Priming and Conservation Between Spatial and Cognitive Search Thomas T. Hills (thills@indiana.edu) Department of Psychological and Brain Sciences 1101 E. 10 th St., Indiana University, Bloomington, IN, 47405 Peter M. Todd (pmtodd@indiana.edu) Program in Cognitive Science 1101 E. 10 th St., Indiana University, Bloomington, IN, 47405 Robert L. Goldstone (rgoldsto@indiana.edu) Department of Psychological and Brain Sciences 1101 E. 10 th St., Indiana University, Bloomington, IN, 47405 Significant evidence from various fields suggests that this relationship between spatial foraging and internal cognitive search is not just a consequence of convergent evolution, but one of evolutionary homology (Hills, 2006). Research from neuroscience, genetics, and human pathology provide evidence that molecular and neural mechanisms that developed over evolutionary time for the purpose of modulating between exploration and exploitation in spatial foraging have subsequently been exapted for the purpose of modulating attention. A key observation is that similar dopaminergic processes are used to modulate goal-directed behavior and attention in multiple behavioral modalities across species (Floresco et al., 1996; Watanabe et al., 1997; Wang et al., 2004; Schultz, 2004). Furthermore, numerous pathologies of goal-directed cognition (e.g., attention- deficit/hyperactivity disorder—ADHD, drug addiction, and obsessive-compulsive disorder) involve dopaminergic defects or respond to dopaminergic drugs in ways that are consistent with dopaminergic effects on spatial movement behavior, as in, for example, the nematode and the fruit fly (Berke et al., 2000; Nieoullon, 2002; Schinka et al., 2002; Hills et al., 2004; Kume et al., 2005). These observations suggest that spatial search in physical space and abstract search in a cognitive space share a common basis in the brain and may therefore share key control features. While prior work has shown that animal foraging theory can be successfully applied to human search behavior (Pirolli & Card, 1999; Wilke, 2006), these efforts have been made based on arguments for optimality or robust decision heuristics. An argument based on a common biological basis for goal-directed cognition, however, would mean that spatial and abstract foraging are not simply similar because of similar selective forces in the environment, but are, in fact, themselves constrained by similar underlying physiologies. Given this, if the search mechanisms for different domains are not independent of one another, then activity in one ‘environment’ may influence activity in another. In such a case, we would expect that differences in individual foraging behavior could be primed across spatial and abstract contexts. That is, prior experience with resource distributions in a spatial environment could prime foraging behavior in an abstract environment. Similarly, we would Abstract There is compelling molecular and behavioral evidence that human goal-directed cognition is an evolutionary descendent of animal foraging behavior. A key observation is that similar dopaminergic processes are used to modulate between exploratory and exploitative foraging behaviors and control attention across animal species. Moreover, defects in these processes lead to predictable goal-directed cognitive pathologies in humans, such as attention-deficit/hyperactivity disorder and Parkinson’s disease. However, the cognitive relationships between exploration in space and exploration in the mind have not been examined. Using a spatial foraging task with two treatment conditions (clumpy and diffuse), followed by a word search task involving patches of words to be found in letter sets, we show that individuals who experienced clumpy resource distributions in space behave as if resources are more densely clumped in the word search task, relative to those who experienced the diffuse spatial treatment. We show this is not a function of general arousal but is consistent with longer giving- up times in the word search task, which is a qualitative prediction of optimal foraging theory. We also show that behavioral tendencies during search are conserved within individuals: Those who explore more of the physical space leave letter sets sooner. Along with the biological evidence, our results support a general search process underlying cognition, which operates both in external and internal environments. Keywords: Goal-directed behavior; attention; animal foraging; foraging; dopamine; search; spatial search; word search; priming; individual differences; ADHD; Parkinson’s. Introduction More than a hundred years ago William James noted “We make search in our memory for a forgotten idea, just as we rummage our house for a lost object” (James, 1890, p654). This relationship is anecdotally supported by the fact that cognitive representations of spatial and semantic knowledge are often characterized as maps or networks (Steyvers & Tenenbaum, 2005; Tolman, 1948). Though these internal representations are specific to particular contexts, the search processes required to navigate them may not be. In all cases, cognitive navigation relies on appropriate modulation of attention between exploration and exploitation in ways fundamentally similar to the behavioral ecology of animal foraging (Kareiva & Odell, 1987; Walsh, 1996).
[1]
E. Tolman.
Cognitive maps in rats and men.
,
1948,
Psychological review.
[2]
Peter M. Todd,et al.
Testing Simple Rules for Human Foraging in Patchy Environments
,
2005
.
[3]
Jeremy K. Seamans,et al.
A selective role for dopamine in the nucleus accumbens of the rat in random foraging but not delayed spatial win-shift-based foraging
,
1996,
Behavioural Brain Research.
[4]
Thomas T. Hills.
Animal Foraging and the Evolution of Goal-Directed Cognition
,
2006,
Cogn. Sci..
[5]
P. Grambsch,et al.
Modeling Survival Data: Extending the Cox Model
,
2000
.
[6]
Allan Collins,et al.
A spreading-activation theory of semantic processing
,
1975
.
[7]
G. Odell,et al.
Swarms of Predators Exhibit "Preytaxis" if Individual Predators Use Area-Restricted Search
,
1987,
The American Naturalist.
[8]
K. Hikosaka,et al.
Increase of extracellular dopamine in primate prefrontal cortex during a working memory task.
,
1997,
Journal of neurophysiology.
[9]
J. H. Neely.
Semantic priming and retrieval from lexical memory: Roles of inhibitionless spreading activation and limited-capacity attention.
,
1977
.
[10]
W. Schultz.
Neural coding of basic reward terms of animal learning theory, game theory, microeconomics and behavioural ecology
,
2004,
Current Opinion in Neurobiology.
[11]
S. Hyman,et al.
Addiction, Dopamine, and the Molecular Mechanisms of Memory
,
2000,
Neuron.
[12]
John R Anderson,et al.
Predicting the practice effects on the blood oxygenation level-dependent (BOLD) function of fMRI in a symbolic manipulation task
,
2003,
Proceedings of the National Academy of Sciences of the United States of America.
[13]
A. Nieoullon.
Dopamine and the regulation of cognition and attention
,
2002,
Progress in Neurobiology.
[14]
W. James,et al.
The Principles of Psychology.
,
1983
.
[15]
Sang Ki Park,et al.
Dopamine Is a Regulator of Arousal in the Fruit Fly
,
2005,
The Journal of Neuroscience.
[16]
Peter Pirolli,et al.
Rational Analyses of Information Foraging on the Web
,
2005,
Cogn. Sci..
[17]
Peter D. Walsh,et al.
Area-restricted Search and the Scale Dependence of Path Quality Discrimination
,
1996
.
[18]
K. Holyoak,et al.
Schema induction and analogical transfer
,
1983,
Cognitive Psychology.
[19]
C. I. Connolly,et al.
Building neural representations of habits.
,
1999,
Science.
[20]
H. Barrett,et al.
Modularity in cognition: framing the debate.
,
2006,
Psychological review.
[21]
K. Holyoak,et al.
Analogical problem solving
,
1980,
Cognitive Psychology.
[22]
L. Cosmides,et al.
The Adapted Mind
,
1992
.
[23]
A. V. Maricq,et al.
Dopamine and Glutamate Control Area-Restricted Search Behavior in Caenorhabditis elegans
,
2004,
The Journal of Neuroscience.
[24]
P J Kelly,et al.
Survival analysis for recurrent event data: an application to childhood infectious diseases.
,
2000,
Statistics in medicine.
[25]
F. Crawford,et al.
DRD4 and novelty seeking: results of meta-analyses.
,
2002,
American journal of medical genetics.
[26]
Joshua B. Tenenbaum,et al.
The Large-Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth
,
2001,
Cogn. Sci..
[27]
P. Goldman-Rakic,et al.
Selective D2 Receptor Actions on the Functional Circuitry of Working Memory
,
2004,
Science.
[28]
David J. Freedman,et al.
Representation of the Quantity of Visual Items in the Primate Prefrontal Cortex
,
2002,
Science.
[29]
James N. McNair,et al.
Optimal Giving-Up Times and the Marginal Value Theorem
,
1982,
The American Naturalist.