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Neural computations for working memory and decision making

Cavanagh, Sean Edward; (2019) Neural computations for working memory and decision making. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

It has long been known that neurons can possess spatial receptive fields, but whether they exhibit temporal receptive fields is relatively unexplored. Higher cognition relies upon processing across long timescales, such as: the holding of information in working memory, or the accumulation of evidence to form decisions. The temporal dynamics of individual neurons during these processes, and how they facilitate circuit-level computations, are pressing questions. This thesis will present four studies that try to address these questions using a variety of techniques: behavioural analyses, single neuron electrophysiology, pharmacology, and computational modelling. It will first present a method to index the temporal receptive field of single neurons, which highlights heterogeneity within prefrontal cortical regions. This heterogeneity is functionally significant, as neurons with longer timescales exhibit stronger and more sustained value correlates during choice. This may provide a neural mechanism for maintaining predictions and updating stored values during learning. A second study shows that the concept of temporal receptive fields can be used to reconcile competing accounts of neuronal activity during working memory tasks. A neuron’s temporal receptive field is predictive of both its degree of task involvement, and its working memory coding dynamics. Next, a further behavioural study probed the role of visual attention in evidence accumulation – revealing fixations are drawn towards valuable and novel stimuli. Finally, data from a complex decision-making task is presented, where monkeys had to accumulate evidence across time. The function of N-methyl-D-aspartate (NMDA) receptors during this extended cognitive process was investigated using pharmacological manipulations. The induced behavioural changes were consistent with those predicted by a lowering of the excitation-inhibition (E/I) ratio in a spiking cortical circuit model. Together these results provide important insights into the role of neuronal timescales in high-level cognition, and have implications for cognitive deficits in neuropsychiatric disorders associated with cortical E/I dysfunction.

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: Neural computations for working memory and decision making
Event: UCL (University College London)
Language: English
Additional information: Copyright © The Author 2019. Original content in this thesis is licensed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) Licence (https://creativecommons.org/licenses/by/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request.
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Clinical and Movement Neurosciences
URI: https://discovery.ucl.ac.uk/id/eprint/10081601
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