fMRI measurements of sound-level encoding in the absence of background scanner noise

Effects of sound-level on auditory cortical activation are seen in neuroimaging data. However, factors such as the cortical response to the intense ambient scanner noise and to the bandwidth of the acoustic stimuli will both confound precise quantification and interpretation of such sound-level effects. The present study used temporally “sparse” imaging to reduce effects of scanner noise. To achieve control for stimulus bandwidth, we compared 3 schemes for sound-level matching across bandwidth: component level, root mean square power and loudness. The calculation of the loudness match was based on the model reported by Moore et al. (1996). Ten normally-hearing volunteers were scanned using fMRI whilst listening to a 300-Hz tone presented at six different sound levels between 66 and 91 dB SPL and a harmonic-complex tone (F0 = 186 Hz) presented at 65 and 85 dB SPL. This range of sound levels encompassed all three bases of sound-level matching. Activation in the superior temporal gyrus, induced by each of the 8 tone conditions relative to a quiet baseline condition, was quantified as to extent and magnitude. Sound level had a small, but significant, effect on the extent of activation for the pure tone, but not for the harmonic-complex tone, whilst it had a significant effect on the response magnitude for both types of stimulus. Response magnitude increased linearly as a function of sound level for the full range of levels for the pure tone. The harmoniccomplex tone produced greater activation than the pure tone, irrespective of the matching scheme for sound level, indicating that bandwidth had a greater effect on the pattern of auditory activation than sound level. Nevertheless, when the data were collapsed across stimulus class, extent and magnitude were significantly correlated with the loudness scale (measured in phons), but not with the intensity scale (measured in SPL). We therefore recommend the loudness formula as the most D.Hall “fMRI measurements of sound-level encoding” 2 appropriate basis of matching sound level to control for loudness effects when cortical responses to other stimulus attributes, such as stimulus class, are the principal concern. PACS numbers : 43.66. Cb, 43.66. Ba, 43.64. Ri D.Hall “fMRI measurements of sound-level encoding” 3 Introduction Functional magnetic resonance imaging (fMRI) is a valuable tool for the study of human auditory cortical processing as it can non-invasively measure the topographical organisation of cortical responses to an acoustic signal. fMRI indirectly measures the neuronal population responses through the metabolic consequences of neuronal activity on changes in the ratio of oxygenated to de-oxygenated haemoglobin in the blood (the blood-oxygen-level-dependent, BOLD, response). Here we sought to quantify the effects of sound level on both the extent and magnitude of activation in the auditory cortex and to determine the form of any relationship between them. By using a sparse imaging protocol with silent intervals between image acquisition, responses to sound level were measured in the absence of background scanner noise. A. Neuroimaging studies of sound intensity Both fMRI and positron emission tomography (PET) studies have measured systematic changes in auditory activation with sound level, particularly on the supratemporal plane and superior temporal gyrus (e.g., Jäncke et al., 1998; Lockwood et al., 1999; Millen et al., 1995; Mohr et al., 1999; Strainer et al., 1997). Results have generally indicated a growth in auditory activation with sound level. Understanding brain responses to sound level contributes not only to knowledge of sensory coding, but also to methodological awareness of stimulus control. However, the organising principles of the cortical response to sound level are not yet clear. The lack of a clear consensus on sound-level effects may be a consequence of differences in the range of sound levels presented, particularly if the response saturates at higher levels. Studies have also used different criteria for the specification of sound level; e.g., sound pressure level (Jäncke et al., 1999), sensation level (Lockwood et al., 1999) or dB D.Hall “fMRI measurements of sound-level encoding” 4 relative to a measure of speech intelligibility for each individual subject (Mohr et al., 1999). The ability to exercise control or draw conclusions has also been limited by the coarse quantization or narrow range of levels. Two or three levels are insufficient to determine accurately the shape of the response curve; e.g., to establish whether or not it is linear in dB. The response to sound level has generally been measured across only a few tens of dB relative to the overall system dynamic range of about 120 dB (Viemeister and Bacon, 1988). B. Effect of the intense background noise in fMRI FMRI measures of the auditory response to sound intensity in particular risk contamination by the intense background scanner noise. The principal source of noise is the mechanical deformation of the gradient coils caused by the electrical currents flowing in them within the high static magnetic field. For fMRI, the level almost invariably exceeds 100 dB SPL and here was about 127 dB SPL (Foster et al., 2000). For the present study, the acoustic spectrum of the scanner noise was dominated by a harmonic-complex tone (F0 = 1.9 kHz) rising above a background of broadband noise (see Hall et al., 2000, Figure 1). The scanner noise is a problem for three main reasons. Firstly, it produces its own auditory activation which can overlap with the stimulus-driven auditory response, particularly with conventional imaging protocols where images are acquired at a continuous rate (e.g., Bandettini et al., 1998; Hall et al., 1999; 2000; Shah et al., 1999; 2000; Talavage et al., 1999). This increased baseline level of activation can reduce the size of the experimental effect, and hence reduce the statistical power for detecting stimulus-induced auditory activation. In addition, the supra-threshold magnitude information in the measured response in part reflects an interaction between the responses to the stimulus and to the background noise. Secondly, the D.Hall “fMRI measurements of sound-level encoding” 5 scanner noise can mask the auditory stimulus whenever the stimulus and image acquisition occur close in time. Masking increases the cognitive load for low stimulus levels relative to higher levels, changing the nature of the task by making it harder to detect target stimuli particularly at low sound levels. To overcome masking, presentation levels have tended towards the upper end of the comfortable range of human hearing, and here the cortical response is most likely to saturate. Thirdly, even with hearing protection, the intense background noise can induce a stapedial muscle reflex that alters the sound level transmitted to the inner ear. The level of the sound that triggers this reflex varies across individuals. Although differences in the acoustic reflex threshold do not necessarily reflect differences in loudness perception in normally-hearing listeners (Olsen et al., 1999; Olsen, 1999), imaging studies that use EPI and/or present stimuli towards the upper end of the dynamic range need to consider its effect on sound-level perception. Temporally sparse imaging can reduce the problems caused by the scanner noise as it intersperses a relatively long period of silence (about 10 s) between bursts of scanner noise and separates the noise in time from stimulus delivery. Sparse imaging minimises perceptual masking and the residual auditory activation effects of the scanner sound. Known effects of intense noise on middle-ear reflexes which may contribute to the masking effects are also thereby minimised. The ability of sparse imaging to detect activation is not measurably compromised by the reduction in the number of data averages because sensitivity is maximised by contrasting the peak response with the post-stimulus negative phase of the response (which maximises the percentage change in the BOLD signal between activation and baseline conditions) and, by achieving greater MR signal recovery between image acquisitions (which enhances the BOLD signal-to-noise ratio) (Hall et al., 1998). D.Hall “fMRI measurements of sound-level encoding” 6 C. Requirement for stimulus control Changes in response magnitude have been used successfully to investigate neural activity patterns associated with different acoustical stimuli including changes in frequency (Talavage et al., 1997), bandwidth (Rauschecker et al., 1997; Wessinger et al., 1997) and pitch strength (Griffiths et al., 1998). When explicitly defining stimulus-evoked activation, it is a potential concern that the observed pattern of activation may partly reflect a response to a separate acoustical property of the stimulus that may not have been tightly controlled across conditions. Evidence to date suggests that both bandwidth (Wessinger et al., 1997) and sound level (Jäncke et al., 1998) have similar effects on the spread of activation on the supra-temporal plane and superior temporal gyrus. Thus, subject to what has been controlled, the two effects may not be easily separable. There may be four possible interpretations for the bandwidth effect as observed. The first explanation, preferred by Wessinger et al. (1997) is that broadband stimuli are intrinsically more effective than pure tones in evoking a neuronal response. This may be especially true in regions of non-primary auditory cortex where neurons respond more strongly to broadband stimuli than to pure tones (Redies et al., 1989). Secondly, the effect of bandwidth could be straightforwardly attributed to the basic spread of auditory excitation across frequency channels, particularly in the multiple tonotopically-organised auditory cortical fields (Merzenich and Brugge, 1973; Thomas et al., 1993). This second explanation is difficult to distinguish operationally from the first. The third ex