Over the past decade or so, social scientists have been trying to understand how social networks can influence people’s beliefs and behavior. Despite the many studies on this topic, currently very little is known about how the human brain makes decisions in networked environments, when humans share their views with one another.

Shedding some light on what happens in the brain when humans are making decisions informed by interactions with others in their social network could also help to better understand phenomena commonly observed in social groups. For example, it could help to unveil the neural underpinnings behind misinformation, the propagation of information across social groups and polarized views.

Researchers at Peking University have recently carried out a study aimed at better understanding how humans learn new things from observing the decisions of others. Their findings, published in Nature Neuroscience, pin-point a neurocomputational mechanism through which the brain filters sources of information and that could explain phenomena like biased learning and misinformation.

“We suspected that the human brain processes information differently when the information is transmitted through social networks versus when it is not,” Lusha Zhu, one of the researchers who carried out the study, told Medical Xpress.

“This is because messages flowing along social connections are often entangled, contradictory, or unnecessary, making it very difficult for the brain to reconcile disparate sources of network-derived information. In our recent study, we asked the following questions: how does the brain integrate information received from connected peers? Why people perform differently when they are embedded in a same network? And how does the structural location of an individual on a network affect how that individual performs in a networked environment?”

As part of their study, Zhu and her colleagues asked groups of human participants to play a game that involved observing others’ behavior and learning from i