Cognitive and neural mechanisms of causal reasoning

Causal beliefs pertain to everything and everyone, not only because things and agents are all potential causal relata (as cause, effect, preventor, enabler), but because even the very notion of a discrete medium-sized object of one sort or another, or of “object permanence”, or a living rather than inanimate thing, or a sentient being, or a person, is in large part essentially causal. An object, force, or agent of a given kind is an item capable of doing and undergoing a range of things. For this reason the ability to acquire, maintain, and put to use a system of causal beliefs is a pervasive necessity of human cognitive life and of life, period, starting with our very capacity to perceive our environment and extending to all our actions and interactions with it.

Beyond this obvious truth, matters are much less clear. Any attempt to look comprehensively at either the psychological processes or neural underpinnings of causal cognition must address a long series of thorny questions concerning causality itself: (1) What is the everyday concept of cause/causality? Is there one, more than one? If more, are these only very loosely connected to one another, or systematically related in some way? (2) What sorts of items can be related as cause and effect? Popular candidates include objects, properties, dispositions, forces, events, omissions, changes, non-changes, chance, et al. (3) How do we represent causal relations and their relata, and how do we correct or update our “standing” causal representations of the world? (4) Can we sometimes directly perceive causes? If so, does this involve a specialized causal processing capacity, possibly even a causality “module”? Or do we perceive causes via already familiar systems (e.g., visual, motor, or auditory)? (5) When we infer rather than directly perceive causes in order to extend our knowledge or to better understand a situation is there any one way this happens or are there multiple ways, depending on the situation or the sort of causal relationships involved (e.g., deterministic versus probabilistic)? (6) Do the facts of causal perception and causal inference support some version of a “dual process” theory of cognition combining associative and rule-based operations? (7) How and why do people sometimes distinguish positive causes from omissions and absences, or from enabling conditions? (9) How do emotions, legal and moral obligations, cognitive biases and heuristics, and background beliefs in general factor into causal attribution and inference? (10) Are traditional “folk theories” about physical objects, living things, etc., a good guide to the study of “causal thought” and its neural implementation, or might they turn out to be quite a bad guide?

Our research has focused primarily on how people utilize existing causal knowledge to draw new causal inferences and has led to the development of two computational models of causal reasoning (the force theory and the causal model theory) and a cognitive neuroscience framework (the causal simulation theory). We are currently conducting neuroscience studies (employing fMRI and lesion methods) to assess the neurobiological predictions of these models and to develop an integrative cognitive neuroscience theory of causal reasoning.

References

Barbey, A.K. & Wolff, P. (submitted). Combining causal relations.

Patterson, R. & Barbey, A.K. (in press). Causal simulation theory: An integrative cognitive neuroscience framework for causal reasoning. In J. Grafman & F. Krueger (Eds.), The Neural Representation of Belief Systems. Psychological Press. [pdf]

Wolff, P., Barbey, A.K. & Hausknecht, M. (in press). For want of a nail: How absences cause events. Journal of Experimental Psychology: General. [pdf]

Barbey A.K. & Barsalou L.W. (2009) Reasoning and Problem Solving: Models. In L. Squire (Ed.) Encyclopedia of Neuroscience, Vol. 8 (pp. 35-43). Oxford: Academic Press. [pdf]

Sloman, S.A., Barbey, A.K. & Hotaling, J. (2009). A causal model theory of the meaning of “cause,” “enable,” and “prevent.” Cognitive Science, 33, 21-50. [pdf]

Chaigneau, S. & Barbey, A.K. (2008). Assessing psychological theories of causal meaning and inference. In Proceedings of the Thirtieth Annual Conference of the Cognitive Science Society. Hillsdale, NJ: Erlbaum. [pdf]

Barbey, A.K. & Wolff, P. (2007). Learning causal structure from reasoning. Proceedings of the 29th Annual Conference of the Cognitive Science Society (pp. 713-718). Mahwah, NJ: Lawrence Erlbaum. [pdf]

Barbey, A.K. & Wolff, P. (2006). Causal reasoning from forces. Proceedings of the 28 Annual Conference of the Cognitive Science Society (p. 2439). Mahwah, NJ: Lawrence Erlbaum. [pdf]

Computational model

Force Theory Simulation Program