Processing of binaural spatial information in human auditory cortex: Neuromagnetic responses to interaural timing and level differences

Neuropsychologia 48 (2010) 2610–2619

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Processing of binaural spatial information in human auditory cortex: Neuromagnetic responses to interaural timing and level differences Blake W. Johnson a,∗ , Michael J. Hautus b a b

Macquarie Centre for Cognitive Science, Macquarie University, Sydney, New South Wales 2109, Australia Research Centre for Cognitive Neuroscience, University of Auckland, Auckland, New Zealand

a r t i c l e

i n f o

Article history: Received 22 December 2009 Received in revised form 30 April 2010 Accepted 1 May 2010 Available online 11 May 2010 Keywords: Magnetoencephalography Auditory evoked fields Auditory perception Interaural timing difference Interaural level difference Dichotic pitch

a b s t r a c t This study was designed to test two hypotheses about binaural hearing: (1) that binaural cues are primarily processed in the hemisphere contralateral to the perceived location of a sound; and (2) that the two main binaural cues, interaural timing differences and interaural level differences, are processed in separate channels in the auditory cortex. Magnetoencephalography was used to measure brain responses to dichotic pitches – a perception of pitch created by segregating a narrow band of noise from a wider band of noise – derived from interaural timing or level disparities. Our results show a strong modulation of interhemispheric M100 amplitudes by ITD cues. When these cues simulated source presentation unilaterally from the right hemispace, M100 amplitude changed from a predominant right hemisphere pattern to a bilateral pattern. In contrast, ILD cues lacked any capacity to alter the right hemispheric distribution. These data indicate that intrinsic hemispheric biases are large in comparison to any contralaterality biases in the auditory system. Importantly, both types of binaural cue elicited a circa 200 ms latency object-related negativity component, believed to reflect automatic cortical processes involved in distinguishing concurrent auditory objects. These results support the conclusion that ITDs and ILDs are processed by distinct neuronal populations to relatively late stages of cortical processing indexed by the M100. However information common to the two cues seems to be extracted for use in a subsequent stage of auditory scene segregation indexed by the object related negativity. This may place a new bound on the extent to which sound location cues are processed in separate channels of the auditory cortex. © 2010 Elsevier Ltd. All rights reserved.

Nature has elected to provide most of its creatures with a pair of ears rather than economizing with a single hearing sensor (Schnupp & Carr, 2009). Binaural hearing – like stereo vision – analyses informational disparities between two sensors to build spatial representations of objects and the underlying neural computations in the two modalities may employ common algorithms (Wagner, 2004). Both stereo vision and binaural hearing serve to enrich our perceptions of the world. In the auditory modality these improvements enhance our capacity to perform a fundamental structuring of perception referred to as ‘auditory scene analysis’ (Bregman, 1990), involving a parsing of the acoustic input stream into behaviourally relevant representations. In a world that contains a cacophony of sounds, binaural hearing is employed to extract out a single sound source, determine its location, and assign it meaning (Erikson & McKinley, 1997, p. 722). Listeners primarily rely on two types of binaural information to localize sounds in the horizontal plane: interaural time and level differences between sounds arriving at the two ears (ITDs and ILDs,

∗ Corresponding author. Tel.: +61 2 9850 6879; fax: +61 2 9850 6059. E-mail address: [email protected] (B.W. Johnson). 0028-3932/$ – see front matter © 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.neuropsychologia.2010.05.008

respectively). ITDs arise from the difference between the distances that a sound needs to travel from the source to each ear, while ILDs are due to the fact that the head attenuates sounds arriving at the ear further from a sound source relative to the ear closer to the sound source. The present study is concerned with how these classes of binaural cues are processed and represented in human auditory cortex. Specifically, our study was designed to bear on two issues of importance to our understanding of binaural hearing: (1) the notion that binaural cues are processed primarily in the hemisphere contralateral to the perceived location of a sound source; and (2) the contention that ITDs and ILDs are processed in separate channels in the auditory cortices. Although the auditory cortices receive both contralateral and ipsilateral projections from each ear, the contralateral projections are considered to dominate since cortical neurons respond more strongly to sounds presented (monaurally) to the contralateral ear. Contralateralized processing of monaural sounds is a robust finding in animal electrophysiological (see review by Pickles, 1981), lesion studies (Jenkins & Masterton, 1982), and human neuroimaging and MEG studies (e.g. Krumbholz et al., 2005; Woldorff et al., 1999), and thus would seem to reflect a fairly basic aspect of spatial representation in the cerebral cortex. Strangely, it remains entirely

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unclear whether binaural sounds are processed contralaterally. A few neuroimaging and MEG studies have reported contralateral responses to binaural stimuli (Krumbholz et al., 2005; McEvoy, Hari, Imada, & Sams, 1993; Palomäki, Tiitinen, Mäkinen, May, & Alku, 2005). However a series of other studies have reported no contralateralized processing (Brunetti et al., 2005; Jäncke, Wustenberg, Schulze, & Heinze, 2002; Woldorff et al., 1999; Zimmer & Macaluso, 2005; Zimmer, Lewald, Erb, & Karnath, 2006). Explanations for a lack of contralaterality in these studies are varied: contralateralization may depend on the type of auditory stimulus (Palomäki et al., 2005); whether the stimulus is static or moving (Krumbholz et al., 2005); hemispheric dominance for processing spatial information (Brunetti et al., 2005); negligible hemispheric differences in the number of binaural cells sensitive to the specific timing difference in the ITD stimuli (Woldorff et al., 1999); or a contralateral bias that is at or below the limit of resolution of functional imaging techniques (Werner-Reiss & Groh, 2008). This puzzle, which bears strongly on our understanding of how locations are represented in the brain (Werner-Reiss & Groh, 2008), remains unresolved and controversial. A second unresolved issue in binaural hearing concerns the processing of ITD and ILD cues in the auditory cortex. It has long been appreciated that ITDs are the dominant cues for low frequency sounds, while ILDs dominate for high frequency sounds, the so-called duplex theory of audition (Rayleigh, 1907). Since the formulation of the duplex theory, researchers have suggested the existence of separate neural processing channels for ITDs and ILDs. Indeed, there are several lines of physiological evidence for independent processing mechanisms from unit recordings in the auditory brainstem of animals (Phillips & Brugge, 1985; Smith, Joris, & Yin, 1993; Yin & Kuwada, 1984) and also from surface recordings of auditory brainstem responses in humans (Pratt, Polyakov, & Kontorovich, 1997). It would seem a logical requirement for the auditory system to eventually pool the spatial information extracted from disparate cues into a common code that can be used to solve the broad perceptual problems posed for auditory scene analysis. However it remains unclear when, or even if, information from ITDs and ILDs may be combined into a common code for spatial lateralization (Schroger, 1996; Ungan, Yagcioglu, & Goksoy, 2001). On the one hand, psychophysical studies have shown that lateralization to one ear induced by one cue can be precisely counterbalanced by the complementary cue leading at the other ear, according to a systematic “trading ratio” (Hafter & Jeffress, 1968; Harris, 1960). This suggests that information from the two cues is eventually merged at some stage of the central nervous system. On the other hand, the trade-off between ITD and ILD does not seem to be complete: Listeners report that they experience distinctly different types of sound lateralization “images” for the two types of cues (Hafter & Carrier, 1972). This suggests that segregation may be maintained, at least to some degree, to the level of conscious perception. Indeed, evidence from the cat (Phillips, 1993) and from brain-damaged human patients (Yamada, Kaga, Uno, & Shindo, 1996) indicates that separate representations of ITDs and ILDs exist at the level of the auditory cortex. Further, an EEG study has reported different surface topographies for the circa 100 ms latency N1 event-related potential (ERP) component elicited by ITDs and ILDs, indicating spatially separated neural representations at a relatively late stage of processing in the cerebral cortex (Ungan et al., 2001). MEG recordings show that the two cues have independent effects on the amplitude of the M100, the magnetic counterpart of the N1 (Palomäki et al., 2005). A similar finding for the mismatch negativity (MMN) component of the ERP (Schroger, 1996) suggests at least partially independent cortical processing of timing and level cues up to 200 ms in latency.

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Taken together, these studies provide good evidence for segregation of ITDs and ILDs to quite late stages of auditory processing. However, they shed little light on when (if ever) ITDs and ILDs might be incorporated into a common signal that could mediate perceptually relevant phenomena. In the present MEG study, we studied binaural processing using a psychophysical paradigm termed “dichotic pitch.” When listeners are presented diotically with a timing or level disparity between two identical sounds they perceive a single sound lateralized to the side of the leading ear. However when posed with identical broadband sounds containing an ITD or ILD restricted to a narrow band of frequencies within their overall spectra, they perceive a dichotic pitch corresponding to this frequency band, concurrent with, but spatially separated from, the remaining background (Yost, 1991). The illusion of “hearing out” a pitch from a background noise (termed “dichotic pitch”) has a close analogy in the visual system, where retinal disparities in random dot stereograms can be used to achieve the “seeing out” of a shape displaced in depth from a random background (Julesz, 1971). Importantly, the perception of two concurrent sounds in dichotic pitch is associated with a well-defined neurophysiological marker of auditory processing that can readily be measured with EEG and MEG techniques. This response has a latency of about 150–250 ms and is termed the object-related negativity (ORN; Alain, Arnott, & Picton, 2001). The ORN is an attention-independent ERP component elicited by complex sounds when they are parsed by the auditory system into two concurrent perceptual objects, by using interaural time differences (Hautus & Johnson, 2005; Hautus, Johnson, & Colling, 2009; Johnson, Muthukumaraswamy, Hautus, Gaetz, & Cheyne, 2004; Sanders, Joh, Keen, & Freyman, 2008), inharmonicity (Alain, Schuler, & McDonald, 2002), or both (McDonald & Alain, 2005). MEG studies have demonstrated a magnetic counterpart of the ORN (Alain & McDonald, 2007; Johnson et al., 2004). We measured auditory brain function with MEG to test three predictions about binaural processing: First, if binaural sounds are processed (at least to some degree) contralaterally, we predicted that a binaural sound containing two oppositely lateralized sounds should result in less contralateral (i.e. more bilateral) activation than a single binaurally lateralized sound. Second, if ITDs and ILDs are processed in segregated neuronal populations, we predicted that MEG responses to these two spatial cues should have distinctive spatial profiles. Third, if the ORN generators draw on spatial information common to ITDs and ILDs, the ORN responses elicited by the two cues should be of similar amplitude and latency. 1. Method 1.1. Subjects Twelve right-handed subjects (7 male, mean age = 29.3) with no reported history of auditory or neurological illness took part. The project was approved by the Macquarie University Human Participants Ethics Committee. 1.2. Experimental design The basic acoustic stimulus was a 500 ms broadband noise. When this stimulus is duplicated and presented identically to both ears, the percept is of a noise located in the centre of the head. When an interaural disparity (timing or level) is introduced, the noise is perceived to be lateralized to the side of the leading or high level ear. When an interaural disparity is introduced only for a narrow frequency range of the noise (e.g. 575–625 Hz), two concurrent sounds are heard: a ‘background noise’ in the centre of the head and a circa 600 Hz ‘dichotic pitch’ lateralized to one side. In

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To produce the ITD stimuli, one copy of the bandpass noise was delayed, relative to the other, by 500 ␮s. The same process was applied to one copy of the notch noise. This led to four possible time-delay combinations; two of which had the same delay for the bandpass and notch noises and two of which had different delays. Two spectrally identical noises were obtained by adding the notchfiltered noise for each channel to the copy of the bandpass-filtered noise for the same channel. For the ILD stimuli, the relative amplitude of the two bandpass noises was adjusted to increase the level in one channel while reducing the level in the other. The same was done for the two notch noises, so that there were four possible patterns of level difference. The two noises for each channel were combined as for the ITD stimuli. The magnitude of the amplitude difference was determined separately for each subject in a perceptual matching procedure to be described shortly. Before presentation, all stimuli were bandpass filtered (4th order Butterworth) with corner frequencies of 400 and 800 Hz. Rise and fall times were 4 ms (cos2 ) and stimuli were generated on two channels of a 16-bit converter (Model NI USB-6251, National Instruments, Austin TX). Stimulus levels (averaged across both channels for the ILD stimuli) were 70 dB SPL at the eardrum and delivered diotically via insert earphones (Model ER-30, Etymotic Research Inc., Elk Grove Village, IL). 1.4. Stimulus matching procedure

Fig. 1. Schematic representation of experimental stimuli and resulting percepts of a listener. Control stimuli (first and third rows) contained an interaural disparity that was uniform over the entire frequency spectrum of the noise stimuli and resulted in a single percept of noise (represented as ###) lateralized to the side of the temporally leading ear (ITD) or the ear with the higher level (ILD). Dichotic pitch stimuli (second and fourth rows) contained interaural disparities that were oppositely directed for a 575–625 notch of frequencies versus the remainder of the frequency spectrum. These stimuli evoked a perception of two concurrent but spatially separated sounds lateralized to opposite sides: a circa 600 Hz dichotic pitch (represented as a musical note), and a background noise.

the present experiment we aimed to maximize the sensation of spatial separation between the dichotic pitch and the background noise by introducing oppositely-directed interaural disparities for the dichotic pitch and background noise portions of the overall stimulus. Thus, listeners perceived a 600 Hz pitch lateralized to one side and a background noise lateralized to the other side. The experiment was a 2 × 2 × 2 design with variables location cue type (ITD or ILD), stimulus type (control or dichotic pitch), leading ear for background noise (noise perceived on left or noise perceived on right). Fig. 1 shows that each location cue type could result in four possible percepts: a single noise on the left or right (control stimuli), or concurrent background noises and dichotic pitches (dichotic pitch stimuli), with the background noise perceived on the right or left and the dichotic pitch perceived on the opposite side (see Fig. 1). 1.3. Stimuli Auditory stimuli, which contained either ITD or ILD cues, were created using a complementary filtering method (Dougherty, Cynader, Bjornson, Edgell, & Giaschi, 1998). For both cue types, two identical 500 ms broadband Gaussian noises (sampling rate, 44.1 kHz) were created. One noise was bandpass filtered (8th order Butterworth), with a centre frequency of 600 Hz and a 3 dB bandwidth of 50 Hz. The other noise was notch filtered, employing the same filter corner frequencies as the bandpass filter. The filter functions of the notch and bandpass filters summed to one for all frequencies. Both noises were reproduced so that there was one copy of each for the left and right aural channels.

The lateralization of pitch percepts for ITD and ILD stimuli are governed by different mechanisms, making an objective measure of stimulus equality difficult. Rather, a matching procedure was used to create perceptual equality for the degree of perceived lateralization of the two stimulus types. On the other hand, the amplitude of the stimuli could easily be set by objective measures of sound pressure. However, there was no matching of pitch (or control) loudness, only physical equating of amplitude. For each subject, the level differences used to create the ILD stimuli were calibrated to produce the closest judged perceptual match for lateralization to the corresponding ITD stimuli. This was accomplished in two phases, each consisting of an adaptive two-stimulus method. The first stimulus presented on a trial was always an ITD stimulus, and the second an ILD stimulus. After each pair of presentations, the subject responded on a keyboard to inform the adjustment of the level difference – toward the left or right channel – that would be used for the next trial. Level differences were adjusted in steps of roughly 10%. The subject continued to adjust the level differences until the closest perceptual match was obtained for the lateralization of the two stimuli, after which the subject indicated that they were satisfied of a perceptual match. The first phase involved the perceptual matching of the ILD control stimuli to the ITD control stimuli. Perceptually, this equated to matching the level of lateralization of the ILD stimulus to that of the fixed ITD stimulus. This was done separately for the left and right control stimuli. The second phase involved the matching of the ILD and ITD pitch stimuli. For this phase, the level differences for the noise component of the ILD stimuli were fixed at the level determined in the first phase. The subject then adjusted the level difference for the narrow band pitch component so that it perceptually matched the pitch component of the ITD stimulus. This was done separately for the left and right pitch stimuli. After completion of both phases, four different level differences were obtained. This whole procedure was undertaken twice for each subject, and the final four level differences were the average of those obtained from each replication. These four level differences were used to produce all ILD stimuli presented during the experiment.

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1.5. MEG Prior to MEG measurements, MEG marker coils were placed on the subject’s head. Marker coil positions and head shape were measured with a pen digitiser (Polhemus Fastrack, Cochester, VT). All measurements were carried out with subjects in a supine position in the MEG environment. MEG recordings were obtained in a magnetically shielded room using a KIT-Macquarie MEG160 system (KIT, Kanazawa, Japan), which consists of 160 coaxial first-order gradiometers with a 50 mm baseline. MEG data were sampled at a rate of 1000 Hz and bandpass filtered from 0.03 to 200 Hz. 1.6. Structural MRI T1-weighted, 3D sagittal MRIs were scanned in a separate session using a 3T Phillips Achieva MRI scanner at St Vincent’s Hospital, Darlinghurst, NSW, Australia. Scans were 1 mm isotropic. 1.7. Procedure Participants were instructed to maintain fixation on a cross projected onto a screen above the MEG helmet dewar. Subjects were presented with blocks of randomised stimuli with equal frequencies for each of the eight versions of stimulus. Each block contained 216 stimuli. Subjects indicated with a button press whether each stimulus contained a pitch or not (i.e., a control stimulus). Two stimulus blocks were presented consecutively with a short break between, during which marker coil measurements were obtained. Interstimulus intervals were drawn from a rectangular distribution between 2000 and 3500 ms. 1.8. Analysis Our analyses added a further 2-level variable of hemisphere (left or right) to the basic 2 × 2 × 2 design with variables location cue type (ITD or ILD), stimulus type (control or dichotic pitch), leading ear for background noise (noise on left or noise on right). The ability of subjects to distinguish between pitch and control stimuli was assessed by calculating the sensitivity measure, d , for each of the four types of pitch stimulus. To do this, control and pitch stimuli, with the noise lateralized to the same side of auditory space (i.e., the same leading ear), were compared. For these pairings, the only difference is the presence or absence of a dichotic pitch; hence the reported values of d represent the ability of the subjects to detect the dichotic pitch. Obtained estimates of d were compared across cue type and leading ear using repeated measures analysis of variance. MEG data were analysed off-line using BESA version 5.2.4 (MEGIS Software GMbH, Grafelfing, Germany) and MEG-MRI coregistration was performed using BrainVoyager version 1.10 (BrainInnovation BV, Maastricht, The Netherlands). MEG data were segmented and averaged into 500-ms epochs, including a pre stimulus baseline of 50 ms. Averaged data were filtered with a passband of 0.2–30 Hz. MEG artefacts including blinks and eye-movements were rejected using the artefact scan tool in BESA 5.2.4, which rejects trials based on abnormally high amplitudes or abrupt rises or falls in amplitude (gradients). Rejection thresholds were set at 2.7 pT (amplitude) and 2 pT (gradient). For each subject and condition, at least 90% of trials survived artifact rejection. Source analysis was conducted by modelling the MEG data with two symmetric dipole sources in a spherical volume conductor fitted to the digitised surface of the head. Dipole fitting was performed over a 20–250 ms time interval encompassing the M50, M100 and ORN components. To achieve the best signal-to-noise

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ratio for source estimation, sources were derived from data averaged over all stimulus conditions for each participant. The dipole fitting strategy was intended to achieve two aims: First, to reduce the dimensionality of the data to a statistically tractable number (from 160 channels of surface data to 2 channels of source data); Second, to achieve a separation of the data between the two hemispheres to allow for straightforward tests of our three main predictions. This dipole model is clearly an oversimplification of reality since the auditory cortices are known to be slightly asymmetrical (e.g. Scherg et al., 1989). However since MEG data from individuals typically does not in any case have a high-enough signal-to-noise ratio to resolve this asymmetry, the symmetric dipole model is a reasonable approximation. The model also oversimplifies in positing a mean location and orientation for the three main components of the AEF (M50, M100 and ORN). However, the errors associated with mis-specifying the location of these components are small in comparison to the size of the hemispheric differences that are the main interest of the present study. For a similar approach to modelling of AEFs see Alain and McDonald (2007). Statistical analyses were computed for three components of the source waveforms: M50 (20–80 ms), M100 (80–130 ms), and ORN (150–250 ms). Component amplitudes were computed as mean voltages over each time window. These data were analysed with a repeated measures analysis of variance using SPSS v. 16. For comparison with the source waveforms, surface waveforms were summarized by computing the root mean square (RMS) of the 20 sensors with the largest amplitude M100 responses (10 for each hemisphere). Component latencies were computed using an automated peak finding utility in BESA 5.2. Because the ORN component does not exhibit a well-defined peak, latencies were analysed only for the M50 and M100 time windows. Statistical analyses were performed only for the source waveforms, since these were based on the entire set of surface recorded data, while the RMS waveforms were based on only a subset of 20 channels. For comparison with the previous literature, we computed an index of the magnitude of contralateralization for the source waveform data, calculated as the amplitude of response from contralateral stimulation divided by the sum of amplitudes from contralateral and ipsilateral stimulation (Woldorff et al., 1999). Where appropriate, degrees of freedom in the ANOVA were corrected for lack of sphericity with the Greenhouse-Geisser Epsilon. 2. Results 2.1. Behavioural data The average values of d across all subjects were: right-leading ITD (d = 2.2, SE = 0.3), left-leading ITD (d = 2.4, SE = 0.4), rightleading ILD (d = 3.0, SE = 0.4), and left-leading ILD (d = 3.3, SE = 0.4). ANOVA (location cue type by leading ear) confirmed an effect of location cue type (F(1,11) = 9.62, p = .01). Despite the matching procedure, the ILD stimuli (d = 3.1, SE = 0.3) were still more detectable than the ITD stimuli (d = 2.3, SE = 0.2). All other effects were not significant. 2.2. MEG data The acoustic stimuli elicited typical auditory evoked fields characterised by a large amplitude magnetic response at a latency of about 100 ms after stimulus onset. Fig. 2 shows that the grand mean surface M100s recorded over the right hemisphere are larger (88 fT) and peak earlier (105 ms) than the left hemisphere M100 (115 ms and 67 fT). A M50 peak is also visible in the left hemisphere waveform at a latency of 55 ms.

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Fig. 2. Grand mean surface M100 RMS waveforms showing right and left hemisphere amplitude and latency differences. Each waveform is an average over all stimulus types taken from the ten sensors with the largest amplitude for each hemisphere.

Fig. 3A shows the M100 surface topography for a typical participant. Table 1 shows Talairach coordinates of dipole sources obtained for each participant. All sources were near the superior temporal plane and the mean dipole sources were located in bilateral BA41 in the transverse temporal gyri, corresponding to the primary auditory cortices (see Fig. 3B). The grand mean source waveforms for the fitted dipoles are shown in Fig. 4A. Note that the main features of the surface waveforms (Fig. 2) are also seen in the source waveforms. Notably, the M100 peak is about 10 ms earlier and larger in amplitude in the right hemisphere (103 ms, 26 nAm) than in the left hemisphere (113 ms, 20 nAm). Further, the M50 peak (latency 56 ms) is much more prominent in the left hemisphere than the right hemisphere. The small mean latency differences between the source and surface waveforms are due to the fact that the source waveforms are derived from a much larger set of sensors than the surface waveforms. Note further that the M50 is rectified in the RMS surface waveforms of Fig. 2 but not in the source waveforms of Fig. 4. The ORN component can be visualized in the grand mean source waveforms of Fig. 4B and C as a increase in source strength for the dichotic pitch response compared to the control response for both ITD and ILD. The ORN onset occurs after the M100 peak and persists until about 350 ms.

Fig. 3. (A) Surface topography of M100 response over all stimulus types for a typical subject and (B) grand mean source location of auditory evoked responses, superimposed on one subject’s Talairach-transformed MRI scan.

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Table 1 Talairach coordinates (mm) and residual variance (%) of dipole sources for each participant. Dipole sources were derived from data averaged over all stimuli for each participant. Talairach coordinates

Residual Variance

X

Y

Z

Entire Epoch 20–250 ms

M50 20–80 ms

M100 80–130 ms

ORN 150–250 ms

S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12

±57.9 ±61.0 ±56.2 ±58.2 ±53.5 ±56.0 ±43.1 ±59.5 ±61.9 ±45.5 ±49.8 ±60.5

−20.0 −14.7 −24.0 −27.4 −32.0 −27.6 −11.3 −26.9 −17.9 −23.6 −9.9 −12.2

4.8 13.6 9.7 12.5 15.2 17.5 −9.0 0.6 9.2 4.7 15.5 12.7

10.5 17.9 9.5 24.3 10.7 18.7 14.3 14.4 24.5 16.0 13.0 10.5

14.6 16.7 13.1 13.2 8.4 12.7 12.1 13.9 15.1 9.9 20.0 19.7

5.1 8.3 6.1 10.1 6.0 5.0 2.1 7.5 9.4 6.7 7.8 5.8

14.8 22.9 16.3 32.0 17.2 30.9 30.7 35.5 38.4 26.3 15.4 17.0

Mean

±55.3

−20.6

8.9

15.4

14.1

6.7

24.8

2.3. Statistical analyses of source waveforms 2.3.1. M50 latencies For the left hemisphere, the mean latency was 56.0 ms while for the right hemisphere the mean latency was 43.1 ms. ANOVA (location cue type, leading ear, stimulus type, hemisphere) confirmed a significant main effect of hemisphere (F(1,11) = 9.1, p = .01). No other main effects or interactions achieved significance. 2.3.2. M50 amplitudes ANOVA (location cue type, leading ear, stimulus type, hemisphere) revealed a significant main effect of leading ear (F(1,11) = 8.3, p = .02). This was because M50 amplitudes were more negative when the noise was heard on the right (−1.1 nAm) than when it was heard on the left (−0.1 nAm). No other main effects or interactions achieved significance. Left hemisphere amplitudes (mean −3.2 nAm) were larger (more negative) than right hemisphere amplitudes (mean 2.1 nAm; F(1,11) = 18.3, p = .002). Note that right hemisphere amplitudes are positive because of overlap with the M100 in this time window. 2.3.3. M100 latencies The mean latency for the left hemisphere was 113.2 ms, while for the right hemisphere it was 103.2 ms. ANOVA (location cue type, leading ear, stimulus type, hemisphere) confirmed a significant main effect of hemisphere (F(1,11) = 15.7, p = .002). No other main effects or interactions achieved significance. 2.3.4. M100 amplitudes ITD cues elicited a slightly larger mean amplitude M100 (18.3 nAm) over the analysis window than did ILD cues (16.56 nAm), and mean M100 amplitude was larger in the right hemisphere (20.7 nAm) than the left (14.2 nAm). ANOVA (location cue type, leading ear, stimulus type, hemisphere) confirmed a significant main effect for location cue type (F(1,11) = 7.2, p = .02), but the main effect of hemisphere did not reach significance (F(1,11) = 2.5, p = .14). There were significant 3-way interactions for location cue type × stimulus type × hemisphere (F(1,11) = 5.9, p = .03) and location cue type × leading ear × hemisphere (F(1,11) = 5.0, p = .04). No other significant effects were found. The 3-way interactions are best interpreted by contrasting experimental effects for each location cue type separately. Considering ITD cues first, Fig. 5 (top left) shows that the left- and right-lateralized sounds (control stimuli only, as dichotic pitches are bilateral) elicited different hemispheric patterns (F(1,11) = 8.8, p = .01): the left-lateralized stimuli elicited larger amplitudes in the right hemisphere (contralateralization index = .62) while right-

Fig. 4. Grand mean source waveforms showing (A) right and left hemisphere amplitude and latency differences over all stimulus types (compare to surface waveforms of Fig. 2); (B) ORN response to ITD stimuli (average over two control stimuli vs. average over two pitch stimuli); and (C) ORN response to ILD stimuli (average over two control stimuli vs. average over two pitch stimuli).

lateralized sounds elicited similar amplitudes in both hemispheres (CI = .47). In contrast, left- and right-lateralized sounds for ILD cues elicited similar hemispheric patterns of activation (F(1,11) = 1.4, p > .05)).

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Fig. 5. M100 amplitude profiles plotted separately for ITDs and ILDs. Control stimuli were perceived unilaterally, on the right or the left. Dichotic pitch stimuli (“Pitch”) were perceived bilaterally as two sounds: a noise on the left and pitch on the right (“Pitch Right”); or a noise on the right and a pitch on the left (“Pitch Left”).

Turning to the effect of the “bilateral” binaurals (dichotic pitch stimuli), Fig. 5 (middle-left plot) shows that an ITD stimulus containing a left-lateralized noise and a right-lateralized pitch (pitch right) elicited a hemispheric pattern of activity that was not significantly different from that elicited by a left-lateralized noise only (F(1,11) < 1, n.s.). In contrast (Fig. 5, bottom left) the stimulus containing a right-lateralized noise and left-lateralized pitch (pitch left) produced a markedly different pattern (CI = .43) than the stimulus containing only a right-lateralized noise (CI = .50; F(1,11) = 6.4, p = .03); that is, the bilateral binaural was more ipsilateral (with respect to leading ear) in comparison to the unilateral binaural. There were no equivalent effects for the ILD stimuli (Fig. 5, middle and bottom right). These results confirm that ITD and ILD cues elicit distinctive hemispheric patterns of activation and support the hypothesis that the two cues are processed in at least partially separated neuronal populations during the M100 time window. The results also show that the bilaterally binaural dichotic pitches had a significant impact upon hemispheric patterns of activation in comparison

to the unilateral binaural control stimuli, albeit in a more specific and more complicated manner than we originally anticipated. We interpret these findings in the discussion. 2.3.5. ORN amplitudes ANOVA (location cue type, leading ear, stimulus type, hemisphere) confirmed a highly significant main effect of stimulus type (F(1,11) = 27.0, p < .001) – confirming an ORN effect across all cues, locations, and hemispheres – and a significant main effect of location cue type (F(1,11) = 8.5, p = .01). This is because ILD amplitudes were higher than ITD amplitudes for both stimulus types (Fig. 3B and C). Thus, while overall ILD amplitudes were higher than ITD amplitudes during the analysis window, the relative amplitude difference between control and pitch stimuli (ORN effect) was not significantly different for the two stimulus types (no significant location cue type x stimulus type interaction, F(1,11) = 2.3, p > .05). No other main effects or interactions achieved significance. These results show that the two types of spatial cues elicited a very similar ORN response, supporting the interpretation that the

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ORN generators may draw on spatial information common to the two cues. 3. Discussion Our study examined the processing of binaural spatial information in the human auditory cortex. We used a psychophysical paradigm, termed “dichotic pitch,” in which listeners are able to use azimuthal location cues to separate a complex sound into two concurrent percepts. This paradigm had two key features. First, it allowed us to produce binaural stimuli containing either a single lateralized sound or two lateralized sounds located in opposite hemispaces. Second, we were able to generate binaural stimuli based on either of two binaural cues, ITDs or ILDs. The results provide new insights into two unresolved issues in binaural hearing: (1) the extent to which binaural cues are represented and processed in the contralateral hemisphere; and (2) the extent to which ITDs and ILDs are represented and processed in separate cortical pathways. 3.1. Contralateral processing of binaural cues In their fMRI/MEG study of lateralized spatial perception, Woldorff et al. (1999) noted a striking contrast between their results for monaural sounds, which produced a clear and substantial contralaterality for both functional measures, and their finding of no significant contralaterality for binaural sounds. Since binaural sounds produce a strongly lateralized perception, this discrepancy must be accounted for by any model that holds the auditory cortices are organized to process stimuli predominantly from the opposite auditory hemispace (e.g. Furukawa & Middlebrooks, 2002; McAlpine, Jiang, & Palmer, 2001). In the subsequent decade, a few studies have in fact reported contralateral responses to binaural stimuli (Krumbholz et al., 2005; Palomäki et al., 2005); however a number of other neuroimaging and MEG studies have concurred with the Woldorff et al. (1999) study in finding of no contralaterality for binaural sounds (Brunetti et al., 2005; Jäncke et al., 2002; Zimmer & Macaluso, 2005; Zimmer et al., 2006). One explanation for these mixed results is that any contralaterality will be superimposed upon and possibly obscured by hemispheric dominance for particular sound patterns in the human brain (Krumbholz et al., 2005). Indeed, our results show prominent right-left differences for the M100 response: the right hemisphere was generally larger in amplitude (although the main effect was nonsignificant), and 10 ms earlier in latency, a timing difference that was highly significant. Palomäki et al. (2005) reported that the amplitude of the M100 component was larger in the right hemisphere and showed that the dynamic range of the right hemisphere M100 was larger for stimuli containing spatial cues compared to nonspatial stimuli. These authors also reported that the M100 latency was an average of 7 ms earlier in the right hemisphere, although this latency difference was not statistically significant. Similarly, Brunetti et al. (2005) reported right hemisphere dominance for spatial processing with both fMRI and MEG responses. These studies, and our own data, support an interpretation that the right hemisphere has an intrinsic preference for analysis of spatial information (e.g. Gazzaniga et al., 2002). However, the role of hemispheric dominance in spatial processing is still a matter of debate and there are alternative interpretations of hemispheric biases. The asymmetric sampling in time (AST) hypothesis (Poeppel, 2003), for example, posits a time-based view of hemispheric differences, such that the left hemisphere is biased to extracting information over shorter temporal integration windows than the right hemisphere. A left hemisphere bias for rapid temporal information in conjunction with a right hemisphere bias for spatial information would account for the strong leading ear x

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hemisphere interaction for ITD control stimuli in this study (Fig. 5, top left). On this view, timing information available in the ITD control stimuli may engage the contralateral left hemisphere more strongly when the temporal delay leads at the right ear, changing a right-hemisphere biased pattern to a bilateral pattern of brain activity. It must be noted that the sub-millisecond timing differences in ITD cues are calculated in the brainstem and are a different order of magnitude than the circa 20–40 ms time scales proposed for the left hemisphere by the AST theory. Microsecond precision is presumably beyond the timing capabilities of cortical neurons; however ITD timing information is ultimately encoded in the auditory cortex, it must be scaled by a factor that can be read and interpreted by other cortical neurons. The outcome of this scaling seems to be a timing representation that can appeal to the strengths of the left hemisphere. A contest that pits a right hemisphere spatial bias against a left hemisphere timing bias can account for the stimulus type x hemisphere interaction for the right-lateralized ITD control stimuli and the corresponding bilateral binaural stimulus (Fig. 5, bottom left). On these data, and that of Fig. 5 middle left, the hemispheric contestants are unevenly matched; the left hemisphere holds its own only if sounds originate solely from the opposite hemispace; the right hemisphere wins the tug of war if any sounds are present in the left hemispace. A non-stimulus based explanation for the right-hemispheric bias involves the ventral frontoparietal network, responsible for the redirection of attention and sensory orienting, which shows a large right-hemispheric advantage (see Corbetta & Shulman, 2002, for a review). This network is thought to be most strongly activated by the detection of unattended or low frequency stimuli and leads to a reorientation of attention. While the stimuli in this study do not fit this profile well, the detection of the pitch stimuli required a search in auditory space and hence attentional shifts. It is conceivable that this may have led to the activation of this lateralized network. 3.2. Segregated processing of ITDs and ILDs While a unilateral ITD cue can engage the left hemisphere if presented in the right hemispace, no such effect was obtained for ILD cues (Fig. 5, right). This finding reinforces the interpretation that it is timing information, contained in the ITD representation but not the ILD representation, that is crucial for engaging the left hemisphere. The greater capacity of ITD cues to activate the left hemisphere cannot be attributed to a greater salience of this cue, since our behavioural data show that the ILD cues were in fact more detectable, despite our efforts at loudness and laterality matching. These results therefore support the hypothesis that, during the time window of the M100 response, ITD and ILD cues are processed in at least partially distinct channels of the auditory cortex (Wright & Fitzgerald, 2001), aimed at differentially elaborating the specific kinds of spatial information represented in each channel. Our results are supported by an EEG topographic mapping study by Tardif, Murray, Meylan, Spierer, & Clarke (2006). These authors also found that ITD/ILD differences were primarily in terms of hemispheric lateralization, although they reported somewhat different hemispheric patterns than ours, with bilateral responses to ILD cues and left-lateralized responses to ITD cues. The differences between studies may be attributable to differences in EEG and MEG recording methodologies, but in any case both studies support a greater involvement of the left hemisphere in processing ITD cues than for ILD cues. An involvement of the left hemisphere in sound localization is supported by a recent study of patients with right or left hemisphere brain damage (Spierer, Bellmann-Thiran, Maeder, Murray, & Clarke, 2009). While these authors found a prominent right hemispheric dominance for auditory localization, significant

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spatial deficits were also observed in patients with strictly left hemisphere damage. These authors concluded, as do we, that right hemispheric dominance is better conceptualized as an asymmetrical activation of both hemispheres, rather than an absolute role for the right hemisphere. 3.3. Pooling of spatial information for auditory scene analysis For both ITD and ILD location cues during a time window of 150–250 ms, sources in both hemispheres showed a prominent increase in amplitude for sounds containing a dichotic pitch, in comparison to sounds that contained no binaurally-embedded pitch. This effect, termed the ORN component, was originally described in an EEG study of concurrent sound segregation by Alain and colleagues (Alain et al., 2001). These investigators presented listeners with complex sounds in which all harmonics were tuned, or that had a single harmonic mistuned with respect to the other harmonics. The degree of mistuning was varied from trial to trial and participants were required to indicate if they heard a single complex “buzz” sound, or a buzz sound and a pure pitch, due to hearing out the mistuned partial. In accordance with previous psychophysical findings, subjects reported a greater likelihood of hearing two concurrent sounds as mistuning was increased. The ORN was concomitant with the perception of two auditory objects, and ORN amplitude was directly proportional to the degree of mistuning. Further, the ORN was elicited independently of whether participants were actively attending to the sounds or were ignoring them while reading a book. These authors proposed that the ORN marked an early, preattentive stage of auditory scene analysis, in which sounds are automatically parsed based on the detection of a mismatch between the harmonic template extracted from the incoming sound, and the harmonic frequency derived from the fundamental of the sound complex. Recent work on the ORN has strengthened the view of this component as a physiological index of preattentive auditory scene segregation (see review by Alain (2007); but also see Chait, Poeppel, & Simon, 2006) but has not supported the spectral template matching hypothesis of its generation. Work with dichotic pitches (Hautus & Johnson, 2005; Johnson, Hautus, & Clapp, 2003) has shown that the ORN can be elicited based solely on ITD rather than harmonicity, since the noise processes, by definition, had no harmonic template to match to. Since the mistuned harmonic stimuli and dichotic pitches are entirely different, it seems reasonable to conclude that the ORN response is more closely related to the overall perceptual problem posed by a sound than to its detailed physical composition or critical cues. This perceptual task of decomposing a complex acoustic stream into distinct perceptual objects seems to demand fairly general mechanisms that can broadly use a range of acoustic cues that can help to separate simultaneous acoustic events. This view readily encompasses the present demonstration that the ORN is elicited to ILD cues to sound location. The mean time window of the ORN effect was essentially identical for both ITD and ILD cues. In contrast to the M100 component, the ORN component was not itself modulated in amplitude by location cues, nor was its lateralization influenced by the type of location cue. While we do not wish to over interpret this negative result, it stands in contrast to previous findings for the M100 and later components (Schroger, 1996; Tardif et al., 2006). Therefore, the ORN can potentially place an important and novel temporal boundary on the extent to which ITD and ILD cues, or the information derived from them, remain segregated in separate channels of the cerebral cortex, since information that can be used to parse a pitch from a background noise must have been extracted from both cues prior to the generation of the ORN. We reiterate that a negative result (no significant modulation of the ORN by location cues) cannot support a strong inference

in this regard. While one could infer different representations for ITD and ILD cues if the ORN amplitude or latency was modulated by location cues, a negative result could be due to a common spatial representation, or simply due to the limits of our measurements or our simple dipole model. Further investigations are required to address these important theoretical issues. We note also that the ORN component is superimposed upon brain activity in the same time window that is strongly modulated by cue type. It seems that the brain may continue to process information in independent streams even after spatial information has been extracted to support auditory scene segregation. 4. Conclusions Our results show a strong modulation of interhemispheric activity by ITD cues, but only when these cues are presented unilaterally from the right hemispace. Our data support the interpretation of a relatively strong right hemisphere bias for spatial information in conjunction pitted against a relatively weaker left hemisphere preference for timing information. The hemispheric biases are large in comparison to the modest contralateral bias exhibited at the population level in primate auditory cortex (Werner-Reiss & Groh, 2008). In contrast, ILD cues lack the capacity of ITDs to engage the left hemisphere, presumably because their cortical representations lack the timing information that is preferentially processed in that hemisphere. Finally, spatial information that is common to both ITD and ILD cues seems to be extracted prior to the ORN time-window for use by the cerebral mechanisms of auditory scene segregation. Acknowledgements This work was supported by Australian Research Council Linkage Infrastructure Equipment and Facilities Grant LEO668421. The authors gratefully acknowledge the collaboration of Kanazawa Institute of Technology and Yokogawa Electric Corporation in establishing the KIT-Macquarie MEG laboratory. We thank Melanie Reid and Graciela Tesan for assistance with data collection. The authors thank two anonymous reviewers whose comments greatly improved an earlier version of this manuscript. References Alain, C. (2007). Breaking the wave: Effects of attention and learning on concurrent sound perception. Hearing Research, 229(1–2), 225–236. Alain, C., Arnott, S. R., & Picton, T. W. (2001). Bottom-up and top-down influences on auditory scene analysis: Evidence from event-related brain potentials. Journal of Experimental Psychology: Human Perception and Performance, 27(5), 1072–1089. Alain, C., & McDonald, K. L. (2007). Age-related differences in neuromagnetic brain activity underlying concurrent sound perception. Journal of Neuroscience, 27(6), 1308–1314. Alain, C., Schuler, B. M., & McDonald, K. L. (2002). Neural activity associated with distinguishing concurrent auditory objects. Journal of the Acoustical Society of America, 111(2), 990–995. Bregman, A. S. (1990). Auditory scene analysis: The perceptual organization of sound. Cambridge: MIT Press. Brunetti, M., Belardinelli, P., Caulo, M., Del Gratta, C., Della Penna, S., Ferretti, A., et al. (2005). Human brain activation during passive listening to sounds from different locations: An fMRI and MEG study. Human Brain Mapping, 26(4), 251–261. Chait, M., Poeppel, D., & Simon, J. Z. (2006). Neural response correlates of detection of monaurally and binaurally created pitches in humans. Cerebral Cortex, 16(6), 835–848. Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3, 201–215. Dougherty, R. F., Cynader, M. S., Bjornson, B. H., Edgell, D., & Giaschi, D. E. (1998). Dichotic pitch: A new stimulus distinguishes normal and dyslexic auditory function. Neuroreport, 9(13), 3001–3005. Erikson, M., & McKinley, R. L. (1997). The intelligibility of multiple talkers separated spatially in noise. In R. H. Gilkey, & T. R. Anderson (Eds.), Binaural and spatial hearing in real and virtual environments (pp. 701–724). New Jersey: Lawrence Erlbaum. Furukawa, S., & Middlebrooks, J. C. (2002). Cortical representation of auditory space: Information-bearing features of spike patterns. Journal of Neurophysiology, 87, 1749–1762.

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