Modulating Reward Induces Differential Neurocognitive Approaches to Sustained Attention

Abstract

Reward and motivation have powerful effects on cognition and brain activity, yet it remains unclear how they affect sustained cognitive performance. We have recently shown that a variety of motivators improve accuracy and reduce variability during sustained attention. In the current study, we investigate how neural activity in task-positive networks supports these sustained attention improvements. Participants performed the gradual-onset continuous performance task with alternating motivated (rewarded) and unmotivated (unrewarded) blocks. During motivated blocks, we observed increased sustained neural recruitment of task-positive regions, which interacted with fluctuations in task performance. Specifically, during motivated blocks, participants recruited these regions in preparation for upcoming targets, and this activation predicted accuracy. In contrast, during unmotivated blocks, no such advanced preparation was observed. Furthermore, during motivated blocks, participants had similar activation levels during both optimal (in-the-zone) and suboptimal (out-of-the-zone) epochs of performance. In contrast, during unmotivated blocks, task-positive regions were only engaged to a similar degree as motivated blocks during suboptimal (out-of-the-zone) periods. These data support a framework in which motivated individuals act as "cognitive investors," engaging task-positive resources proactively and consistently during sustaining attention. When unmotivated, however, the same individuals act as "cognitive misers," engaging maximal task-positive resources only during periods of struggle.

Keywords: dorsal attention network; motivation; reward; sustained attention; task-positive networks.

Published by Oxford University Press 2016.

Figures

Figure 1.

Overall effects of reward. (A) Commission error rate during rewarded versus unrewarded blocks. (B) Time spent out of the zone during rewarded versus unrewarded blocks. When rewarded, participants had a significantly lower lapse/CE rate and spent less time out of the zone (P< 0.001). Error bars represent standard error of the mean. (C) Overall sustained activation differences between rewarded and unrewarded bocks, when controlling for transient target-evoked activations (map displayed after correction for multiple comparisons: corrected P < 0.05; nominalP < 0.01, cluster size >78 voxels; see Table 1 for clusters).

Figure 2.

Interactions between reward and behavioral performance. (A) Event-related averages associated with successes (maroon) and lapses (blue) for target mountain trials during unrewarded and rewarded blocks. Time courses are expressed as percent signal change from the mean and were averaged across individuals and task-positive ROIs (see Supplementary Figure 1 for individual ROIs). Time points across each of the pre-trial windows (shaded) were averaged and extracted in panel “C”. (B) Event-related time courses associated with high (orange; out of the zone) and low (blue; in the zone) RT variability for non-target city trials during unrewarded and rewarded blocks (see Supplementary Figure 2 for individual ROIs). Time points across the city trial-evoked window (shaded) were averaged and extracted in panel “E”. (C) Pre-trial activation following success and lapse trials during rewarded and unrewarded blocks exhibiting a significant interaction between reward and accuracy on target mountain trials. (D) Mountain-evoked activations (β values), when controlling for sustained reward effects. (E) City trial-evoked activation when in and out of the zone during the rewarded and unrewarded blocks exhibiting a significant interaction between reward and state of variability (in vs. out of zone). Error bars represent standard error of the mean.

Figure 3.

Whole-brain fMRI analysis of reaction time variability/VTC-BOLD signal correlation for (A) unrewarded blocks; (B) rewarded blocks and (C) the contrast of reward and unrewarded VTC maps. For panels A and B, regions in orange were positively correlated with the VTC and thus were associated with relative instability of RTs (higher variability, out of the zone). Blue regions were associated with a negative VTC correlation and being in the zone. All maps are displayed after correction for multiple comparisons (correctedP < 0.05; nominal P < 0.01, cluster size >78 voxels; see Table 1 for clusters). (D) VTC β-values extracted for each task-positive network/ROI, reflecting coupling with variability with and without reward. Error bars represent standard error of the mean.