fMRI and Social Interaction
Hyperscanning, which involves scanning the brains of two or more people at the same time, holds a lot of potential for understanding the neurological underpinnings of social cognitive functions. A study handled by Misaki et al. (2020) aims to examine the premise of using fMRI hyperscanning in social neuroscience, discuss the benefits and limitations of fMRI hyperscanning for revealing interbrain systems of social interaction, and present appropriate experimental paradigms and possible analysis methods. It begins with a summary of prior fMRI hyperscanning discoveries to set the stage for the current topic. Misaki et al. (2020) discuss the ramifications of fMRI hyperscanning synchronization and how it differs from EEG and behavioral synchronization analyses. The research suggests that the actual potential of fMRI hyperscanning is achieved not just in investigations of interbrain synchrony but also in examining asymmetric brain activation with whole-brain mapping based on these considerations. Hyperscanning investigations are designed to expose the brain basis of social cognitive skills during real-time social interaction.
The cooperative or competitive game is a frequent fMRI hyperscanning paradigm. Krill and Platek (2012) investigated the brain correlates of collaboration during a maze challenge using fMRI hyperscanning. They employed a general linear model (GLM) analysis to find brain activation related to each condition in the task. They discovered activation in the caudate and putamen reward areas of the brain. This highlights the value of fMRI in detecting activation in subcortical areas that EEG and fNIRS cannot detect. However, a single-brain technique, in which only one participant is examined while the other remains outside the scanner, may reveal the same activation as the GLM analysis. It should be mentioned that fMRI hyperscanning is a time-consuming and expensive experimental method. Without fMRI hyperscanning, many second-person social neuroscience questions can be answered (Constable, 2006). Researchers should focus their efforts on specific social neuroscience topics and problems that can only be addressed using fMRI hyperscanning to support this expensive neuroimaging methodology.
While Misaki et al. (2020) provide guidelines for determining whether or not fMRI hyperscanning is required, broad principles may not apply to all experimental paradigms that exist or are developed. Even if a circumstance does not meet all of the requirements, fMRI hyperscanning may be necessary and/or acceptable. Compared to a sequential strategy, fMRI hyperscanning could save time and reduce participant burden. It is worth noting that our considerations are limited to fMRI hyperscanning. Other hyperscanning methods (e.g., EEG, fNIRS) that are less expensive and can be utilized for face-to-face interactions offer many advantages and can be used for a wide range of study questions. Our goal is to emphasize the best application of fMRI hyperscanning, given its benefits and drawbacks, rather than suggest that other applications and paradigms lack empirical validity or make meaningful contributions.
Researchers’ major gripe is that fMRI can only look at blood flow in the brain. It cannot focus on the activity of individual nerve cells (neurons), which are essential for mental function (Constable, 2006). Each fMRI-studied area of the brain comprises thousands of individual neurons, each with its tale to tell. It is difficult to say exactly what kind of brain activity is reflected on an fMRI scan because specific parts of the brain that lit up on the scan could represent a variety of tasks.
fMRI does not directly detect brain activity, instead relying on indirect changes in blood flow and volume produced by neuronal activity modulation. To begin with, we still do not understand how fMRI measurements relate to brain activity (Constable, 2006). To understand how fMRI signals relate to cerebral activity, we must quantify both simultaneously, which will necessitate the use of animals. This demonstrates that there will be no alternatives to animal experimentation. Furthermore, the spatial resolution of fMRI is just around a cubic millimeter (Constable, 2006). One hundred thousand neurons can be found in such a volume. Put another way, the ‘fMRI microphone’ cannot listen to individual cells but rather a stadium full of them. Finally, because the time course of hemodynamic signals is in the order of 5 seconds, fMRI signals are substantially slower than neuronal activity.
EEG and Social Cognition
Perceived information is exchanged among individuals’ brains when they engage with others. Since 2010, the EEG-based hyperscanning technology, which allows researchers to investigate dynamic brain activities between two or more interactive individuals and their underlying neural mechanisms, has been used to investigate various aspects of social interactions. In recent years, there has been a surge in the study into EEG-based hyperscanning of social interactions. According to the experimental designs and contents, Liu et al. (2018) summarize the application of EEG-based hyperscanning on dynamic brain activities during social interactions, discuss the possibility of applying inter-brain synchrony to social communication systems, and analyzes the contributions and limitations of these studies. This work also highlights several new obstacles for future EEG-based hyperscanning investigations and the developing area of EEG-based hyperscanning for pursuing the broader research subject of social interactions.
Many studies using EEG-based hyperscanning have revealed that inter-brain synchrony occurs more directly and precisely as a result of ongoing social interactions, ranging from coordinated behaviors to effective communication, and have focused on describing the specific time and frequency ranges of neural processing (Kawasaki et al., 2013). Most studies regarded inter-brain synchrony or phase coherence as an important index of interpersonal interaction and attributed inter-brain synchrony or phase coherence to interpersonal action coordination based on quantifying functional similarities or temporal synchronization between brains during social interactions (Konvalinka et al., 2014). The results of various experimental tasks revealed that inter-brain synchronization occurred at various rates. People were able to interact naturally because of the portability of EEG devices, and the inter-brain impact was observed in a fairly realistic context. The above-mentioned social interactive experiment design is more realistic, and social interaction research has been expanded to a wide range of fields.
In conclusion, the study handled by Misaki et al. (2020), which provides information about the role of fMRI in explaining social interaction, does not offer useful insights into social cognition. fMRI has many limitations described in the paper, making it not credible enough to build research based on the method. On the other hand, the study by Liu et al. (2018) brings important insights into understanding social interactions since it discusses the mechanisms and implementation of the EEG. It reveals that EEG has a big potential and contribution to investigating brain processes and social cognition.
References
Constable, R. T. (2006). Challenges in fMRI and its limitations. In Functional MRI (pp. 75-98). Springer, New York, NY.
Kawasaki, M., Yamada, Y., Ushiku, Y., Miyauchi, E., & Yamaguchi, Y. (2013). Inter-brain synchronization during the coordination of speech rhythm in human-to-human social interaction. Scientific reports, 3(1), 1-8. Web.
Konvalinka, I., Bauer, M., Stahlhut, C., Hansen, L. K., Roepstorff, A., & Frith, C. D. (2014). Frontal alpha oscillations distinguish leaders from followers: multivariate decoding of mutually interacting brains. Neuroimage, 94, 79-88. Web.
Krill, A. L., & Platek, S. M. (2012). Working together may be better: Activation of reward centers during a cooperative maze task. PloS one, 7(2), e30613. Web.
Liu, D., Liu, S., Liu, X., Zhang, C., Li, A., Jin, C., Chen, Y., Wang, H. & Zhang, X. (2018). Interactive brain activity: review and progress on EEG-based hyperscanning in social interactions. Frontiers in Psychology, 9, 1862. Web.
Misaki, M., Kerr, K. L., Ratliff, E. L., Cosgrove, K. T., Simmons, W. K., Morris, A. S., & Bodurka, J. (2021). Beyond synchrony: the capacity of fMRI hyperscanning for the study of human social interaction. Social Cognitive and Affective Neuroscience, 16(1-2), 84-92. Web.