By Davis Hobley
Neural coupling, or brain-to-brain synchronization, has become an increasingly prominent area of research within computational neuroscience over the last couple of decades (Kinreich et al., 2017). With the emergence of neuroimaging techniques, such as functional magnetic resonance imaging (fMRI) in the 1990s, that can measure changes in oxygen consumption within millisecond intervals, studying brain-to-brain synchronization became much more feasible. Research in the field generally began with the work of Neurobiologist Uri Hasson and his team. They originally presented two individuals with the same stimuli and monitored their respective brain activation via fMRI. He remarkably found statistically significant correlations between these individuals time and time again (Hasson et al., 2004).
Neural coupling can be measured in a few different ways, but in the case of fMRI, it tends to be a function of intersubject correlation (ISC) of BOLD signals that are produced by fMRI using magnetic resonance. ISC in this case is the extent to which the BOLD signals between two individuals rise or fall together and is rated as a value that’s between -1 and 1, with -1 being completely inversely (oppositely) correlated and 1 being completely positively correlated (overlapping). Statistical significance tests, such as t and p-value tests, are often run with calculations for ISC to determine whether or not the neural coupling observed is more likely to be or not to be due to chance (Lahnakoski & Chang, 2021). Both statistically significant positive and negative intersubject correlations are valuable for understanding neural coupling. In many studies, several ISC and significant values will be produced in large cohorts (pairs) of individuals and variables. By subsetting the data into more discrete categories, we can understand what is driving an ISC value’s total to be as high or low as it is.
As it became increasingly clear that neural coupling could be implicated in learning — initially elucidated by Stephens et al. (2010) when showing significant neural coupling in successful communication between a storyteller and a listener — brain synchronization and development started to emerge as a topic in the field. As the topic focus began to shift to learning during development; however, there were originally logistical problems in studying this phenomenon. Primarily because fMRI requires study participants to stay still inside the chamber of the machine, which tends not to be a comfortable or even feasible experience for developing toddlers and infants. As a result, a newer neuroimaging technique, known as functional near-infrared spectroscopy (fNIRS), began being used in the field (Rahman et al., 2020). fNIRS works similarly to fMRI, but instead of producing a BOLD signal via magnetic resonance, it outputs concentrations of oxygenated and deoxygenated hemoglobin via light absorption and refraction, which together implicate brain activation. Additionally, it makes use of a flexible fabric cap and barely noticeable channels in contrast to the stationary fMRI.
There still are logistical difficulties with the process; however, in many cases, finding a significant ISC with a small sample size is difficult, especially when employing p-value tests. The fabric caps themselves, though flexible, also often need to be repaired if infants pull at the material. Despite these difficulties, the field has been growing significantly.
With the tools and capabilities to measure neural coupling in younger populations, around 2019, research quickly emerged surrounding brain synchronization between children and their caregivers. In a study by neuroscientist Piazza et al. (2019), it was first found that neural coupling between an infant and their caregiver is statistically significantly higher than the infant with a non-caregiving adult, specifically in the prefrontal cortex (PFC). This finding has provided evidence that caregiver interactions are especially important for the development of the prefrontal cortex, an area linked to processes such as emotional control, forming goals, and maintaining focus. This foundational study has provided the field with a basis for how to approach measuring neural coupling between caregivers and infants in any number of scenarios and measuring any number of factors.
Figure 1
Note: The above figure shows the neural channels to have significantly significant (p < 0.05) coupling between infant and adult brains during play in a sample of 18 infant-adult dyads (Piazza et al., 2019).
Over the past few years, studies intertwining neural coupling and development have become more and more prevalent, branching out and sampling various other disciplines. In 2021, a neuroendocrinology study by professors Sofia Carozza & Victoria Leong revealed that touch between parents and their infants may facilitate neural coupling and subsequent development. The same year, language development was shown to be associated with the extent to which neural coupling was occurring between infants and their caregivers (Piazza et al.). In 2022, it was suggested that the degree to which neural coupling occurs during dual-attention tasks could be correlated with later social learning (Pan et al.). More than anything, neural coupling has become a new method for evaluating almost anything and everything in the field of development, though we still might not completely understand what neural coupling means.
The natural assumption could be that the more neural coupling occurring between infants and caregivers the better, though this isn’t necessarily always the case. For example, in cases where an infant is developing at a slower pace than standard, a caregiver might be more prone to inject themselves into an infant's vocal play, which could hinder their development, despite likely driving higher neural coupling (Long et al., 2022). Even assuming that neural coupling means someone is “in tune” with someone else might not necessarily be true. The meaning and interpretations of neural coupling will continue to be an integral exploration and an ongoing topic of the field.
The field of neural coupling itself is still novel; the field of developmental neural coupling, even more so. As we begin to learn more about what exactly causes neural coupling during early development and its benefits or consequences, we will have yet another tool to study one of the most nuanced and involved aspects of the field: development.
Bibliography
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