Reducing contributions from non-neuronal sources is a crucial step in functional magnetic
resonance imaging (fMRI) connectivity analyses. Many viable strategies for denoising fMRI …

Alzheimer's disease (AD) is a brain network disorder where pathological proteins
accumulate through networks and drive cognitive decline. Yet, the role of network …

Functional interactions between brain regions can be viewed as a network, enabling
neuroscientists to investigate brain function through network science. Here, we …

Social information is a centerpiece of human experience. Despite a wealth of research into
the way we understand social relationships and how aspects of social life might be …

Affective neuroscience has traditionally relied on cross-sectional studies to uncover the
brain correlates of affects, emotions, and moods. Such findings obfuscate intraindividual …

A complicated neurodevelopmental illness known as Autism Spectrum Disorder (ASD)
impacts behavior, speech, and social interaction. For early diagnosis and intervention, it is …

Improving diagnostic accuracy of obsessive-compulsive disorder (OCD) using models of
brain imaging data is a key goal of the field, but this objective is challenging due to the …

Improving diagnostic accuracy of obsessive-compulsive disorder (OCD) using models of
brain imaging data is a key goal of the field, but this objective is challenging due to the …

Bipolar disorder (BD) is characterized by a dynamic process encompassing various episode
states, including manic episodes (BipM), depressive episodes (BipD), and periods of …

Artificial neural networks are emerging as key tools to model brain processes associated
with sound in auditory neuroscience. Most modelling works fit a single model with brain …