Jonathan Levy
Iiro P. Jääskeläinen
Margot J. Taylor- 1Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
- 2Ivcher School of Psychology, Reichman University, Herzliya, Israel
- 3Departments of Medical Imaging and Psychology, University of Toronto, Toronto, ON, Canada
- 4Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada
Editorial on the Research Topic
Magnetoencephalography for social science
The past two decades have seen the growth of the field of social and affective neuroscience. By using a range of neuroimaging tools, research in this field has progressed in uncovering the neural substrates and systems involved in social and affective processes (Cacioppo and Decety, 2011; Singer, 2012; Stanley and Adolphs, 2013). Yet, despite half a century of invaluable contribution to various aspects in neuroscience, magnetoencephalography (MEG) (Hämäläinen et al., 1993; Baillet, 2017; Hari and Puce, 2017; Gross, 2019) has only recently been applied to investigating social and affective processes: From probing neural dynamics, through quantifying connectivity patterns of large-scale brain systems, to representing neural generators of multiple rhythms and oscillations and how they relate to social and affective behaviours. Examples range from studies on interpersonal interaction (Hari et al., 2015; Levy et al., 2017), developmental emotion inhibition (Vandewouw et al., 2021), watching social movies (Chang et al., 2015; Levy et al., 2016b), theory of mind (Vistoli et al., 2011; Mossad et al., 2016, 2021; Yuk et al., 2020); intergroup empathy (Levy et al., 2016a; Zhou et al., 2020), emotional face processing (Roesmann et al., 2020; Im et al., 2021; Safar et al., 2021), intergroup bias and interventions (Levy et al., 2021, 2022). These recent works revealed the potential of MEG in uncovering complex neural dynamics underlying psychological processes in the social world (Levy et al., 2020). In this special topic of “Magnetoencephalography for social science” we aimed at expanding this literature by editing four MEG studies that investigate various social processes: from morality, through the neural development of social-cognitive functioning and of face processing, to surprise. These studies, which are summarized below, relied on the uniqueness of MEG data to reveal complex neural dynamics underlying these social processes.
In one study, Hiraishi et al. used MEG to distinguish between morally good and bad judgments. They addressed a gap in the literature on the neuroscience of morality that has mainly focused on brain areas using fMRI neuroimaging, while rarely examining the temporal and connectivity patterns related to moral processes. Using MEG, the study revealed differences at regional, temporal and functional connectivity levels.
Another study by Sato et al. investigated a vulnerable population of children who were born with very low birth weight. They investigated their functional connectivity at rest and its associations with early nutrition and IQ and behavioural problems. The authors found that at preschool-age, these children show altered resting-state connectivity despite IQ and behaviour being in the average range, possibly reflecting functional reorganization of networks to support social-cognitive and behavioural functioning. The authors emphasized the importance of early postnatal nutrition in the development of resting-state networks that support social functions in childhood.
A paper by Mousavi et al. analyzed MEG data in an oddball task to investigate the phenomenon of surprise from a detailed neurodynamic outlook. Although surprise has been examined in many studies, the authors set forth an information-theoretical model to describe and predict the surprise level of an external stimulus in MEG data. The results of their analyses found that middle temporal components and the right and left fronto-central regions offer the strongest power for decoding surprise. The authors concluded that this is a practical and rigorous method for evaluating the interactive and social effects of surprising events on the brain.
Finally, Chen et al. studied face processing during the developmental period between 1 and 4 years. Despite this period being characterized by rapid changes in the ability to encode facial information, there are very few studies which investigate the neural processes of face encoding during this age, and this study sought to fill the gap between prior studies in infants and school-aged children. While implementing a longitudinal MEG approach across the first 4 years of life, they examined the maturation of the MEG responses in the fusiform gyri, which are primary nodes in the face-encoding network. The findings reported face-sensitive maturational changes, providing foundational data to the literature.
Overall, although MEG studies on social processes are increasing, the contribution of this Research Topic has been to consolidate this budding literature and increase exposure to this growing field of research. We contend that this has the potential to motivate social neuroscientists to use MEG, on one hand, and on the other hand motivate MEG scientists to explore social processes. Our ambition is to support the use of this non-invasive method for exploring new horizons that would expand the understanding of social phenomena and their underlying neural mechanisms. Finally, we note that recent technological progress in wearable-MEG, optically-pumped magnetometers, dual-MEG and multiple-brain analyses will certainly yield novel ecologically-valid paradigms that would enhance MEG's ability to emulate real-life validity in the near future (Hari et al., 2015; Brookes et al., 2022).
Author contributions
JL wrote an initial draft for the editorial. All authors contributed to editorial revision, read, and approved the submitted version.
Funding
JL was funded by the Academy of Finland (grant no. 328674).
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
Baillet, S. (2017). Magnetoencephalography for brain electrophysiology and imaging. Nat. Neurosci. 20, 327–339. doi: 10.1038/nn.4504
Brookes, M. J., Leggett, J., Rea, M., Hill, R. M., Holmes, N., Boto, E., et al. (2022). Magnetoencephalography with optically pumped magnetometers (OPM-MEG): the next generation of functional neuroimaging. Trends Neurosci. 45, 621–634. doi: 10.1016/j.tins.2022.05.008
Cacioppo, J. T., and Decety, J. (2011). Social neuroscience: challenges and opportunities in the study of complex behavior. Ann. N. Y. Acad. Sci. doi: 10.1111/j.1749-6632.2010.05858.x
Chang, W. T., Jääskeläinen, I. P., Belliveau, J. W., Huang, S., Hung, A. Y., Rossi, S., et al. (2015). Combined MEG and EEG show reliable patterns of electromagnetic brain activity during natural viewing. Neuroimage 114, 49–56. doi: 10.1016/j.neuroimage.2015.03.066
Gross, J. (2019). Magnetoencephalography in cognitive neuroscience: a primer. Neuron 104, 189–204. doi: 10.1016/j.neuron.2019.07.001
Hämäläinen, M., Hari, R., Ilmoniemi, R. J., Knuutila, J., and Lounasmaa, O. V. (1993). Magnetoencephalography theory, instrumentation, and applications to noninvasive studies of the working human brain. Rev. Mod. Phys. 65, 413–497. doi: 10.1103/RevModPhys.65.413
Hari, R., Henriksson, L., Malinen, S., and Parkkonen, L. (2015). Centrality of Social Interaction in Human Brain Function. Neuron 88, 181–193. doi: 10.1016/j.neuron.2015.09.022
Hari, R., and Puce, A. (2017). MEG-EEG Primer, 1 Edn. New York, NY: Oxford Academic Press. doi: 10.1093/med/9780190497774.001.0001
Im, H. Y., Cushing, C. A., Ward, N., and Kveraga, K. (2021). Differential neurodynamics and connectivity in the dorsal and ventral visual pathways during perception of emotional crowds and individuals: a MEG study. Cogn. Affect. Behav. Neurosci. 21, 776–792. doi: 10.3758/s13415-021-00880-2
Levy, J., Goldstein, A., and Feldman, R. (2017). Perception of social synchrony induces mother–child gamma coupling in the social brain. Soc. Cogn. Affect. Neurosci, 12, 1036–1046. doi: 10.1093/scan/nsx032
Levy, J., Goldstein, A., Influs, M., Masalha, S., and Feldman, R. (2021). Neural rhythmic underpinnings of intergroup bias: implications for peace-building attitudes and dialogue. Soc. Cogn. Affect. Neurosci. 7, 408–420. doi: 10.1093/scan/nsab106
Levy, J., Goldstein, A., Influs, M., Masalha, S., Zagoory-Sharon, O., and Feldman, R. (2016a). Adolescents growing up amidst intractable conflict attenuate brain response to pain of outgroup. Proc. Natl. Acad. Sci. U. S. A. 113, 13696–13701. doi: 10.1073/pnas.1612903113
Levy, J., Goldstein, A., Zagoory-Sharon, O., Weisman, O., Schneiderman, I., Eidelman-Rothman, M., et al. (2016b). Oxytocin selectively modulates brain response to stimuli probing social synchrony. Neuroimage 124, 923–930. doi: 10.1016/j.neuroimage.2015.09.066
Levy, J., Influs, M., Masalha, S., Goldstein, A., and Feldman, R. (2022). Dialogue intervention for youth amidst intractable conflict attenuates neural prejudice response and promotes adults' peacemaking. PNAS Nexus 1, pgac236. doi: 10.1093/pnasnexus/pgac236
Levy, J., Lankinen, K., Hakonen, M., and Feldman, R. (2020). The integration of social and neural synchrony: a case for ecologically valid research using MEG neuroimaging. Soc. Cogn. Affect. Neurosci. 16, 143–152. doi: 10.1093/scan/nsaa061
Mossad, S., AuCoin-Power, M., Urbain, C. M., Smith, M. L., and Taylor, M. J. (2016). Thinking about the thoughts of others; temporal and spatial neural activation during false belief reasoning. Neuroimage 134, 320–327. doi: 10.1016/j.neuroimage.2016.03.053
Mossad, S. I., Vandewouw, M. M., Smith, M. L., and Taylor, M. J. (2021). The preterm social brain: examining social attribution skills in very preterm born children using MEG and fMRI. Brain Commun. 3, fcaa237. doi: 10.1093/braincomms/fcaa237
Roesmann, K., Wiens, N., Winker, C., Rehbein, M. A., Wessing, I., and Junghoefer, M. (2020). Fear generalization of implicit conditioned facial features - behavioral and magnetoencephalographic correlates. Neuroimage 205, 116302. doi: 10.1016/j.neuroimage.2019.116302
Safar, K., Vandewouw, M. M., and Taylor, M. J. (2021). Atypical development of emotional face processing networks in autism spectrum disorder from childhood through to adulthood. Dev. Cogn. Neurosci 51, 101003. doi: 10.1016/j.dcn.2021.101003
Singer, T. (2012). The past, present and future of social neuroscience: a European perspective. Neuroimage 61, 437–449. doi: 10.1016/j.neuroimage.2012.01.109
Stanley, D. A., and Adolphs, R. (2013). Toward a neural basis for social behavior. Neuron 80, 816–826. doi: 10.1016/j.neuron.2013.10.038
Vandewouw, M. M., Safar, K., Sato, J., Hunt, B. A. E., Urbain, C. M., Pang, E. W., et al. (2021). Ignore the faces: neural characterisation of emotional inhibition from childhood to adulthood using MEG. Hum. Brain Mapp. 42, 3608–3619. doi: 10.1002/hbm.25651
Vistoli, D., Brunet-Gouet, E., Lemoalle, A., Hardy-Baylé, M. C., and Passerieux, C. (2011). Abnormal temporal and parietal magnetic activations during the early stages of theory of mind in schizophrenic patients. Soc. Neurosci. 6, 316–326. doi: 10.1080/17470919.2010.530870
Yuk, V., Anagnostou, E., and Taylor, M. J. (2020). Altered connectivity during a false-belief task in adults with autism spectrum disorder. Biol. Psychiatry CNNI 5, 901–912. doi: 10.1016/j.bpsc.2020.04.007
Keywords: magnetoencephalography (MEG), social neuroscience, social neurodevelopment, cognitive and affective neuroscience, functional connectivity
Citation: Levy J, Jääskeläinen IP and Taylor MJ (2023) Editorial: Magnetoencephalography for social science. Front. Syst. Neurosci. 16:1105923. doi: 10.3389/fnsys.2022.1105923
Received: 23 November 2022; Accepted: 06 December 2022;
Published: 04 January 2023.
Edited and reviewed by: Cyriel Pennartz, University of Amsterdam, Netherlands
Copyright © 2023 Levy, Jääskeläinen and Taylor. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Jonathan Levy, 
am9uYXRoYW4ubGV2eSYjeDAwMDQwO2FhbHRvLmZp