Joint Attention During Live Person-to-Person Contact Activates rTPJ, Including a Sub-Component Associated With Spontaneous Eye-to-Eye Contact

Dravida, Swethasri; Noah, J. Adam; Zhang, Xian; Hirsch, Joy

doi:10.3389/fnhum.2020.00201

Cited by 31 publications

(47 citation statements)

References 78 publications

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“…These regions were consistent with expectations of canonical models of human language systems (Gabrieli et al, 1998;Binder et al, 2000;Price, 2012;Hagoort, 2014;Poeppel, 2014). Similar comparisons have led to the use of deOxyHb signals in prior fNIRS investigations of overt speaking (Zhang et al, 2017;Hirsch et al, 2018;Descorbeth et al, 2020); eye-to-eye contact (Hirsch et al, 2017); competitive games (Piva et al, 2017); dyadic communication via interactive drumming (Rojiani et al, 2018); and joint attention (Dravida et al, 2020).…”

Section: Signal Validation and Regions Of Interest (Roi)supporting

confidence: 81%

Interpersonal Agreement and Disagreement During Face-to-Face Dialogue: An fNIRS Investigation

Hirsch

Tiede

Zhang

et al. 2021

Front. Hum. Neurosci.

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Although the neural systems that underlie spoken language are well-known, how they adapt to evolving social cues during natural conversations remains an unanswered question. In this work we investigate the neural correlates of face-to-face conversations between two individuals using functional near infrared spectroscopy (fNIRS) and acoustical analyses of concurrent audio recordings. Nineteen pairs of healthy adults engaged in live discussions on two controversial topics where their opinions were either in agreement or disagreement. Participants were matched according to their a priori opinions on these topics as assessed by questionnaire. Acoustic measures of the recorded speech including the fundamental frequency range, median fundamental frequency, syllable rate, and acoustic energy were elevated during disagreement relative to agreement. Consistent with both the a priori opinion ratings and the acoustic findings, neural activity associated with long-range functional networks, rather than the canonical language areas, was also differentiated by the two conditions. Specifically, the frontoparietal system including bilateral dorsolateral prefrontal cortex, left supramarginal gyrus, angular gyrus, and superior temporal gyrus showed increased activity while talking during disagreement. In contrast, talking during agreement was characterized by increased activity in a social and attention network including right supramarginal gyrus, bilateral frontal eye-fields, and left frontopolar regions. Further, these social and visual attention networks were more synchronous across brains during agreement than disagreement. Rather than localized modulation of the canonical language system, these findings are most consistent with a model of distributed and adaptive language-related processes including cross-brain neural coupling that serves dynamic verbal exchanges.

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Section: Signal Validation and Regions Of Interest (Roi)supporting

confidence: 81%

Interpersonal Agreement and Disagreement During Face-to-Face Dialogue: An fNIRS Investigation

Hirsch

Tiede

Zhang

et al. 2021

Front. Hum. Neurosci.

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“…For instance, eye-contact has been shown to be associated with increased activity in the rTPJ compared to looking at a video of a dynamic face 14 . An increase in interbrain rTPJ coupling was also found by a study 12 looking at eye-contact during live interactions. While we cannot know the precise neural sources of this effect due to our limited spatial resolution, we can generate predictions regarding the dynamics of the interactions based roughly on the locations of these areas on the scalp and the previous literature on eye-contact and social interactions.…”

Section: Discussionsupporting

confidence: 64%

“…Research has made remarkable progress towards understanding how eye-contact is processed in a single (perceiver's) brain, but eyecontact is an interactive process between two people. More recently, we have begun to extend this understanding to multiple brains -for example, the synchronization of activity between two brains has been found to increase during eye-contact [12][13][14] . However, we still do not know how both intra and inter brain activity is integrated, nor the functional role of this synchronised activity.…”

Section: Introductionmentioning

confidence: 99%

Social synchronisation of brain activity by eye-contact

Luft

Zioga²,

Giannopoulos

et al. 2021

Preprint

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Humans make eye-contact to extract information about other people’s mental states, recruiting dedicated brain networks that process information about the self and others. Recent studies show that eye-contact increases the synchronization between two brains. We investigated how eye-contact affects the frequency and direction of the synchronization within and between brains and the characteristics of the dual brain network (i.e. hyperbrain). Eye-contact was associated with higher coherence in the gamma frequency band (30-45Hz) for between and within brain connections. Network analysis revealed that some brain areas served as hubs which linked within- and between- brain networks (midparietal, midfrontal and right parietal areas). Friends showed more efficient eye-contact hyperbrain networks than strangers. During eye-contact, some dyads spontaneously adopted leader/follower roles, resulting in an increase in synchronization from leader to follower (interbrain) in the alpha frequency band. Eye-contact affected directed and undirected synchronization between brains more than within brains, offering support to the interactive brain hypothesis.

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“…Functional NIRS signal acquisition, optode localization, and signal processing, including global mean removal, were similar to methods described previously (Dravida et al, 2018;Dravida et al, 2020;Hirsch et al, 2017;Noah et al, 2015;Noah et al, 2020;Piva et al, 2017;Zhang et al, 2016;Zhang et al, 2017) and are summarized below. Hemodynamic signals were acquired using an 80-fiber multichannel, continuous-wave fNIRS system (LABNIRS, Shimadzu Corporation, Kyoto, Japan).…”

Section: Fnirs Data Acquisition Signal Processing and Data Analysismentioning

confidence: 99%

“…The right temporoparietal junction (rTPJ) was chosen as it is a processing hub for social cognition (Carter & Huettel, 2013) which is believed to be involved in reasoning about the internal mental state of others, referred to as theory of mind (ToM) (Molenberghs et al, 2016;Premack and Woodruff, 1978;Saxe and Kanwisher, 2003;Saxe, 2010). Not only has past research shown that the rTPJ is involved in explicit ToM (Sommer et al, 2007;Aichhorn et al, 2008), it is also spontaneously engaged during tasks with implicit ToM implications (Molenberghs et al, 2016;Dravida et al, 2020;Richardson and Saxe, 2020). It is active during direct human eye-to-eye contact at a level much higher than that found during human picture or video eye-contact (Hirsch et al, 2017;Noah et al, 2020).…”

Section: Introductionmentioning

confidence: 97%

Comparison of Human Social Brain Activity During Eye-Contact With Another Human and a Humanoid Robot

et al. 2021

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Robot design to simulate interpersonal social interaction is an active area of research with applications in therapy and companionship. Neural responses to eye-to-eye contact in humans have recently been employed to determine the neural systems that are active during social interactions. Whether eye-contact with a social robot engages the same neural system remains to be seen. Here, we employ a similar approach to compare human-human and human-robot social interactions. We assume that if human-human and human-robot eye-contact elicit similar neural activity in the human, then the perceptual and cognitive processing is also the same for human and robot. That is, the robot is processed similar to the human. However, if neural effects are different, then perceptual and cognitive processing is assumed to be different. In this study neural activity was compared for human-to-human and human-to-robot conditions using near infrared spectroscopy for neural imaging, and a robot (Maki) with eyes that blink and move right and left. Eye-contact was confirmed by eye-tracking for both conditions. Increased neural activity was observed in human social systems including the right temporal parietal junction and the dorsolateral prefrontal cortex during human-human eye contact but not human-robot eye-contact. This suggests that the type of human-robot eye-contact used here is not sufficient to engage the right temporoparietal junction in the human. This study establishes a foundation for future research into human-robot eye-contact to determine how elements of robot design and behavior impact human social processing within this type of interaction and may offer a method for capturing difficult to quantify components of human-robot interaction, such as social engagement.

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Joint Attention During Live Person-to-Person Contact Activates rTPJ, Including a Sub-Component Associated With Spontaneous Eye-to-Eye Contact

Cited by 31 publications

References 78 publications

Interpersonal Agreement and Disagreement During Face-to-Face Dialogue: An fNIRS Investigation

Interpersonal Agreement and Disagreement During Face-to-Face Dialogue: An fNIRS Investigation

Social synchronisation of brain activity by eye-contact

Comparison of Human Social Brain Activity During Eye-Contact With Another Human and a Humanoid Robot

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