Seediscussions,stats,andauthorprofilesforthispublicationat:https://www.researchgate.net/publication/263815769

Humancorticalresponsestoslowandfastbinauralbeatsrevealmultiplemechanismsofbinauralhearing

ArticleinJournalofNeurophysiology·July2014

DOI:10.1152/jn.00224.2014·Source:PubMed

CITATION

1

READS

212

5authors,including:

BernhardRoss

UniversityofToronto

138PUBLICATIONS4,983CITATIONS

SEEPROFILE

ShahabJamali

UniversityofToronto

12PUBLICATIONS53CITATIONS

SEEPROFILE

TakakoFujioka

StanfordUniversity

28PUBLICATIONS1,052CITATIONS

SEEPROFILE

Allin-textreferencesunderlinedinbluearelinkedtopublicationsonResearchGate,

lettingyouaccessandreadthemimmediately.

Availablefrom:BernhardRoss

Retrievedon:20September2016

doi:10.1152/jn.00224.2014 112:1871-1884, 2014. First published 9 July 2014;J NeurophysiolTakako FujiokaBernhard Ross, Takahiro Miyazaki, Jessica Thompson, Shahab Jamali andbeats reveal multiple mechanisms of binaural hearingHuman cortical responses to slow and fast binaural

You might find this additional info useful...

71 articles, 19 of which can be accessed free at:This article cites /content/112/8/1871.full.html#ref-list-1

including high resolution figures, can be found at:Updated information and services /content/112/8/1871.full.html

can be found at:Journal of Neurophysiologyabout Additional material and information http://www.the-aps.org/publications/jn

This information is current as of October 16, 2014. 

American Physiological Society. ISSN: 0022-3077, ESSN: 1522-1598. Visit our website at http://www.the-aps.org/.(monthly) by the American Physiological Society, 9650 Rockville Pike, Bethesda MD 20814-3991. Copyright © 2014 by the

publishes original articles on the function of the nervous system. It is published 12 times a yearJournal of Neurophysiology

on October 16, 2014

Dow

nloaded from on O

ctober 16, 2014D

ownloaded from

Human cortical responses to slow and fast binaural beats reveal multiplemechanisms of binaural hearing

Bernhard Ross,1,2 Takahiro Miyazaki,1 Jessica Thompson,3 Shahab Jamali,1 and Takako Fujioka4

1Rotman Research Institute, Baycrest Centre, Toronto, Ontario, Canada; 2Department of Medical Biophysics, University of Toronto,Toronto, Ontario, Canada; 3International Laboratory for Brain, Music and Sound Research, Department of Psychology, University ofMontreal, Montreal, Quebec, Canada; and 4Center for Computer Research in Music and Acoustics, Stanford University, Stanford,California

Submitted 21 March 2014; accepted in final form 7 July 2014

Ross B, Miyazaki T, Thompson J, Jamali S, Fujioka T. Humancortical responses to slow and fast binaural beats reveal multiplemechanisms of binaural hearing. J Neurophysiol 112: 1871–1884,2014. First published July 9, 2014; doi:10.1152/jn.00224.2014.—When two tones with slightly different frequencies are presented toboth ears, they interact in the central auditory system and induce thesensation of a beating sound. At low difference frequencies, weperceive a single sound, which is moving across the head between theleft and right ears. The percept changes to loudness fluctuation,roughness, and pitch with increasing beat rate. To examine the neuralrepresentations underlying these different perceptions, we recordedneuromagnetic cortical responses while participants listened to bin-aural beats at a continuously varying rate between 3 Hz and 60 Hz.Binaural beat responses were analyzed as neuromagnetic oscillationsfollowing the trajectory of the stimulus rate. Responses were largest inthe 40-Hz gamma range and at low frequencies. Binaural beat re-sponses at 3 Hz showed opposite polarity in the left and right auditorycortices. We suggest that this difference in polarity reflects theopponent neural population code for representing sound location.Binaural beats at any rate induced gamma oscillations. However, theresponses were largest at 40-Hz stimulation. We propose that theneuromagnetic gamma oscillations reflect postsynaptic modulationthat allows for precise timing of cortical neural firing. Systematicphase differences between bilateral responses suggest that separatesound representations of a sound object exist in the left and rightauditory cortices. We conclude that binaural processing at the corticallevel occurs with the same temporal acuity as monaural processingwhereas the identification of sound location requires further interpre-tation and is limited by the rate of object representations.

binaural beat; binaural hearing; sound localization; opponent-channelcode; hemispheric asymmetry; gamma oscillation; steady-state re-sponses; phase synchrony; magnetoencephalography; auditory cortex

BINAURAL HEARING based on interaural time differences (ITDs)is important for multiple perceptual abilities such as localizingsound in the horizontal plane (Wightman and Kistler 1992) aswell as improving speech understanding in noise throughsegregating sound sources in space (Hawley et al. 2004). Bothperceptual qualities show noticeable different temporal dynam-ics. Perception of sound motion is limited in speed by a timeconstant of several hundred milliseconds or �3 Hz for periodicmovements (Grantham and Wightman 1978). In contrast, bin-aural temporal modulation, important for speech understand-ing, is perceived with high temporal acuity, similar to thesensitivity for monaural temporal modulation (Siveke et al.

2008). This suggests that multiple levels of temporal process-ing of binaural cues exist at the cortical level.

While birds use multiple channels of ITD detection andestablish a topographic map of sound locations at the level ofthe auditory brain stem (Carr and Konishi 1990; Konishi2003), mammals use only a single channel of coincidencedetection for each hemisphere and encode the sound locationthrough asymmetry of activation in broadly tuned bilateralchannels (Grothe et al. 2010). This opponent-channel modelwas supported by the finding of spatially selective neurons inthe inferior colliculus (McAlpine et al. 2001) and the auditorycortex (Stecker et al. 2005). How this encoding of binauralcues is interpreted at the cortical level is still an open researchquestion. Besides generally larger cortical responses contralat-eral to the sound location, it seems unlikely that a spatial mapis solely based on hemispheric imbalance. For example, thatthe right hemispheric is dominantly involved in sound local-ization has been concluded from findings that spatial neglectpatients with right hemispheric lesions are often unable tolocalize sound (Zimmer et al. 2003). However, spatial hearingis commonly preserved if a unilateral lesion is confined to theauditory cortex, suggesting that spatial maps exist in bilateralauditory cortices (Zatorre and Penhune 2001). Similar findingsof spared sound lateralization have been reported in patientswith auditory cortex lesions, in contrast to more general defi-cits in dichotic listening, which were found in patients withextensive unilateral lesions. A recent TMS study demonstratedparallel processing of sound identity features in anterior audi-tory cortex and sound location in posterior auditory cortex(Ahveninen et al. 2013).

Thus it seems that opponent-channel coding of sound isalready established at the level of the inferior colliculus, andthe auditory cortex may have the role of an overarchinginterpreter for perception. Observing how auditory corticesrespond to spatial hearing may inform about underlying neuralmechanisms at and below the auditory cortex. Several recentstudies of auditory cortex responses provided direct evidencefor the opponent-channel model using stimuli that specificallymanipulated ITD (Magezi and Krumbholz 2010), recordingauditory evoked potentials in sound field stimulation (Briley etal. 2013), and using a stimulus adaptation paradigm in MEG(Salminen et al. 2009). Thus our aim was to expand on theprevious research and use binaural beats and acoustic beatstimuli to study the cortical processes of ITD across a widerange of frequencies.

Address for reprint requests and other correspondence: B. Ross, RotmanResearch Inst., Baycrest Centre, 3560 Bathurst St., Toronto, ON, Canada M6A2E1 (e-mail: bross@research.baycrest.org).

J Neurophysiol 112: 1871–1884, 2014.First published July 9, 2014; doi:10.1152/jn.00224.2014.

18710022-3077/14 Copyright © 2014 the American Physiological Societywww.jn.org

on October 16, 2014

Dow

nloaded from

EEG and MEG are the methods of choice for examiningtime-sensitive cortical processes in humans because of theirhigh temporal resolution. Previous EEG and MEG studies oncortical responses to ITD processing reported either transientresponses to sudden changes in the interaural time or phaserelation (Chait et al. 2005, 2007; Jones et al. 1991; McEvoy etal. 1990; Ross et al. 2007a, 2007b; Schröger and Wolff 1996;Soeta et al. 2004) or steady-state responses evoked with peri-odic stimulation (Dajani and Picton 2006) and directly withbinaural beating (Draganova et al. 2008; Karino et al. 2006;Schwarz and Taylor 2005) to address the temporal dynamics ofbinaural hearing. However, these studies have never addressedsystematically how frequency-dependent processes of binauralhearing are differently represented in human auditory cortex.

In this study, we used the binaural beat paradigm for study-ing binaural processing at slow and fast rates. Dichotic presen-tation of two pure tones with slightly different frequencies f1and f2 induces a rhythmic sensation at the difference frequency�f � f2 � f1, which is termed the binaural beat (Stewart 1917).Perception of the binaural beat requires neural interaction. Incontrast, the physical superimposition of the same tones resultsin a beating sound, synonymously termed the physical beat,acoustic beat, or monaural beat. Therefore, sometimes thedistinction is made between the “central” (binaural) beat andthe “peripheral” (acoustic) beat. Psychoacoustical studies haveshown that the perceptual quality of the binaural beat dependsprimarily on the frequency region of the tones and on thefrequency difference between the tones (Licklider et al. 1950;Perrott and Nelson 1969). At f1,f2 � 500 Hz, where thebinaural effects are strongest, we can distinguish between fourtypes of perception, depending on the beat rate. At �f below�3 Hz, the binaural beat is perceived as rhythmic change in thelateralization of the sound, sometimes termed a rotating tone(Perrott and Musicant 1977). As �f increases, the percept ofmotion changes to fluctuation of loudness and becomes a roughsound above 20–25 Hz. At higher �f, finally, two separatetones are perceived with different pitches in each ear (Licklideret al. 1950). The transitions between the various percepts arenot sharply defined. The various binaural beat percepts primar-ily correspond to different qualitative perceptions of ampli-tude-modulated (AM) sound or the acoustic beat, which alsodepend on the modulation frequency or �f, respectively. Below�3 Hz, distinct sound bursts are perceived as single auditoryevents. The AM bursts fuse into a sound stream with fluctu-ating amplitude when the modulation frequency increases. Arough buzzing sound is perceived above �25 Hz, and at higherAM frequencies the spectral components are resolved andperceived as distinct pitches. More recent studies have shownthat binaural beat perception is not limited to tonal stimuli andcan be created by binaural noise stimuli, in which spectralphase and amplitude components are transposed slightly in oneear relative to the other (Akeroyd 2010; Dietz et al. 2008;Siveke et al. 2008). Interestingly, the salience of sound motionat low frequencies may be even more pronounced for noisethan for pure tones.

When using the binaural beat stimulus, it is important toseparate characteristics of the cortical responses that reflect thegeneral processing of rhythmic sound and those that reflectspecific properties of binaural hearing. For this reason, severalprevious studies compared cortical responses to binaural andmonaural beats (Draganova et al. 2008; Pratt et al. 2009, 2010).

One limitation of those studies was that only a single beat rateor a small number of beat rates was investigated. Conse-quently, it is unknown whether the results found at differentfrequencies in those studies, especially about hemisphericasymmetries of response amplitudes and phases, were causedby different experimental approaches or truly reflect the codingschemata for both the monaural and the binaural beats acrossthe range of beat rates. Therefore our main experimentalapproach was to compare brain responses to the acoustic beatand the binaural beat elicited by two-tone complexes whilecontinuously sweeping the beat frequency between 3 Hz and60 Hz.

When comparing brain responses to both binaural andacoustic beating, one should consider the different saliences ofthe two types of beat sensation. The perceptual strength of thebinaural beat is relatively weak compared with a same-inten-sity monaural two-tone complex. For matching the sensationstrength of a binaural beat with the loudness fluctuation of anAM sound, the modulation index m was varied in severalstudies. In the 500-Hz range and at beat rates between 3 Hz and4 Hz, a matching AM depth of m � �25 dB was found atstimulus intensities between 30 dBSL and 60 dBSL (Groen1964; Grose et al. 2012; Rutschmann and Rubinstein 1965).This means that about �5% amplitude fluctuation in the AMsound is sufficient to produce a sensation strength equivalent tothat of the binaural beat.

For our experimental design, we had to choose whether tomatch the sensation strength of an AM sound for the acousticbeat stimulation, which would allow a fair quantitative com-parison of binaural beat and acoustic beat responses. Alterna-tively, we chose to use same-intensity two-tone complexes,which resulted in noticeably larger responses for the acousticbeat. At first, this allowed us to study the temporal dynamics ofthe cortical responses evoked by the acoustic beat across awide frequency range, the results of which have been reportedrecently (Miyazaki et al. 2013). In the present study, weanalyzed the binaural beat responses in the frequency domain,which improved the signal-to-noise ratio through integrationover time. This approach allowed a detailed comparison of thebinaural beat responses and acoustic beat responses across beatrates between 3 Hz and 60 Hz.

MATERIALS AND METHODS

Participants. Fifteen healthy adults (7 women, 8 men) aged 19–40yr (mean 24.4 yr) participated in this study. Hearing thresholdsbetween 250 Hz and 8,000 Hz were below 20-dB normal hearing astested in a soundproof audiometric booth with a clinical audiometer(GSI 61, Grason-Stadler, Eden Prairie, MN) and according to theguidelines of the American Speech-Language-Hearing Association(1978). According to self-reports, three participants were left-handedand the others were right-handed. None of the participants reported ahistory of otological or neurological disorders. All provided theirconsent in written form after being informed about the nature and aimof the study in accordance with protocols reviewed and approved bythe Research Ethics Board at Baycrest Centre. Participants received anhonorarium.

Stimuli and procedure. Two pure-tone stimuli with frequenciesf1 � f2 presented dichotically induced the binaural beat. Dioticpresentation of the sum of both tones generated the acoustic beat. Theinteraction between the two tones results in an amplitude fluctuationin case of the acoustic beat (see Fig. 9B) and fluctuations of theinteraural phase difference (IPD) for the binaural beat (see Fig. 9C).

1872 BINAURAL BEATS

J Neurophysiol • doi:10.1152/jn.00224.2014 • www.jn.org

on October 16, 2014

Dow

nloaded from

We varied the difference frequency �f smoothly from 3 Hz to 60 Hzand back over a 16-s time interval, while keeping the mean of f1 andf2 equal to 500 Hz. We designed the time course of �f such that thefrequency gradient linearly increased between 0 and 15 Hz/s. In thebinaural beat condition, we presented the lower-frequency tone f1

(498.5–470 Hz) always to the right ear and the higher-frequency tonef2 (501.5–530 Hz) to the left ear. The stimulus intensity was 65 dBabove the individual sensation threshold for a single 500-Hz tone,which was assessed at the beginning of each session. Stimuli werepresented with ER3A transducers (Etymotic Research, Elk GroveVillage, IL), which were connected to the participant’s ears via3.4-m-long plastic tubes and foam earplugs. We considered theacoustic transmission delay of 10 ms during data analysis. Thestimulation was controlled by Presentation software (NeurobehavioralSystems, Albany, CA).

Behavioral test. We presented two-tone complex sounds of 1-sduration with �f between 0 Hz and 60 Hz in 5-Hz steps in randomorder as acoustic or binaural beat stimuli. The mean frequency of thetwo tones was always 500 Hz. The participants judged for eachstimulus whether the sound was steady or beating.

MEG recording. The MEG was recorded in a quiet magneticallyshielded room with a 151-channel whole-head axial gradiometer-typeMEG system (VSM Medtech, Port Coquitlam, BC, Canada) at theRotman Research Institute. Participants were seated comfortably in anupright position with the head resting inside the helmet-shaped MEGsensor. They watched a closed-captioned silent movie of their choiceto maintain a constant level of vigilance. The head location relative toMEG sensors was registered at the beginning and end of eachrecording block with electromagnetic coils attached to the nasion andleft and right preauricular points. The mean of repeated fiduciallocations defined the head-based Cartesian coordinate system withthe origin at the midpoint between the bilateral preauricular points.The postero-anterior x-axis was oriented from the origin to the nasion,the mediolateral y-axis (positive toward the left ear) was perpendic-ular to x in the plane of the three fiducials, and the inferior-superiorz-axis was perpendicular to the x–y plane (positive toward the vertex).The MEG was recorded in blocks of 390-s duration (6.5 min),containing 24 sweep periods each. Five blocks with acoustic beatstimulation and eight bocks with binaural beat stimulation wererepeated in random order in two MEG sessions of �1-h duration each.The larger number of recording blocks for the binaural beat waschosen because previous studies showed significantly smaller responsescompared with the acoustic beat. A block was repeated when thefiducial locations differed more than �5 mm from the mean. Mostparticipants performed both sessions on the same day; otherwise,participants came on the following day.

MEG data processing and source estimation. The magnetic fielddata were low-pass filtered at 200 Hz, sampled at 625 Hz, and storedcontinuously. From the continuous data, the time points of eyeblinkand heartbeat artifacts were identified with independent componentanalysis (Ille et al. 2002). The MEG was averaged according toeyeblink and heartbeat events, respectively, and the first principalcomponents of the averaged artifacts were used as spatiotemporaltemplates to eliminate artifacts in the continuous data (Kobayashi andKuriki 1999).

Dipole source analysis was performed based on the 40-Hz re-sponses evoked by the acoustic beat, which was the most prominentresponse component (Miyazaki et al. 2013). Short 200-ms intervals ofthe MEG were averaged related to the onset of each beat cycle (i.e.,the nodes of the beating sound) between 20 Hz and 60 Hz. The resultshowed a brief burst of oscillations with an amplitude peak at 50 msand dipolar magnetic field distribution above bilateral temporal lobes.The magnetic field was approximated by single equivalent currentdipoles in the left and right hemispheres. The head model was a singlesphere of homogeneous conductivity, individually approximated tothe head shape, which was digitized before MEG recording with athree-dimensional digitizer (FASTRAK, Polhemus, Colchester, VT).

The electromagnetic forward model as implemented in the CTF dipolefit software was used. Dipole sources were estimated for each repeatedblock, and the means of the dipole coordinates and orientations weretaken as individual source model for calculating time series of corticalsource activity with the method of source space projection (Ross et al.2000; Teale et al. 2013; Tesche et al. 1995). All further data analysiswas based on the time series of bilateral source activity measured innano-amp meters. Group mean dipole coordinates were calculated inthe head-based coordinate system and transformed into Talairachcoordinates by coregistering the three fiducials with a template brain.

Frequency-domain analysis. We reported previously a detailedtime-domain analysis of the responses to the acoustic beat (Miyazakiet al. 2013). Because of the substantially smaller response amplitudesin case of the binaural beat, such time-domain analysis was notfeasible. However, frequency-domain analysis provided highly reli-able response measures with excellent signal-to-noise ratio for com-parison between the acoustic and binaural beat responses.

The time series of left and right cortical source activities weresegmented in 18-s-long epochs, each containing the 16-s sweep of thebeat frequency and two additional 1-s intervals before the beginningand after the end of the sweep period. We applied a time-frequencyanalysis to each single-trial waveform, using complex Morlet wave-lets with carrier frequencies between 2 Hz and 80 Hz (Samar et al.1999). The width of the wavelet, which determines the temporal-spectral resolution, was adjusted to the carrier frequencies to containtwo cycles at half-maximum width at 2 Hz and 8 cycles at 60 Hz. Themain outcome measure in this study was the phase coherence becauseit involves a normalization of the spectral amplitudes and accounts forthe 1/f low-pass characteristics of the MEG spectrum by equallyweighting all frequency components in the range of interest. Thischoice of data analysis was specifically important for this study toattain a fair comparison between the brain responses across therelatively wide spectral range. The phase coherence can be interpretedas a metric of how much of the ongoing brain signal has beensynchronized with the stimulus. A close relationship between thephase coherence and the signal-to-noise ratio has been shown (Dobieand Wilson 1989). For calculating intertrial phase coherence we usedthe magnitude-squared coherence algorithm (Dobie and Wilson1989). For all N trials from repeated blocks we calculated the mean ofall complex wavelet coefficients a(t,f) and normalized it by thevariance according to

PC�t, f� �

1

N�1

N

a�t, f�

� 1

N�1

N

a�t, f� · a*�t, f�

in which a* denotes the conjugate of the complex wavelet coefficient.The main difference compared with a more common method ofcalculating the phase coherence was that the normalization wasapplied after accumulating mean and variance instead of normalizingeach trial (Lachaux et al. 1999). The magnitude-squared coherenceconsiders amplitude information and has been shown to be especiallysensitive to auditory evoked oscillatory responses (Dobie and Wilson1994). One important property of the phase coherence measure is thatits statistical distribution under the null hypothesis is known, whichdirectly provides P values for the test. For a large number of trials(N 50), the approximation P � exp(�N PC2) can be used (Fisher1996). The number of trials was N � 120 for the acoustic beat andN � 192 for the binaural beat stimulation for each participant. Thecomplex phase coherence was averaged across participants for calcu-lating the grand averages, and its absolute values were color-coded intime-frequency maps. We also used the time-frequency representation(TFR) of the response as a time-dependent band-pass filter (Bertrandet al. 1994), which was centered at the stimulus frequency at each time

1873BINAURAL BEATS

J Neurophysiol • doi:10.1152/jn.00224.2014 • www.jn.org

on October 16, 2014

Dow

nloaded from

point, by reconstructing the time series from the wavelet coefficientsalong the contour of the stimulus beat frequency over time.

Correlation analysis. We applied a correlation analysis between thetime series of the sweeping stimulus envelope and the MEG sourcewaveforms to estimate amplitude and phase measures. These mea-sures were then used to compare the left and right hemispheres atvarious beat frequencies. The correlation analysis was performed in20 frequency bands with center frequencies fC logarithmically spacedbetween 3 Hz and 60 Hz. Both the time series of the stimulus and theaveraged response waveforms were band-pass filtered between 0.8 fC and fC/0.8. The cross-correlation function was calculated betweenboth with the MATLAB signal processing toolbox function xcorr,with time lags in the range of �400 samples (equivalent to �640 ms).The time points of the maxima of the cross-correlation providedestimates of the response latency. The phase of the correlationfunction was measured at the time point of the maximum correlationand compared between left and right auditory cortex. The magnitudeof correlation was used for calculating a laterality index LI � (right �left)/(right � left). The laterality index equals 1.0 if the responseappears solely at the right side, 0 for equal-magnitude bilateralresponses, and �1.0 in the case of a left hemispheric response.

Confidence intervals for all group-mean measures were obtainedfrom bootstrap resampling. For this analysis, the set of participants(n � 15) was resampled 1,000 times and the respective grand averagewas calculated from the resampled set. The 2.5% and 97.5% percen-tiles were taken as confidence limits. All analysis was performed witha library of MATLAB functions developed at the Rotman ResearchInstitute.

RESULTS

Behavioral results. Participants detected the acoustic beatalmost perfectly up to the beat rate of 60 Hz (Fig. 1). Beyond60 Hz, the likelihood of judging the sound as beating deceasedgradually and reached the 50% level at �90 Hz. The binauralbeat was less certainly detected, even at low frequencies. Thedetection rate decreased beyond a beat rate of 15 Hz, reachedthe 50% level at 35 Hz, and asymptotically approached at 65Hz the level of false positive responses, which was found forthe nonbeating tone pairs of equal frequency.

Cortical sources. Localization of equivalent current dipolesources was successful in all participants for the 40-Hz com-ponent of the evoked response to the acoustic beat. Mean

dipole locations in the head-based coordinate system were x ��7.0 mm, y � �49.8 mm, z � 58.3 mm for the righthemisphere and x � �10.8 mm, y � 50.7 mm, z � 57.1 mmfor the left hemisphere, corresponding to Talairach coordinatesof the MNI-colin27 template brain of x � �45 (right), y � 22(posterior), and z � 13 (superior) in the right hemisphere andx � 51, y � 23, z � 10 in the left hemisphere. The auditorysources in the right hemisphere were 6 mm more anterior than thosein the left hemisphere [t(14) � 5.5, P � 0.001], which is character-istic for the asymmetry of auditory cortices (Penhune et al. 1996)and demonstrates the reliability of the source estimation.

Time-frequency representations. Figure 2 provides an over-view of the stimulus-evoked responses in the time-frequencydomain. The acoustic beat elicited responses predominantly atthe beat frequency. Figure 2A shows the concentration of theresponse around the bell-shaped white line, which indicates thetime course of the stimulus sweep in the TFR. In addition,acoustic beat responses occurred at integer multiples of the beatfrequency, again indicated as concentration along the trajectories of 2,3, 4, and 5 times the beat frequency in Fig. 2A. Responses wereespecially expressed at low frequencies (�10 Hz) and at �-frequen-cies (30–60 Hz). The binaural beat elicited generally smaller re-sponses indicated by lower phase coherence values (Fig. 2B). Thebinaural beat response was especially dominant in the �-band, asclearly noticeable in the TFR.

Rearranging the x-axis of the TFR according to the beatfrequency instead of the time resulted in the time-frequencymaps shown in Fig. 3 for the acoustic beat. The responsesobtained with the upward sweep between 3 Hz and 60 Hz andthe downward sweep were averaged separately for the left andright auditory cortices. A cross section of the time-frequencymaps at 40 Hz is shown in Fig. 3, top. It indicates that a 40-Hzresponse was elicited not only by the 40-Hz beat but also at 20Hz, 14 Hz, and 10 Hz. Moreover, the overlay of responsesobtained during up sweep and down sweep illustrates that theresponse sizes were largely independent of the sweep direction.The �-band responses appeared to be larger right comparedwith left. Measuring the response magnitude at the beat fre-quencies, which are the response magnitudes along the diago-nal in the time-frequency maps in Fig. 3, A and B, results in thebeat transfer characteristics shown in Fig. 3C. The transfercharacteristic for the acoustic beat showed maxima at lowfrequencies (�3 Hz) and around 12 Hz and the largest maxi-mum at 40 Hz, as well as minima at 8 Hz and 20 Hz, for boththe left and right responses. The thin lines in Fig. 3C indicatethe 95% confidence limits for the group means. The confidenceintervals include the mean magnitude of the contralateralhemisphere across the beat frequency range, except in the40-Hz range. This indicates significantly larger 40-Hz re-sponses in the right hemisphere than in the left hemisphere.

Similarly arranged time-frequency maps of the phase coher-ence for the binaural beat demonstrate most prominent re-sponses in the 30–60 Hz �-frequency range (Fig. 4, A and B).However, the response magnitudes were clearly smaller thanfor the acoustic beat. The beat transfer function (Fig. 4C)showed noticeable differences between responses in the leftand right auditory cortex. The response was significantlygreater in the left hemisphere at beat frequencies around 6 Hzand in the right hemisphere at around 15 Hz. In contrast to theacoustic beat, no hemispheric difference was obvious for thebinaural beat in the 40-Hz range.

0

20

40

60

80

100

5 10 20 30 40 50 60 70 80 90

Stim

uli i

dent

ified

as

beat

ing

(%)

Beat Frequency (Hz)

Acoustic Beat

Binaural Beat

Fig. 1. Group mean behavioral results of identifying the stimuli as beatingsound. Whereas the acoustic beat was perceived at beat rates up to 60 Hz, theability to identify the binaural beat decreased above 15 Hz. Dashed line equals% of false positive responses to equal-frequency nonbeating tones. Error barsdenote 95% confidence limits for the group mean.

1874 BINAURAL BEATS

J Neurophysiol • doi:10.1152/jn.00224.2014 • www.jn.org

on October 16, 2014

Dow

nloaded from

Response time series. Time courses of the group meanacoustic and binaural beat responses are shown in Fig. 5A. Thewavelet filter, which was effectively a time-varying band-passfilter with the center frequency adjusted to the beat frequency,resulted in clean waveforms of the oscillating response at thebeat frequency. Both types of beat responses show large-

magnitude fluctuation across the frequency range between 3 Hzand 60 Hz, and the fluctuations were rather different for theacoustic and binaural beats. A common property of the timeseries was the response maximum at 40 Hz.

Another difference between the acoustic beat and the bin-aural beat was revealed when the responses from the left and

0 2 4 6 8 10 12 14 16Time (s)

0

10

20

30

40

50

60

Freq

uenc

y (H

z)

0

.05

.10

.15

Pha

se C

oher

ence

0 2 4 6 8 10 12 14 16 0

10

20

30

40

50

60

Freq

uenc

y (H

z)

0

0.1

0.2

0.3

0.4

0.5

0.6

Pha

se C

oher

ence

B

A 5 4 3 2 2 3 4 5

Fig. 2. Group mean time-frequency represen-tations (TFRs). A: TFR for the phase coher-ence of responses to the acoustic beat. Thetime axis spans the 16-s interval of sweepingthe beat frequency between 3 Hz and 60 Hzand back. Bell-shaped white lines indicate thetrajectories of the beat frequency �f and 2–5times �f, as indicated by the numbers on topof the TFR. Most prominent is the responsefollowing the trajectory of �f, with maxima atlow frequencies and in the �-frequency range.In addition, responses occurred at multiples of�f, especially at �-frequencies. B: TFR for theresponses to the binaural beat, which were ofsmaller magnitude but clearly expressed atlow and �-frequencies.

3 10 20 30 40 50 60Beat Frequency (Hz)

3

10

20

30

40

50

60

Res

pons

e Fr

eque

ncy

(Hz)

3 10 20 30 40 50 60Beat Frequency (Hz)

3

10

20

30

40

50

60

0.1

0.2

0.3

0.4

Pha

se C

oher

ence

A Left

5 4 3 2 1

B Right

5 4 3 2 1

0

0.2

0.4

0.6

3 4 5 6 8 10 15 20 30 40 50 60

Pha

se C

oher

ence

Beat Frequency (Hz)

C

LeftRight

0

0.2

0.4

0.6

3 10 20 30 40 50 60

Pha

se C

oh.

up sweepdown sweep

0

0.2

0.4

0.6

3 10 20 30 40 50 60

up sweepdown sweep

Fig. 3. TFR for the acoustic beat response. A:the TFR shown in Fig. 3 was reorganizedaccording to the beat frequency for the leftauditory cortex. The trajectory of the beatsweep appears in the main diagonal. Re-sponses to both sweep directions were aver-aged. Top graph demonstrates that for theresponse at 40 Hz the upward sweep and thedownward sweep resulted in similar responseamplitudes. The 40-Hz response shows peaksat 10-Hz, 14-Hz, 20-Hz, and 40-Hz beat stim-ulation. B: the TFR for the right auditorycortex shows larger response amplitudes at�-frequencies. C: transfer characteristics forthe acoustic beat response obtained by takingthe amplitude along the diagonal in A and B.Thin lines indicate the 95% confidence limitsfor the group mean, indicating significantlylarger amplitudes around 40 Hz in the rightauditory cortex.

1875BINAURAL BEATS

J Neurophysiol • doi:10.1152/jn.00224.2014 • www.jn.org

on October 16, 2014

Dow

nloaded from

right auditory cortices were overlaid, which is shown for threeselected frequencies of 3 Hz, 40 Hz, and 60 Hz in Fig. 5B.Whereas the phases of the bilateral time series were exactlyaligned for the acoustical beat, the binaural beat responsesshowed systematic phase differences between left and rightauditory cortices. Specifically at 3 Hz, the bilateral responseswere of almost opposite polarity. The phase differences weresignificant, as indicated by nonoverlapping 95% confidenceintervals for the group mean phase (Fig. 5C). At 3 Hz, the lefthemispheric response was leading by almost 180°, while in the�-frequency range (40–60 Hz) the right hemispheric responsewas leading by �120°.

Cross-correlation analysis. More detailed information aboutthe hemispheric phase relations was obtained with a cross-correlation analysis of the stimulus beat and the brain re-sponses, summarized in Fig. 6. The analysis revealed that thephases of bilateral acoustic beat responses were exactly alignedfor the entire frequency range, whereas the binaural beatresponses were characterized by noticeable left-right phasedifferences. Even for beat frequencies at which the acousticbeat response was very small, and where some variation dueto noise could be expected, the bilateral phases were strictlyaligned. Moreover, the binaural beat response showed largedifferences in bilateral response magnitudes at certain frequencies.

The time point of the maximum of the absolute values of thecross-correlation was taken as an estimate of the responselatency. Characteristics of the response latencies are shown inFig. 7. Although the latencies were within a similar range forboth response types, the frequency characteristics of the laten-cies were widely variable. Only in the 40- to 60-Hz range didboth responses have the same latency of �50 ms.

Hemispheric asymmetry. The hemispheric differences inresponse magnitude and phase are summarized in Fig. 8.Whereas the bilateral phases were confined within a �20°band across the entire frequency range for the acoustic beat, thebinaural beat responses were of almost opposite polarity at 3

Hz (Fig. 8A). The binaural beat phase difference changedgradually with increasing frequency to �120° at 10 Hz andremained constant at this phase difference for the beat rangefrom 10 Hz to 60 Hz. The almost constant phase over thisfrequency range suggests that the cross-hemispheric rela-tionship is defined by the phase and not by a certain delaytime.

The different hemispheric phase relationships for the acous-tic beat and the binaural beat are illustrated with the spatialmaps of the magnetic field response at 3 Hz in Fig. 8B. In thecase of the acoustic beat the spatial map showed patterns oftwo dipolar distributions above the left and right temporal lobe,which are characteristic for auditory cortex sources of samepolarity. In contrast, the topographic map for the binaural beatresponse showed dipolar maxima at similar places but the rightand left hemispheric dipoles showed opposite orientations.

The hemispheric balance of the response magnitude wasexpressed with the laterality index, visualized in Fig. 8C. Theacoustic beat response showed symmetric response magnitudesup to 20 Hz and more right-lateralized responses in the 30- to60-Hz �-frequency range. The binaural beat response showeda strong left lateralization around 6 Hz, right lateralizationaround 15 Hz, and symmetric responses in the �-frequencyrange. These patterns were consistent between upward anddownward sweeps.

Response phase at low frequency (3 Hz). At low beatfrequencies, the dichotically presented two-tone stimuli inducethe illusion of a moving sound rotating back and forth betweenleft and right ears. We showed that in this case the responseswere of opposite polarities in the left and right auditorycortices. The temporal relationship between the stimulus andthe brain response at 3 Hz is visualized in Fig. 9. While the IPDincreases continuously over time, wrapping the phase aroundthe interval (��, �) results in a sawtoothlike time course of theIPD (Fig. 9D). However, lateralization of the 500-Hz sound ismaximal around 0.5� and crosses the midline smoothly at

3 10 20 30 40 50 60Beat Frequency (Hz)

3

10

20

30

40

50

60

Res

pons

e Fr

eque

ncy

(Hz)

3 10 20 30 40 50 60Beat Frequency (Hz)

3

10

20

30

40

50

60

0.02

0.04

0.06

0.08

0.10

Pha

se C

oher

ence

A Left B Right

0

0.1

0.2

3 4 5 6 8 10 15 20 30 40 50 60

Pha

se C

oher

ence

Beat Frequency (Hz)

C

LeftRight

Fig. 4. TFR for the binaural beat response. Aand B: TFR characteristics for the left audi-tory cortex (A) and for the right auditorycortex (B). C: binaural beat amplitudes wereleft dominant around 6 Hz, larger rightaround 15 Hz, and bilaterally strongest at40–60 Hz.

1876 BINAURAL BEATS

J Neurophysiol • doi:10.1152/jn.00224.2014 • www.jn.org

on October 16, 2014

Dow

nloaded from

equal and opposite bilateral phases (Domnitz and Colburn1977). Therefore we approximated the time course of theIPD by the sine wave of its first-order Fourier expansion toobtain an estimate of the perceived lateralization (coloredgraph in Fig. 9D). At the maxima of this sine wave, the ITDwas �0.5 ms, equivalent to a quarter of the cycle of the500-Hz sound, which is close to the physiological period of�0.6 ms, corresponding to an acoustic wavelength equal tothe size of the human head. We compared this time series of

the IPD stimulus (Fig. 9D) with the grand-averaged auditorycortex responses observed from the correlation analysis(Fig. 9E). The latency between the time point of maximallyleft localization of the stimulus and the time point of theresponse maximum in the contralateral right auditory cortexwas 83 ms in mean. The responses in bilateral auditorycortices were of opposite polarity and reached maximalamplitudes after a delay with respect to the assumed timepoint of maximal sound lateralization.

-.10

-.05

0

.05

.10

-.40

-.20

0

.20

.40

0 2 4 6 8 10 12 14 16

3 5 10 20 40 60 40 20 10 5 3

Pha

se C

oher

ence

Time (s)

Frequency (Hz)

AAcoustic Beat

Binaural Beat

-.05

0

.05

-.40

-.20

0

.20

.40

-1 0 1

Pha

se C

oher

ence

3HzB

6.45 6.5 6.55

Time (s)

40Hz

7.95 8 8.05

60HzLeft

Right

-180

0

180

3 4 5 35 40 45 50 55 60

Pha

se D

iffer

ence

(Deg

)

Frequency (Hz)

C

Binaural Beat

Acoustic Beat

Fig. 5. Time series of the responses at the beat frequency. A: time series for both types of beat responses observed in the left auditory cortex. x-Axis scales indicatethe time span of the sweep period (bottom) and the corresponding beat frequencies (top). Note that y-axis scale for the binaural beat is enlarged by 4 times. B:overlays of left and right response time series indicate consistent phase for the acoustic beat and different response phases for the binaural beat. C: significantphase differences were observed for the binaural beat at low frequencies and at �-frequencies. Gray shaded areas indicate 95% confidence intervals for the groupmean phase.

1877BINAURAL BEATS

J Neurophysiol • doi:10.1152/jn.00224.2014 • www.jn.org

on October 16, 2014

Dow

nloaded from

DISCUSSION

We report human auditory cortex responses to acoustic beatand binaural beat stimuli over the physiologically relevantrange of beat frequencies. We found that the response ampli-tudes and phases fluctuated across the beat range, whichsuggests different underlying brain processes in different fre-quency bands. This calls for separate discussions of the differ-

ent frequency bands. While responses were maximal in the�-band for both types of stimulation, the binaural beat responseswere generally smaller than the acoustic beat responses. Differ-ences between binaural and acoustic beat responses were moststrongly expressed in interhemispheric phase differences. Wefound bilateral phase differences for the binaural beat, whilethe acoustic beats elicited responses with equal phase in the left

Time (ms)

3.0Hz

3.5Hz

4.1Hz

4.8Hz

5.6Hz

6.6Hz

7.7Hz

9.0Hz

10.6Hz

12.3Hz

14.5Hz

17.0Hz

19.9Hz

23.3Hz

27.3Hz

31.9Hz

37.4Hz

43.7Hz

51.2Hz

60.0Hz

B

Cro

ss C

orre

latio

n be

twee

n S

timul

us B

eat a

nd R

espo

nse

Time (ms)

3.0Hz

3.5Hz

4.1Hz

4.8Hz

5.6Hz

6.6Hz

7.7Hz

9.0Hz

10.6Hz

12.3Hz

14.5Hz

17.0Hz

19.9Hz

23.3Hz

27.3Hz

31.9Hz

37.4Hz

43.7Hz

51.2Hz

60.0Hz

A

-300 -200 -100 0 100 200 300 400

1.0

-300 -200 -100 0 100 200 300 400

0.25

Fig. 6. Analysis of cross-correlation between the stimulus beat and the auditory cortex responses for the acoustic beat (A) and for the binaural beat (B). Thecross-correlation was calculated for 20 logarithmically spaced frequencies between 3 Hz and 60 Hz. Gamma-frequency correlations are displayed on largertimescale in subpanels for better visualization of the phase relationships. Correlation was in general smaller for the binaural beat; note the different scale bars.Whereas for the acoustic beat the time series of correlation were aligned without time delay for left and right auditory cortices, phase differences were evidentat all frequencies for the binaural beat.

1878 BINAURAL BEATS

J Neurophysiol • doi:10.1152/jn.00224.2014 • www.jn.org

on October 16, 2014

Dow

nloaded from

and right hemispheres. Specifically at the lowest frequency of3 Hz, the binaural beat responses were of opposite polarity,supporting the hypothesis of sound localization encodingthrough bilateral asymmetry in the central auditory system.

Behavioral results. Although our behavioral test procedurewas relatively simple, the obtained transfer characteristicsagree with the literature. Performance on the acoustic beat

detection task showed a low-pass characteristic comparable toknown amplitude modulation transfer characteristics (Viemeis-ter 1979). Fast binaural processing with an upper frequencylimit similar to that for AM detection has been shown withnoise stimuli containing fast interaural phase transitions(Siveke et al. 2008). However, we found a noticeably lowercutoff frequency for the binaural beat. The performance wasbest between 10 Hz and 15 Hz, decreased for higher frequen-cies, and reached the 50% level at �30 Hz, which is consistentwith earlier reports (Perrott and Nelson 1969).

The different low-pass characteristics for binaural andacoustic beat perception have previously been taken as indica-tion for lower temporal acuity in the binaural system comparedwith the monaural system. However, for a fair comparison onemust consider the significantly reduced salience of the binauralbeat compared with the acoustic beat for equally intensetwo-tone complexes (Grose et al. 2012). When manipulatingthe phase characteristics of noise stimuli, which largelyovercomes the saliency problem, similar characteristicshave been found for both the monaural and binaural sys-tems, suggesting that they have similar temporal acuity(Siveke et al. 2008).

Previous event-related potential literature. Previous reportsof binaural beat responses may appear to be inconsistent, as

0

50

100

150

200

3 5 10 20 40 60

Late

ncy

(ms)

Beat Frequency (Hz)

Binaural Beat

Acoustic Beat

Fig. 7. Response latency estimated from the maxima of cross-correlationbetween the stimulus beat and the response. Shaded areas indicate 95%confidence intervals for the group means.

-45

0

45

3 4 5 6 8 10 20 40 60

Acoustic Beat

-270

-180

-90

0

90

180

3 4 5 6 8 10 20 40 60Rig

ht-L

eft P

hase

Diff

eren

ce (D

egre

es)

Frequency (Hz)

Binaural Beat

-0.2

0

0.2

0.4

3 4 5 6 8 10 20 40 60

Right

Left Acoustic Beat

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

3 4 5 6 8 10 20 40 60

Late

ralit

y In

dex

Frequency (Hz)

Right

LeftBinaural Beat Binaural Beat

B

3.0 HzAcoustic Beat

A

C

Fig. 8. Phase and amplitude balances be-tween left and right hemispheres. A: groupmean phase difference between left and rightauditory cortex source activities. Diotic stim-ulation, which generates acoustic beating,elicited phase-aligned cortical responses.Phase differences were �20° across the fre-quency range. Error bars indicate 90% con-fidence intervals for the group mean. Thebinaural beat in case of dichotic stimulationcauses phase differences between left andright hemispheres. At low frequencies theright hemisphere is leading by close to 180°.Between 10 Hz and 60 Hz, the left hemi-spheric response is leading by 120°. B: top-ographic maps of the MEG at 3 Hz show 2dipolar pattern above the temporal lobes,characteristic for auditory cortex sources. Ar-rows indicate underlying the dipoles withsame polarity. In the case of the binauralbeat, the dipoles are of opposite polarity. C:the amplitudes of responses to the acousticbeat were balanced between hemispheres be-low 20 Hz and showed a right hemisphericpreference in the �-frequency range. The re-sponse amplitudes elicited by the binauralbeat were strongly left lateralized around 6Hz and right lateralized around 15 Hz. Theywere, however, balanced at low frequenciesand in the �-band.

1879BINAURAL BEATS

J Neurophysiol • doi:10.1152/jn.00224.2014 • www.jn.org

on October 16, 2014

Dow

nloaded from

Pratt and colleagues (2010) lamented. For example, regardingresponse lateralization, studies reported symmetric bilateralresponses (Karino et al. 2006), right lateralization (Draganovaet al. 2008), and left dominance of the binaural beat response(Pratt et al. 2009). In our opinion, the apparent disagreementlikely resulted from comparison of different experimental con-ditions, notably different beat rates. The strength of the presentstudy is that we provide the first coherent report of binauralbeats across a wide beat range. In fact, we found that theresponse properties changed strongly across the frequencyrange between 3 Hz and 60 Hz, which was not evident fromobservations at only a few samples of the beat frequency in theearly studies.

The first EEG study about steady-state responses to binauraland acoustic beats used a beat rate of 40 Hz and stimulusfrequencies around 400 Hz and 3,200 Hz (Schwarz and Taylor2005). Whereas acoustic beat responses were elicited with low-and high-frequency sounds, a binaural beat response wasdetectable at 400 Hz but not at 3,200 Hz, which is consistentwith the finding that cortical responses to ITD changes arelimited to the frequency range below 1,500 Hz (Ross 2008;Ross et al. 2007b). Other studies used lower frequencies only.Still, response amplitudes were smaller at 1,000 Hz than at 250Hz (Pratt et al. 2010). Binaural beat responses were consis-tently recorded with a 390/430-Hz tone pair. However, noresponse was detectable with an 810/850-Hz tone pair in mostof the same participants (Grose and Mamo 2012). The findingin the latter study, that simultaneously recorded frequency-following responses were strongly attenuated for the higher-frequency stimuli, supports the hypothesis that neural synchro-

nization with the stimulus carrier at the brain stem level isrequired for binaural processing.

The first MEG study of the binaural beat showed small butsignificantly detectable responses to 4-Hz and 6.66-Hz binauralbeats at stimulus frequencies of 240 Hz and 480 Hz (Karino etal. 2006). Although multiple sources were suspected, the mostprominent responses were localized in bilateral temporal areasaround the primary auditory cortex. Phase measures werevariable and not consistent across stimulus conditions. Ourpresent data revealed a phase transition in the 4-Hz to 6.66-Hzinterval (Fig. 8A). This frequency interval corresponds to theperceptual transition between perceiving dominantly a movingsound at lower frequencies and loudness fluctuations for beatfrequencies above 5 Hz. We observed left-lateralized responsesaround 6 Hz and more balanced bilateral responses at 4 Hz.Because of this dependence on the beat frequency, a consistentpattern of amplitude and phase measures could not be obtainedfrom previous observations at two frequencies only.

Larger left hemispheric responses were reported from EEGstudies with short sequences of binaural beats at 3 Hz and 6 Hz(Pratt et al. 2009, 2010), which was corroborated by a signif-icant left laterality at 6 Hz in our data. However, we found nosignificant left lateralization of the response at 3 Hz. Thebilateral phase differences found in our study at 3 Hz and 6 Hzwere not seen in the EEG studies. Differences in stimulusdesign and recording modalities may have contributed to thisdiscrepancy.

In MEG, significantly larger 40-Hz auditory cortex re-sponses in the right hemisphere have been reported for bothbinaural beats and acoustic beats (Draganova et al. 2008). Ourpresent data showed considerably larger right hemispheric

-200 -100 0 100 200Time (ms)

0 π-0.5π 0.5π-πIPD

Beat Cycle

f1:f2:

Right

Left

83 ms

A

B

C

D

ELeft

Right

Fig. 9. Phase relationship between the 3-Hz beatstimulus and the brain responses. A: dichoticstimulus tones with f1 presented left and f2 right.B: superimposition leading to the acoustic beat.The time course of the envelope (red line) wasused as the reference signal for the cross-corre-lation analysis. C: dichotic stimulus presentationresulting in interaural phase differences (IPDs).During the interval (��, 0) of the beat cycle, theleft ear sound is leading; during the interval (0,�) the right ear sound is leading. D: time courseof the assumed sound lateralization. Dashed lineindicates time course of the IPD, and coloredsine wave is first-order Fourier approximation ofthe IPD. Red color indicates localization towardright and blue toward left. E: time courses of thebinaural beat response as analyzed by cross-correlation with the stimulus beat showed oppo-site polarities in auditory cortices and a delaywith respect to the time course of assumed soundlateralization.

1880 BINAURAL BEATS

J Neurophysiol • doi:10.1152/jn.00224.2014 • www.jn.org

on October 16, 2014

Dow

nloaded from

responses for the acoustic beat as we showed before for AMsounds (Ross et al. 2005), while the binaural beat responseswere not asymmetric between hemispheres. Our finding thatbilateral 40-Hz response phases were identical for the acousticbeat but differed by �90° for the binaural beat is consistentwith previous reports by Draganova et al. (2008).

In summary, the apparent inconsistencies across previousstudies from different laboratories can be explained by a closelook at the frequency characteristics of the beat responses. It isimportant to note that several previous studies came to theconclusion that the cortical responses to binaural and acousticbeats share common characteristics and suggested commonunderlying neural mechanisms for low-frequency (Pratt et al.2010) and 40-Hz (Draganova et al. 2008) responses. However,investigating the responses across a wide frequency rangerevealed characteristic differences between both types of re-sponses in addition to commonalities. In the following sectionwe consider separately response characteristics in the differentfrequency regions.

It would be desirable to correlate responses at various beatrates with behavioral findings. However, given the small re-sponse amplitudes we could report results on the level of groupaverages only and compare those to behavioral findings re-ported in the literature. Future work is required to focus onbrain responses and behavioral performances at distinct beatrates.

Responses at low beat rates—sound localization. Two per-ceptual phenomena emerge at low beat rates: the bilateral tonesfuse into a single tone, and this tone is localized as movingperiodically between the left and right ears. The upper limit forperception of such a “rotating tone” has been described as �fequal to 5–10% of the tonal frequency (Perrott and Musicant1977) or as the absolute value of 5 Hz (Blauert 1972; Granthamand Wightman 1978). Although we did not test the perceptualquality explicitly, we assume that our lowest beat rate of 3 Hzwas capable of inducing the illusion of a moving sound. Werecorded brain responses evoked by slowly changing beats inthe 3-Hz range for 2 s in each trial. This resulted in asufficiently large number of epochs for signal averaging toobtain clear responses.

The binaural beat response in the 3-Hz range was charac-terized by balanced bilateral amplitudes of opposite polarity,while the acoustic beat elicited bilateral responses with equalpolarity. Previous EEG recordings may have missed the phasedifferences because the dipolar potential patterns from left andright auditory responses overlap in frontal central areas. Theoverlapping signals with opposite polarity, typically close totemporal T5/T6 electrodes, may not have had a large enoughsignal-to-noise ratio to allow for a reliable phase comparison(Pratt et al. 2010).

We interpret our finding of opposite phases in left and rightauditory cortices in the context of cortical representation ofsound localization through asymmetry of the magnitudes ofcortical responses between hemispheres. Evidence for suchopponent-channel coding of ITD in humans has been con-cluded from using stimuli that elicited responses specific forITD transitions. The opponent-channel model predicts largerresponses for an outward location shift from central to lateral.Accordingly, larger EEG responses to outward ITD changescompared with inward changes have been found (Magezi andKrumbholz 2010). Our low-frequency finding of a steady-state

response that continuously follows the ITD changes of period-ically moving sound reflects the principle that cortical re-sponses are largest contralateral to the lateralized sound.

The response latency was on the order of 100 ms, which maysuggest a relationship to the sensory evoked P1-N1-P2 re-sponse. The evoked response signals a change in the acousticenvironment and is likely involved in the encoding of singleauditory objects (e.g., as in speech and music). The timeconstant of 200 ms for temporal integration in this auditoryprocess defines the trade-off between perception of singleevents and an auditory stream (Yabe et al. 2001) and mayapply to identification of the sound location in an analogousway. Thus the time constants of auditory analysis and inter-pretation effectively limit the perception of moving sounditems, while the binaural system itself may resolve much finertimescales.

40-Hz �-responses—binaural temporal modulation. Large40-Hz responses for both the acoustic and the binaural beatwere outstanding findings in this study. However, the sharplytuned frequency characteristic seems not to be compatible withpresent and previous behavioral findings. The acoustic beatwas equally well perceived for low frequencies including 40Hz. In contrast, detection performance for the binaural 40-Hzbeat was close to chance level. Then how can we explain thedominance of the 40-Hz response? First, it is noteworthy thatsingle-unit recordings of binaural beat responses showed thatcortical neurons do not fire particularly at rate of 40 Hz. Inanesthetized cats the cortical spike rate increased with increas-ing binaural beat rate, reached a maximum at 13 Hz, anddecreased continuously for higher rates (Reale and Brugge1990). The highest beat rate in that study was 45 Hz, and noincrease in the spike rate was observed around 40 Hz. Notablythe spikes in the 40-Hz range were strictly phase-locked to thebeat cycle, which was not the case at other frequencies.Anesthesia could have caused a suppression of the 40-Hzresponses. Indeed, in anesthetized macaque predominantlytransient responses were found, whereas sustained neural firingwas observed in the alert animal (Scott et al. 2009). In thatstudy, the spike rate was largest around 10 Hz and showedlow-pass characteristics with reaching the 50% level at 20 Hz,and no specifically larger binaural beat response was foundaround 40 Hz.

Predominant MEG responses at 40 Hz more likely reflect ageneral mechanism of cortical processing. Intracellular record-ings in cat revealed that fast-spiking interneurons in superficialand deep cortical layers are the main sources for 40-Hzoscillations in cortico-thalamic networks (Steriade et al. 1998).The role of 40-Hz �-oscillations for neural communicationbased on synchronization and phase coding has been concep-tualized (Womelsdorf et al. 2007) and has been proposed as theneural mechanism underlying sensory binding and object rep-resentation for conscious perception (Bertrand and Tallon-Baudry 2000; Engel and Singer 2001). Recent experimentalfindings from an optogenetic study supported those concepts:When fast-spiking interneurons in barrel cortex in mice weresynchronized with laser-light pulses at 40 Hz, neurons weresensitive to concurrent whisker stimuli at a specific phase ofthe �-cycle and sensory response timing was most precise atthis phase (Cardin et al. 2009). Consistent with the concept that�-oscillations modulate the synaptic input of cortical neurons isthe fact that the EEG and MEG signal is mainly generated by

1881BINAURAL BEATS

J Neurophysiol • doi:10.1152/jn.00224.2014 • www.jn.org

on October 16, 2014

Dow

nloaded from

postsynaptic current flows in the apical dendrites of largepyramidal cells in layer IV–VI of the cortex (Lopes Da Silva2004). Thus a reasonable assumption is that the 40-Hz MEGreflects postsynaptic oscillations that sharpen the timing ofcortical neurons and thus control sensory processing and per-ceptual binding.

In our study, 40-Hz oscillations were strongest when thestimulus beat rate was also 40 Hz. However, partials of 40 Hz(20 Hz, 14 Hz, 10 Hz, etc.) elicited 40-Hz responses also, atleast for the acoustic beat. In our previous analysis of thetemporal structure of responses to the acoustic beat, we foundthat each beat elicited a short wave of 40-Hz oscillations atlower beat rates (Miyazaki et al. 2013). Our time-frequencyanalysis of the acoustic beat responses showed that the re-sponses strength doubled when the beat rate increased from 20Hz to 40 Hz, which could be explained by the effect oftemporal integration across twice as many beats at 40 Hzcompared with 20 Hz. Both our analyses in the time domainand in the frequency domain agree that each acoustic beatelicits a burst of 40-Hz oscillations, and the superimpositionresults in the strongest response at 40 Hz. Nonetheless, super-imposition of a 40-Hz burst to each beat cycle does notcompletely explain the predominant 40-Hz activity, and likelyfurther synchronization of intrinsic �-oscillations contributedto the response (Ross et al. 2012). Our finding that stimulationat integer fractions of 40 Hz synchronized 40-Hz oscillationssuggests that stimuli at any frequency elicited �-responses.Responses were exceptionally large and best observable at40-Hz simulation.

When comparing the time-frequency maps for the acousticbeat and the binaural beat, it seems reasonable to assume acommon mechanism for the generation of �-oscillations. How-ever, the �-amplitude for the binaural beat was smaller than forthe acoustic beat, and we could not detect a prominent 40-Hzresponse with the 20-Hz or 10-Hz binaural beat. This isessentially a matter of sufficient signal-to-noise ratio, whichcould be obtained with substantially increased measurementtime. The amplitude of the 40-Hz steady-state response to AMsound depends strongly on the modulation depth. Given thatthe salience of the binaural beat stimulus corresponds to anAM sound of �5% modulation, we would expect only 20% ofthe amplitude observed for a fully modulated AM sound of thesame intensity (Ross et al. 2000), which is consistent with thereduction of the 40-Hz binaural beat response compared withthe acoustic beat response in the present study and previousreports (Draganova et al. 2008; Schwarz and Taylor 2005).

If the phase of �-oscillations provides a mechanism forprecise timing and synchronization of neural firing within the�-cycle (i.e., 25 ms) (Singer 2009), faster stimuli would causeambiguity in such a coding schema. Therefore, the �-rhythmmay reflect the upper limit for temporal processing in thecortex. Our behavioral finding of the frequency characteristicsfor perception of the acoustic beat as well as previous reportsof the temporal modulation transfer functions for AM detectionshow low-pass characteristics with corner frequencies in the�-range, which is consistent with the concept of a temporalprocessing limit at �-frequencies.

Asymmetry in interhemispheric phases. Besides differentamplitudes, we found significant asymmetries in bilateralphases. Over a wide frequency range between 10 Hz and 60Hz, the binaural beat response showed a phase difference on

the order of 90° compared with aligned phases for the acousticbeat. This is a very unique finding. The topographic map of theevoked magnetic field of the bilateral dipolar pattern as foundfor the acoustical beat has been shown in hundreds of auditoryMEG studies and reflects common timing of bilateral responsesfor monaural and binaural stimulation. Out-of-phase binauralbeat responses strongly contrast the common findings. Even forcompletely lateralized sounds, no latency differences werefound in the auditory evoked MEG response (Woldorff et al.1999).

Differences in response latency have been proposed as aneural code for simultaneous processing of concurrent objects(Oram et al. 2002). Oscillations with 90° phase difference, asobserved over a wide range of beat frequencies, may beespecially suitable for such encoding because the responses areorthogonal and therefore most independent. Following thisconcept, one can assume that separate representations of theauditory input exist in bilateral auditory cortices in the case ofthe binaural beat.

The hemispheric amplitude asymmetry, with predominantamplitudes around 6 Hz left and 15 Hz right, may furthercontribute to separate auditory cortex representations in binau-ral hearing. Although the present findings were consistent withprevious reports, the specific role of the response lateralityneeds further investigation. Different time constants for pro-cessing in the left and right auditory cortex have been found,and preferences for processing temporal information have beensuggested. However, hemispheric laterality may also dependstrongly on the actual experimental procedure and may even bemodulated by the stimulus context through top-down mecha-nisms (Schönwiesner et al. 2007). Binaural beat responses inthe 6–15 Hz range were small and variable between partici-pants and hence less accessible to interpretation compared withthe low-frequency responses. Our analysis of the low-fre-quency responses revealed an opponent-channel code forsound localization and �-oscillation, which suggests a temporalcode for separation of binaural sound representations.

In brief summary, we would like to emphasize three keyfindings of our study. First, the opposite polarity of binauralbeat responses at low frequencies supports the hypothesis ofopponent-channel encoding of sound localization in bilateralauditory cortices. Second, phase differences between left andright auditory cortex responses suggest separate bilateral audi-tory representations, supporting the roles of auditory corticesfor binaural hearing based on the temporal structures of sound.Third, 40-Hz oscillations evoked by all binaural transients mayreflect a neural mechanism for precise response timing ratherthan a correlate of perceptual performance.

GRANTS

This work was supported by grants from the Canadian Institutes of HealthResearch (CIHR, MOP125195) to B. Ross and fellowships of the NaturalSciences and Engineering Research Council of Canada (NSERC CREATE) toJ. Thompson and T. Miyazaki and from the Music and Health ResearchCollaborative (MaHRC) of the Faculty of Music, University of Toronto to S.Jamali.

DISCLOSURES

No conflicts of interest, financial or otherwise, are declared by the author(s).

1882 BINAURAL BEATS

J Neurophysiol • doi:10.1152/jn.00224.2014 • www.jn.org

on October 16, 2014

Dow

nloaded from

AUTHOR CONTRIBUTIONS

Author contributions: B.R., T.M., J.T., and T.F. conception and design ofresearch; B.R. and S.J. analyzed data; B.R., T.M., J.T., S.J., and T.F. inter-preted results of experiments; B.R. prepared figures; B.R. drafted manuscript;B.R., T.M., J.T., S.J., and T.F. approved final version of manuscript; T.M. andJ.T. performed experiments; T.M., J.T., S.J., and T.F. edited and revisedmanuscript.

REFERENCES

Ahveninen J, Huang S, Nummenmaa A, Belliveau JW, Hung AY, Jääskel-äinen IP, Rauschecker JP, Rossi S, Tiitinen H, Raij T. Evidence fordistinct human auditory cortex regions for sound location versus identityprocessing. Nat Commun 4: 2585, 2013.

Akeroyd MA. A binaural beat constructed from a noise (L). J Acoust Soc Am128: 3301–3304, 2010.

American Speech-Language-Hearing Association. Guidelines for manualpure-tone threshold audiometry. ASHA 20: 297–301, 1978.

Bertrand O, Bohorquez J, Pernier J. Time-frequency digital filtering basedon an invertible wavelet transform: an application to evoked potentials.IEEE Trans Biomed Eng 41: 77–88, 1994.

Bertrand O, Tallon-Baudry C. Oscillatory gamma activity in humans: apossible role for object representation. Int J Psychophysiol 38: 211–223,2000.

Blauert J. On the lag of lateralization caused by interaural time and intensitydifferences. Audiology 11: 265–270, 1972.

Briley PM, Kitterick PT, Summerfield AQ. Evidence for opponent processanalysis of sound source location in humans. J Assoc Res Otolaryngol 14:83–101, 2013.

Cardin JA, Carlén M, Meletis K, Knoblich U, Zhang F, Deisseroth K, TsaiLH, Moore CI. Driving fast-spiking cells induces gamma rhythm andcontrols sensory responses. Nature 459: 663–667, 2009.

Carr CE, Konishi M. A circuit for detection of interaural time differences inthe brain stem of the barn owl. J Neurosci 10: 3227–3246, 1990.

Chait M, Poeppel D, De Cheveigné A, Simon JZ. Human auditory corticalprocessing of changes in interaural correlation. J Neurosci 25: 8518–8527,2005.

Chait M, Poeppel D, Simon JZ. Stimulus context affects auditory corticalresponses to changes in interaural correlation. J Neurophysiol 98: 224–231,2007.

Dajani HR, Picton TW. Human auditory steady-state responses to changes ininteraural correlation. Hear Res 219: 85–100, 2006.

Dietz M, Ewert SD, Hohmann V, Kollmeier B. Coding of temporallyfluctuating interaural timing disparities in a binaural processing model basedon phase differences. Brain Res 1220: 234–245, 2008.

Dobie RA, Wilson MJ. Analysis of auditory evoked potentials by magnitude-squared coherence. Ear Hear 10: 2–13, 1989.

Dobie RA, Wilson MJ. Objective detection of 40 Hz auditory evokedpotentials: phase coherence vs. magnitude-squared coherence. Electroen-cephalogr Clin Neurophysiol 92: 405–413, 1994.

Domnitz RH, Colburn HS. Lateral position and interaural discrimination. JAcoust Soc Am 61: 1586–1598, 1977.

Draganova R, Ross B, Wollbrink A, Pantev C. Cortical steady-state re-sponses to central and peripheral auditory beats. Cereb Cortex 18: 1193–1200, 2008.

Engel AK, Singer W. Temporal binding and the neural correlates of sensoryawareness. Trends Cogn Sci 5: 16–25, 2001.

Fisher NI. Statistical Analysis of Circular Data. Cambridge, UK: CambridgeUniv. Press, 1996.

Grantham DW, Wightman FL. Detectability of varying interaural temporaldifferences. J Acoust Soc Am 63: 511–523, 1978.

Groen JJ. Super- and subliminal binaural beats. Acta Otolaryngol 57: 224–230, 1964.

Grose JH, Buss E, Hall JW. Binaural beat salience. Hear Res 285: 40–45,2012.

Grose JH, Mamo SK. Electrophysiological measurement of binaural beats:effects of primary tone frequency and observer age. Ear Hear 33: 187–194,2012.

Grothe B, Pecka M, McAlpine D. Mechanisms of sound localization inmammals. Physiol Rev 90: 983–1012, 2010.

Hawley ML, Litovsky RY, Culling JF. The benefit of binaural hearing in acocktail party: effect of location and type of interferer. J Acoust Soc Am 115:833–843, 2004.

Ille N, Berg P, Scherg M. Artifact correction of the ongoing EEG using spatialfilters based on artifact and brain signal topographies. J Clin Neurophysiol19: 113–124, 2002.

Jones SJ, Pitman JR, Halliday AM. Scalp potentials following suddencoherence and discoherence of binaural noise and change in the inter-auraltime difference: a specific binaural evoked potential or a “mismatch”response? Electroencephalogr Clin Neurophysiol 80: 146–154, 1991.

Karino S, Yumoto M, Itoh K, Uno A, Yamakawa K, Sekimoto S, Kaga K.Neuromagnetic responses to binaural beat in human cerebral cortex. JNeurophysiol 96: 1927–1938, 2006.

Kobayashi T, Kuriki S. Principal component elimination method for theimprovement of S/N in evoked neuromagnetic field measurements. IEEETrans Biomed Eng 46: 951–958, 1999.

Konishi M. Coding of auditory space. Annu Rev Neurosci 26: 31–55, 2003.Lachaux JP, Rodriguez E, Martinerie J, Varela FJ. Measuring phase

synchrony in brain signals. Hum Brain Mapp 8: 194–208, 1999.Licklider JC, Webster JC, Herdlun JM. On the frequency limits of binaural

beats. J Acoust Soc Am 22: 468–473, 1950.Lopes Da Silva F. Functional localization of brain sources using EEG and/or

MEG data: volume conductor and source models. Magn Reson Imaging 22:1533–1538, 2004.

Magezi DA, Krumbholz K. Evidence for opponent-channel coding of inter-aural time differences in human auditory cortex. J Neurophysiol 104:1997–2007, 2010.

McAlpine D, Jiang D, Palmer AR. A neural code for low-frequency soundlocalization in mammals. Nat Neurosci 4: 396–401, 2001.

McEvoy LK, Picton TW, Champagne SC, Kellet AJ, Kelly JB. Humanevoked potentials to shifts in the lateralization of a noise. Audiology 29:163–180, 1990.

Miyazaki T, Thompson J, Fujioka T, Ross B. Sound envelope encoding inthe auditory cortex revealed by neuromagnetic responses in the theta togamma frequency bands. Brain Res 1506: 64–75, 2013.

Oram MW, Xiao D, Dritschel B, Payne KR. The temporal resolution ofneural codes: does response latency have a unique role? Philos Trans R SocLond B Biol Sci 357: 987–1001, 2002.

Penhune VB, Zatorre RJ, MacDonald JD, Evans AC. Interhemisphericanatomical differences in human primary auditory cortex: probabilisticmapping and volume measurement from magnetic resonance scans. CerebCortex 6: 661–672, 1996.

Perrott DR, Musicant AD. Rotating tones and binaural beats. J Acoust SocAm 61: 1288–1292, 1977.

Perrott DR, Nelson MA. Limits for the detection of binaural beats. J AcoustSoc Am 46: 1477–1481, 1969.

Pratt H, Starr A, Michalewski HJ, Dimitrijevic A, Bleich N, Mittelman N.Cortical evoked potentials to an auditory illusion: binaural beats. ClinNeurophysiol 120: 1514–1524, 2009.

Pratt H, Starr A, Michalewski HJ, Dimitrijevic A, Bleich N, Mittelman N.A comparison of auditory evoked potentials to acoustic beats and to binauralbeats. Hear Res 262: 34–44, 2010.

Reale RA, Brugge JF. Auditory cortical neurons are sensitive to static andcontinuously changing interaural phase cues. J Neurophysiol 64: 1247–1260, 1990.

Ross B. A novel type of auditory responses: temporal dynamics of 40-Hzsteady-state responses induced by changes in sound localization. J Neuro-physiol 100: 1265–1277, 2008.

Ross B, Borgmann C, Draganova R, Roberts LE, Pantev C. A high-precision magnetoencephalographic study of human auditory steady-stateresponses to amplitude-modulated tones. J Acoust Soc Am 108: 679–691,2000.

Ross B, Fujioka T, Tremblay KL, Picton TW. Aging in binaural hearingbegins in mid-life: evidence from cortical auditory-evoked responses tochanges in interaural phase. J Neurosci 27: 11172–11178, 2007a.

Ross B, Herdman AT, Pantev C. Right hemispheric laterality of human 40Hz auditory steady-state responses. Cereb Cortex 15: 2029–2039, 2005.

Ross B, Miyazaki T, Fujioka T. Interference in dichotic listening: the effectof contralateral noise on oscillatory brain networks. Eur J Neurosci 35:106–118, 2012.

Ross B, Tremblay KL, Picton TW. Physiological detection of interauralphase differences. J Acoust Soc Am 121: 1017–1027, 2007b.

Rutschmann J, Rubinstein L. Binaural beats and binaural amplitude-modu-lated tones: successive comparison of loudness fluctuations. J Acoust SocAm 38: 759–768, 1965.

Salminen NH, May PJ, Alku P, Tiitinen H. A population rate code ofauditory space in the human cortex. PLoS One 4: e7600, 2009.

1883BINAURAL BEATS

J Neurophysiol • doi:10.1152/jn.00224.2014 • www.jn.org

on October 16, 2014

Dow

nloaded from

Samar VJ, Bopardikar A, Rao R, Swartz K. Wavelet analysis of neuroelec-tric waveforms: a conceptual tutorial. Brain Lang 66: 7–60, 1999.

Schönwiesner M, Krumbholz K, Rübsamen R, Fink GR, Von CramonDY. Hemispheric asymmetry for auditory processing in the human auditorybrain stem, thalamus, and cortex. Cereb Cortex 17: 492–499, 2007.

Schröger E, Wolff C. Mismatch response of the human brain to changes insound location. Neuroreport 7: 3005–3008, 1996.

Schwarz DW, Taylor P. Human auditory steady state responses to binauraland monaural beats. Clin Neurophysiol 116: 658–668, 2005.

Scott BH, Malone BJ, Semple MN. Representation of dynamic interauralphase difference in auditory cortex of awake rhesus macaques. J Neuro-physiol 101: 1781–1799, 2009.

Singer W. Distributed processing and temporal codes in neuronal networks.Cogn Neurodyn 3: 189–196, 2009.

Siveke I, Ewert SD, Grothe B, Wiegrebe L. Psychophysical and physiolog-ical evidence for fast binaural processing. J Neurosci 28: 2043–2052, 2008.

Soeta Y, Hotehama T, Nakagawa S, Tonoike M, Ando Y. Auditory evokedmagnetic fields in relation to interaural cross-correlation of band-pass noise.Hear Res 196: 109–114, 2004.

Stecker GC, Harrington IA, Middlebrooks JC. Location coding by oppo-nent neural populations in the auditory cortex. PLoS Biol 3: 520–528, 2005.

Steriade M, Timofeev I, Dürmüller N, Grenier F. Dynamic properties ofcorticothalamic neurons and local cortical interneurons generating fastrhythmic (30–40 Hz) spike bursts. J Neurophysiol 79: 483–490, 1998.

Stewart GW. Binaural beats. Phys Rev 9: 502–508, 1917.

Teale P, Pasko B, Collins D, Rojas D, Reite M. Somatosensory timingdeficits in schizophrenia. Psychiatry Res 212: 73–78, 2013.

Tesche CD, Uusitalo MA, Ilmoniemi RJ, Huotilainen M, Kajola M,Salonen O. Signal-space projections of MEG data characterize both distrib-uted and well-localized neuronal sources. Electroencephalogr Clin Neuro-physiol 95: 189–200, 1995.

Viemeister NF. Temporal modulation transfer functions based upon modula-tion thresholds. J Acoust Soc Am 66: 1364–1380, 1979.

Wightman FL, Kistler DJ. The dominant role of low-frequency interauraltime differences in sound localization. J Acoust Soc Am 91: 1648–1661,1992.

Woldorff MG, Tempelmann C, Fell J, Tegeler C, Gaschler-Markefski B,Hinrichs H, Heinze HJ, Scheich H. Lateralized auditory spatial perceptionand the contralaterality of cortical processing as studied with functionalmagnetic resonance imaging and magnetoencephalography. Hum BrainMapp 7: 49–66, 1999.

Womelsdorf T, Schoffelen JM, Oostenveld R, Singer W, Desimone R,Engel AK, Fries P. Modulation of neuronal interactions through neuronalsynchronization. Science 316: 1609–1612, 2007.

Yabe H, Winkler I, Czigler I, Koyama S, Kakigi R, Sutoh T, Hiruma T,Kaneko S. Organizing sound sequences in the human brain: the interplay ofauditory streaming and temporal integration. Brain Res 897: 222–227, 2001.

Zatorre RJ, Penhune VB. Spatial localization after excision of humanauditory cortex. J Neurosci 21: 6321–6328, 2001.

Zimmer U, Lewald J, Karnath HO. Disturbed sound lateralization in patientswith spatial neglect. J Cogn Neurosci 15: 694–703, 2003.

1884 BINAURAL BEATS

J Neurophysiol • doi:10.1152/jn.00224.2014 • www.jn.org

on October 16, 2014

Dow

nloaded from