The Memory Tesseract: Developing a Unified Framework for Modelling Memory and Cognition
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Computational memory models can explain the behaviour of human memory in diverse experimental paradigms—whether it be recall or recognition, short-term or long-term retention, implicit or explicit learning. Simulation has led to parsimonious theories of memory, but at a cost of a profusion of competing models. As different models focus on different phenomena, there is no best model. However, the models share many characteristics, indicating wide agreement on the mathematics of how memory works in the brain. On the basis of an analysis of computational memory models, we argue that these models can be understood in terms of a single neurally-plausible computational and theoretical framework. We present a proof of concept neural implementation, integration with the ACT-R cognitive architecture, and demonstrate model performance on procedural, declarative, episodic, and semantic learning tasks. This research aims to advance cognitive psychology towards a single integrated, computational model of human memory that can account for human performance on diverse experimental tasks, that can be implemented at a neural level of detail, and can be scaled to modelling arbitrarily long-term learning.
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Copyright © 2016 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.
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- 2016
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kelly-thememorytesseractdevelopingaunifiedframework.pdf | 2023-05-05 | Public | Download |