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Please use this identifier to cite or link to this item: http://hdl.handle.net/10012/5385

Title: The Ordinal Serial Encoding Model: Serial Memory in Spiking Neurons
Authors: Choo, Feng-Xuan
Keywords: serial memory
neural engineering framework
spiking neuron model
HRR
working memory
serial-order recall
Approved Date: 26-Aug-2010
Date Submitted: 2010
Abstract: In a world dominated by temporal order, memory capable of processing, encoding and subsequently recalling ordered information is very important. Over the decades this memory, known as serial memory, has been extensively studied, and its effects are well known. Many models have also been developed, and while these models are able to reproduce the behavioural effects observed in human recall studies, they are not always implementable in a biologically plausible manner. This thesis presents the Ordinal Serial Encoding model, a model inspired by biology and designed with a broader view of general cognitive architectures in mind. This model has the advantage of simplicity, and we show how neuro-plausibility can be achieved by employing the principles of the Neural Engineering Framework in the model’s design. Additionally, we demonstrate that not only is the model able to closely mirror human performance in various recall tasks, but the behaviour of the model is itself a consequence of the underlying neural architecture.
Program: Computer Science
Department: School of Computer Science
Degree: Master of Mathematics
URI: http://hdl.handle.net/10012/5385
Appears in Collections:Electronic Theses and Dissertations (UW)
Faculty of Mathematics Theses and Dissertations

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