The Noise-Resilient Brain: Resting-State Oscillatory Activity Predicts Words-In-Noise Recognition

Abstract

The role of neuronal oscillations in the processing of speech has recently come to prominence. Since resting-state (RS) brain activity has been shown to predict both task-related brain activation and behavioural performance, we set out to establish whether inter-individual differences in spectrally-resolved RS-MEG power are associated with variations in words-in-noise recognition in a sample of 88 participants made available by the Human Connectome Project. Positive associations with resilience to noise were observed with power in the range 21 and 29Hz in a number of areas along the left temporal gyrus and temporo-parietal association areas peaking in left posterior superior temporal gyrus (pSTG). Significant associations were also found in the right posterior superior temporal gyrus in the frequency range 30 to 40Hz. We propose that individual differences in words-in-noise performance are related to baseline excitability levels of the neural substrates of phonological processing. HighlightsO_LIPower of resting MEG activity predicts Words-In-Noise recognition performance C_LIO_LISignificant associations in higher beta and lower gamma frequency band C_LIO_LIStrongest in left-lateralised perisylvian cluster peaking in posterior STG C_LIO_LIEffects are spectrally and spatially consistent with phoneme-level processing C_LI