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19 - Multivariate Neuroimaging in Social and Personality Psychology

from Part III - Deep Dives on Methods and Tools for Testing Your Question of Interest

Published online by Cambridge University Press:  12 December 2024

By
Robert S. Chavez ,
William A. Cunningham  and
Elliot T. Berkman
Edited by
Harry T. Reis ,
Tessa West  and
Charles M. Judd
Harry T. Reis
Affiliation:
University of Rochester, New York
Tessa West
Affiliation:
New York University
Charles M. Judd
Affiliation:
University of Colorado Boulder
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Summary

Methodological approaches in social neuroscience have been rapidly evolving in recent years. Fueling these changes is the adoption of a variety of multivariate approaches that allow researchers to ask a wider and richer set of questions than was previously possible with standard univariate methods. In this chapter, we introduce several of the most popular multivariate methods and discuss how they can be used to advance our understanding of how social cognition and personality processes are represented in the brain. These methods have the potential to allow neuroscience measures to inform and advance theories in social and personality psychology more directly and are likely to become the dominant approaches in social neuroscience in the near future.

Keywords

social neurosciencemultivariate pattern analysisneuroimagingsocial cognitionindividual differences
Type
Chapter
Information
Handbook of Research Methods in Social and Personality Psychology , pp. 453 - 468
Publisher: Cambridge University Press
Print publication year: 2024

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References

Berkman, E. T., Cunningham, W. A., and Lieberman, M. D. (2014). Research methods in social and affective neuroscience. In Reis, H. T. and Judd, C. M. (eds.) Handbook of Research Methods in Social and Personality Psychology, 2nd ed. Cambridge University Press.Google Scholar
Cacioppo, J. T., and Berntson, G. G. (1992). Social psychological contributions to the decade of the brain. Doctrine of multilevel analysis. American Psychologist, 47(8), 1019–1028.CrossRefGoogle Scholar
Cacioppo, J. T., Berntson, G. G., Lorig, T. S., Norris, C. J., Rickett, E., and Nusbaum, H. (2003). Just because you’re imaging the brain doesn’t mean you can stop using your head: A primer and set of first principles. Journal of Personality and Social Psychology, 85(4), 650–661.CrossRefGoogle Scholar
Cacioppo, S., Bolmont, M., and Monteleone, G. (2018). Spatio-temporal dynamics of the mirror neuron system during social intentions. Social Neuroscience, 13(6), 718–738.CrossRefGoogle ScholarPubMed
Cacioppo, S., Weiss, R. M., Runesha, H. B., and Cacioppo, J. T. (2014). Dynamic spatiotemporal brain analyses using high performance electrical neuroimaging: Theoretical framework and validation. Journal of Neuroscience Methods, 238, 11–34.CrossRefGoogle ScholarPubMed
Chang, L. J., Gianaros, P. J., Manuck, S. B., Krishnan, A., and Wager, T. D. (2015). A sensitive and specific neural signature for picture-induced negative affect. PLOS Biology, 13(6), e1002180.CrossRefGoogle ScholarPubMed
Chavez, R. S. (2021). Tangled representations of self and others in the medial prefrontal cortex. In Gilead, M. and Ochsner, K. N. (eds.) The Neural Basis of Mentalizing. Springer International Publishing.Google Scholar
Chavez, R. S., Tovar, D. T., Stendel, M. S., and Guthrie, T. D. (2022). Generalizing effects of frontostriatal structural connectivity on self-esteem using predictive modeling. Cortex, 146, 66–73.CrossRefGoogle ScholarPubMed
Coutanche, M. N., and Thompson-Schill, S. L. (2012). The advantage of brief fMRI acquisition runs for multi-voxel pattern detection across runs. Neuroimage, 61(4), 1113–1119.CrossRefGoogle ScholarPubMed
Davis, K. D., Aghaeepour, N., Ahn, A. H., Angst, M. S., Borsook, D., Brenton, A., Burczynski, M. E., Crean, C., Edwards, R., Gaudilliere, B., Hergenroeder, G. W., Iadarola, M. J., Iyengar, S., Jiang, Y., Kong, J.-T., Mackey, S., Saab, C. Y., Sang, C. N., Scholz, J., … Pelleymounter, M. A. (2020). Discovery and validation of biomarkers to aid the development of safe and effective pain therapeutics: Challenges and opportunities. Nature Reviews Neurology, 16(7), 381–400.CrossRefGoogle ScholarPubMed
Denny, B. T., Kober, H., Wager, T. D., and Ochsner, K. N. (2012). A meta-analysis of functional neuroimaging studies of self- and other judgments reveals a spatial gradient for mentalizing in medial prefrontal cortex. Journal of Cognitive Neuroscience, 24(8), 1742–1752.CrossRefGoogle ScholarPubMed
Duchaine, B., and Yovel, G. (2015). A revised neural framework for face processing. Annual Review of Vision Science, 1(1), 393–416.CrossRefGoogle ScholarPubMed
Eger, E., Michel, V., Thirion, B., Amadon, A., Dehaene, S., and Kleinschmidt, A. (2009). Deciphering cortical number coding from human brain activity patterns. Current Biology, 19(19), 1608–1615.CrossRefGoogle ScholarPubMed
Eisenberger, N. I., Lieberman, M. D., and Williams, K. D. (2003). Does rejection hurt? An fMRI study of social exclusion. Science, 302(5643), 290–292.CrossRefGoogle ScholarPubMed
Guthrie, T. D., Benadjaoud, Y. Y., and Chavez, R. S. (2022). Social relationship strength modulates the similarity of brain-to-brain representations of group members. Cerebral Cortex, 32(11), 2469–2477.CrossRefGoogle ScholarPubMed
Hassabis, D., Spreng, R. N., Rusu, A. a, Robbins, C. A., Mar, R. A., and Schacter, D. L. (2014). Imagine all the people: How the brain creates and uses personality models to predict behavior. Cerebral Cortex, 24(8), 1979–1987.CrossRefGoogle ScholarPubMed
Haxby, J. V. (2012). Multivariate pattern analysis of fMRI: The early beginnings. Neuroimage, 62(2), 852–855.CrossRefGoogle ScholarPubMed
Haxby, J. V., Gobbini, M. I., Furey, M. L., Ishai, A., Schouten, J. L., and Pietrini, P. (2001). Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science, 293(5539), 2425–2430.CrossRefGoogle ScholarPubMed
Hundrieser, M., Mattes, A., and Stahl, J. (2021). Predicting participants’ attitudes from patterns of event-related potentials during the reading of morally relevant statements: An MVPA investigation. Neuropsychologia, 153, 107768.CrossRefGoogle ScholarPubMed
Jimura, K., and Poldrack, R. A. (2012). Analyses of regional-average activation and multivoxel pattern information tell complementary stories. Neuropsychologia, 50(4), 544–552.CrossRefGoogle ScholarPubMed
Jolly, E., and Chang, L. J. (2021). Multivariate spatial feature selection in fMRI. Social Cognitive and Affective Neuroscience, 16(8), 795–806.CrossRefGoogle ScholarPubMed
Kanwisher, N., McDermott, J., and Chun, M. M. (1997). The fusiform face area: A module in human extrastriate cortex specialized for face perception. Journal of Neuroscience, 17(11), 4302–4311.CrossRefGoogle ScholarPubMed
Kenny, D. A., and Albright, L. (1987). Accuracy in interpersonal perception: A social relations analysis. Psychological Bulletin, 102(3), 390–402.CrossRefGoogle ScholarPubMed
Kragel, P. A., Koban, L., Barrett, L. F., and Wager, T. D. (2018). Representation, pattern information, and brain signatures: From neurons to neuroimaging. Neuron, 99(2), 257–273.CrossRefGoogle ScholarPubMed
Kriegeskorte, N., Mur, M., and Bandettini, P. (2008). Representational similarity analysis: Connecting the branches of systems neuroscience. Frontiers in Systems Neuroscience, 2, 4, 1–28.Google ScholarPubMed
Kriegeskorte, N., Mur, M., Ruff, D. A., Kiani, R., Bodurka, J., Esteky, H., Tanaka, K., and Bandettini, P. A. (2008). Matching categorical object representations in inferior temporal cortex of man and monkey. Neuron, 60(6), 1126–1141.CrossRefGoogle ScholarPubMed
McIntosh, A. R. (1998). Understanding neural interactions in learning and memory using functional neuroimaging. Annals of the New York Academy of Sciences, 855(1), 556–571.CrossRefGoogle ScholarPubMed
McIntosh, A. R., Bookstein, F. L., Haxby, J. V., and Grady, C. L. (1996). Spatial pattern analysis of functional brain images using partial least squares. NeuroImage, 3(3), 143–157.CrossRefGoogle ScholarPubMed
Mumford, J. A., Davis, T., and Poldrack, R. A. (2014). The impact of study design on pattern estimation for single-trial multivariate pattern analysis. NeuroImage, 103, 130–138.CrossRefGoogle ScholarPubMed
Parkinson, C., Kleinbaum, A. M., and Wheatley, T. (2017). Spontaneous neural encoding of social network position. Nature Human Behaviour, 1(5), 0072.CrossRefGoogle Scholar
Parkinson, C., Liu, S., and Wheatley, T. (2014). A common cortical metric for spatial, temporal, and social distance. Journal of Neuroscience, 34(5), 1979–1987.CrossRefGoogle ScholarPubMed
Poldrack, R. A. (2011). Inferring mental states from neuroimaging data: From reverse inference to large-scale decoding. Neuron, 72(5), 692–697.CrossRefGoogle ScholarPubMed
Popal, H., Wang, Y., and Olson, I. R. (2019). A guide to representational similarity analysis for social neuroscience. Social Cognitive and Affective Neuroscience, 14(11), 1243–1253.CrossRefGoogle ScholarPubMed
Stendel, M., and Chavez, R. S. (2023). Beyond the brain localization of complex traits: Distributed white matter markers of personality. Journal of Personality, 91, 1140–1151.CrossRefGoogle ScholarPubMed
Stolier, R. M., and Freeman, J. B. (2016). Neural pattern similarity reveals the inherent intersection of social categories. Nature Neuroscience, 19(6), 795–797.CrossRefGoogle ScholarPubMed
Thornton, M. A., and Mitchell, J. P. (2017). Consistent neural activity patterns represent personally familiar people. Journal of Cognitive Neuroscience, 29(9), 1583–1594.CrossRefGoogle ScholarPubMed
Wager, T. D., Atlas, L. Y., Lindquist, M. A., Roy, M., Woo, C.-W., and Kross, E. (2013). An fMRI-based neurologic signature of physical pain. New England Journal of Medicine, 368(15), 1388–1397.CrossRefGoogle ScholarPubMed
Wagner, D. D., Chavez, R. S., and Broom, T. W. (2019). Decoding the neural representation of self and person knowledge with multivariate pattern analysis and data-driven approaches. WIREs Cognitive Science, 10(1), e1482.CrossRefGoogle ScholarPubMed
Weaverdyck, M. E., Lieberman, M. D., and Parkinson, C. (2020). Multivoxel pattern analysis in fMRI: A practical introduction for social and affective neuroscientists. Social Cognitive and Affective Neuroscience, 15(4), 487–509.CrossRefGoogle ScholarPubMed
Woo, C.-W., Chang, L. J., Lindquist, M. A., and Wager, T. D. (2017). Building better biomarkers: Brain models in translational neuroimaging. Nature Neuroscience, 20(3), 365–377.CrossRefGoogle ScholarPubMed
Woo, C. W., Koban, L., Kross, E., Lindquist, M. A., Banich, M. T., Ruzic, L., … Wager, T. D. (2014). Separate neural representations for physical pain and social rejection. Nature Communications, 5(1), 1–12.CrossRefGoogle ScholarPubMed

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