Smyth A. N., Bannerman D. M., Rushworth M. F., Separate neural pathways process different decision costs. Nat. Neurosci.9, 1161 (2006).
22
Matsumoto K., Suzuki W., Tanaka K., Neuronal correlates of goal-based motor selection in the prefrontal cortex.Science301, 229 (2003).
23
Quilodran R., Rothé M., Procyk E., Behavioral shifts and action valuation in the anterior cingulate cortex.Neuron57, 314 (2008).
24
Daw N. D., O’Doherty J. P., Dayan P., Seymour B., Dolan R. J., Cortical substrates for exploratory decisions in humans. Nature441, 876 (2006).
25
Hayden B. Y., Pearson J. M., Platt M. L., Fictive reward signals in the anterior cingulate cortex. Science324, 948 (2009).
26
Boorman E. D., Behrens T. E., Rushworth M. F., Counterfactual choice and learning in a neural network centered on human lateral frontopolar cortex. PLoS Biol.9, e1001093 (2011).
27
Poldrack R. A., Can cognitive processes be inferred from neuroimaging data?Trends Cogn. Sci.10, 59 (2006).
28
Magno E., Foxe J. J., Molholm S., Robertson I. H., Garavan H., The anterior cingulate and error avoidance. J. Neurosci.26, 4769 (2006).
29
Kennerley S. W., Behrens T. E., Wallis J. D., Double dissociation of value computations in orbitofrontal and anterior cingulate neurons. Nat. Neurosci.14, 1581 (2011).
30
Wise S. P., Forward frontal fields: Phylogeny and fundamental function. Trends Neurosci.31, 599 (2008).
31
Beckmann C. F., Jenkinson M., Smith S. M., General multilevel linear modeling for group analysis in FMRI. Neuroimage20, 1052 (2003).
32
Deichmann R., Gottfried J. A., Hutton C., Turner R., Optimized EPI for fMRI studies of theorbitofrontal cortex. Neuroimage19, 430 (2003).
33
Friston K. J., et al., Psychophysiological and modulatory interactions in neuroimaging.Neuroimage6, 218 (1997).
34
Smith S. M., Fast robust automated brain extraction. Hum. Brain Mapp.17, 143 (2002).
35
Smith S. M., et al., Advances in functional and structural MR image analysis and implementation as FSL.Neuroimage23, (Suppl. 1), S208(2004).
36
Woolrich M. W., Ripley B. D., Brady M., Smith S. M., Temporal autocorrelation in univariate linear modeling of FMRI data.Neuroimage14, 1370 (2001).
37
Woolrich M. W., Behrens T. E., Beckmann C. F., Jenkinson M., Smith S. M., Multilevel linear modelling for FMRI group analysis using Bayesian inference.Neuroimage21, 1732 (2004).

Information & Authors

Information

Published In

Science
Volume 336 | Issue 6077
6 April 2012

Submission history

Received: 21 November 2011
Accepted: 17 February 2012
Published in print: 6 April 2012

Permissions

Request permissions for this article.

Acknowledgments

Funded by U.K. Medical Research Council and the Wellcome Trust.

Authors

Affiliations

Nils Kolling* [email protected]
Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, UK.
Timothy E. J. Behrens
Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, UK.
Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), University of Oxford, Oxford OX3 9DU, UK.
Rogier B. Mars
Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, UK.
Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), University of Oxford, Oxford OX3 9DU, UK.
Matthew F. S. Rushworth
Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, UK.
Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), University of Oxford, Oxford OX3 9DU, UK.

Notes

*
To whom correspondence should be addressed. E-mail: [email protected]

Metrics & Citations

Metrics

Article Usage
Altmetrics

Citations

Export citation

Select the format you want to export the citation of this publication.

Cited by

  1. Neural mechanisms resolving exploitation-exploration dilemmas in the medial prefrontal cortex, Science, 369, 6507, (2021)./doi/10.1126/science.abb0184
    Abstract
  2. Action Monitoring and Medial Frontal Cortex: Leading Role of Supplementary Motor Area, Science, 343, 6173, (888-891), (2021)./doi/10.1126/science.1247412
    Abstract
  3. Foundations of human reasoning in the prefrontal cortex, Science, 344, 6191, (1481-1486), (2021)./doi/10.1126/science.1252254
    Abstract
  4. Network Resets in Medial Prefrontal Cortex Mark the Onset of Behavioral Uncertainty, Science, 338, 6103, (135-139), (2012)./doi/10.1126/science.1226518
    Abstract
Loading...

View Options

Check Access

Log in to view the full text

AAAS ID LOGIN

AAAS login provides access to Science for AAAS Members, and access to other journals in the Science family to users who have purchased individual subscriptions.

Log in via OpenAthens.
Log in via Shibboleth.
More options

Register for free to read this article

As a service to the community, this article is available for free. Login or register for free to read this article.

Purchase this issue in print

Buy a single issue of Science for just $15 USD.

View options

PDF format

Download this article as a PDF file

Download PDF

Media

Figures

Multimedia

Tables

Share

Share

Share article link

Share on social media