Social interaction and communication are fundamental human functions and are conserved across cultures and other mammalian species. Yet little is known about the underlying neural dynamics that drive these behaviors. Conventional functional imaging studies using fMRI and PET that investigate the neural underpinnings of spoken language have generally been limited to investigations of single subjects and non-interactive paradigms. Thus, questions of the neural mechanisms specialized for interpersonal exchanges remain understudied. The motivating hypothesis for this investigation is that interpersonal dialogue between two individuals engages a neural complex that extends beyond the functional specializations of Broca's and Wernicke's Areas known as the canonical language system and serves as a paradigm to investigate social behavior in real-time paradigms. Specifically, we hypothesize that a neural complex specialized for multi-agent interpersonal communication incorporates synchronizing information shared between the partners (transmission), using meaningful visual and auditory input cues (reception), and integrates functions that guide turn-taking behavior (regulation) between speakers. Near-infrared spectroscopy (NIRS) provides a non- invasive imaging technique that acquires the Blood Oxygen Level Dependent (BOLD) signals using absorbance spectra, and is suitable for the study of brain function in pairs of behaving subjects which is enabled by the use of portable and wearable optodes located on the surface of the head. We propose to use fNIRS and interacting pairs of subjects to compare neural responses during monologue, dialogue, and simultaneous recitation conditions, as well as face-to-face and occluded conditions that systematically limit visual and auditory input. Computational approaches will be based on coherence measures determined by wavelet analyses between homologous regions of the two interacting brains as evidence for the neural response to social engagement and of the associated underlying neural circuitry. We anticipate that dialogue tasks will activate the canonical language system more than monologue tasks, as well as additional social brain systems that receive facial information and are associated with regulatory and control functions. For example, these areas may include fusiform gyrus (interpretation of facial information) and dorsal lateral prefrontal cortex (regulation and control of neural events) respectively. Findings will provide the basis for a transceiver model of human communication including the neural underpinnings of a transmitter (speech production), a receiver (visual and auditory input), and a regulator (control of turn-taking in a conversation).
The aims of this proposal are intended to provide a foundation that enables extended studies of inter-brain synchronization during social behavior and interpersonal communication in socially-healthy individuals that can be applied to social disorders in subsequent studies.

Public Health Relevance

Social behavior is a basic aspect of human interpersonal communication; however, the neural mechanisms that underlie the interaction between two subjects who are communicating in real time are not well understood. This study aims to understand the neural mechanisms that underlie synchronization of two brains during social interactions by applying wavelet analysis to signals acquired simultaneously from multiple homologous brain regions in pairs of speakers and responders. Functional near-infrared spectroscopy, fNIRS, a neural imaging technology that enables acquisition of brain responses in natural interacting situations is used to test hypotheses related to neural systems specialized for social behavior including reception, transmission, and control mechanisms.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
1R01MH107513-01
Application #
8943261
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Simmons, Janine M
Project Start
2015-09-01
Project End
2020-05-31
Budget Start
2015-09-01
Budget End
2016-05-31
Support Year
1
Fiscal Year
2015
Total Cost
Indirect Cost
Name
Yale University
Department
Psychiatry
Type
Schools of Medicine
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code
Dravida, Swethasri; Noah, Jack Adam; Zhang, Xian et al. (2018) Comparison of oxyhemoglobin and deoxyhemoglobin signal reliability with and without global mean removal for digit manipulation motor tasks. Neurophotonics 5:011006
Hirsch, Joy; Adam Noah, J; Zhang, Xian et al. (2018) A cross-brain neural mechanism for human-to-human verbal communication. Soc Cogn Affect Neurosci 13:907-920
Pinti, Paola; Tachtsidis, Ilias; Hamilton, Antonia et al. (2018) The present and future use of functional near-infrared spectroscopy (fNIRS) for cognitive neuroscience. Ann N Y Acad Sci :
Rojiani, Rahil; Zhang, Xian; Noah, Adam et al. (2018) Communication of emotion via drumming: dual-brain imaging with functional near-infrared spectroscopy. Soc Cogn Affect Neurosci 13:1047-1057
Noah, J Adam; Dravida, Swethasri; Zhang, Xian et al. (2017) Neural correlates of conflict between gestures and words: A domain-specific role for a temporal-parietal complex. PLoS One 12:e0173525
Lapborisuth, Pawan; Zhang, Xian; Noah, Adam et al. (2017) Neurofeedback-based functional near-infrared spectroscopy upregulates motor cortex activity in imagined motor tasks. Neurophotonics 4:021107
Zhang, Xian; Noah, Jack Adam; Dravida, Swethasri et al. (2017) Signal processing of functional NIRS data acquired during overt speaking. Neurophotonics 4:041409
Hirsch, Joy; Zhang, Xian; Noah, J Adam et al. (2017) Frontal temporal and parietal systems synchronize within and across brains during live eye-to-eye contact. Neuroimage 157:314-330
Piva, Matthew; Zhang, Xian; Noah, J Adam et al. (2017) Distributed Neural Activity Patterns during Human-to-Human Competition. Front Hum Neurosci 11:571
Zhang, Xian; Noah, Jack Adam; Hirsch, Joy (2016) Separation of the global and local components in functional near-infrared spectroscopy signals using principal component spatial filtering. Neurophotonics 3:015004

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