Abstract
Previously learned reward values can have a pronounced impact, behaviorally and neurophysiologically, on the allocation of selective attention. All else constant, stimuli previously associated with a high value gain stronger attentional prioritization than stimuli previously associated with a low value. The N2pc, an ERP component indicative of attentional target selection, has been shown to reflect aspects of this prioritization, by changes of mean amplitudes closely corresponding to selective enhancement of high value target processing and suppression of high value distractor processing. What has remained unclear so far is whether the N2pc also reflects the flexible and repeated behavioral adjustments needed in a volatile task environment, in which the values of stimuli are reversed often and unannounced. Using a value-based reversal learning task, we found evidence that the N2pc amplitude flexibly and reversibly tracks value-based choices during the learning of reward associated stimulus colors. Specifically, successful learning of current value-contingencies was associated with reduced N2pc amplitudes, and this effect was more apparent for distractor processing, compared with target processing. In addition, following a value reversal the feedback related negativity(FRN), an ERP component that reflects feedback processing, was amplified and co-occurred with increased N2pc amplitudes in trials following low-value feedback. Importantly, participants that showed the greatest adjustment in N2pc amplitudes based on feedback were also the most efficient learners. These results allow further insight into how changes in attentional prioritization in an uncertain and volatile environment support flexible adjustments of behavior.
Highlights
Visual selective attention allows the prioritization of task-relevant over irrelevant stimuli in the visual field
Since participants used trial-by-trial feedback to evaluate choices, we examined feedback-related differences to the N2pc and learning-related differences to frontal feedback related negativity (FRN), which has previously been shown to change during reversal learning and has been suggested to encode prediction error signals and behavioral adjustments (e.g., Cohen and Ranganath, 2007; Chase et al, 2011; Walsh and Anderson, 2011)
Participants performed the task very well and generally showed quick increases in the proportion of high value choices following a value reversal (Figures 2B, 3Ai,Bi), in line with the behavioral assumptions (Figure 1A). This is further shown in the distribution of block lengths observed across all participants, whereby the majority of blocks had a length of approximately 25 trials, indicating a performance of 80% high value choices around the time trial 25 was reached (Figure 3Aii, note that blocks shorter than 25 trials were possible following the rejection of incorrect responses, see ‘‘Materials and Methods’’ section)
Summary
Visual selective attention allows the prioritization of task-relevant over irrelevant stimuli in the visual field. In recent years it has become evident that this dichotomy does not suffice to explain all instances in which a stimulus, or a set of stimuli, become the target of attentional priority (Awh et al, 2012; Anderson, 2013; Womelsdorf and Everling, 2015). Previously learned reward value has been shown to be a strong modulator of attentional prioritization (e.g., Della Libera and Chelazzi, 2009; Krebs et al, 2010; Anderson et al, 2011b, 2013, 2014; Della Libera et al, 2011; Hickey et al, 2011, 2015; Sali et al, 2014; Bucker and Theeuwes, 2017). Non-salient and task-irrelevant distractors that have previously been associated with reward can capture attention involuntarily and cause slower reaction times (RTs) in classical visual search tasks, and this is modulated by reward level, such that the higher the previously-associated reward, the greater the subsequent capture (e.g., Anderson et al, 2011b, 2013; Munneke et al, 2015)
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