This paper considers the way mathematical and computational models are used in network
neuroscience to deliver mechanistic explanations. Two case studies are considered: Recent …

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 …

Neuroscience constrains psychology, but stating these constraints with precision is not
simple. Here I consider whether mechanistic analysis provides a useful way to integrate …

Written for cognitive scientists, psychologists, computer scientists, engineers, and
neuroscientists, this book provides an accessible overview of how computational network …

Network theory provides an intuitively appealing framework for studying relationships
among interconnected brain mechanisms and their relevance to behaviour. As the space of …

We describe how computational models can be useful to cognitive and behavioral
neuroscience, and discuss some guidelines for deciding whether a model is useful. We …

The central aim of this paper is to shed light on the nature of explanation in computational
neuroscience. I argue that computational models in this domain possess explanatory force …

Network analysis is increasingly used to discover and represent the organization of complex
systems. Focusing on examples from neuroscience in particular, I argue that whether …

The philosophy of neuroscience has been a dynamic field of research in the philosophy of
science since the turn of the century. As a result of this activity, a new mechanistic …

The overarching goal of cognitive neuroscience is to understand how the brain gives rise to
thought. Toward this goal, researchers employ various methods to measure neural variables …