Neural Influencers in the Brain

Brain network analysis is a crucial advance for the understanding of brain circuits and information processing in the brain. The techniques developed in the context of network theory offer a unique toolkit for the investigation of the brain. Of particular interest is the identification of essential brain areas for the performance of cognitive tasks, i.e., areas that if inactivated would cause a considerable impairment to performance. In this chapter we discuss theoretical frameworks to rigorously predict these areas in information-processing networks with specialized modules such as the brain. Brains are composed of tight local clusters exhibiting strongly correlated neural activity reflecting the functional specialization of different areas. How do these local clusters interact at the systems level to generate an integrated unity for global computation without loosing local independence? Here, we show that influencer theory is able to identify the crucial integrators of the modular brain network. We discuss how the identification of essential neural populations is of importance for the treatment of brain diseases and prevention of brain deficits. Evidence suggests that a number of brain dysfunctions and neurological disorders might be caused by alterations in the functional network connectivity across brain regions. This chapter aims to discuss advances in this direction. The ability to accurately predict the localization of core nodes for a given cognitive function and how these nodes reorganize under pathological conditions can improve our understanding of how the brain recovers function after an insult. We finally show how influencer theory is specifically designed to understand the consequence in the brain to insults such as tumor resection, and can guide brain tumor surgery in the clinical setting.