Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.793773
Title: Computational modelling of decision uncertainty
Author: Atiya, Nadim
ISNI:       0000 0004 8504 1871
Awarding Body: Ulster University
Current Institution: Ulster University
Date of Award: 2019
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Abstract:
This PhD thesis contributes towards the development and analysis of a neural circuit computational model of perceptual decision uncertainty and change-of-mind behaviour. This highly-interdisciplinary work integrates biological neural network modelling, cognitive psychology and neurophysiology of metacognitive behaviour, and the mathematics of dynamical systems theory. The thesis begins with a concise review of the various experimental observations of decision uncertainty and change-of-mind. This is done through an overview of the evolution of the experimental tasks that have been developed over the years to understand decision uncertainty in humans and animals. This is followed by an overview of the existing models of decision uncertainty and change-of-mind, with a focus on cognitive models (dynamical and probabilistic) and neural models. The thesis has led to three original research contributions. In the first contribution, the first cortical neural circuit model of decision uncertainty and change-of-mind is introduced, effectively unifying the two fields of study. The proposed model accounts for a variety of behavioural and neural signatures of decision uncertainty and change-of-mind, while explaining the shared neural mechanism that links both metacognitive features. In the second contribution, more rigorous theoretical analyses of the model are presented. This is done through systematic variation of key model parameters proposed in the first contribution. Furthermore, the robustness of the model is highlighted, and reward rate is investigated to identify the impact of various parameter values on optimal performance. In the third contribution, changes-of-mind are investigated in situations when additional evidence is not available after the initial decision, a type of situation that has been neglected by the current theoretical and experimental accounts. Using an experimental task, it is demonstrated that changes-of-mind can occur in the absence of new post-decision evidence. Furthermore, using a reduced version of the proposed neural circuit model, the neural mechanisms underlying such changes-of-mind are uncovered. In particular, it is shown that changes-of mind in the absence of new post-decision evidence are strongly linked to elevated neural activity in the uncertainty-encoding population of the model, consistent with recent neurophysiological evidence implicating higher order networks in change-of-mind behaviour. Overall, the three contributions shed light on the neural circuit dynamics underlying decision uncertainty and change-of-mind behaviour, and offer a biologically-motivated theoretical framework for future investigations.
Supervisor: Wong-Lin, Kongfatt ; Prasad, Girijesh Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.793773  DOI: Not available
Keywords: Decision-making ; Change-of-mind ; Computational neuroscience ; Artificial Intelligence
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