Neural models that convince: Model hierarchies and other strategies to bridge the gap between behavior and the brain
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Philosophical Psychology 20 (6):749 – 772 (2007)
Computational modeling of the brain holds great promise as a bridge from brain to behavior. To fulfill this promise, however, it is not enough for models to be 'biologically plausible': models must be structurally accurate. Here, we analyze what this entails for so-called psychobiological models, models that address behavior as well as brain function in some detail. Structural accuracy may be supported by (1) a model's a priori plausibility, which comes from a reliance on evidence-based assumptions, (2) fitting existing data, and (3) the derivation of new predictions. All three sources of support require modelers to be explicit about the ontology of the model, and require the existence of data constraining the modeling. For situations in which such data are only sparsely available, we suggest a new approach. If several models are constructed that together form a hierarchy of models, higher-level models can be constrained by lower-level models, and low-level models can be constrained by behavioral features of the higher-level models. Modeling the same substrate at different levels of representation, as proposed here, thus has benefits that exceed the merits of each model in the hierarchy on its own.
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References found in this work BETA
John R. Anderson (2002). Spanning Seven Orders of Magnitude: A Challenge for Cognitive Modeling. Cognitive Science 26 (1):85-112.
William Bechtel (2007). Reducing Psychology While Maintaining its Autonomy Via Mechanistic Explanations. In M. Schouten & H. L. De Joong (eds.), The Matter of the Mind: Philosophical Essays on Psychology, Neuroscience and Reduction. Blackwell Publishing.
Noam Chomsky (1965). Aspects of the Theory of Syntax. The Mit Press.
Michael Devitt (1991). Realism and Truth. B. Blackwell.
Carl Hempel (1965). Aspects of Scientific Explanation and Other Essays in the Philosophy of Science. The Free Press.
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