Manohar, SG; (2015) Frontostriatal contributions to reward processing. Doctoral thesis , UCL (University College London).

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Abstract

Dopaminergic projections to striatum and prefrontal cortex are thought to signal rewards, thereby energising movement, facilitating learning, and motivating effort. Extensive evidence links reward to attention and to dopamine. However a direct characterisation of how dopamine influences reward sensitivity in humans is lacking. This thesis examines the effects of dopamine and reward on eye movements. First, I introduced incentive manipulations into an “oculomotor capture” task, in which involuntary saccades are generated towards salient distractors. Whereas rewards increased both speed and accuracy, penalties slowed responses while increasing accuracy. A previously unreported effect is described, in which missed rewards capture attention. Subsequently, I developed a new paradigm that manipulates incentives trial-to-trial, during a speeded saccadic distraction task. In healthy volunteers, reward reduced distractibility and increased vigour (in terms of reaction time and velocity), and pupillary dilatation reflected reward expectation. This new task was then employed in a pharmacological study, in which I found that the dopaminergic D2-selective agonist cabergoline increased reward sensitivity in healthy volunteers. Parkinson's disease (PD) results in dopamine deficiency. PD patients performing my task had reduced reward sensitivity in saccade velocity and distractibility, as well as pupil dilatation. Patients were compared on versus off their dopaminergic medication, and although oculomotor vigour did not improve, medication normalised their blunted autonomic responses. Finally, 20 patients with medial prefrontal damage following subarachnoid haemorrhage performed the oculomotor task. Using lesion mapping, I found specific medial orbitofrontal regions in which damage correlated with reduced reward sensitivity. The results demonstrate that the extent to which reward invigorates behaviour is influenced by dopamine. Importantly, reward improves both speed and accuracy, contravening the theoretically predicted trade-off. To resolve this paradox, I develop an extension of optimal control theory that includes a costly precision signal. This model helps conceptualise reward's power to improve both speed and accuracy.

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