PROCEEDINGS of the
23rd International Congress on Acoustics
9 to 13 September 2019 in Aachen, Germany

The object-related negativity (ORN) component as an objective
measure of concurrent sound segregation
Alexandra BENDIXEN1
1

Chemnitz University of Technology, Germany

ABSTRACTElectroencephalography (EEG) is a popular technique for deriving objective measures of auditory function
due to its sensitivity to fine details of auditory processing, its high temporal precision, and its applicability
across a wide range of participant groups with low testing burden. I will discuss the suitability of a specific
EEG measure as a tool for objectively studying the perceptual segregation of concurrent sound sources:
namely the object-related negativity (ORN) component of the event-related brain potential (ERP). The
ORN component was introduced by Alain and colleagues almost twenty years ago to reflect the perceptual
segregation of simultaneous sounds. I will show recent ORN results from healthy young adults and fromelderly listeners with slight hearing impairment, indicating high sensitivity of the ORN at group level. I will
extend these results towards the question whether ORN is sensitive enough to measure sound segregation
abilities at single-subject level. Based on detailed correlation analyses between ORN measurements andperceptual judgments in young and elderly listeners, I will point out promises but also caveats in using the
ORN for individual diagnostics of auditory function.
Keywords: sound source separation, electroencephalography (EEG), diagnostics

1. INTRODUCTION
Humans show inter- and intraindividual differences in their auditory processing skills, just like inany other ability. Diagnostic tools for assessing individual auditory processing abilities are valuable
in various application scenarios, be it for selecting particularly adept persons as sound engineers orfor quantifying the need – and then the success – of providing treatment opportunities (e.g., hearing
aids or cochlear implants) to those whose auditory processing abilities fall short of healthy hearing.
An individual’s ability to process sounds can be probed at great detail with psychophysicalmethods. These psychophysical methods can be categorized along various dimensions, including:• the aspect of auditory processing they target (threshold measurements, supra-thresholdcomprehension, sound source separation / auditory scene analysis, etc.),• their efficiency (with adaptive or staircase procedures being more efficient than classicalconstant-stimulus procedures),• their objectivity. The objectivity term is used somewhat differently across disciplines.
In psychophysics, a subjective method is one where only the listener knows the correct answer: A
typical question is “Did you hear a sound?”, with the listener replying “Yes” or “No”, and with asound always present. With settings of this type, listeners can pretend to hear better (or worse) thanthey actually do; and even if the listener has the intent to answer as honestly as possible, the answer
will depend on their response criterion (put simply, on their tendency to say “Yes” or “No” when thesensory evidence is ambiguous). To overcome such subjective influences that are unrelated tohearing ability per se, objective psychophysical measurement techniques have been developed. In
so-called criterion-free measurements, the experimenter knows the correct answer and hence canvalidate the listener’s response: A typical question is “Was this sound high or low?” The key point ofsuch objective measurement approaches is that a false response is clearly indicative of the listener
not having heard the sound, while a correct response is indicative of successful hearing after
correction for the guess rate. Alternatively, the question might remain “Did you hear a sound?”, butwith the twist that no sound is present on some trials (so-called catch trials). In this case, thelistener’s response criterion can be estimated from the distribution of “Yes” and “No” responses
1

alexandra.bendixen@physik.tu-chemnitz.de

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across trials with and without sound presentation based on signal detection theory (1). Pure-toneaudiometry is still partly based on subjective measurements, whereas modern speech comprehension
tests usually employ objective criterion-free measurements (2). Both use staircase procedures
nowadays to render testing more efficient and more accurate at the same time.
Besides subjective and objective psychophysical measurements, a third way of assessing soundprocessing abilities is the use of psychophysiological measurements such as otoacoustic emissions,
eyetracking/pupillometry, or electroencephalography (EEG). These measurements have in common
that they no longer require an overt response by the listener, as they infer auditory processing
abilities from physiological responses to certain sounds. Some authors reserve the term “objective”
exclusively for these techniques (3), which is important to acknowledge to avoid terminologicalconfusion across different disciplines. The notion that a physiological measurement is more objective
than any psychophysical one mainly stems from the worry that involving listener responses
confounds the test result with factors unrelated to hearing ability. Yet a criterion-free psychophysicalmeasurement largely alleviates this problem because “faking good” is impossible since responses canbe validated, and “faking bad” is unlikely as it requires a fair amount of knowledge about the testingprocedure. Some other factors affecting behavioral responses, such as the amount of attention
devoted to the sounds or the task, affect psychophysical and psychophysiological responses alike – atleast those psychophysiological responses that are more remote from the initial sensory transduction,such as eye movements and EEG responses elicited by sounds (4).
Nevertheless, for some questions there are undisputable advantages of psychophysiological over(even objective) psychophysical measurements. One of these advantages is the applicability to arange of contexts in which measurements requiring a response by the listener are impossible: Either
because the ability to respond is temporarily unavailable (e.g., during sleep or anesthesia), or
because it is restricted for longer periods of time (e.g., in neonates or coma patients). Anotheradvantage of psychophysiological measurements lies in the fact that they can assess auditory
processing outside the focus of the listener’s attention, which greatly reduces the testing burden:
Ideally, the listener can engage in an enjoyable activity like watching a sub-titled movie or reading abook (5), while their auditory processing abilities are assessed in the background. This opportunity
could be a great relief to hearing-aid or cochlear-implant patients, who otherwise would have toparticipate in lengthy fitting sessions that involve performing the same listening task over and overagain – which can be heavily frustrating for those who are hard of hearing.
Psychophysiological measurements thus have the potential to facilitate auditory diagnostics in avariety of listeners, ranging from sleeping neonates (6) to listeners with severe degrees of hearing
impairment for which behavioral testing would present too much of a burden (7). The remainder ofthis paper focuses on diagnosing higher auditory processing abilities on the basis of EEG, and more
specifically, on event-related brain potentials (ERPs) extracted from the listener’s continuous EEG
recording. ERPs are popular measures of auditory function due to their sensitivity to fine details ofauditory processing, their high temporal precision, and their applicability across a wide range ofparticipant groups with low testing burden.

2. AUDITORY CORTICAL EVENT-RELATED BRAIN POTENTIALS
Auditory ERPs are elicited in response to above-threshold sounds. They are usually uncovered byaveraging EEG epochs across a certain number (on the order of 100) of stimulus presentations toremove high-amplitude spontaneous brain activity. When adequate signal-to-noise ratio has beenreached, ERPs show a characteristic series of deflections, some of which can be directly mapped tostages of auditory function (8). For instance, the brainstem-evoked potentials (auditory brainstem
responses, ABRs) and middle-latency responses (MLRs) reflect the bottom-up flow of information
through different subcortical and thalamocortical processing stages along the auditory pathway, as
well as their modulation by top-down information. Of particular interest for the present work areauditory long-latency responses (LLRs) reflecting auditory information processing in the cortex.
Several long-latency ERP components have been identified that correlate with abilities involved
in sound processing. For the present purposes, those ERP components that are elicited automatically(i.e., without any need for the listener to pay attention to the sounds or perform a task on them) are ofgreatest interest, because they exploit the full potential of psychophysiological measurements –studying listeners who are not able to give behavioral responses, and reducing the testing burden for
any listener. Besides the obligatory sensory ERP components P1/P50 and N1, the bulk of work on“automatic” auditory cortical ERPs has employed the mismatch negativity (MMN) component.

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MMN is elicited when the auditory system detects an unexpected sound – usually a rare soundamongst a series of frequent sounds (9). This, in turn, can be used to probe the listener’s ability tomake certain acoustic distinctions, since detecting the rarity of a sound is only possible if the listener
can perceive the difference between rare and frequent sounds. Depending on the attribute defining
the rarity, MMN can be employed to probe the listener’s accuracy in physical feature discrimination,
their ability to extract complex regularities (patterns) between successive sounds, or their sequential
auditory scene analysis abilities in situations with more than two putative sound streams. Thesewide-spread options, together with its ease of application, have made the MMN component a popular
tool for tapping into auditory processing. A large body of work is now available showing the utilityof MMN-based measurements across a wide range of research questions at group level (e.g., 6, 7,
10,11). There are also many successful extensions to diagnostic questions at single-subject level (e.g.,
3, 12). One remaining challenge of MMN-based diagnostics is the small amplitude of the component,
requiring a large number of trials to achieve sufficient signal-to-noise ratio. This poses a particularchallenge because MMN paradigms crucially depend on the rarity of the eliciting stimulus:
increasing the frequency of the rare stimulus unavoidably reduces MMN amplitude. The optimum
frequency has been estimated at 8-10% (13), leading to the requirement to present ten times morestimuli than the one of interest. One important optimization of the MMN paradigm involves
presenting many different types of physical feature changes in one sequence (14), which makes theparadigm much more efficient – yet it does not affect the challenge that the overall frequency of eachphysical feature change should not exceed 10%. Hence long data collection times are required.
Almost twenty years ago, the work by Claude Alain and colleagues (15) has brought anotherauditory ERP component onto the picture: the so-called object-related negativity (ORN). The ORN
component is elicited when simultaneous sounds are perceived as originating from two separatesound sources. This perceptual process is called concurrent sound segregation, and the ORN reflects
either the process itself or its result: the perception of two or more sounds in a mixture. The ORN
inherited its name (i.e., object-related negativity) from the fact that the decomposition of a soundmixture into its constituent parts is also called auditory object formation.
Unlike the MMN, the ORN is largely independent of the eliciting event’s probability (16, but see
17). Surprisingly, compared to the MMN, the ORN has received a considerably smaller amount ofresearch attention; in fact, its potential as a diagnostic tool of auditory function might be greatly
underestimated. The remainder of this paper discusses the suitability of the ORN as a tool for
objectively studying the perceptual segregation of concurrent sound sources at group level as well as
at single-subject level (i.e., for individual diagnostics).

3. EMPIRICAL WORK ON ORN & CONCURRENT SOUND SEGREGATION
3.1 ORN-based measurements at group level
Alain and colleagues introduced the ORN as an ERP correlate of concurrent sound segregation(15). ORN is elicited by many different cues inducing perceptual segregation of simultaneous sounds
such as inharmonicity (15), dichotic pitch (16), simulated echo (18), differences or discontinuities inlocation (19), and onset asynchrony (20, 21, see Figure 1).

Figure 1 – Stimulus (left) and ORN results (right) of sound segregation based on onset asynchrony

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For instance, a study in our lab (21) investigated the segregation of simultaneous sounds based on
small amounts of onset asynchrony between them. Harmonic tone complexes were presented with thesecond partial being delayed within a range of 0 to 100 ms. This mimics the fact that even when two
independent sound sources emit sounds concurrently, it hardly ever happens that they start producing
sounds at exactly the same time. The processing of onset asynchrony as a cue for concurrent soundsegregation was compared between young, normal-hearing listeners (N=20, Æ26 years) and elderly
listeners with mild hearing impairment (N=18, Æ65 years).
Stimulus configuration and ORN results are displayed in Figure 1. ORN was calculated bysubtracting ERPs elicited by stimuli without onset asynchrony from those with onset asynchrony.
Similar to the better-known MMN, the ORN presents as a frontocentral negativity with polarity
inversion at the mastoid electrodes when nose reference is used. This is consistent with generators in
the auditory cortex (15, 22). ORN latency, amplitude, and topography were all highly similar in the
two age groups, as displayed on Figure 1 for the highest amount of onset asynchrony that wasinvestigated – the same was true for all other levels of onset asynchrony as well. ORN amplitude
increased with onset asynchrony (p<.001) independently of age group. Figure 2 illustrates this for
ORN amplitude at a frontocentral electrode (Fz) and at the average of the mastoid electrodes (CM).
The apparent similarity and statistical indistinguishability of the two age groups suggests that
concurrent sound segregation by onset asynchrony is preserved in healthy auditory aging (21).

Figure 2 – ORN amplitude as a function of group and onset asynchrony at Fz and Common Mastoids (CM)
These results were confirmed in an independent study on new samples of young and elderly
listeners, using speech sounds rather than complex tones, with the same manipulation of onset
asynchrony (23). Again, both age groups benefitted to a similar extent from using onset asynchrony
for concurrent sound segregation. This contrasts other segregation cues like inharmonicity, whose
use has been shown to decline with age (24). Such findings are informative for models of concurrent
sound segregation, for hearing training programs, and for hearing aid design.
Regarding the core conclusion that the ability to segregate concurrent sounds by onset asynchrony
is relatively preserved in older listeners, in both studies (21, 23) the ORN results obtained duringpassive listening were well in line with the results of psychophysical testing during active listening.
For the harmonic tone complexes displayed in Figure 1, active listening consisted in a thresholdmeasurement regarding the sound level at which the delayed partial must be presented for the listenerto hear two concurrent sounds. Elderly listeners showed generally lower performance in this task,
which was evident in the condition without onset asynchrony and was carried through all conditions
with onset asynchrony. Importantly, the elderly listeners’ performance increase across the different
onset asynchrony levels was identical to that of the young listeners. This corresponds to ORN
amplitudes being indistinguishable between the age groups, since ORN directly reflects thedifference of conditions with versus without onset asynchrony. This correspondence of EEG andbehavioral data suggests that the ORN component is a valuable tool to complement or even replace
psychophysical testing in cases where behavioral measurements are impossible or present too muchof a burden. The successful application of ORN for group-level investigations naturally leads to thequestion whether it might be suitable for individual diagnostics. An extension to the purposes ofindividual diagnostics, however, requires revisiting the results at the single-subject level.

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3.2 ORN-based measurements at single-subject level
Similar to the onset asynchrony study shown in Section 3.1 (21), group-level investigations havedemonstrated that the ORN is elicited by a great variety of cues inducing concurrent soundsegregation (15, 16, 18, 19, 20). In turn, the ORN could be used to measure the integrity of theprocessing of each of these cues in the auditory system of an individual listener for diagnostic
purposes. This possibility has been explored in some studies regarding age-related changes (25),effects of musicianship (26), and changes in auditory processing of persons diagnosed with
autism-spectrum disorder (27). In contrast, it has not received much attention as an auxiliary
diagnostic tool for listeners with hearing loss, such as for fitting or follow-up success control ofhearing aids or cochlear implants – MMN seems to be considered the key EEG indicator in thosecases (28). Similar to the MMN, ORN can be recorded outside the focus of attention and thus offers a
low-burden measurement for individual patients. It also lends itself towards investigations in
populations in which behavioral testing is difficult or impossible, such as in pre-verbal infants.
Yet the transition from the group level to the individual level requires careful examination ofseveral prerequisites: Is the ORN sensitive enough to measure sound segregation abilities at the levelof a single listener? Does it show adequate test-retest reliability? Does the strong relation between
the amount of physical feature change and the ORN amplitude (Figure 2) hold at the individuallevel? Do single-subject ORN amplitudes correlate highly with behavioral testing scores, such that it
is feasible to replace psychophysical with psychophysiological measurements in this case?
We were able to address some of these questions in our study outlined in Section 3.1 on
onset-asynchrony-based segregation of concurrent sounds in young and elderly adults (21). Figure 3
shows the results of correlation analyses between psychophysiological data (ORN amplitude; withmore negative values indicating better processing of the cue) and psychophysical data (behavioral
threshold improvement for hearing the delayed partial; again with more negative values indicating
better performance).

Figure 3 – Relation of EEG and behavioral data within listeners (left) and across listeners (right)
The left panel of Figure 3 shows a scatter plot of the group-level relation between ORN amplitude
at Fz and behavioral threshold improvement within listeners, separately for each age group (young ingreen, elderly in orange). ORN amplitude and behavioral threshold improvement were averaged
across listeners separately for each onset asynchrony level, yielding six scores (10/20/40/60/80/100ms) for each of the two measures (behavioral threshold improvement/ORN amplitude). Each circle
thus indicates one onset asynchrony condition. Pearson correlation between ORN amplitude andbehavioral threshold improvement was significant for the whole sample (r=.878, p<.05), and wasnumerically even higher in the elderly group (r=.962, p<.01) than in the young group (r<.794,
p=.059). Hence, at group level, the elicitation of higher (more negative) ORN amplitudes in a given
condition (onset asynchrony level) was associated with larger performance improvements in
detecting the delayed partial (i.e., the delayed partial could be detected at lower sound levels).
The good correspondence between EEG and behavioral data might be suggestive of theconclusion that the two approaches measure similar aspects of concurrent sound segregation by onset
asynchrony, and hence that one could replace the other. However, when the aim is individual

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diagnostics, showing strong correlation at group level is not sufficient: The relation might be much
weaker in the individual datasets simply due to reduced signal-to-noise ratio. Hence the correlationmust be revisited at the single-subject level. This is possible by recomputing the correlation of ORN
amplitude and behavioral threshold improvement for each listener, yielding 38 individual correlation
scores. In order to assess whether the single-subject correlations exceed chance level, the average
individual correlation can be tested against zero by applying Fisher’s z transformation. The
group-average z value was 0.661, corresponding to a back-transformed average correlation of 0.579,
which was significantly higher than zero (p<.001). Again, results were highly similar when analyzed
separately within each age group (young listeners: z=0.602, back-transformed r=0.539, p<.001;
elderly listeners: z=0.726, back-transformed r=0.621, p<.001). This implies that, within the majorityof the listeners, a higher (more negative) ORN amplitude in a given condition (onset asynchrony
level) was associated with higher behavioral threshold improvement in this condition. The reductionof the single-subject correlation (r=.579) relative to the group-level correlation (r=.878) is well inline with previous studies (25, 26); the amount of reduction is tied to the signal-to-noise ratio in theindividual data. In the current case, signal-to-noise ratio and thus sensitivity of the measurement wasapparently sufficient at single-subject level.
It is important to realize that these correlations were conducted within each listener across onset
asynchrony levels. Therefore, they permit the following conclusion: If a listener shows a higher ORN
amplitude in condition 1 than in condition 2, that same listener will tend to also show a higher
behavioral threshold improvement in condition 1 than in condition 2. This conclusion is beneficial
when drawing comparisons across conditions (e.g., different stimuli, or different ways to present
these stimuli, such as in different preprocessing settings of a hearing aid). It must not be confusedwith a possible relation between EEG and behavior across listeners. In other words, it does not allow
for the following conclusion: If listener A shows higher ORN amplitude than listener B, listener A
will tend to also show a higher behavioral threshold improvement than listener B. This issue must be
tested in a different way as follows.
The right panel of Figure 3 shows a scatter plot of the single-level relation between ORN
amplitude at Fz and behavioral threshold improvement across listeners, separately for each age group(young in green and elderly in orange). ORN amplitude and behavioral threshold improvement wereaveraged across onset asynchrony levels separately for each listener, yielding 38 scores for each of
the two measures (behavioral threshold improvement/ORN amplitude). Each circle thus indicates one
listener. In contrast to the analyses above, Pearson correlation between ORN amplitude andbehavioral threshold improvement was not significant across the whole sample (r=.181, p=.277), nor
was it significant within either age group (young listeners: r=.232, p=.324; elderly listeners: r=.136,
p=.591). Hence a listener with higher (more negative) average ORN amplitudes did not necessarily
have larger average performance improvements in detecting the delayed partial – in other words,
mean ORN amplitude of a listener could not be used as a proxy for mean behavioral threshold
improvement of the same listener.
The patterns of each of these correlation analyses was highly similar to those obtained in ourparallel study (23) employing the same manipulation with speech sounds. Together, the results
suggest that direct inference from ORN amplitude on behavioral measures (and vice versa) is
feasible when comparing different conditions within each group or within each listener, but not
feasible when comparing different groups or different listeners with each other. This is not a matterof excessive noise in the individual data: The correlation within listeners (left panel of Figure 3) was
significant both at group level and at single-subject level. The sensitivity of the measurement(including its signal-to-noise ratio) was thus adequate.
It should be emphasized that the specific correlation pattern presented here was obtained for thisparticular context (i.e., comparing the processing of onset asynchrony in young and mildly
hearing-impaired elderly listeners) – in other contexts, correlations of ORN amplitude andbehavioral scores across listeners have indeed been reported (27). Hence a general recommendationis that the different levels of making comparisons (within or across listeners) should not be confusedwith one another, and that the validity of equating psychophysiological with psychophysical data
must be tested in each specific context.
3.3 Promises and caveats
Based on the work presented in the above sections, complementing or even replacing
psychophysical by psychophysiological (ORN-based) testing is highly promising for certain research

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and applied questions. In the context of fitting a hearing-assistive device (i.e., testing different
settings against each other) or evaluating its success (reassessing hearing ability in longitudinalfollow-ups), the lack of correlation across listeners does not matter because the correlation within
listeners gives the necessary piece of information: Higher ORN amplitude of a listener with setting 2
than with setting 1 implies that this listener is likely to show a larger perceptual benefit from setting
2 than setting 1. Higher ORN amplitude of a listener at time-point 2 than at time-point 1 implies that
this listener’s perception likely has also improved. Hence, psychophysiological data gives exactly
what is needed to make a choice for the listener’s benefit. It can be recorded with low testing burden(mainly the application of the electrodes; the testing itself can be done outside the focus of attention,
while the listener engages in an enjoyable activity like watching a video). This alleviates some of thefrustration involved in running many different psychophysical tests in listeners who are hard ofhearing. At the same time, ORN-based testing has high face validity for the listener: The situationthat two sounds are overlapping and must be disentangled is one that any listener frequently
encounters in daily life, and a situation that many hearing-impaired listeners struggle with.
Of course, many questions still need to be addressed before applying the ORN in a routine manner.
An important question concerns the number of stimulus presentations needed to achieve acceptableaccuracy and reliability of the measurement. (It is worthy to note that this is an open question forother components as well, even if they are already routinely applied.) One beneficial aspect of the
ORN is that increasing the stimulus number does not come with a large overhead because component
amplitude is largely independent of overall stimulus probability (16, but see 17).
One note of caution is needed regarding the interpretation of the ORN as a correlate of perceptual
segregation. In the study presented in Sections 3.1. and 3.2 (21), the ORN could equally well be asimple response to the physical difference between the synchronous and asynchronous sounds (e.g.,an N1 component elicited by the delayed part of the sound). This caveat applies to many other ORN
studies as well, because the stimuli leading to perceptual segregation typically differ in physicalterms from the stimuli perceived as a unitary sound. However, there is some evidence that ORN
elicitation matches perception with physically identical stimuli that can be interpreted as one or two
sounds (18). Moreover, even if the ORN turns out to be dominated by physical rather than perceptual
factors, its elicitation still speaks to the integrity of processing this particular physical difference(cue) in the listener’s auditory system. For many applied questions, this is fully sufficient, whereas
whether the response reflects mere cue processing or higher-level object formation is not a key issue.
What would be more important from an applied point of view, is to study whether ORN elicitation ispredictive of being able to use the eliciting cue in real-life auditory scene analysis.

4. CONCLUSIONS
Starting from some general considerations about the utility of psychophysiological measurements
for studying auditory function, this paper introduced the notion that the ORN component should be
explored more widely in this context. Despite some caveats and outstanding issues, this component
seems to bears great promise for diagnosing an individual’s ability to segregate concurrent soundsources, and to process the acoustic cues that are needed therein. The ORN component may have thepotential to become a routine tool for evaluations in the context of hearing-assistive devices.

ACKNOWLEDGEMENTS
The empirical work reported in this paper received financial support from the German Research
Foundation (Deutsche Forschungsgemeinschaft, DFG).

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