Evidence accumulation during perceptual decision-making is sensitive to the dynamics of attentional selection

被引:11
|
作者
Rangelov, Dragan [1 ]
Mattingley, Jason B. [1 ,2 ]
机构
[1] Univ Queensland, Queensland Brain Inst, St Lucia, Qld 4072, Australia
[2] Univ Queensland, Sch Psychol, St Lucia, Qld 4072, Australia
基金
澳大利亚研究理事会; 英国医学研究理事会;
关键词
Decision making; Visual attention; Encephalography; Mixture distribution modelling; Frequency tagging; Multivariate analyses; GAIN-CONTROL; MULTIPLE; SIGNALS; ONSET; TEMPLATE; MODELS; MOTION; SHIFTS; TIME;
D O I
10.1016/j.neuroimage.2020.117093
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
The ability to select and combine multiple sensory inputs in support of accurate decisions is a hallmark of adaptive behaviour. Attentional selection is often needed to prioritize task-relevant stimuli relative to irrelevant, potentially distracting stimuli. As most studies of perceptual decision-making to date have made use of task-relevant stimuli only, relatively little is known about how attention modulates decision making. To address this issue, we developed a novel 'integrated' decision-making task, in which participants judged the average direction of successive target motion signals while ignoring concurrent and spatially overlapping distractor motion signals. In two experiments that varied the role of attentional selection, we used regression to quantify the influence of target and distractor stimuli on behaviour. Using electroencephalography, we characterised the neural correlates of decision making, attentional selection and feature-specific responses to target and distractor signals. While targets strongly influenced perceptual decisions and associated neural activity, we also found that concurrent and spatially coincident distractors exerted a measurable bias on both behaviour and brain activity. Our findings suggest that attention operates as a real-time but imperfect filter during perceptual decision-making by dynamically modulating the contributions of task-relevant and irrelevant sensory inputs.
引用
收藏
页数:12
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