Computational Approaches to Neurological Disease

Computational models have contributed to current understanding of normal brain function, and can offer new insights into the pathophysiology of neurological disease. We define some of the outstanding clinical questions in stroke, CNS injury, Alzheimer's disease, Parkinson's disease, and epilepsy from a neurologist's perspective, and discuss the potential impact of computational neurology on computational neuroscience. We consider representative examples of models constructed at several different levels of biological detail--from detailed membrane-level simulations to connectionist networks. We focus on what has been learned from several generations of models concerned with the after-effects of neural injury. In particular, we discuss how model assumptions, sometimes of ancillary importance, have constrained the ability to predict subsequent experimental results.

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