Network Model for Social Media Tracking Sheds Light on Neural Networks

In a study recently published in the journal Neuron, an international team of researchers from Indiana University and Switzerland used data-mapping methods that were created to track the spread of information on social media networks to help trace the spread of information in the human brain. By applying the social network models to the brain, researchers were able to study specific connections and nodes that may be responsible for higher forms of cognition. In order to conduct the study, the research team performed diffusion spectrum imaging on the brains of 40 research volunteers at University Hospital Lausanne in Switzerland. The team then created a composite map of regions and long-range connections in the brain and applied a dynamic model for information spreading based, in part, on a lead researcher’s model for tracking viral content on the Internet. The model highlighted the pattern of this information’s spread. The researchers could trace a signal from a specific point and observe how quickly it spread through the brain. They could also use the model to infer what connections were used in the brain or identify the connections used at the start of a signal to provide an initial foothold or a fastest path through the network. “We found these connections are not randomly distributed; they have a fairly conspicuous structure,” said a leader researcher of the study. “Certain pathways, for example, form a compact, highly organized pattern, which supports early spreading. There’s also a prominent central component, which gives the signal an initial boost. These are all things we didn’t know until now.” To read more about this study, click here.