NeuroImage 46 (2009) 1200–1208

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Interaural temporal and coherence cues jointly contribute to successful soundmovement perception and activation of parietal cortex

U. Zimmer a,b,⁎, E. Macaluso a

a NeuroImaging Laboratory, Santa Lucia Foundation, Italyb Center for Cognitive Neuroscience, Duke University, USA

⁎ Corresponding author. Center for Cognitive Neuro90999, Duke University, NC 27708, Durham, USA. Fax: +

E-mail address: ulrike.zimmer@duke.edu (U. Zimme

1053-8119/$ – see front matter © 2009 Elsevier Inc. Aldoi:10.1016/j.neuroimage.2009.03.022

a b s t r a c t

a r t i c l e i n f o

Article history:Received 31 August 2008Revised 27 January 2009Accepted 8 March 2009Available online 19 March 2009

The perception of movement in the auditory modality requires dynamic changes in the input that reaches thetwo ears (e.g. sequential changes of interaural time differences; dynamic ITDs). However, it is still unclear as towhat extent these temporal cues interact with other interaural cues to determine successful movementperception, and which brain regions are involved in soundmovement processing. Here, we presented trains ofwhite-noise bursts containing either static or dynamic ITDs, and we varied parametrically the level of binauralcoherence (BC) of both types of stimuli. Behaviorally, we found that movement discrimination sensitivitydecreased with decreasing levels of BC. fMRI analyses highlighted a network of temporal, frontal and parietalregions where activity decreased with decreasing BC. Critically, in the intra-parietal sulcus and the supra-marginal gyrus brain activity decreased with decreasing BC, but only for dynamic-ITD sounds (BC by ITDinteraction). Thus, these regions activated selectively when the sounds contained both dynamic ITDs and highlevels of BC; i.e. when subjects perceived sound movement. We conclude that sound movement perceptionrequires both dynamic changes of the auditory input and effective sound-source localization, and that parietalcortex utilizes interaural temporal and coherence cues for the successful perception of sound movement.

© 2009 Elsevier Inc. All rights reserved.

Introduction

Accurate processing of movement signals in the auditory modalitycan help inmany daily situations, such as when crossing the street andhaving to discriminate stationary versus moving cars. The perceptionof auditory movement requires dynamic changes of sensory input tothe two ears. Nonetheless it is still unclear exactly what aspects of thebinaural input are critical for detection of the presence of a movingauditory stimulus. For movement faster than 20°/s, the “revisitedsnapshot model” of Grantham (1997) suggests that detection ofposition changes of the sound source over time is critical forperception of movement, thus linking movement perception withspatial localization of sounds. On the other hand, neurophysiologicalevidence indicates that the discharge pattern of neurons, which areselectively responsive to direction of motion, shows broad tuning tostatic spatial locations and differs in one motion direction comparedto the other (e.g. Poirier et al., 1997; Ahissar et al., 1992; cf. Toronchuket al., 1992). Further, psychophysical data in humans reveals specificthresholds for velocity discrimination (Perrott, 1989; Carlile and Best,2002). These latter results suggest the existence of motion-detectionmechanisms beyond location coding.

science, LSRC Rm B242, Box1 919 681 0815.r).

l rights reserved.

One way to address the role of spatial localization in auditoryperception is to manipulate the level of binaural coherence (BC).Variable levels of binaural coherence, such as when multiple soundsources produce similar sounds, can play a role in many everyday lifesituations. One example of this is the perception of the sound of a carthat is approaching in a place with a lot of traffic. Increasing trafficnoise reduces the binaural coherence and makes the localization andmovement perception of the approaching car more difficult, withsignificant and dangerous consequences. Psycho-physiologically,auditory localization in the horizontal plane relies mainly on binauralcues such as timing differences (ITD: interaural time differences:Rayleigh, 1907; Jeffress, 1948, Klump and Eady, 1956; Blauert, 1997)and sound pressure differences (ILD: interaural level differences;Rayleigh, 1907; Feddersen et al., 1957; Blauert, 1997). However, theinterpretation of ITD cues depends on the level of similarity/difference between the inputs presented to the two ears (i.e. thelevel of binaural coherence). Both (static) ITD and BC modulateactivity of coincidence-detecting neurons in the medial superior olive(Goldberg and Brown, 1969; Yin and Chan, 1990), where ITD tuningdecreases with decreasing levels of BC (see also Shackleton et al.,2005; Joris et al., 2006, for related effects in the inferior colliculus; andJoris and Yin, 2007, for review). Psychophysical studieswith stationarysounds demonstrated that only sounds with high levels of BC can besuccessfully localized on the basis of ITD. For example, the deviationbetween perceived and real horizontal sound positions increaseswith decreasing BC (Jeffress et al., 1962), leading to a decrease in

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localization performance (e.g. Saberi and Petrosyan, 2005; see alsoZimmer and Macaluso, 2005).

Accordingly, if sound localization – through processing of static ITD –

is critical for movement perception (cf. “revisited snapshot model”,Grantham, 1997), it is to be expected that movement perception willdeteriorate with decreasing levels of BC. Conversely, if ITD changes (i.e.velocity) over a short time interval are sufficient to trigger motionperception, the manipulation of BC should have little effect on motionperception (i.e. detection of a change without localization, e.g. Perrott,1989). In a human psychophysical study, Saberi and Petrosyan (2005)investigated the role of BCduringdiscriminationof stationary ormovingsounds. Binaural coherence was varied between 1 (same input to bothears) and 0.1 (highly de-correlated inputs) and dynamic changes of ITDwere used to produce movements of different velocities. The resultsshowed a greater impact of decreasing BC on moving than stationarysounds and also that the discriminability of sound movementdeteriorated more rapidly for fast than slow stimuli. The authors wereable to predict subjects' performance, for both stationary and movingstimuli, with a single model that combined ITD and BC information.These modeling results suggest that movement processing in theauditory modality shares the same neural system as (static) soundlocalization, but perhaps not exclusively, as indicated by the greaterdeterioration in detection of sound movement.

A different picture seems to emerge from neuroimaging studiesthat have investigated sound movement processing by the humanbrain. Overall, the results indicate a selective involvement of poster-ior/superior temporal regions and the inferior parietal cortex formoving sounds (Barrett and Hall, 2006; Griffiths et al., 1998; Lewis etal., 2000; Warren et al., 2002; Pavani et al., 2002; but see also Smith etal., 2007). However, several details of the experimental procedurescould have influenced the pattern of activation associated withmovement processing in these studies.

For instance, studies that used passive movement perceptionrevealed activation of the planum temporale, but with only relativelyweak effects in inferior parietal regions (Griffiths et al., 2000;Krumbholz et al., 2005a). On the other hand, studies focusing on theactive perception of sound movement found a greater involvement ofparietal cortex (e.g. Lewis et al., 2000). Furthermore, it should benoted that many previous imaging studies on sound movementcompared moving sounds to sounds at a single central static position(ITD=0, Krumbholz et al., 2005a,b; or evoking perception of centralsound image, Griffiths et al., 1998). Thus, brain areas that activatedselectively for moving stimuli may in fact just process sounds that areperceived to originate from lateralized positions (see also Zatorre etal., 2002; who reported parietal activation already for spatialdiscrimination of static lateralized sounds). A few recent studies onauditory movement have included lateralized stationary sounds as acontrol condition. These revealed activation of posterior auditorycortex and an adjacent temporo-parietal region for sound movement(Barrett and Hall, 2006;Warren et al., 2002; Pavani et al., 2002, but seeSmith et al., 2007 for no difference between these two types ofsounds). These fMRI findings appear to support the hypothesis of adedicated motion perception system in the posterior part of thesuperior temporal cortex and inferior parietal lobule.

All previous neuroimaging studies on sound movement, however,used only high levels of binaural coherence yielding clearly moving orclearly stationary percepts. A question remains about possible linksbetween successful perception of movement and activation of brainareas beyond the posterior auditory cortex (cf. also Zatorre et al.,2002; Zimmer andMacaluso 2005; for related studies using stationarysounds only). Accordingly, here we varied BC during active discrimi-nation of sound movement versus stationary sounds, aiming to studythe interplay between these two types of binaural cues and their rolefor successful perception of sound movement. We orthogonallymanipulated the presence of ITD changes in the auditory stimulus(dynamic versus static) and the level of BC (parametrically, from 1 to

0). To control the level of BC, we presented sounds via headphonesdirectly to the subject's ears, excluding influences of other spectro-temporal cues (e.g. head related transfer function). Subjects perceivedall sounds inside the head, rather than in external space. Nonethelessthis experimental set-up allowed us to assess the role of BC directly onmoving versus stationary discrimination performance. Co-varyingbehavioral performance during the fMRI with brain activity, wesought to distinguish areas where activity decreased with BC(irrespective of static versus dynamic ITD: overall effect of auditoryspatial performance) from areas where ITD and BC interacted toproduce successful movement perception (consistent with a selectivesystem for sound movement perception).

Experimental procedures

Subjects

Thirteen healthy, right-handed subjects participated in a pre-scanning test (see below). Seven of them plus nine additional subjectstook part in the subsequent fMRI experiment (age 20–35 yrs; 7males). After receiving an explanation of the procedures, all subjectsgave written informed consent. The study was approved by theindependent Ethics Committee of the Santa Lucia Foundation(Scientific Institute for Research Hospitalisation and Health Care).

Design

The aim of the fMRI study was to assess the role of interaural cuesfor successful perception of soundmovement and related activation ofparietal and/or temporal brain regions. In particular, we askedwhether changes of ITD over a short time interval (i.e. dynamicITDs) are sufficient to trigger motion perception (and brain activa-tion); or whether auditory motion perception requires both dynamicITDs and high levels of BC. Accordingly, we used a 2×5 factorial designwith ITD type (dynamic vs static) and BC level (5 different coherencevalues) as independent factors.

During fMRI, the 10 event-types resulting from crossing the twofactors (2 ITD types×5 BC levels) were presented in randomised andunpredictable order, using an event-related protocol. On each trial, thesubjects reported whether they perceived a moving or stationarysound by pressing one of two buttons with the right-hand (2AFCprocedure). We used Signal Detection Theory to estimate soundmovement detection sensitivity (d′) for each level of BC. Thisbehavioral measure was then used for fMRI data analysis, allowingus to test for any link between movement perception and changes ofbrain activity.

Before fMRI scanning, we performed a pre-scanning test utilizingthe same procedures as the main fMRI experiment (movementdiscrimination with 10 randomly presented event-types: 2 ITDtypes×5 BC levels). Aim of this test was to verify that the chosenlevels of BC lead to suitable changes of movement discriminationperformance. The test was performed in a quite room, but pre-recorded scanner noise was continuously delivered via headphones,together with the target stimuli.

Stimuli and task

Each trial consisted of a train of 18 successive white-noise pulses(30 ms on, 35 ms off), presented binaurally (total stimulusduration=1135 ms). For dynamic-ITD trials, the ITD of the 18 pulseschanged progressively over a distance from−500 to+500 μs (left-to-right; or from +500 to −500, right-to-left) in steps of 59 μs. Thiscorresponds to a moving stimulus with a velocity of approx. 881 μs/s(i.e. approximately 52°/s, see Kuhn, 1977). For static-ITD trials all 18pulses had the same ITD (within the+500/−500 μs range), resultingin the perception of a stationary sound located in one of 18 positions.

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The utilization of train pulses, rather than continuous stimuli, allowedus to present sounds from exactly the same external positions indynamic and static-ITD trials, while only generating a sense ofmovement in dynamic-ITD trials (Perrott and Strybel, 1997; Strybel etal., 1992). All data analyses averaged the 18 possible spatial positionsof static sounds because we were interested in sound movementperception (dynamic versus static ITDs) rather than the processing ofstatic sounds at different positions (cf. Zimmer and Macaluso, 2005).

BC levels were calculated according to Jeffress and Robinson(1962) and expressed in k-values. In brief, two independent white-noises were mixed to varying degrees for one ear channel (“mixed-sample”) while the other ear received one unchanged white-noisesignal (“constant-sample”). The mixing of the two independentwhite-noises is expressed as follows: WN2=WN1⁎sqrt(k/(1−k)),where WN2 andWN1 are the percentage rate of the two independentwhite-noises and k is the desired value of BC. Five different k-values ofcoherence were used: k=0, k=0.3, k=0.4, k=0.5, k=1. Accord-ingly, for k=[0 0.3 0.4 0.5 1] one ear received %WN1=[100 100 100100 100] and %WN2=[0 0 0 0 0]; while for the second ear %WN1=[065 82 100 100] and %WN2=[100 100 100 100 0]. Therefore to obtaink=1, the same signal (WN1) was delivered to both ears setting WN2to 0% (rather than WN1 to infinity, as implied by the mathematicaldefinition). All sound stimuli were adjusted for equal sound pressurelevel (mean=−36±5 dB [mean±SD]) to exclude any confoundingeffect of dB-differences. The level of BC and ITD type (dynamic orstatic) was randomised on a trial-by-trial basis. The inter-trial intervalwas variable (2135–3135 ms).

During fMRI, sounds were transmitted from two speakers outsidethe scanner to the subject's headphones, via air-conducting tubes. TheMR compatible headphones provide a scanner-noise attenuation ofapprox. 20 dB. This experimental setting produced suitable soundlocalization psychophysical curves in a previous study (Zimmer andMacaluso, 2005) and allowed us to produce variable movementdiscrimination performance as a function of k, in the currentexperiment (see Fig. 1). Each subject underwent 5 separate fMRI-runs of 5.3 min each, overall receiving 300 stimuli with dynamic and300 stimuli with static ITD. On each trial, the subject reportedwhethershe/he perceived amoving or stationary sound by pressing one of twobuttons with the right-hand (2-AFC procedure).

Image acquisition

Imaging was carried out with a 3-T Siemens ALLEGRA (Siemens,Erlangen, Germany). BOLD (blood oxygenation level-dependent)contrast was obtained using echo-planar T2⁎-weighted imaging

Fig. 1. Sound movement discriminability as a function of the level of binaural coherence duringdeviation) of the movement discriminability (d′) for the different levels of binaural coherenceversus stationary sounds decreased. Behavioral performance during fMRI (B)was used to fit theeffect of sound, see also Experimental procedures section).

(EPI). The acquisition of 32 transverse slices gave coverage of thewhole cerebral cortex. Repetition time was 2.08 s and in-planeresolution is 3×3 mm, slice thickness and gap were 2.5 mm and1.25 mm respectively.

It should be noted that our study required intermixing all event-types (static vs dynamic ITD, at different k-levels) in order to obtainvalid behavioral data concerning movement discrimination perfor-mance. This would not be possible using a sparse imaging protocolthat, one hand may facilitate auditory perception, but on the otherwould require several stimuli of the same type to be presented insuccession yielding to predictable sequences of trials.

Data analysis

Psychophysical data (pre-scanning test and during fMRI)On each trial, subjects responded with a button-press, reporting

whether they had perceived a “moving sound” or a “stationary sound”.For each level of BC, we determined the movement detectionsensitivity (d′), considering the presence/absence of dynamic ITDand subjects' responses (movement detected, or not). Thus, wecomputed the number of hits (dynamic ITD, movement percept),misses (dynamic ITD, stationary percept), false alarms (static ITD,movement percept) and correct rejections (static ITD, stationarypercept). Detection sensitivity was computed as the distance betweenthe means of two probability density distributions: d′=z (p[hit])−z(p[false alarm]) (cf. Macmillan and Creelman, 1991).

fMRI dataData were analysed using SPM2 (http://www.fil.ion.ucl.ac.uk).

The first four image-volumes of each run were discarded to allow forstabilization of longitudinal magnetization (leaving 890 volumes).Pre-processing included rigid-body transformation (realignment) andslice-timing to correct for head movement and slice-acquisitiondelays. The images were normalized to MNI-space using the meanof all functional volumes and smoothed isotropically to 10 mm(FWHM). Statistical inference was based on a random effectsapproach (Penny et al., 2003).

Inference comprised two steps. First, each subject's datawere best-fitted at every voxel using a combination of effects of interest. Theeffects of interest were the timing of the 10 event-types (given bycrossing the two stimulus factors: 2 ITD types×5 BC levels). Allstimulus-functions were convolved with the SPM2 standard haemo-dynamic response function. For each subject, linear compounds(contrasts) were used to determine subject-specific activations forthe ten event-types, averaging across fMRI-runs. This resulted in ten

the pre-scanning test (A) and during fMRI (B). The plots show the mean (+/−standard(BC). As coherence decreased (lower k-levels), the subjects' ability to discriminate movingfMRI data, after removing themean value (i.e. orthogonalizationwith respect of the overall

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contrast-images per subject. For group analyses, the contrast-imagesfrom all 16 subjects were submitted to an ANOVA modeling 10conditions (2 ITD types×5 BC levels). Linear compounds (contrasts)were used to compare condition-effects in this multiple regressionmodel, now using between-subjects variance. Correction for non-sphericity (Friston et al., 2002) was used to account for possibledifferences in error variance across conditions and any non-indepen-dent error terms associated with repeated measures.

The aim of the study was to investigate possible interactionsbetween different types of interaural cues (ITD and BC) for theperception of auditory motion. Because of our central interest in therelationship between behavior and brain activity we used detectionsensitivity measures (d′, assessed during fMRI scanning) to test for co-variation between brain activity and movement perception. We firsttested for any modulation of brain activity by d′-coefficients, poolingacross ITD types (dynamic and static). Note that movement detectionsensitivity (d′) changed systematically with changes of BC levels(correlation coefficient=0.79). Therefore this contrast sought tohighlight all brain regions sensitive to binaural coherence cues (maineffect of coherence). The d′ coefficients were mean-adjusted toorthogonalize the effect of sensitivity with respect of the overall

Fig. 2. Main effect of binaural sound coherence. Central panel: This shows areas where actdynamic). This revealed modulation of brain activity in a bilateral network, including a clussupra-marginal gyrus (SMG) and dorsally to the intra-parietal sulcus. In addition, activity inlevel of BC. Side panels: Signal plots for the activation-peaks in the insulae (A, B) and posteriarbitrary units (i.e. changes of activation are computed with respect of the mean signal acrthreshold is p-corrected=0.05, at the voxel-level.

effect of task (i.e. controlling for any process that is common to allevent-types, e.g. manual responses). For this comparison the SPMthreshold was set to p-correctedb0.05 (Family Wise Error at thevoxel-level).

We then tested for the critical interactions betweenBC level and ITDtype, again usingmean-adjusted d′ coefficients to index the coherenceeffect. Note that any influence of the scanner background noise will bematched in these interaction contrasts. This interaction highlightsbrain areas activated selectively by sounds that contained the criticalcombination of ITD and coherence cues resulting in auditory motionperception (i.e. sounds with dynamic ITD and high levels of BC). Forthis comparison, corrected p-values (b0.05, FWE-voxel-level) wereassigned using a small volume correction procedure (Worsley et al.,1996). This correction procedure is based on Gaussian random fieldtheory and corrected p-values are computed for each single voxel. Thevolume of interest for the small volume correction included all voxelsshowing a main effect of binaural coherence (see above).

For completeness, we also tested for the main effect of dynamicversus static ITD, irrespective of BC. The SPM threshold was set to p-correctedb0.05 (Family Wise Error at the voxel-level), for the wholebrain.

ivity decreased with decreasing binaural coherence, irrespective of ITD type (static orter that extended from the posterior superior temporal sulcus (STG), anteriorly to thethe insulae, plus dorsal and ventral pre-motor areas bilaterally also co-varied with theor STG (C, D). The level of activation is adjusted to a mean of zero, and it is expressed inoss the 10 conditions). Error bars represent 90% confidence intervals (C.I.). The display

Table 1Main effect of BC.

Cluster size p-corrected MNI coordinates z-value

Right hemispherepSTG 3012 b0.001 66 −38 14 6.50Supra-marginal gyrus b0.001 58 −35 30 6.32Intra-parietal sulcus b0.001 40 −46 46 6.14dPM 24 0.017 30 −2 62 4.76vPM 714 b0.001 58 4 34 5.56Insula 196 0.001 32 26 −6 5.36

Left hemispherepSTG 78 0.010 −62 −22 16 4.88Supra-marginal gyrus 0.012 −60 −18 28 4.84Intra-parietal sulcus 1051 b0.001 −36 −44 50 6.10dPM 382 b0.001 −26 −10 62 6.24vPM 48 0.005 −60 6 26 5.05Insula 86 0.003 −32 22 −4 5.14

Main effect of BC. Anatomical location, cluster size, corrected p-values, peak coordinatesand z-values for the main effect of BC (i.e. activity decreasing with decreasing k-level,weighted by d′), independent of sound types (static or dynamic ITD). p-values arecorrected for multiple comparisons at the voxel-level (Family Wise Error), consideringthe whole brain as the volume of interest.

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Results

Psychophysical data during pre-scanning test and fMRI

The task of the subjects was always to respond on each trialreporting the perception of “moving sound” or “stationary sound”(2AFC-procedure) irrespective of BC. For each subject and BC level, themovement detection sensitivity (d′) was computed using hits, misses,false alarms and correct rejections.

In the pre-scanning test the group mean d′ as a function of kwere:d′(1)=3.60 SD(0.58); d′(0.5)=3.30 SD(0.65); d′(0.4)=1.42 SD(0.84); d′(0.3)=0.67 SD(0.64); d′(0)=0.45 SD(0.64), see Fig. 1A. Arepeated-measures ANOVA revealed an effect of BC on movementdetection performance (F(4,27.89)b0.001). Paired t-tests showedsignificant differences between k=0.5 and k=0.4 (pb0.001; t(12)=6.17), but also k=0.4 and k=0.3 (p=0.002; t(12)=3.52). Further-more, there was a statistical trend between k=0.5 and k=1 (t(12)=1.72; p=0.055). One-sample t-tests showed performance abovechance even for k=0.3 (p=0.003; t(12)=3.744) and k=0(p=0.016; t(12)=2.816). Thus, the pre-scanning test indicated thatthe chosen coherence levels gave rise to suitable changes ofdiscrimination performance with changing BC.

During fMRI, the group mean d′ as a function of k were: d′(1)=2.87 SD(1.3); d′(0.5)=2.94 SD(1.26); d′(0.4)=0.54 SD(0.44); d′(0.3)=0.48 SD(0.56); d′(0)=0.30 SD(0.55); see Fig. 1B. A repeated-measures ANOVA revealed a highly significant effect of BC level onmovement detection (F(4, 29.32)=55.06, pb0.001), demonstratingthat the perception of movement deteriorated with decreasing BCduring fMRI. Paired-tests confirmed significant differences betweenk=0.5 and k=0.4 (pb0.001; t(15)=3.04), but unlike in the pre-scanning test, now performance for k=0.4 versus k=0.3 did notdiffer significantly (p=0.355; t(15)=0.38). Nonetheless, one-samplet-tests showed performance above chance for k=0.4 (pb0.001;t(15)=4.95), k=0.3 (p=0.004; t(15)=3.43) and k=0 (p=0.049;t(15)=2.14). While favoring a more gradual change of d′ duringfMRI, we should stress that our aimwas to modulate the ability of thesubjects to detect dynamic vs static ITD, rather than to define a precisevalue of BC that permit such discrimination. Accordingly, behavioraldata during fMRI still fulfilled our main aim showing interplaybetween of BC and ITD cues for movement perception.

fMRI data

The fMRI analyses first identified brain regions modulatedaccording to the level of BC, averaging across dynamic and staticITDs. Behaviorally only stimuli with high BC and dynamic ITD elicitedthe percept of sound movement during fMRI. Therefore, within theseregions, we then tested for a selective effect of BC on soundscontaining dynamic ITDs (ITD×BC interaction). To emphasise thelink between the behavior percept and changes of brain activity, allour analyses utilized movement detection sensitivity (d′, rather thank-values) as the contrast weights in the multiple regression model.

This parametric analysis revealed a bilateral network including acluster that extended from posterior STG (pSTG), anteriorly to thesupra-marginal gyrus (SMG) and dorsally to the intra-parietalsulcus (IPS; see central panel Fig. 2; and Table 1). In addition, thelevel of BC co-varied with activity in dorsal and ventral pre-motorareas bilaterally, plus the insulae. It should be noted that thisparametric test showed no change of activity in motor cortex,confirming that the d′ adjustment procedure (see Experimentalprocedures section) successfully removed any overall effect ofauditory stimulation and task (i.e. activations common for all 10event-types).

Fig. 2 shows the signal plots for two representative areas of the BC-modulated network (insulae in panels A–B; and posterior STG inpanels C–D). The plots indicate that activity decreased with decreas-

ing BC. In these regions, the effect of binaural coherence was observedirrespective of ITD type, with a decrease of brain activity withdecreasing BC for both dynamic (bars 1–5, in each signal plot) andstatic-ITD sounds (see bars 6–10). These findings demonstrate that anextensive network is implicated in the processing of binauralcoherence cues. Nonetheless, the presence of a BC effect on static-ITD sounds indicates that these changes in brain activity do not relateselectively to the perception of sound movement.

To specifically investigate areas that combined ITD and BC togenerate auditory motion perception we tested for interactionsbetween ITD types and BC levels (again using d′ values, as contrastweights in the multiple regression model). Specifically, we set up aninteraction contrast to highlight regions showing larger effects of BCwith dynamic ITDs thanwith static-ITD stimuli. Statistical significancefor this interaction contrast was restricted to voxels in a volume ofinterest of the main effect of BC (see black outlines in Fig. 3). Thisrevealed a selective modulation of activity in the intra-parietal sulcusand supra-marginal gyrus (SMG; see Fig. 3 and Table 2). In the leftSMG this effect failed to fully meet our criteria for statisticalsignificance because the main effect of BC (averaged across staticand dynamic ITDs) was not significant in these voxels (see blackoutlines in the central panel of Fig. 3). Nonetheless, we should notethat the anatomical location of the critical interaction between BC andITD was remarkably symmetrical in the two hemispheres (see Fig. 3,central panel). Furthermore, the pattern of activation in left SMG washighly consistent with its homologous region in the right hemisphere(cf. panels C and D, in Fig. 3).

The signal plots from the intra-parietal sulcus (Figs. 3A–B) andSMG (Figs. 3C–D) show that activity decreased with decreasing BC(and decreasing detection sensitivity, d′), but only when the stimulicontained dynamic ITDs (see the five leftmost bars of each signalplot, Fig. 3). In contrast, sounds with the same binaural coherencelevels but without change of ITD (static-ITD trials) elicited a similarlevel activation for all five BC levels (see the five rightmost bars ofeach signal plot, in Fig. 3). Thus, activity in IPS and SMGmirrored theability to perceive auditory motion, with maximal activation forsounds containing dynamic ITD presented at high levels of BC. Theseresults indicate that IPS and SMG combine different types ofinteraural cues (dynamic ITD and BC) to generate sound movementperception.

Finally we tested for the main effect of dynamic versus static ITD,across BC levels. This showed a pattern of activation similar to themain effect of BC, with activation of the posterior STG (significantonly in the right hemisphere), intra-parietal sulcus (IPS), supra-

Fig. 3. Interactions between binaural coherence and ITD type. Top and central panels: 3D rendering (top panel), coronal and transverse sections (central panel) showing the intra-parietalsulcus (IPS) and supra-marginal gyrus (SMG), where activity decreasedwith decreasing BC selectively for soundswith dynamic ITDs. In the coronal and transverse sections, the activationmap is superimposed on the average anatomy of the participants. Corrected p-values were assigned considering all voxels that showed amain effect of BC (black outlines, cf. also Fig. 2) asthe volume of interest. Side panels: Signal plots for the IPS (A and B) and SMG (C andD) showing selective activation for soundswith high levels of BC and dynamic ITD (see bars 1 and 2 ineach of four signal plots). Accordingly, the activation pattern in these regions mirrored subjective movement perception. The level of activation is adjusted to a mean of zero and it isexpressed in arbitrary units (i.e. changes of activation are computedwith respect of themean signal across the 10 conditions). Error bars represent 90% CI. The display thresholdwas set top-uncorrected=0.001, in order to also show the interaction effect in the left SMG that did not survive the corrected threshold (white bars in panel C, see also Table 2).

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marginal gyrus (SMG) and the insulae (see Table 3). The presence ofthis main effect in IPS and SMG is not surprising given that dynamic-sounds at high levels of BC activated these regions mostly (see signal

Table 2Interaction between BC and ITD.

p-corrected MNI coordinates z-value

L Intra-parietal sulcus b0.001 −46 −36 56 5.84R Intra-parietal sulcus 0.029 34 −42 46 3.78L Supra-marginal gyrus n.a. −52 −24 16 3.49R Supra-marginal gyrus 0.006 68 −22 18 4.20

Interaction between BC and ITD. The effect of BC (k-level weighted by d′) that wasspecific for sounds containing changes of ITD (dynamic ITD); see also Figs. 2A–D.p-values are corrected at the voxel-level, considering areas activating for themain effectof BC (see Fig. 2), as volume of interest. The peak in the left SMG (in italics) was notwithin the volume of interest, but it showed a pattern of activation similar to the rightSMG (see also Figs. 3C–D) and is reported here for completeness. (L/R: Left/Righthemisphere; n.a.: not applicable, because not in the volume of interest).

plots in Fig. 3). The main effect of dynamic-sounds in anterior regionscan be seen in Fig. 2, where the signal plot of the insulae (panels Aand B) shows that both main effects combined within this region:activity increased progressively for the 5 levels of BC (dynamic ITD:bar 5 to 1; static ITD: bars 10 to 6); but also that overall the averageactivity for dynamic-ITD sounds (i.e. the mean of bars 1–5) wasgreater than the average activity for static-ITD sounds (mean of bars6–10).

Discussion

In this study we investigated the link between successfulperception of sound movement and the activation of brain areasinvolved in auditory spatial processing. We manipulated orthogonallythe level of binaural coherence (BC) and the presence of ITD changesin auditory stimuli (dynamic versus static) during active discrimina-tion between moving and stationary sounds. This allowed us to

Table 3Main effect of dynamic versus static-ITD sounds.

Cluster size p-corrected MNI coordinates z-value

Right hemispherepSTG 1057 b0.001 66 −22 20 3.79Supra-marginal gyrus b0.001 62 −38 26 4.23Intra-parietal sulcus b0.001 44 −46 46 3.32Insula 833 0.001 36 22 −8 5.46

Left hemispherepSTG n.s. −64 −20 16 3.44Supra-marginal gyrus 1874 b0.001 −62 −24 40 4.17Intra-parietal sulcus b0.001 −48 −40 58 5.73dPM 382 b0.001 −26 −10 66 5.14Insula 546 0.002 −34 22 −4 4.61

Main effect of dynamic vs. static-ITDs sounds. Anatomical location, cluster size,corrected p-values, peak coordinates and z-values for the main effect of dynamic minusstatic-ITD sounds. p-values are corrected for multiple comparisons at the voxel-level(Family Wise Error), considering the whole brain as the volume of interest. The peak inthe left posterior STG (in italics) was not significant (n.s.) after correction for multiplecomparisons, but it showed a pattern of activation similar to the right pSTG and isreported for completeness only.

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investigate how these two interaural cues are combined for successfulperception of sound movement (ITD×BC interaction). Psychophysicalresults (pre-scanning test, plus behavior during fMRI) demonstratedthat the ability to discriminate between static and moving sounds inthe horizontal plane deteriorated with decreasing BC (Fig. 1).Concurrently, fMRI data revealed BC-modulated activity in severalbrain regions beyond primary auditory cortex, but with differentpatterns of activation depending on the presence or absence ofdynamic-ITD cues. We found that activity in a large network of brainareas (including posterior STG and supra-marginal gyrus (SMG),dorsal and ventral pre-motor areas, IPS and insulae, see Fig. 2)increased with increasing BC. Critically, BC interacted with ITD cuesjointly affecting activity in SMG and IPS. In these regions maximalactivity was observed for sounds delivered at high levels of BC whencontaining dynamic ITDs (Fig. 3), thus mirroring subject perception ofsound movement. In summary, our behavioral and fMRI resultssuggest that movement perception in the auditory modality requires acombination dynamic changes of interaural time differences (ITD) andhigh levels of binaural coherence; and that this is associated withactivation of IPS and SMG.

Both pre-scanning and behavioral data during fMRI demonstratethat the two interaural cues (ITD and BC) jointly contribute to elicitthe perception of auditory motion. While during the pre-scanning testthe relationship between BC (k) and performance (d′) was gradualwith changes of d′ over the entire range of k, during fMRI there was anabrupt change of performance between k=0.5 and k=0.4. Thus,despite our best attempts to select suitable k-levels for fMRI (note thatthe pre-scanning test included simulated scanner background), wefailed to obtain a full range of d′ variation during scanning. Greater d′variability across k-values would be better for the parametric analyses,but the distribution obtained here does not invalidate our results. Onthe contrary, the parametric manipulation of k allowed us avoidingany assumption about processes occurring in the active condition butnot in the baseline, as it is typically the case in categorical designs(active vs. baseline condition; see Friston et al., 1996). Thus, even if d′did not change gradually, the behavioral data still demonstrate aninterplay between of BC and ITD cues for movement perception.

Our behavioral findings are in agreement with previous workshowing that only dynamic-ITD sounds delivered at high levels of BCproduce the perception of auditory motion (Saberi and Petrosyan,2005). This suggests a key role of sound localization for successfulauditory movement perception (see Grantham, 1997; see also Carlileand Best, 2002, showing that the ability to discriminate the speed ofmoving sounds increases when the start and end position of a

movement can be used for velocity discrimination). However, Saberiand Petrosyan (2005) also demonstrated a greater impact ofdecreasing BC on moving than stationary sounds, and that movementdetection sensitivity decreasedmore rapidly for fast than slow stimuli.In agreement with this, here we found lower movement detectionperformance around k=0.4, compared with a previous study onlocalization of static sounds including exactly the same experimentalapparatus and fMRI scanning sequences (Zimmer and Macaluso,2005). These findings suggest that additional mechanisms other thansound localization may also contribute to sound movement percep-tion. For example, the involvement of “velocity-detectors” has beensuggested both in animal (Poirier et al., 1997) and human studies(Xiang et al., 2005) of auditory movement processing.

Our imaging data showed selective activation of parietal cortex(IPS plus SMG) for dynamic-ITD sounds delivered at high levels of BC:i.e. when subjects perceived soundmovement inside the head. Severalprevious studies investigated brain activity associated with soundmovement processing (e.g. Barrett and Hall 2006; Baumgart et al.,1999, Lewis et al., 2000; Poirier et al., 2005; Smith et al., 2007), butnone of these addressed explicitly the issue of movement perception.For example, Baumgart et al. (1999) used detection of an amplitude-modulated gap in moving sounds during fMRI, whereas Barrett andHall (2006) asked subjects to detect pitch and coherence in movingand static sounds. Thus, subjects' attention was focused on soundfeatures other than movement. In another fMRI study (Lewis et al.,2000), subjects had to discriminate the velocity of auditory stimuli,thus explicitly attending to sound movement. Lewis' study revealedactivation mainly of auditory and parietal cortices, the latter includingIPS. Other neuroimaging studies have compared moving versusstationary sounds (Smith et al., 2007; Pavani et al., 2002; Poirier etal., 2005; Warren et al., 2002; see also Ducommun et al., 2002, forrelated EEG studies). In these studies subjects had to make left/rightdecisions about the spatial position of stationary sounds, or theyreported the direction of moving sounds, or they passively listened tothe stimuli; again not explicitly measuring behavioral sensitivity tosound movement. Further, in some of these studies moving andstationary sounds were alternated in blocks (Poirier et al., 2005;Ducommun et al., 2002) or in pairs of identical stimulus conditions(Smith et al., 2007). Accordingly, subsequent stimuli did not needmovement versus static decisions as they could be automaticallycategorized by the identity of the preceding stimulus.

The overall picture emerging from these studies suggests thatposterior temporal areas and parietal cortex are both involved insound movement processing. However, the exact contribution ofposterior temporal versus parietal regions remains somewhat under-specified. Griffiths and Warren (2002) proposed a multi-stage modelof auditory processing, suggesting that the planum temporale (PT)acts as a computation al hub for the analysis of complex spectro-temporal information, feeding the results of these computations tohigher-order areas. In this context, we suggest that both static anddynamic-sounds require processing of spatial information derivedfrom binaural cues (ITD at high levels of binaural coherence). Theresults of this initial computation will engage higher-order regions inparietal cortex (IPS and SMG) selectively when additional processingabout the dynamic spatial aspects of the stimuli becomes possible (i.e.movement perception at high BC).

Correspondingly, we found a common effect of BC level for bothstatic and dynamic ITD, plus a main effect of dynamic-ITD sounds inposterior temporal cortex. Processing within PT would be importantfor the analysis of auditory motion, but it may not be strictly linked toperception itself and could be considered a task-independent, pre-attentive stage. This would include an initial “automatic” representa-tion of auditory spatial features common for both moving and staticsounds (Deouell et al., 2007), also explaining why a few previousstudies found overlapping activation for moving and static soundsthere (Smith et al., 2004; Smith et al., 2007; always using high BC

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sounds). It should be noted that the processing of binaural informa-tion is likely to start even at lower levels within the auditory pathway.For instance, neurons in the medial superior olive and the inferiorcolliculus process ITD and have tuning curves that are modulated bythe level of BC (Joris and Yin, 2007; see also McAlpine et al., 2000, onthe effect of dynamic changes of interaural cues in these regions). Inthe owls' midbrain, increasing of BC leads to a decline of the neuronsITD selectivity (Saberi et al., 1998). Further, this decrement correlateswith decreasing localization performance (Saberi et al., 1998),indicating that changes of BC can influence ITD processing alreadyat early stages within the binaural system.

On the other hand, the involvement of parietal regions may reflecthigher-level perceptual factors (as shown here, see also Griffiths et al.,1998), task-related factors and attention. So far, the role of attentionduring sound movement perception has not been investigateddirectly. A recent fMRI study (Salmi et al., 2007) showed a specificinvolvement of inferior parietal regions during maintenance andorienting of attention to static sounds. Further, selective attention toposition versus pitch using static sounds was found to modulateevent-related brain potentials thought to originate in the inferiorparietal cortex (Degerman et al., 2008). Additional studies arerequired to formally address the role of attention on sound movementprocessing, for example comparing directly attended versus unat-tended sound movement, with identical sensory input.

In summary, our findings are in agreement with previousneuroimaging studies showing movement-specific activation inparietal cortex. Our results go beyond previous studies highlightingthe critical interplay between dynamic-ITD and BC binaural cues. Weshow that both cues are required to perceive auditory movement andto activate the supra-marginal gyrus (SMG) and the intra-parietalsulcus (IPS). These results suggest that dynamic ITDs are not sufficientto trigger motion perception and that processing of position informa-tion is necessary, but not sufficient, for motion perception in theauditory modality. Accordingly, successful motion perception entailsthe analysis of specificmotion parameters (e.g. dynamic ITDs) that canbe computed only after successful extraction of spatial informationfrom the sensory input.

Acknowledgments

The Neuroimaging Laboratory is supported by The Italian Ministryof Health. We thank R. Frackowiak and Sarah Donohue for their helpon the manuscript.

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