New approaches to the study of amnesic patients: what can a neurofunctional philosophy and neural network methods offer?
In this paper I first consider a neurofunctional approach to the study of amnesic patients. This approach stresses the need for theorising about the processing operations of brain regions and circuits rather than for theorising about neuropsychological syndromes. A syndrome such as amnesia-may not exist, in any meaningful sense, if there is marked heterogeneity within the patients grouped together in this way. Powerful neuroimaging techniques may now allow a more useful basis for grouping patients in terms of lesion location rather than aetiology. In turn this will allow an evaluation of the information processing functions subserved by the lesioned structures. The second strand to the present paper stresses the weakness in the specification of current theories. This has made it difficult to select experimental tasks that decisively measure the key components of those theories. The paper makes the case that explicit neural network models are a useful way to try to overcome this problem. In line with these ideas, the paper begins to build a model of how the brain may achieve useful kinds of stimulus representations. Considerations of human behaviour in category learning tasks have emphasised parallel and interacting roles for both exemplar- and element-based stimulus representations. It is suggested that the hippocampus itself may encode exemplar representations, and these may provide a basis for episodic memory as well as some types of category learning. It is further suggested that the ventral striatum may encode the element-based representations. The model allows some new and detailed predictions for the performance of amnesic subjects related to lesion location.
Pickering
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Department of Psychology, St George's Hospital Medical School, University of London, UK. a.pickering@sghms.ac.uk
D000647:Amnesia / Q000503:physiopathology*; D001921:Brain / Q000503:physiopathology*; D001930:Brain Injuries / Q000503:physiopathology; D003071:Cognition; D006801:Humans; D007858:Learning; D008960:Models, Psychological; D009415:Nerve Net