Scanner acoustic noise in resting-state fMRI

Resting-state functional magnetic resonance imaging (rs-fMRI) is usually acquired during rapid gradient switching that produces intense, spectrally structured sound. Scanner sound activates auditory pathways and can alter neural, vigilance, autonomic, respiratory, and movement-related states, but its sound-specific causal effect on intrinsic functional-connectivity estimates remains unresolved. Direct human comparisons are few and heterogeneous: some report stronger or more extensive network estimates under quieter acquisition, whereas others find broadly preserved topology and within-network connectivity. Near-silent Looping Star imaging can recover canonical resting-state networks with marked sound reduction, but reduced temporal signal-to-noise ratio and functional sensitivity expose a trade-off between acoustic burden and measurement performance. Most quiet-versus-standard contrasts simultaneously alter temporal sampling, gradient vibration, reconstruction, steady-state behavior, or image quality and therefore identify a total protocol effect rather than a sound-specific effect. A structured, original-scale comparison reports acoustic levels and metrics, measurement conditions, acquisition parameters, and resting-state outcomes without pooling unlike measures. Vigilance, autonomic activity, respiration, and movement are potential mediators; indiscriminate regression of these variables can remove part of the total acoustic effect. Current evidence establishes that acquisition protocols can alter rs-fMRI estimates and that scanner sound is biologically active, but it does not establish a universal, directionally uniform suppression of human resting-state connectivity by conventional echo-planar imaging. Future sound-specific attribution would require randomized within-subject manipulation, protected-ear frequency-resolved dosimetry, control of co-varying vibration and sequence properties, and synchronized state and physiological monitoring.