The frequency content of resting-state fMRI signals contains information that can characterize and predict local variations in hemodynamic response timing which enhances the temporal precision of fMRI.

Using simultaneous recordings of electrophysiology, respiration, and resting-state fMRI, a respiration-associated neural network is identified.

There is a disparity in temporal and spatial relationships between resting-state electrophysiological and functional magnetic resonance imaging (fMRI) signals, suggesting the electrophysiological signal alone cannot fully explain the effects observed in the resting-state fMRI signal.

A functional connectivity gradient in striatum is obtained that maps onto DaT SPECT-derived dopaminergic projections and thereby likely provides a new biomarker for investigating dopaminergic (dys)function in the human brain.

The structural characteristics of a circuit and its hierarchical dimensions are shown to influence regional time-series dynamics after targeted cellular-level manipulations.

Resting-state functional connectivity between core regions of fronto-temporal auditory networks can distinguish music transmitters from innovators.

Connectivity fingerprint matching bridges the gap between mouse and primate neuroanatomy, addressing crucial questions surrounding brain evolution that likely impact translation across species.

Resting state spinal fMRI will be useful in studies of normal spinal cord function and central nervous system disorders.

Unprecedented 4D spatiotemporal infant regional cerebral blood flow framework and region-specific physiology–function coupling across infancy were elucidated, highlighting strong physiology–function coupling specifically at the default-mode network to meet extraneuronal metabolic demand for network emergence.

The variability of the pupil–fMRI relationship was characterized through a combination of clustering and prediction methods, which revealed brain state-specific subcortical and neuromodulatory activation patterns reflected in pupil dynamics.