Title |
A new methodical approach in neuroscience: assessing inter-personal brain coupling using functional near-infrared imaging (fNIRI) hyperscanning
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Published in |
Frontiers in Human Neuroscience, January 2013
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DOI | 10.3389/fnhum.2013.00813 |
Pubmed ID | |
Authors |
Felix Scholkmann, Lisa Holper, Ursula Wolf, Martin Wolf |
Abstract |
Since the first demonstration of how to simultaneously measure brain activity using functional magnetic resonance imaging (fMRI) on two subjects about 10 years ago, a new paradigm in neuroscience is emerging: measuring brain activity from two or more people simultaneously, termed "hyperscanning". The hyperscanning approach has the potential to reveal inter-personal brain mechanisms underlying interaction-mediated brain-to-brain coupling. These mechanisms are engaged during real social interactions, and cannot be captured using single-subject recordings. In particular, functional near-infrared imaging (fNIRI) hyperscanning is a promising new method, offering a cost-effective, easy to apply and reliable technology to measure inter-personal interactions in a natural context. In this short review we report on fNIRI hyperscanning studies published so far and summarize opportunities and challenges for future studies. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Canada | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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France | 2 | <1% |
United States | 2 | <1% |
Netherlands | 1 | <1% |
Germany | 1 | <1% |
Czechia | 1 | <1% |
Italy | 1 | <1% |
Spain | 1 | <1% |
United Kingdom | 1 | <1% |
Unknown | 266 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 57 | 21% |
Researcher | 45 | 16% |
Student > Master | 40 | 14% |
Student > Bachelor | 20 | 7% |
Student > Doctoral Student | 16 | 6% |
Other | 40 | 14% |
Unknown | 58 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 80 | 29% |
Neuroscience | 43 | 16% |
Engineering | 17 | 6% |
Computer Science | 16 | 6% |
Agricultural and Biological Sciences | 8 | 3% |
Other | 38 | 14% |
Unknown | 74 | 27% |