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Theeuwes, J.

Publications and source records attributed to Theeuwes, J..

3 recordsLinked to original sources

Dopaminergic medication reduces striatal sensitivity to negative outcomes in Parkinson’s disease

Reduced levels of dopamine in Parkinsons disease (PD) contribute to changes in learning, resulting from the loss of midbrain dopamine neurons that transmit a teaching signal to the striatum. Dopamine medication used by PD patients has previously been linked to either behavioral changes during learning itself or adjustments in approach and avoidance behavior after learning. To date, however, very little is known about the specific relationship between dopaminergic medication-driven differences during learning and subsequent changes in approach/avoidance tendencies in individual patients. We assessed 24 PD patients on and off dopaminergic medication and 24 healthy controls (HC) performing a probabilistic reinforcement learning task, while undergoing functional magnetic resonance imaging. During learning, medication in PD reduced an overemphasis on negative outcomes. When patients were on medication, learning rates were lower for negative (but not positive) outcomes and concurrent striatal BOLD responses showed reduced prediction error sensitivity. Medication-induced shifts in negative learning rates were predictive of changes in approach/avoidance choice patterns after learning, and these changes were accompanied by striatal BOLD response alterations. These findings highlight dopamine-driven learning differences in PD and provide new insight into how changes in learning impact the transfer of learned value to approach/avoidance responses in novel contexts.

neuroscience

Pupil responses as indicators of value-based decision-making

Pupil responses have been used to track cognitive processes during decision-making. Studies have shown that in these cases the pupil reflects the joint activation of many cortical and subcortical brain regions, also those traditionally implicated in value-based learning. However, how the pupil tracks value-based decisions and reinforcement learning is unknown. We combined a reinforcement learning task with a computational model to study pupil responses during value-based decisions, and decision evaluations. We found that the pupil closely tracks reinforcement learning both across trials and participants. Prior to choice, the pupil dilated as a function of trial-by-trial fluctuations in value beliefs. After feedback, early dilation scaled with value uncertainty, whereas later constriction scaled with reward prediction errors. Our computational approach systematically implicates the pupil in value-based decisions, and the subsequent processing of violated value beliefs. These dissociable influences provide an exciting possibility to non-invasively study ongoing reinforcement learning in the pupil.

neuroscience

Global interactions between feature-based and spatial attention redistribute feature sensitivity across visual space

Spatial attention changes the sampling of visual space. Behavioral studies suggest that feature-based attention modulates this resampling to optimize the attended features sampling. We investigate this hypothesis by estimating spatial sampling in visual cortex while independently varying both feature-based and spatial attention.\n\nOur results show that spatial and feature-based attention interacted: resampling of visual space depended on both the attended location and feature (color vs. temporal frequency). This interaction occurred similarly throughout visual cortex, regardless of an areas overall feature preference. However, the interaction did depend on spatial sampling properties of voxels that prefer the attended feature. These findings are parsimoniously explained by variations in the precision of an attentional gain field.\n\nOur results demonstrate that the deployment of spatial attention is tailored to the spatial sampling properties of units that are sensitive to the attended feature.

neuroscience