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Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
Published on: October 24, 2012
Physiological synchrony in EEG, electrodermal activity and heart rate reflects shared selective auditory attention
Ivo V Stuldreher1, Nattapong Thammasan, Jan B F van Erp
1Perceptual and Cognitive Systems, Netherlands Organisation for Applied Scientific Research (TNO), Soesterberg, The Netherlands. Human Media Interaction, University of Twente, Enschede, The Netherlands.
Objective:
Concurrent changes in physiological signals across multiple listeners (physiological synchrony-PS), as caused by shared affective or cognitive processes, may be a suitable marker of selective attentional focus. We aimed to identify the selective attention of participants based on PS with individuals sharing attention with respect to different stimulus aspects.
Approach:
We determined PS in electroencephalography (EEG), electrodermal activity (EDA) and electrocardiographic inter-beat interval (IBI) of participants who all heard the exact same audio track, but were instructed to either attend to the audiobook or to interspersed auditory events such as affective sounds and beeps that attending participants needed to keep track of.
Main Results:
PS in all three measures reflected the selective attentional focus of participants. In EEG and EDA, PS was higher for participants when linked to participants with the same attentional instructions than when linked to participants instructed to focus on different stimulus aspects, but in IBI this effect did not reach significance. Comparing PS between a participant and members from the same or the different attentional group allowed for the correct identification of the participant's attentional instruction in 96%, 73% and 73% of the cases, for EEG, EDA and IBI, respectively, all well above chance level. PS with respect to the attentional groups also predicted performance on post-audio questions about the groups' stimulus content.
Significance:
Our results show that selective attention of participants can be monitored using PS, not only in EEG, but also in EDA and IBI. These results are promising for real-world applications, where wearables measuring peripheral signals like EDA and IBI may be preferred over EEG sensors.
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