The sheer complexity of the human brain means that, despite the tremendous advances made in neuroscience, there is still much we don’t know about what goes on inside our heads and how it goes awry in mental disorders. Even with the most advanced techniques, much of what we’ve learned about the brain is descriptive — telling that something is different between health and unhealthy function — but not why that something is different or how we could change it.
Among the approaches that have provided important insights into these questions is network science, which seeks to understand the brain as a complex system of multiple interacting components. Now, in a review published recently in Neuron, Danielle Bassett, Ph.D., Eduardo D. Glandt Faculty Fellow and Associate Professor of Bioengineering, and Richard Betzel, Ph.D., a postdoc in Dr. Bassett’s lab, have collaborated with scientists from the University of Heidelberg in Germany. The review covers a broad range of discoveries and innovations, moving from earlier, two-dimensional approaches to understanding the brain, such as graph theory, to newer approaches including multilayer networks, generative network models, and network control theory.
“Stating what is different in brain networks of individuals with disorders of mental health is not the same as identifying why” says Bassett. “Here we propose that emerging tools from network science can be used to identify true mechanisms of mental health disorders, and bridge molecular and genetic mechanisms through brain physiology, thus informing interventions in the form of pharmacological manipulations and brain stimulation.”