Researchers from UPenn and Indiana University review techniques that thoroughly analyze networks of brain region and interpersonal interactions.
- These investigational tools are meant to help scientists reach a better comprehension of neurological system, behavioral, and social interactions.
- Such new methods include physiological recordings from DNA to proteins and from brain regional communication to social dynamics.
- The new brain recording techniques will allow multiscale brain system analyses for a deeper understanding of how inherited traits and environment shape socialization.
Neuroscience is a burgeoning field of science, and with that being said, researchers have devised new ways to not only analyze the brain but how it forms networks within and between people. Despite recent progress in neuroscience in the ways of analyzing brainwaves, blood flow, tissue volume, and metabolism, neuroscientists have turned to genetics and mathematical modeling. These new analytical methods are seminal to understand “networks” of brain region interactions and ultimately socialization itself for figuring out how to alleviate neurological deterioration. Neuroscientists essentially would like to gain better insight into how genetics influence brain structure and function for manipulations of the environment and then how that environment alters genetic expression.
Bassett and Sporns from the University of Indiana published in Nature Neuroscience in 2017 showing that reductionism, breaking components of the brain to their simplest units, does not provide insight. Instead, they present in their review methods to analyze neuronal, brain region, and interpersonal interactions, which show that networks of interactions produce distinct scientific phenomena. These phenomena give rise to social cliques, cultures, and economies.
What Network Neuroscience Constitutes
In their review, Bassett and Sporns first provide a detailed explanation of what exactly encompasses network neuroscience – the pursuit of understanding neuro network phenomena. They show that the field engenders the study of spatial and time-dependent scales, ranging from molecules to neuronal circuits to the brain and ultimately, to the environment. These neurological components are then measured across timescales ranging from milliseconds to years. Examples of techniques used to measure these neurological components across these timescales include mathematical modeling of gene and protein interactions, along with whole brain imaging. By analyzing neuro network interactions across multiple time scales, network neuroscience seeks to bridge the gaps in knowledge of the brain to gain better insight into human cognition.
Different Spatiotemporal Scales of Neurological Analysis
Bassett and Sporns convey that relational data between genes, binding events between molecules in the brain, connections between brain regions, and links in behavior can be measured. Once these analyses are completed, the relational data are mathematically analyzed to give a broader statistical picture of how gene, neuronal, brain region, and social network interactions occur. Once these data are acquired, neuroscientists can then review their accumulated network neuroscience observations to form new ideas and hypotheses regarding human cognition.
An example of how these data are collected and analyzed to create a broader overview of human cognition comes from brain measurements during socialization. For instance, as people socialize with one another through speech and body language, brain activity can track together through brainwaves correlated across similar brain regions between individuals. Interacting people’s brain activity correlations can be studied from a network perspective using mathematical graphing to better understand similarities and differences in patterns of brain activity. Thus, how our brains respond to our social networks and environments may be used to direct important resources for health interventions at larger social scales like neighborhoods, cities, countries, and cultures.
From gene-gene, protein-protein, to brain regional and even social interactions, network neuroscience works to reveal high-level phenomena that escape detection using reductionism. Where will the future of network neuroscience take us? Perhaps we will not only have the capacity to predict people’s behavior but may also provide humans with better resources to combat age-related brain dysfunction. Not only that, but possibly, neuroscientists will provide better ways to give people what they need to drive economies, culture, and to receive educational opportunities.
Bassett DS, Sporns O. Network neuroscience. Nat Neurosci. 2017;20(3):353-364. doi:10.1038/nn.4502