Foraging under Competition: The Neural Basis of Input-Matching in Humans

Input-matching is a key mechanism by which animals optimally distribute themselves across habitats to maximize net gains based on the changing input values of food supply rate and competition. To examine the neural systems that underlie this rule in humans, we created a continuous-input foraging task where subjects had to decide to stay or switch between two habitats presented on the left and right of the screen. The subject's decision to stay or switch was based on changing input values of reward-token supply rate and competition density. High density of competition or low-reward token rate was associated with decreased chance of winning. Therefore, subjects attempted to maximize their gains by switching to habitats that possessed low competition density and higher token rate. When it was increasingly disadvantageous to be in a habitat, we observed increased activity in brain regions that underlie preparatory motor actions, including the dorsal anterior cingulate cortex and the supplementary motor area, as well as the insula, which we speculate may be involved in the conscious urge to switch habitats. Conversely, being in an advantageous habitat is associated with activity in the reward systems, namely the striatum and medial prefrontal cortex. Moreover, amygdala and dorsal putamen activity steered interindividual preferences in competition avoidance and pursuing reward. Our results suggest that input-matching decisions are made as a net function of activity in a distributed set of neural systems. Furthermore, we speculate that switching behaviors are related to individual differences in competition avoidance and reward drive.

[1]  H. Harris,et al.  The Rat , 1958, Nature.

[2]  S. Fretwell,et al.  On territorial behavior and other factors influencing habitat distribution in birds , 1969 .

[3]  S. Fretwell,et al.  On territorial behavior and other factors influencing habitat distribution in birds , 1969 .

[4]  S. Fretwell Populations in a seasonal environment. , 1973, Monographs in population biology.

[5]  A. Mcgeorge,et al.  The organization of the projection from the cerebral cortex to the striatum in the rat , 1989, Neuroscience.

[6]  W. Schultz,et al.  Dopamine neurons of the monkey midbrain: contingencies of responses to active touch during self-initiated arm movements. , 1990, Journal of neurophysiology.

[7]  R. Gray,et al.  Can ecological theory predict the distribution of foraging animals? A critical analysis of experiments on the ideal free distribution , 1993 .

[8]  R. Adolphs,et al.  The human amygdala in social judgment , 1998, Nature.

[9]  C. Gallistel,et al.  Computational Versus Associative Models of Simple Conditioning , 2001 .

[10]  C. Gallistel,et al.  The rat approximates an ideal detector of changes in rates of reward: implications for the law of effect. , 2001, Journal of experimental psychology. Animal behavior processes.

[11]  David G. Amaral,et al.  The primate amygdala and the neurobiology of social behavior: implications for understanding social anxiety , 2002, Biological Psychiatry.

[12]  M. Delgado,et al.  Dorsal striatum responses to reward and punishment: Effects of valence and magnitude manipulations , 2003, Cognitive, affective & behavioral neuroscience.

[13]  John Duncan,et al.  State Anxiety Modulation of the Amygdala Response to Unattended Threat-Related Stimuli , 2004, The Journal of Neuroscience.

[14]  Timothy Edward John Behrens,et al.  Changes in connectivity profiles define functionally distinct regions in human medial frontal cortex. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[15]  Kae Nakamura,et al.  Basal ganglia orient eyes to reward. , 2006, Journal of neurophysiology.

[16]  P. Dayan,et al.  Cortical substrates for exploratory decisions in humans , 2006, Nature.

[17]  B. Balleine,et al.  The Role of the Dorsal Striatum in Reward and Decision-Making , 2007, The Journal of Neuroscience.

[18]  M. Reuter,et al.  Genetically Determined Differences in Learning from Errors , 2007, Science.

[19]  Radford M. Neal Pattern Recognition and Machine Learning , 2007, Technometrics.

[20]  Angela J. Yu,et al.  Should I stay or should I go? How the human brain manages the trade-off between exploitation and exploration , 2007, Philosophical Transactions of the Royal Society B: Biological Sciences.

[21]  J. Silk Social Components of Fitness in Primate Groups , 2007, Science.

[22]  Mark Laubach,et al.  The Dorsomedial Striatum Reflects Response Bias during Learning , 2009, The Journal of Neuroscience.

[23]  J. O'Doherty,et al.  Evidence for a Common Representation of Decision Values for Dissimilar Goods in Human Ventromedial Prefrontal Cortex , 2009, The Journal of Neuroscience.

[24]  D. Hassabis,et al.  Choking on the Money , 2009, Psychological science.

[25]  Colin Camerer,et al.  Self-control in decision-making involves modulation of the vmPFC valuation system , 2009, NeuroImage.

[26]  Daniel P. Kennedy,et al.  Personal Space Regulation by the Human Amygdala , 2009, Nature Neuroscience.

[27]  A. Craig,et al.  How do you feel — now? The anterior insula and human awareness , 2009, Nature Reviews Neuroscience.

[28]  D. Mobbs,et al.  Neural activity associated with monitoring the oscillating threat value of a tarantula , 2010, Proceedings of the National Academy of Sciences.

[29]  Ben Seymour,et al.  Insula and Striatum Mediate the Default Bias , 2010, The Journal of Neuroscience.

[30]  A. Zapata,et al.  Shift from Goal-Directed to Habitual Cocaine Seeking after Prolonged Experience in Rats , 2010, The Journal of Neuroscience.

[31]  B. Balleine,et al.  Human and Rodent Homologies in Action Control: Corticostriatal Determinants of Goal-Directed and Habitual Action , 2010, Neuropsychopharmacology.

[32]  R. Adolphs,et al.  Annals of the New York Academy of Sciences What Does the Amygdala Contribute to Social Cognition? , 2022 .

[33]  Jessica A. Grahn,et al.  Putting brain training to the test , 2010, Nature.

[34]  V. Stuphorn,et al.  Medial Frontal Cortex Motivates But Does Not Control Movement Initiation in the Countermanding Task , 2010, The Journal of Neuroscience.

[35]  Siegfried Kasper,et al.  Reduced resting-state functional connectivity between amygdala and orbitofrontal cortex in social anxiety disorder , 2011, NeuroImage.

[36]  John M. Pearson,et al.  Neuronal basis of sequential foraging decisions in a patchy environment , 2011, Nature Neuroscience.

[37]  M. Walton,et al.  Re‐evaluating the role of the orbitofrontal cortex in reward and reinforcement , 2012, The European journal of neuroscience.

[38]  Timothy E. J. Behrens,et al.  Neural Mechanisms of Foraging , 2012, Science.

[39]  Matthias Sutter,et al.  Affirmative Action Policies Promote Women and Do Not Harm Efficiency in the Laboratory , 2012, Science.