Abstract
Neuropsychological decision-making in the clinical setting can be investigated from the perspective of different computational models derived from cognitive science. In this chapter, we focus on four of these models: Multivariate analyses, expert knowledge-based systems, exemplar-based reasoning models, and connectionist models. All presuppose that neuropsychological decision-making is essentially a complex pattern recognition task. For example, the neuropsychologist might attempt to recognize the locus of a lesion on the basis of a pattern of symptoms, test scores, and historical data. The four models in this chapter provide substantially different solutions for this complex pattern recognition problem.
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Long, D.L., Graesser, A.C., Long, C.J. (1988). Four Computational Models for Investigating Neuropsychological Decision-making. In: Williams, J.M., Long, C.J. (eds) Cognitive Approaches to Neuropsychology. Human Neuropsychology. Springer, Boston, MA. https://doi.org/10.1007/978-1-4684-5577-9_1
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DOI: https://doi.org/10.1007/978-1-4684-5577-9_1
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