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Dieffenbach MC, Gillespie GSR, Burns SM, McCulloh IA, Ames DL, Dagher MM, Falk EB, Lieberman MD. Neural reference groups: a synchrony-based classification approach for predicting attitudes using fNIRS. Soc Cogn Affect Neurosci 2021; 16:117-128. [PMID: 33025001 PMCID: PMC7812626 DOI: 10.1093/scan/nsaa115] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Revised: 06/19/2020] [Accepted: 09/29/2020] [Indexed: 12/13/2022] Open
Abstract
Social neuroscience research has demonstrated that those who are like-minded are also 'like-brained.' Studies have shown that people who share similar viewpoints have greater neural synchrony with one another, and less synchrony with people who 'see things differently.' Although these effects have been demonstrated at the 'group level,' little work has been done to predict the viewpoints of specific 'individuals' using neural synchrony measures. Furthermore, the studies that have made predictions using synchrony-based classification at the individual level used expensive and immobile neuroimaging equipment (e.g. functional magnetic resonance imaging) in highly controlled laboratory settings, which may not generalize to real-world contexts. Thus, this study uses a simple synchrony-based classification method, which we refer to as the 'neural reference groups' approach, to predict individuals' dispositional attitudes from data collected in a mobile 'pop-up neuroscience' lab. Using functional near-infrared spectroscopy data, we predicted individuals' partisan stances on a sociopolitical issue by comparing their neural timecourses to data from two partisan neural reference groups. We found that partisan stance could be identified at above-chance levels using data from dorsomedial prefrontal cortex. These results indicate that the neural reference groups approach can be used to investigate naturally occurring, dispositional differences anywhere in the world.
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Affiliation(s)
- Macrina C Dieffenbach
- Annenberg School of Communication, University of Pennsylvania, Philadelphia, Philadelphia, PA 19104, USA
| | - Grace S R Gillespie
- Annenberg School of Communication, University of Pennsylvania, Philadelphia, Philadelphia, PA 19104, USA
| | - Shannon M Burns
- Annenberg School of Communication, University of Pennsylvania, Philadelphia, Philadelphia, PA 19104, USA
| | - Ian A McCulloh
- Accenture Federal Services, 800 N Glebe Rd, Arlington, VA 22203
| | - Daniel L Ames
- Annenberg School of Communication, University of Pennsylvania, Philadelphia, Philadelphia, PA 19104, USA
| | - Munqith M Dagher
- Independent Institute & Administration Civil Society Studies (IIACSS) Research Group, Al Hussam Center 2 270 Arar Mustafa Wahbii Al Tal, Amman, Jordan
| | - Emily B Falk
- Annenberg School of Communication, University of Pennsylvania, Philadelphia, PA 19104, USA, Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104, USA, Wharton Marketing Department, University of Pennsylvania, Philadelphia, PA 19104, USA, University of Pennsylvania
| | - Matthew D Lieberman
- Annenberg School of Communication, University of Pennsylvania, Philadelphia, Philadelphia, PA 19104, USA
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