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Caitlin Sisk, Emily Twedell, Wilma Koutstaal, Scott Cooper, Yuhong Jiang; Unimpaired habit-guided spatial attention in patients with Parkinson's disease. Journal of Vision 2018;18(10):899. doi: https://doi.org/10.1167/18.10.899.
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Extensive research has examined how current goals influence spatial attention. Yet the allocation of spatial attention is also guided by a search habit, which is acquired when a visual search target is frequently found in one region of space. Here, we examined the role of the dopaminergic system in acquiring and maintaining habit-guided spatial attention. Patients with Parkinson's disease (PD) and age-matched healthy controls completed a difficult visual search task. Parkinson's patients were tested in an off-medication and off-stimulator status. Unbeknownst to the participants, the target appeared most often in one quadrant in an early, training phase of the experiment. In a later, testing phase of the experiment, the target was randomly located (equally probable across all four quadrants). Healthy controls acquired an attentional preference toward the high-probability quadrant. They were faster in finding the target in the high-probability quadrant than in the other quadrants, and learning did not depend on having explicit awareness of the target's location probability. In addition, control participants maintained this attentional preference in the testing phase. Despite slower response times, Parkinson's patients also showed intact acquisition and maintenance of location probability learning. These findings contrast with PD patients' deficits in acquiring habit learning in other tasks, as found previously in probabilistic learning (the "weather prediction task"), object association learning, and spatial context learning. Our findings suggest that not all habit learning depends on the basal ganglia and the dopaminergic system, which are known to be impaired in PD. Preservation of habit-guided spatial attention may compensate for other types of attentional deficits in PD.
Meeting abstract presented at VSS 2018
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