ArticleCerebral cortex (New York, N.Y. : 1991)2021
Brain Knows Who Is on the Same Wavelength: Resting-State Connectivity Can Predict Compatibility of a Female-Male Relationship.
Article in Cerebral cortex (New York, N.Y. : 1991), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Predicting conversational satisfaction of face-to-face conversation through interpersonal similarity in resting-state functional connectivity.Scientific reports · 2024Article
- Frequency-specific brain network architecture in resting-state fMRI.Scientific reports · 2023Article
- Neural Processing of Facial Attractiveness and Romantic Love: An Overview and Suggestions for Future Empirical Studies.Frontiers in psychology · 2022Review
- The Brain Understands Social Relationships: The Emerging Field of Functional-Connectome-Based Interpersonal Research.Neuroscience insights · 2022Article
Corrections and comments
- Commented on by
- Erratum issued
Authors and funding
3 authors.
Funding
Abstract
Prediction of the initial compatibility of heterosexual individuals based on self-reported traits and preferences has not been successful, even with significantly developed information technology. To overcome the limitations of self-reported measures and predict compatibility, we used functional connectivity profiles from resting-state functional magnetic resonance imaging (fMRI) data that carry rich individual-specific information sufficient to predict psychological constructs and activation patterns during social cognitive tasks. Several days after collecting data from resting-state fMRIs, participants undertook a speed-dating experiment in which they had a 3-min speed date with every other opposite-sex participant. Our machine learning algorithm successfully predicted whether pairs in the experiment were compatible or not using (dis)similarity of functional connectivity profiles obtained before the experiment. The similarity and dissimilarity of functional connectivity between individuals and these multivariate relationships contributed to the prediction, hence suggesting the importance of complementarity (observed as dissimilarity) as well as the similarity between an individual and a potential partner during the initial attraction phase. The result indicates that the salience network, limbic areas, and cerebellum are especially important for the feeling of compatibility. This research emphasizes the utility of neural information to predict complex phenomena in a social environment that behavioral measures alone cannot predict.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.