Physiological synchrony in EEG, electrodermal activity and heart rate reflects shared selective auditory attention

Stuldreher, Ivo V.; Thammasan, Nattapong; Erp, J.B.F. van; Brouwer, Anne-Marie

doi:10.1088/1741-2552/aba87d

Cited by 33 publications

(58 citation statements)

References 68 publications

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“…In the context of physiological or behavioral signals, this is often referred to as "interpersonal synchronization", and a variety of mechanisms have been hypothesized to be the sources of inter-subject correlation such as social interactions 1 , physical interactions 4,7,21 , shared emotions 9,11 , empathy 22,23 , shared arousal 4,24 , shared attention 25 , and more 1 . The diversity of explanations parallels the diversity of factors known to affect physiological signals.…”

Section: Introductionmentioning

confidence: 99%

Cognitive processing of a common stimulus synchronizes brains, hearts, and eyes

Madsen

Parra

2021

Preprint

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Neural, physiological and behavioral signals synchronize between human subjects in a variety of settings. Multiple hypotheses have been proposed to explain this interpersonal synchrony, but there is no clarity under which conditions it arises, for which signals, or whether there is a common underlying mechanism. We hypothesized that similar cognitive processing of a shared stimulus is the source of interpersonal synchrony, measured here as inter-subject correlation. To test this we presented informative videos to participants in an attentive and distracted condition and subsequently measured information recall. Inter-subject correlation was observed for electro-encephalography, gaze position, pupil size and heart rate, but not respiration and head movements. The strength of correlation was co-modulated in the different signals, changed with attentional state, and predicted subsequent recall of information presented in the videos. There was robust within-subject coupling between brain, heart and eyes, but not respiration or head movements. The results suggest that inter-subject correlation is the result of similar cognitive processing and thus emerges only for those signals that exhibit a robust brain-body connection. While physiological and behavioral fluctuations may be driven by multiple features of the stimulus, correlation with other individuals is co-modulated by the level of attentional engagement with the stimulus.

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Section: Introductionmentioning

confidence: 99%

Cognitive processing of a common stimulus synchronizes brains, hearts, and eyes

Madsen

Parra

2021

Preprint

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“…Neural PS was found to be directly proportional to attentional engagement, as strong correlations were found between PS and performance on questionnaires reflective of paid attention (Cohen and Parra, 2016;Cohen et al, 2018;Stuldreher et al, 2020). This directly proportional relationship may thus be used to circumvent supervised learning approaches and the problems that come with such approaches, such as the dependency on labeled training data.…”

Section: Introductionmentioning

confidence: 92%

“…Participants in the stimulus-attending group (SA) were instructed to focus their attention on the interspersed stimuli and ignore the audiobook. In a previous paper on this experiment (Stuldreher et al, 2020), we showed that PS can be used to correctly classify a listener as being instructed to attend to the audiobook or to the sounds. In the current paper, we use PS among individuals in the same group to predict the occurrence of interspersed stimuli over time, for each of the three physiological measures.…”

Section: Introductionmentioning

confidence: 97%

“…Positive results found in these contexts may (partly) be driven by shared attentional engagement to external events, as connectedness between people may be strongly associated with mutual attentiveness (Tickle-Degnen and Rosenthal, 1990). Recently, it was found that PS in EDA and heart rate can indeed reflect shared attention toward narrative stimuli (Pérez et al, 2020;Stuldreher et al, 2020).…”

Section: Introductionmentioning

confidence: 98%

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Physiological Synchrony in EEG, Electrodermal Activity and Heart Rate Detects Attentionally Relevant Events in Time

et al. 2020

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Interpersonal physiological synchrony (PS), or the similarity of physiological signals between individuals over time, may be used to detect attentionally engaging moments in time. We here investigated whether PS in the electroencephalogram (EEG), electrodermal activity (EDA), heart rate and a multimodal metric signals the occurrence of attentionally relevant events in time in two groups of participants. Both groups were presented with the same auditory stimulus, but were instructed to attend either to the narrative of an audiobook (audiobook-attending: AA group) or to interspersed emotional sounds and beeps (stimulus-attending: SA group). We hypothesized that emotional sounds could be detected in both groups as they are expected to draw attention involuntarily, in a bottom-up fashion. Indeed, we found this to be the case for PS in EDA or the multimodal metric. Beeps, that are expected to be only relevant due to specific “top-down” attentional instructions, could indeed only be detected using PS among SA participants, for EDA, EEG and the multimodal metric. We further hypothesized that moments in the audiobook accompanied by high PS in either EEG, EDA, heart rate or the multimodal metric for AA participants would be rated as more engaging by an independent group of participants compared to moments corresponding to low PS. This hypothesis was not supported. Our results show that PS can support the detection of attentionally engaging events over time. Currently, the relation between PS and engagement is only established for well-defined, interspersed stimuli, whereas the relation between PS and a more abstract self-reported metric of engagement over time has not been established. As the relation between PS and engagement is dependent on event type and physiological measure, we suggest to choose a measure matching with the stimulus of interest. When the stimulus type is unknown, a multimodal metric is most robust.

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“…The latter may range from indicating where a meeting's attendee is gazing at, to monitoring shared attention through interindividual synchrony in heart rate as recorded through the webcam (cf. Stuldreher et al, 2020). In the context of evaluating consumers' mental state when interacting with systems or products, Consumer Neuroergonomics is especially relevant when mental state is studied over the course of interaction and repeated questioning would influence the mental state of interest itself (Ayaz et al, 2012;Shewokis et al, 2017;Brouwer et al, 2019), or when systematic response biases are expected, e.g., because consumers under study systematically differ in cultural background (Torrico et al, 2018(Torrico et al, , 2019Kaneko et al, in press).…”

Section: Challengesmentioning

confidence: 99%