Literature DB >> 27322000

Patients with Parkinson's Disease Show Impaired Use of Priors in Conditions of Sensory Uncertainty.

Alessandra Perugini1, Jochen Ditterich2, Michele A Basso3.   

Abstract

Perceptual decisions arise after considering the available sensory evidence [1]. When sensory information is unreliable, a good strategy is to rely on previous experience in similar situations to guide decisions [2-6]. It is well known that patients with Parkinson's disease (PD) are impaired at value-based decision-making [7-11]. How patients combine past experience and sensory information to make perceptual decisions is unknown. We developed a novel, perceptual decision-making task and manipulated the statistics of the sensory stimuli presented to patients with PD and healthy participants to determine the influence of past experience on decision-making. We show that patients with PD are impaired at combining previously learned information with current sensory information to guide decisions. We modeled the results using the drift-diffusion model (DDM) and found that the impairment corresponds to a failure in adjusting the amount of sensory evidence needed to make a decision. Our modeling results also show that two complementary mechanisms operate to implement a bias when two sets of priors are learned concurrently. Asymmetric decision threshold adjustments, as reflected by changes in the starting point of evidence accumulation, are responsible for a general choice bias, whereas the adjustment of a dynamic bias that develops over the course of a trial, as reflected by a drift-rate offset, provides the stimulus-specific component of the prior. A proper interplay between these two processes is required to implement a bias based on concurrent, stimulus-specific priors in decision-making. We show here that patients with PD are impaired in these across-trial decision threshold adjustments.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Glass patterns; basal ganglia; bias; cognition; decision-making; drift-diffusion model; expectancy; implicit learning; memory; perception

Mesh:

Year:  2016        PMID: 27322000      PMCID: PMC5633083          DOI: 10.1016/j.cub.2016.05.039

Source DB:  PubMed          Journal:  Curr Biol        ISSN: 0960-9822            Impact factor:   10.834


  36 in total

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