On the nature of explanations offered by network science: A perspective from and for practicing neuroscientists

Network neuroscience represents the brain as a collection of regions and inter‐regional connections. Given its ability to formalize systems‐level models, network neuroscience has generated unique explanations of neural function and behavior. The mechanistic status of these explanations and how they can contribute to and fit within the field of neuroscience as a whole has received careful treatment from philosophers. However, these philosophical contributions have not yet reached many neuroscientists. Here we complement formal philosophical efforts by providing an applied perspective from and for neuroscientists. We discuss the mechanistic status of the explanations offered by network neuroscience and how they contribute to, enhance, and interdigitate with other types of explanations in neuroscience. In doing so, we rely on philosophical work concerning the role of causality, scale, and mechanisms in scientific explanations. In particular, we make the distinction between an explanation and the evidence supporting that explanation, and we argue for a scale‐free nature of mechanistic explanations. In the course of these discussions, we hope to provide a useful applied framework in which network neuroscience explanations can be exercised across scales and combined with other fields of neuroscience to gain deeper insights into the brain and behavior.
On the nature of explanations offered by network science: A perspective from and for practicing neuroscientists This paper focuses on the level of neural networks. It argues that tools and models in network science can successfully bridge explanations of neural and cognitive phenomena at multiple scales. On the basis of various examples, Bertolero and Bassett explain how network neuroscience can uncover aspects the neural mechanisms of cognitive phenomena.