Abstract
The distribution of attention between competing processing demands can have dramatic real-world consequences, however little is known about how limited attentional resources are distributed during real-world behaviour. Here we employ mobile EEG to characterise the allocation of attention across multiple sensory-cognitive processing demands during naturalistic movement. We used a neural marker of attention, the Event-Related Potential (ERP) P300 effect, to show that attention to targets is reduced when human participants walk compared to when they stand still. In a second experiment, we show that this reduction in attention is not caused by the act of walking per se. A third experiment identified the independent processing demands driving reduced attention to target stimuli during motion. ERP data reveals that the reduction in attention seen during walking reflects the linear and additive sum of the processing demands produced by visual and inertial stimulation. The mobile cognition approach used here shows how limited resources are precisely re-allocated according to the sensory processing demands that occur during real-world behaviour.
Highlights
The distribution of attention between competing processing demands can have dramatic real-world consequences, little is known about how limited attentional resources are distributed during real-world behaviour
The findings presented below come from three independent experiments (N = 11; 24; 24 respectively), all involving the recording of P300 Event-Related Potential (ERP) effects during performance of the same auditory oddball task
In an initial experiment we showed that attention allocated to the detection of infrequent target stimuli was reduced when human participants walk through a hallway compared to when they stand still
Summary
The distribution of attention between competing processing demands can have dramatic real-world consequences, little is known about how limited attentional resources are distributed during real-world behaviour. The mobile brain imaging approach allows questions to be asked that cannot be examined using laboratory experiments (e.g., the effects that changes in context have on episodic memory retrieval12), and www.nature.com/scientificreports has the potential to reveal embodied aspects of human cognitive experience that could not be captured within the framework of traditional laboratory settings[5,13] Applying this mobile brain imaging approach brings methodological challenges related to data acquisition (reliability and consistency of mobile recordings), processing (disentangling brain signals from artifactual sources) and interpretation (integration of multimodal data collected in complex environments) that differ from the challenges inherent to traditional laboratory studies. The current studies demonstrate that such difficulties can be overcome
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