Intermittent brain network reconfigurations and the resistance to social media influence

Author:

Lima Dias Pinto Italo’Ivo1,Rungratsameetaweemana Nuttida2,Flaherty Kristen13,Periyannan Aditi14,Meghdadi Amir5,Richard Christian5,Berka Chris5,Bansal Kanika16,Garcia Javier Omar1ORCID

Affiliation:

1. US DEVCOM Army Research Laboratory, Aberdeen Proving Ground, MD, USA

2. The Salk Institute for Biological Studies, La Jolla, CA, USA

3. Cornell Tech, New York, NY, USA

4. Tufts University, Medford, MA, USA

5. Advanced Brain Monitoring, Carlsbad, CA, USA

6. Department of Biomedical Engineering, Columbia University, New York, NY, USA

Abstract

Abstract Since its development, social media has grown as a source of information and has a significant impact on opinion formation. Individuals interact with others and content via social media platforms in a variety of ways, but it remains unclear how decision-making and associated neural processes are impacted by the online sharing of informational content, from factual to fabricated. Here, we use EEG to estimate dynamic reconfigurations of brain networks and probe the neural changes underlying opinion change (or formation) within individuals interacting with a simulated social media platform. Our findings indicate that the individuals who changed their opinions are characterized by less frequent network reconfigurations while those who did not change their opinions tend to have more flexible brain networks with frequent reconfigurations. The nature of these frequent network configurations suggests a fundamentally different thought process between intervals in which individuals are easily influenced by social media and those in which they are not. We also show that these reconfigurations are distinct to the brain dynamics during an in-person discussion with strangers on the same content. Together, these findings suggest that brain network reconfigurations may not only be diagnostic to the informational context but also the underlying opinion formation.

Funder

Army Research Laboratory

Defense Advanced Research Projects Agency

Publisher

MIT Press

Subject

Applied Mathematics,Artificial Intelligence,Computer Science Applications,General Neuroscience

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