Attention improves the processing of specific information while other stimuli are disregarded. A good balance between bottom-up (attentional capture by unexpected salient stimuli) and top-down (selection of relevant information) mechanisms is crucial to be both task-efficient and aware of our environment. Only few studies have explored how an isolated unexpected task-irrelevant stimulus outside the attention focus can disturb the top-down attention mechanisms necessary to the good performance of the ongoing task, and how these top-down mechanisms can modulate the bottom-up mechanisms of attentional capture triggered by an unexpected event. We recorded scalp electroencephalography in 18 young adults performing a new paradigm measuring distractibility and assessing both bottom-up and top-down attention mechanisms, at the same time. Increasing task load in top-down attention was found to reduce early processing of the distracting sound, but not bottom-up attentional capture mechanisms nor the behavioral distraction cost in reaction time. Moreover, the impact of bottom-up attentional capture by distracting sounds on target processing was revealed as a delayed latency of the N100 sensory response to target sounds mirroring increased reaction times. These results provide crucial information into how bottom-up and top-down mechanisms dynamically interact and compete in the human brain, i.e. on the precarious balance between voluntary attention and distraction.

Event-related potentials (ERPs) associated with the involuntary orientation of (bottom-up) attention toward an unexpected sound are of larger amplitude in high dream recallers (HR) than in low dream recallers (LR) during passive listening, suggesting different attentional functioning. We measured bottom-up and top-down attentional performance and their cerebral correlates in 18 HR (11 women, age = 22.7 years, dream recall frequency = 5.3 days with a dream recall per week) and 19 LR (10 women, age = 22.3, DRF = 0.2) using EEG and the Competitive Attention Task. Between-group differences were found in ERPs but not in behavior. The results show that HR present larger ERPs to distracting sounds than LR even during active listening, arguing for enhanced bottom-up processing of irrelevant sounds. HR also presented larger contingent negative variation during target expectancy and P3b to target sounds than LR, speaking for an enhanced recruitment of top-down attention. The attentional balance seems preserved in HR since their performances are not altered, but possibly at a higher resource cost. In HR, increased bottom-up processes would favor dream recall through awakening facilitation during sleep and enhanced top-down processes may foster dream recall through increased awareness and/or short-term memory stability of dream content.

Taking other people’s interests into account is a fundamental ability allowing humans to maintain relationships. Yet, the mechanisms by which monetary incentives for close others influence perceptual decision-making processes remain elusive. Here, we compared perceptual decisions motivated by payoffs for oneself or a close relative. According to drift diffusion models (DDMs), perceptual decisions are made when sensory evidence accumulated over time – with a given drift rate – reaches one of the decision boundaries. We used these computational models to identify whether the drift rate of evidence accumulation or the decision boundary is affected by these two sources of motivation. Reaction times and sensitivity were modulated by three factors: the Difficulty (motion coherence of the moving dots), the Payoff associated with, and the Beneficiary of the decision. Reaction times (RTs) were faster for easy compared to difficult trials and faster for high payoffs as compared to low payoffs. More interestingly, RTs were also faster for self than for other-affecting decisions. Finally, using DDM, we found that these faster RTs were linked to a higher drift rate of the decision variable. This study offers a mechanistic understanding of how incentives for others and motion coherence influence decision-making processes.