Understanding communication and information processing in nervous systems is a central
goal of neuroscience. Over the past two decades, advances in connectomics and network …

In the last decade, deep learning has reinvigorated the machine learning field. It has solved
many problems in computer vision, speech recognition, natural language processing, and …

The pathology of Alzheimer disease (AD) damages structural and functional brain networks,
resulting in cognitive impairment. The results of recent connectomics studies have now …

Brain atlases are fundamental to understanding the topographic organization of the human
brain, yet many contemporary human atlases cover only the cerebral cortex, leaving the …

Electroencephalography (EEG) measures the neuronal activities in different brain regions
via electrodes. Many existing studies on EEG-based emotion recognition do not fully exploit …

Background: Analysis of the human connectome using functional magnetic resonance
imaging (fMRI) started in the mid-1990s and attracted increasing attention in attempts to …

Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging
technique that enables in vivo reconstruction of the brain's white matter connections at …

Network neuroscience is a thriving and rapidly expanding field. Empirical data on brain
networks, from molecular to behavioral scales, are ever increasing in size and complexity …

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) …

Despite substantial recent progress, our understanding of the principles and mechanisms
underlying complex brain function and cognition remains incomplete. Network neuroscience …