The number of network science applications across many different fields has been rapidly
increasing. Surprisingly, the development of theory and domain-specific applications often …

A defining aspect of brain organization is its spatial heterogeneity, which gives rise to
multiple topographies at different scales. Brain parcellation—defining distinct partitions in …

The anatomy of the brain necessarily constrains its function, but precisely how remains
unclear. The classical and dominant paradigm in neuroscience is that neuronal dynamics …

A central goal in systems neuroscience is the parcellation of the cerebral cortex into discrete
neurobiological “atoms”. Resting-state functional magnetic resonance imaging (rs-fMRI) …

Technological and data sharing advances have led to a proliferation of high-resolution
structural and functional maps of the brain. Modern neuroimaging research increasingly …

Achieving a comprehensive understanding of brain function requires multiple imaging
modalities with complementary strengths. We present an approach for concurrent widefield …

Graph representations are often used to model structured data at an individual or population
level and have numerous applications in pattern recognition problems. In the field of …

A key principle of brain organization is the functional integration of brain regions into
interconnected networks. Functional MRI scans acquired at rest offer insights into functional …

Network neuroscience has emerged as a leading method to study brain connectivity. The
success of these investigations is dependent not only on approaches to accurately map …

Abstract Machine learning techniques have gained prominence for the analysis of resting-
state functional Magnetic Resonance Imaging (rs-fMRI) data. Here, we present an overview …