5 research outputs found
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The Dopaminergic Midbrain Mediates an Effect of Average Reward on Pavlovian Vigor
Dopamine plays a key role in motivation. Phasic dopamine response reflects a reinforcement prediction error (RPE), whereas tonic dopamine activity is postulated to represent an average reward that mediates motivational vigor. However, it has been hard to find evidence concerning the neural encoding of average reward that is uncorrupted by influences of RPEs. We circumvented this difficulty in a novel visual search task where we measured participants' button pressing vigor in a context where information (underlying an RPE) about future average reward was provided well before the average reward itself. Despite no instrumental consequence, participants' pressing force increased for greater current average reward, consistent with a form of Pavlovian effect on motivational vigor. We recorded participants' brain activity during task performance with fMRI. Greater average reward was associated with enhanced activity in dopaminergic midbrain to a degree that correlated with the relationship between average reward and pressing vigor. Interestingly, an opposite pattern was observed in subgenual cingulate cortex, a region implicated in negative mood and motivational inhibition. These findings highlight a crucial role for dopaminergic midbrain in representing aspects of average reward and motivational vigor
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Reward Sensitivity and Waiting Impulsivity: Shift towards Reward Valuation away from Action Control
Background: Impulsivity and reward expectancy are commonly inter-related. Waiting impulsivity, measured using the rodent 5-Choice Serial Reaction Time (5-CSRT) task, predicts compulsive cocaine seeking and sign (or cue) tracking. Here we assess human waiting impulsivity using a novel translational task, the 4-CSRT, and the relationship with reward cues. Methods: Healthy volunteers (n=29) performed the monetary incentive delay task as a functional MRI study where subjects observe a cue predicting reward (cue) and wait to respond for high (£5), low (£1) or no reward. Waiting impulsivity was tested with the 4-CSRT. Results: For high reward prospects (£5 – no reward), greater waiting impulsivity on the 4-CSRT correlated with greater medial orbitofrontal cortex (OFC) and lower supplementary motor area (SMA) activity to cues. In response to high reward cues, greater waiting impulsivity was associated with greater subthalamic nucleus connectivity with OFC and greater subgenual cingulate connectivity with anterior insula but decreased connectivity with regions implicated in action selection and preparation. Conclusion: These findings highlight a shift towards regions implicated in reward valuation and a shift towards compulsivity away from higher level motor preparation and action selection and response. We highlight the role of reward sensitivity and impulsivity, mechanisms potentially linking human waiting impulsivity with incentive approach and compulsivity, theories highly relevant to disorders of addiction.This work was supported by the Wellcome Trust Fellowship grant for V.V. (093705/Z/10/Z). V.V. is currently supported by a Medical Research Council Senior Fellowship (MR/P008747/1). N.D. is a research fellow of the Deutsche Forschungsgemeinschaft (DO1915/1-1). The BCNI is supported by a WT and MRC grant
Separate mesocortical and mesolimbic pathways encode effort and reward learning signals
Optimal decision making mandates organisms learn the relevant features of choice options. Likewise, knowing how much effort we should expend can assume paramount importance. A mesolimbic network supports reward learning, but it is unclear whether other choice features, such as effort learning, rely on this same network. Using computational fMRI, we show parallel encoding of effort and reward prediction errors (PEs) within distinct brain regions, with effort PEs expressed in dorsomedial prefrontal cortex and reward PEs in ventral striatum. We show a common mesencephalic origin for these signals evident in overlapping, but spatially dissociable, dopaminergic midbrain regions expressing both types of PE. During action anticipation, reward and effort expectations were integrated in ventral striatum, consistent with a computation of an overall net benefit of a stimulus. Thus, we show that motivationally relevant stimulus features are learned in parallel dopaminergic pathways, with formation of an integrated utility signal at choice
Neurocomputational Accounts of Choice Variability and Affect during Decision-making
Humans exhibit surprising variability in behaviour, often making different choices under identical conditions. While the outcomes of these choices typically lead to explicit rewards that have been shown to influence subsequent affective states, less well understood is how the brain represents rewards that are intrinsically meaningful to an individual. The first part of this thesis examines the contributions of endogenous fluctuations in brain activity to behaviour. Resting-state studies suggest that ongoing endogenous fluctuations in brain activity can influence low-level perceptual and motor processes but it remains unknown whether such fluctuations also influence high-level cognitive processes including decision making. Using a novel application of real-time functional magnetic resonance imaging, I find that low pre-stimulus brain activity lead to increased occurrences of risky choice. Using computational modeling, I show that greater risk taking is explained by enhanced phasic responses to offers in a decision network. These findings demonstrate that endogenous brain activity provides a physiological basis for variability in complex behaviour. I then examine how the neuroanatomy of the brain in the form of tissue microstructure relates to risk preferences by leveraging on in vivo histology using magnetic resonance imaging. The second part of this thesis investigates how experienced events, such as rewards received following choice, are aggregated into affective states. Despite their relevance to ideas like goal-setting and well-being, little is known about the impact of intrinsic rewards on affective states and their representation in the brain. A reinforcement learning task incorporating a skilled performance component that did not influence payment was developed to examine this. Computational modeling revealed that momentary happiness depended on past extrinsic rewards and also intrinsic rewards related to the experience of successful skilled performance. Individuals for whom intrinsic rewards more strongly influence momentary happiness exhibit stronger ventromedial prefrontal cortex responses for successful skilled performance. These findings show that the ventromedial prefrontal cortex represents the subjective value of intrinsic rewards, and that computational models of mood dynamics provide a tool that can be used to measure implicit values of abstract goods and experiences