Connectome-based predictive modeling (CPM; Finn et al., 2015; Shen et al., 2017) was
recently developed to predict individual differences in traits and behaviors, including fluid …

Although both resting and task-induced functional connectivity (FC) have been used to
characterize the human brain and cognitive abilities, the potential of task-induced FCs in …

Neuroimaging is a fast-developing research area in which anatomical and functional images
of human brains are collected using techniques such as functional magnetic resonance …

The search for an 'ideal'approach to investigate the functional connections in the human
brain is an ongoing challenge for the neuroscience community. While resting-state …

Attention is central to many aspects of cognition, but there is no singular neural measure of a
person's overall attentional functioning across tasks. Here, using original data from 92 …

Dynamic functional connectivity (DFC) aims to maximize resolvable information from
functional brain scans by considering temporal changes in network structure. Recent work …

Global signal regression (GSR) is one of the most debated preprocessing strategies for
resting-state functional MRI. GSR effectively removes global artifacts driven by motion and …

Resting-state functional connectivity (RSFC) is widely used to predict behavioral measures.
To predict behavioral measures, representing RSFC with parcellations and gradients are the …

Although we typically talk about attention as a single process, it comprises multiple
independent components. But what are these components, and how are they represented in …

Abstracts Brain functional connectivity features can predict cognition and behavior at the
level of the individual. Most studies measure univariate signals, correlating timecourses from …