This thesis is concerned with the computational modelling and simulation of physiological structures and cognitive functions of brains through the use of artificial neural nets. While the structures of these models are loosely related to neurons and physiological structures observed in brains, the extent to which we can accept claims about how neurons and brains really function based on such models depends largely on judgments about the fitness of (virtual) computer experiments as empirical evidence. The thesis examines the computational foundations of neural models, neural nets, and some computational models of higher cognitive functions in terms of their ability to provide empirical support for theories within the framework of Parallel Distributed Processing (PDP). Models of higher cognitive functions in this framework are often presented in forms that hybridise top-down (e.g. employing terminology from Psychology or Linguistics) and bottom-up (neurons and neural circuits) approaches to cognition. In this thesis I argue that the use of terminology from either approach can blind us to the highly theory-laden nature of the models, and that this tends to produce overly optimistic evaluations of the empirical value of computer experiments on these models. I argue, further, that some classes of computational models and simulations based on methodologies that hybridise top-down and bottom-up approaches are ill-designed. Consequently, many of the theoretical claims based on these models cannot be supported by experiments with such models. As a result, I question the effectiveness of computer experiments with artificial neural nets as an empirical technique for cognitive modelling.
| Identifer | oai:union.ndltd.org:ADTP/215536 |
| Date | January 2007 |
| Creators | Krebs, Peter Rudolf, School of History & Philosophy of Science, UNSW |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
| Rights | http://unsworks.unsw.edu.au/copyright, http://unsworks.unsw.edu.au/copyright |
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