We investigated the relationship of lifetime noise exposure with subcortical and cortical auditory fMRI BOLD responses to broadband noise in 62 individuals with clinically normal audiometric thresholds. We demonstrate robust individual and group responses to a broadband noise across structures in the auditory pathway. In line with animal models, we show a significantly increased BOLD response to stimulus onset in individuals with high noise exposure compared to those with low noise exposure in all auditory structures assessed. We also show a trend towards individuals with high noise exposure exhibiting a greater sustained BOLD response.
62 individuals (age 25-40 years) with normal audiometric hearing (thresholds in each ear ≤20 dB HL over 500–8 kHz) were recruited to the study. Comprehensive assessment of lifetime noise exposure used the Noise Exposure Structured Interview [2]. To examine the effects of lifetime noise exposure, participants were recruited to ‘low’ and ‘high’ exposure groups. The cut-off between groups was pre-specified at 15 lifetime noise exposure units, equivalent to 85 dB(A) across a 50-year working lifetime (8 hours/day, 5 days/week, 48 weeks/year). Groups were actively matched for age using stratified recruitment across five age ranges as in the pre-published protocol [3]. Tinnitus and sound-level tolerance were assessed using the Tinnitus and Hearing Survey [4].
fMRI data were collected on a Philips Ingenia 3.0 T MR scanner (Philips Medical Systems, The Netherlands) with a 32-channel head coil. fMRI data were acquired using a gradient echo echo-planar imaging (GE-EPI) acquisition with 1.5 mm3 voxels; field of view, FOV=168×168 mm; echo time, TE=35 ms; flip angle 90°; sensitivity encoding (SENSE) factor 2.5; and repetition time, TR=2 s. 23 coronal-oblique contiguous slices were acquired with equidistant temporal slice spacing providing coverage of the brainstem and Heschl’s gyrus. The fMRI paradigm comprised 24 seconds of broadband noise followed by a 42-second rest, sounds were presented using the OptoACTIVE Optical MRI Communication System (Optoacoustics Ltd., Israel) system during active noise cancellation, typically reducing scanner acoustic noise to 70 dB-SPL.
Image analysis was performed using FSL (FMRIB Software Library), SPM12, and software toolboxes coded in Matlab. Pre-processing of fMRI data comprised correction of cardiac and respiratory physiological noise [5], image distortion [6,7] and head motion. Statistical analyses were performed using a general linear model (GLM) of the responses to the transients (onset and offset) of the stimulus and the sustained BOLD response over 24 s, within the GLM the motion parameters, and white matter and cerebrospinal fluid (CSF) noise regressors were included as covariates of no interest. Resulting individual statistical parameter maps (SPMs) were normalised to MNI space [8], and a random-effects group analysis performed. A region-of-interest (ROI) analysis was performed using functionally defined auditory pathway ROIs: cochlear nucleus, superior olivary complex, nucleus of lateral lemniscus, inferior colliculus, medial geniculate body, and auditory cortex (Figure 1). ANCOVAs were performed on the beta-estimates of the onset, offset and sustained fMRI responses with factors group (between-subjects) and ROI (within-subjects), and covariate de-meaned age.
1. Liberman MC, Epstein MJ, Cleveland SS, Wang H, Maison SF. “Toward a Differential Diagnosis of Hidden Hearing Loss in Humans”. PLoS ONE. 2016;11(9): e0162726.
2. The Noise Exposure Structured Interview (NESI): An Instrument for the Comprehensive Estimation of Lifetime Noise Exposure. Guest H, Dewey RS, Plack CJ, Couth S, Prendergast G, Bakay W, Hall DA. Trends in Hearing 2018.
3. The Physiological Bases of Hidden Noise-Induced Hearing Loss: Protocol for a Functional Neuroimaging Study. Dewey RS, Hall DA, Guest H, Prendergast G, Plack CJ, Francis ST. JMIR Res Protoc. 2018 Mar 9;7(3):e79. doi: 10.2196/resprot.9095.
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