Connectivity network matrices, as estimated with masking or dual regression against group-level parcellations, reflect little or no unique cross-subject information that is not also captured by spatial topographical variability.
The estimation of functional connectivity network matrices from resting state fMRI is driven by a combination of spatial and temporal factors in the presence of spatially overlapping network structure.
As the scientific community adapts to new working conditions in response to the growing pandemic, early-career researchers recommend actions to help lessen the unintended consequences of canceled conferences.
A more balanced distribution of NIH grant funding among investigators would strengthen the diversity of the research enterprise, increase the likelihood of scientific breakthroughs, and lead to a greater return on taxpayers' investments.
Combining psychophysics and functional MRI reveals a qualitative asymmetry in neural engagement when reflecting on whether a stimulus is seen (detection) compared to reflecting on what a stimulus is (discrimination).