Fast detection of unexpected sound intensity decrements as revealed by human evoked potentials.
ABSTRACT The detection of deviant sounds is a crucial function of the auditory system and is reflected by the automatically elicited mismatch negativity (MMN), an auditory evoked potential at 100 to 250 ms from stimulus onset. It has recently been shown that rarely occurring frequency and location deviants in an oddball paradigm trigger a more negative response than standard sounds at very early latencies in the middle latency response of the human auditory evoked potential. This fast and early ability of the auditory system is corroborated by the finding of neurons in the animal auditory cortex and subcortical structures, which restore their adapted responsiveness to standard sounds, when a rare change in a sound feature occurs. In this study, we investigated whether the detection of intensity deviants is also reflected at shorter latencies than those of the MMN. Auditory evoked potentials in response to click sounds were analyzed regarding the auditory brain stem response, the middle latency response (MLR) and the MMN. Rare stimuli with a lower intensity level than standard stimuli elicited (in addition to an MMN) a more negative potential in the MLR at the transition from the Na to the Pa component at circa 24 ms from stimulus onset. This finding, together with the studies about frequency and location changes, suggests that the early automatic detection of deviant sounds in an oddball paradigm is a general property of the auditory system.
[show abstract] [hide abstract]
ABSTRACT: It has been proposed that the functional role of the mismatch negativity (MMN) generating process is to issue a call for focal attention toward any auditory change violating the preceding acoustic regularity. This paper reviews the evidence supporting such a functional role and outlines a model of how the attentional system controls the flow of bottom-up auditory information with regard to ongoing-task demands to organize goal-oriented behavior. Specifically, the data obtained in auditory-auditory and auditory-visual distraction paradigms demonstrated that the unexpected occurrence of deviant auditory stimuli or novel sounds captures attention involuntarily, as they distract current task performance. These data indicate that such a process of distraction takes place in three successive stages associated, respectively, to MMN, P3a/novelty-P3, and reorienting negativity (RON), and that the latter two are modulated by the demands of the task at hand. (PsycINFO Database Record (c) 2012 APA, all rights reserved)Journal of Psychophysiology 10/2012; 21(3-4):251-264. · 1.54 Impact Factor
[show abstract] [hide abstract]
ABSTRACT: In a dichotic listening situation stimuli were presented one at a time and at random to either ear of the subject at constant inter-stimulus intervals of 800 msec. The subject's task was to detect and count occasional slightly different stimuli in one ear. In Experiment 1, these ‘signal’ stimuli were slightly louder, and in Experiment 2 they had a slightly higher pitch, than the much more frequent, ‘standard’, stimuli. In both experiments signals occured randomly at either ear. Separate evoked potentials from three different locations were recorded for each of the four kinds of stimuli (attended signals, unattended signals, attended standards, unattended standards). Contrary to Hillyard et al. (1973), no early (N1 component) evoked-potential enhancement was observed to stimuli to the attended ear as compared with those to the unattended ear, but there was a later negative shift superimposed on potentials elicited by the former stimuli. This negative shift was considered identical to the N1 enhancement of Hillyard and his colleagues which in the present study was forced, by the longer inter-stimulus interval used, to demonstrate temporal dissociation with the N1 component. The ‘Hillyard effect’ was, consequently, explained as being caused by a superimposition of a CNV kind of negative shift on the evoked potential to the attended stimuli rather than by a growth of the ‘real’ N1 component of the evoked potential.Acta Psychologica 08/1978; 42(4):313-29. · 2.26 Impact Factor
Article: Cerebral generators of mismatch negativity (MMN) and its magnetic counterpart (MMNm) elicited by sound changes.[show abstract] [hide abstract]
ABSTRACT: Infrequent ("deviant") sounds occurring in a sequence of repetitive ("standard") sounds elicit an event-related brain potential (ERP) response called the mismatch negativity (MMN) even in the absence of attention to these sounds. MMN appears to be caused by a neuronal mismatch between the deviant auditory input and a sensory-memory trace representing the standard stimuli. This automatic mismatch process has presumably a central role in discrimination of changes in the acoustic environment outside the focus of attention. Thus, localizing cerebral generators of MMN might help identify brain mechanisms of auditory sensory memory and involuntary attention. This review summarizes results from studies aimed at localizing MMN generators on the basis of (1) scalp-distribution, (2) magnetoencephalographic (MEG), (3) intracranial, and (4) brain-lesion data. These studies indicate that a major MMN source is located in the auditory cortex. However, the exact location of this MMN generator appears to depend on which feature of a sound is changed (e.g., frequency, intensity, or duration), as well as on the complexity of the sound (e.g., a simple tone versus complex sound). Consequently, memory traces for different acoustic features, as well as for sounds of different complexity, might be located in different regions of auditory cortex. However, MMN appears to have generators in other brain structures, too. There is some evidence for contribution of frontal-lobe activity to the MMN, which might be related to the involuntary switching of attention to a stimulus change occurring outside the focus of attention. In addition, intracranial MMN recordings in animals suggest that at least in some species, MMN subcomponents also may be generated in the thalamus and hippocampus.Ear and Hearing 03/1995; 16(1):38-51. · 2.58 Impact Factor
Fast Detection of Unexpected Sound Intensity
Decrements as Revealed by Human Evoked Potentials
Heike Althen1,2, Sabine Grimm1,2, Carles Escera1,2*
1Institute for Brain, Cognition and Behavior (IR3C), University of Barcelona, Barcelona, Catalonia, Spain, 2Cognitive Neuroscience Research Group, Department of
Psychiatry and Clinical Psychobiology, University of Barcelona, Barcelona, Catalonia, Spain
The detection of deviant sounds is a crucial function of the auditory system and is reflected by the automatically elicited
mismatch negativity (MMN), an auditory evoked potential at 100 to 250 ms from stimulus onset. It has recently been shown
that rarely occurring frequency and location deviants in an oddball paradigm trigger a more negative response than
standard sounds at very early latencies in the middle latency response of the human auditory evoked potential. This fast and
early ability of the auditory system is corroborated by the finding of neurons in the animal auditory cortex and subcortical
structures, which restore their adapted responsiveness to standard sounds, when a rare change in a sound feature occurs. In
this study, we investigated whether the detection of intensity deviants is also reflected at shorter latencies than those of the
MMN. Auditory evoked potentials in response to click sounds were analyzed regarding the auditory brain stem response,
the middle latency response (MLR) and the MMN. Rare stimuli with a lower intensity level than standard stimuli elicited (in
addition to an MMN) a more negative potential in the MLR at the transition from the Na to the Pa component at circa 24 ms
from stimulus onset. This finding, together with the studies about frequency and location changes, suggests that the early
automatic detection of deviant sounds in an oddball paradigm is a general property of the auditory system.
Citation: Althen H, Grimm S, Escera C (2011) Fast Detection of Unexpected Sound Intensity Decrements as Revealed by Human Evoked Potentials. PLoS
ONE 6(12): e28522. doi:10.1371/journal.pone.0028522
Editor: Mark W. Greenlee, University of Regensburg, Germany
Received August 15, 2011; Accepted November 9, 2011; Published December 6, 2011
Copyright: ? 2011 Althen et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, pro ided the original author and source are credited.v
Funding: This work was supported by the program Consolider-Ingenio 2010 (CDS2007-00012), the National Program for Fundamental Research (PSI2009-
08063) from the Spanish Ministry of Science and Innovation, the Bial Foundation (Portugal, grant #37/10), a grant from the Catalan Government (SGR2009-11),
and an ICREA Academia Distinguished Professorship awarded to C.E. URLs: http://www.ingenio2010.es/contenido.asp?menu1=&menu2=&menu3=&dir=./
?vgnextoid=33881f4368aef110VgnVCM1000001034e20aRCRD&lang_choosen=en. http://www.bial.com/en/bial_foundation.11.html. http://www.gencat.cat/
index_eng.htm. http://www.icrea.cat/web/home.aspx. The funders had no role in study design, data collection and analysis, decision to publish, or
preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: firstname.lastname@example.org
The automatic detection of deviant or contextual novel stimuli
is a crucial function of the auditory system, as it can trigger an
attention switch to unexpected events (for a review, see ). It is
reflected by the auditory evoked potential (AEP) called mismatch
negativity (MMN; ), a negative deflection between 100 and
250 ms after stimulus onset with sources in auditory and prefrontal
cortex areas [3–4] that is elicited by rare regularity-violating
stimuli, which occur amongst a regular sound pattern. MMN is the
most prominent component reflecting auditory deviance detection
in humans. Yet, based on animal research, it has been proposed
that the detection of deviant stimuli is a multi-stage process  that
begins at early latencies of about 20 ms [6–7] and extends over
auditory areas from the IC to the cortex (for a review, see ).
This hypothesis is supported by several recent studies that give
evidence of a deviance-related modulation in the human middle
latency response (MLR). According to Grimm et al. , frequency
deviants of a controlled oddball paradigm elicit a more negative
response than standard sounds at circa 40 ms after stimulus onset
(Nb component). A still earlier deviance-related effect in the MLR
was found by Slabu et al. . They report an enhanced Pa
component in response to band-pass-filtered broadband noise
deviants at latencies of circa 30 ms. Moreover, the detection of
location deviants has been shown to modulate the Na component
of the MLR at approximately 25 ms after change onset [11–12].
This data suggest that deviance-related modulations at early
latencies of the AEP occur for sound changes in frequency and
location. However, whether this generalizes to other sound
features, like intensity or duration, has not been investigated yet.
Furthermore encoding mechanisms of sound probabilities are
evident at the cellular level at comparably early latencies in the
form of a stimulus-specific adaptation (SSA) to repetitive stimuli;
that is, a strong decrease of neuronal response and a sudden
restoration of firing rates when deviant sounds occur. This
phenomenon has been found in the mammalian inferior colliculus
[7,13], the thalamic medial geniculate body and reticular nucleus
[6,14], the auditory cortex [15–18], the avian external nucleus of
the inferior colliculus, as well as in the avian homolog to the
mammalian superior colliculus and frontal eye fields . It is still
a matter of discussion how those novelty-sensitive auditory
neurons correspond to the cortical MMN. The MLR reflects the
auditory evoked activity in the auditory cortex [20–21], and
possibly also in the medial geniculate body of the thalamus [22–
23] between circa 12 and 70 ms after stimulus onset. Therefore,
the MLR facilitates the comprehension of the relation between
SSA at the cellular level and the emergence of the scalp-recorded
MMN, as shown by recent studies in humans mentioned above, in
PLoS ONE | www.plosone.org1December 2011 | Volume 6 | Issue 12 | e28522
which the analysis of the MLR points to an earlier detection of
frequency and location deviants than reflected by the MMN.
In this study, we aim at investigating whether the processing of
deviant sound intensities becomes evident by modulations in the
MLR or even in the auditory brainstem response (ABR) of the
human AEP. This is based on the fact that, on the one hand,
probabilities of stimulus intensity levels are encoded in terms of
SSA at the neuronal level [16,19,24]; and on the other hand, that
the MMN is elicited in response to stimuli with rare intensity
increments and decrements [2,25].
Materials and Methods
Participants gave informed written consent before the experi-
ment. The experimental protocol was approved by the Ethical
Committee of the University of Barcelona and was in accordance
with the Code of Ethics of the World Medical Association
(Declaration of Helsinki).
Twenty-eight young, normal-hearing subjects (18–33 years, 14
females) participated in the experiment for payment (J6 per hour).
None of them reported any neurological or psychiatric disorders
or any treatment with psychotropic drugs. All participants had a
hearing threshold below a peak-equivalent sound intensity of
30 dB SPL (group average=22 dB peSPL) for click tones with a
duration of 100 ms. The electroencephalogram (EEG) data of five
participants had to be excluded from analysis due to a high
number of artifacts.
Experimental design and procedure
Participants were sitting comfortably in an electrically shielded
and sound-attenuated room. They were asked to relax, to
concentrate on a silent movie with subtitles and to ignore the
sounds. Click tones of 100 ms duration were presented binaurally
through headphones with an onset-to-onset interval varying
randomly in 8-ms steps between 256 and 344 ms (mean=300 ms).
Sound intensities were presented above the individual hearing
threshold (sensation level, dB SL) which was detected by means of
an audiometry using the same stimuli as in the experiment. Sound
presentation was controlled using the software MATLAB (Release
14) and the Psychophysics Toolbox extensions . Stimuli were
presented in three different auditory sequences: the oddball,
reversed oddball and control condition (Fig. 1). In the oddball
condition, stimuli were either standard sounds with an intensity
level of 50 dB SL and a presentation probability of 6/7 or rare
deviant sounds with a presentation probability of 1/7 and an
intensity level of 40 dB SL. In the reversed condition, the
presentation probabilities were the same as in the oddball
condition, but the intensity levels of the stimulus types were
swapped so that the standard stimuli were presented at an intensity
level of 40 dB SL and the deviants at an intensity level of 50 dB SL
(standard stimuli of this reversed condition will from now on be
referred to as ‘‘standards’’). This condition was included in order
to compare AEPs to the same physical stimuli while holding
different contextual roles. It should be noticed the outmost
importance to control for physical differences of the stimuli,
because especially at short latencies, the AEP is very sensitive to
stimulus properties. This is demonstrated by the AEPs in response
to the control stimuli. The latency and amplitude of the Wave V
(ABR) and Na component (MLR) change systematically with
stimulation intensity (see the results section below). Comparing
AEPs in response to deviant and standard stimuli having different
intensities could lead to mixing deviance-related modulations of
the AEPs with signal differences due to the physical differences of
the stimuli. An additional control condition served to control for
the refractoriness-based explanation of deviance-related effects
([25,27]; cf.). It consisted of seven different stimuli with the
intensities 10, 20, 30, 40, 50, 60 and 70 dB SL, each occurring
with a probability of 1/7. Stimuli were presented randomly with
the restriction that a deviant was preceded by at least two
standards and a control stimulus was followed by at least two
control stimuli of a different intensity. The three conditions were
subdivided into 18, approx. 5.5 min. lasting, blocks. Blocks of the
oddball and control conditions were presented alternating whereas
the reversed condition was applied in the first and the last block. In
total, standards, deviants and the different control stimuli were
presented 1,248 times each.
The EEG was recorded continuously from seven scalp
electrodes (Ag/AgCl). An additional electrode was placed on the
tip of the nose to analyze the MMN. Recording positions of the
scalp electrodes were Cz, FCz, Fz, FC3, FC4, PO7, PO8,
Figure 1. The three stimulation conditions. Stimuli were clicks of
100 ms duration, presented binaurally through headphones. The onset-
to-onset interval varied randomly in 8-ms steps between 256 and
344 ms, with a mean of 300 ms A. In the oddball blocks, two types of
stimuli were presented randomly. Standard stimuli, indicated in black,
were presented with an intensity of 50 dB SL and a probability of 6/7.
Deviant stimuli, indicated in grey, were presented with an intensity of
40 dB SL and a probability of 1/7. B. In the reversed oddball blocks, the
intensities of standards and deviants were exchanged. Probabilities and
colors are as in A. C. In the control blocks seven different stimuli with
intensities of 10, 20, 30, 40, 50, 60 or 70 dB SL, each with a probability of
1/7 were presented randomly.
Intensity Deviants Modulate the MLR
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mounted according to the 10–20 system using an elastic cap (64-
Charlotte, NC). Additionally, the eye movements were controlled
with two bipolar electrodes placed above and below the left eye
(vertical electrooculogram) and two electrodes placed at the outer
canthi of each eye (horizontal electrooculogram). The recorded
signal was referenced to linked electrodes placed on the earlobes.
Impedances were kept below 5 kV. The amplified signal
(SynAmpsRT, NeuroScan, Compumedics, Charlotte, NC) was
online bandpass-filtered from 0.05 to 1500 Hz and digitized with a
sampling rate of 20 kHz using the software Scan 4.4 (NeuroScan,
Compumedics, Charlotte, NC).
For AEP analysis in the long latency range (LLR) and the MLR,
the EEG-data was down-sampled to 2000 Hz. For offline filtering,
bandpass filters ranging from 1.5 to 30 Hz for the LLR, from 15–
250 Hz for the MLR, and from 100–1500 Hz for the ABR were
applied. The LLR data was re-referenced to the nose. Thereafter,
the AEPs to deviants, standards and controls were averaged
separately in epochs ranging from 2100 to 300 ms for the LLR,
250 to 100 ms for the MLR, and 230 ms to 20 ms for the ABR.
Averaged epochs included a pre-stimulus baseline with duration of
100 ms, 50 ms and 30 ms respectively. Trials including peak-to-
peak amplitudes exceeding 80 mV (LLR), 50 mV (MLR) or 35 mV
(ABR) were automatically rejected. AEPs elicited by the control
stimuli were analyzed in the MLR and ABR ranges. As the Wave
V of the ABR in response to control stimuli of 40 dB SL was
maximal at the FCz electrode and the Na component at Fz, AEPs
at these electrodes were taken for statistical analyses and
illustration. Peak amplitudes and latencies of Wave V and the
Na component revealed a clear dependence on stimulation
intensity. Therefore, linear regression analyses were calculated
for peak amplitudes and latencies of those components. Moreover,
peak amplitudes and latencies, elicited by adjacent control stimuli
(e.g. control 20 dB SL and control 30 dB SL), were tested for
differences with Wilcoxon-Tests or paired samples two-tailed
Student’s t-tests. With the purpose of disclosing deviance-related
changes in the AEP, the responses to deviants, standards and
control stimuli of 40 dB SL were compared. Consequently, all
three stimulus types were physically equal and presented at the
same intensity level. To evaluate the signal of the components
Wave V, Na and Pa (Nb and Pb components were not elicited for
stimulation at 40 dB SL), repeated measures analysis of variance
(ANOVAs) were calculated on mean voltages of a time window
centered on the grand-average peak. For Wave V, a 2-ms time
window from 7 to 9 ms and for the Na and Pa component 10-ms
time windows from 14 to 24 ms and from 26 to 36 ms,
respectively, were used. The ANOVAs included the factors
Comparison (standard and deviant, standard and control, deviant
and control, respectively) and electrode (Fz, FCz, Cz, FC3 and
FC4). Peak latencies of the Wave V and the Na component were
tested at the electrodes FCz and Fz, respectively, for differences
regarding the stimulus type (Wilcoxon’s signed-rank test).
Additionally, difference waveforms of the response to the three
stimulus types were plotted and screened visually for deflections. In
the MLR, standard, deviant and control mean voltages of a 6-ms
time window centered on the peak of the largest deflections of the
deviant-standard difference waveform (21 to 27 ms) were
compared. As the difference curve for deviants and controls
peaked at 20 ms after stimulus onset, additionally the deviant and
the control responses in a time window centered on the deviant-
control difference waveform (17 to 23 ms) were compared. The
mean amplitudes were tested for differences by repeated measures
ANOVAs with the factors Comparison (standard and deviant,
standard and control, deviant and control, respectively) and
electrode (Fz, FCz, Cz, FC3 and FC4). In the LLR, mean voltages
of the time window 158–188 ms centered on the deviant-standard
difference wave and of the time window 163–193 ms centered on
the deviant-control difference wave in the typical time range of
MMN (100–250 ms) were tested for differences at the electrode
FCz using paired samples two-tailed Student’s t-tests. Paired
samples two-tailed Student’s t-tests and Wilcoxon’s signed-rank
tests were corrected using a Bonferroni correction for multiple
comparisons. Results were considered significant when p,.05.
The number of individual trials per stimulus type after artifact
rejection exceeded 900 trials for the ABR, 990 for the MLR, and
350 for the LLR. Click stimuli elicited a robust ABR, which
depended linearly in amplitude and latency on the stimulation
level, but not on the contextual novelty of a stimulus. For high
stimulation levels, the four principle components of the MLR were
clearly elicited. Strikingly, deviant stimuli in the oddball condition
elicited a more negative response than standard stimuli at around
24 ms after stimulus onset, corresponding to the transition from
the Na component to the Pa component. Moreover, the standard
Na component was reduced compared to the response to the same
physical control stimulus.
Wave V, the most prominent component of the ABR, could be
identified at the single-subject level from a stimulus level of 10 to
20 db SL on. The subsequent Wave VI and the preceding Waves
I, II, and III were pronounced for moderate to high stimulus levels
(Fig. 2A). The peak amplitude of Wave V for stimulation from 20
to 70 dB SL displayed a positive linear relationship to the
stimulation level (Fig. 2B,C), as revealed by a linear regression
analysis (R2=.307, b =.555, t(136)=7.771, p,.001). Compar-
ison of peak amplitudes of Wave V elicited by adjacent stimulation
intensities resulted in statistically significant differences for
stimulation with 20 and 30 dB SL (z=24.045, p,.001), 30 and
40 dB SL (z=23.194, p,.01) and 60 and 70 dB SL (z=23.771,
p,.001; Fig. 2C). The peak latency of Wave V also depended on
the stimulation level, being negatively related to stimulus intensity,
that is, it decreased with increasing stimulation level (Fig. 2B,D;
R2=.722, b=2.849, t(136)=218.771, p,.001). This relation-
ship was also reflected in significantly different peak latencies in
response to adjacent stimulation levels (Fig. 2D; 20/30 dB SL:
z=24.0, p,.001; 30/40 dB SL: z=23.317, p,.01; 40/50 dB
SL: z=23.0, p,.01; 50/60 dB SL: z=23.0, p,.01; 60/70 dB
SL: z=22.646, p,.01).
In the MLR, the four typical components Na, Pa, Nb and Pb,
were obtained (Fig. 3A,B). In Table 1, mean amplitudes, mean
latencies as well as the latency range of the MLR components for
stimulation with 70 dB SL are given. Whereas the Na and Pa
components were elicited for most subjects already at lower
intensities, the Nb and Pb components where measurable only for
a part of the group when stimulating with low intensities. The Na
amplitude and latency depended linearly on the stimulation
intensity (Fig. 3C,D). Linear regression analysis revealed an
amplitude increase (Fig. 3C; R2=.161, b=2.402, t(106)=
24.518 p,.001) and latency decrease (Fig. 3D; R2=.457,
b=2.676, t(106)= 29.441, p,.001) with increasing stimulation
intensity. Na mean amplitudes for stimulation at 20 and 30 dB SL
(t(17)=3.623, p,.05) as well as for stimulation at 30 and 40 dB SL
(t(17)=3.381, p,.05) differed significantly from each other
Intensity Deviants Modulate the MLR
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(Fig. 3C). Significant latency differences were observed for
stimulation at 20 and 30 dB SL (z=23.116, p,.05) as well as
for stimulation at 40 and 50 dB SL (Fig. 3D; z=23.051, p,.05).
Peak latencies of Wave V elicited by deviant, standard and
control stimuli were tested for differences at FCz. Mean
amplitudes were tested for differences from 7 to 9 ms after
stimulus onset at the electrodes Fz, FCz, Cz, FC3 and FC4.
Repeated measures ANOVAs did not reveal any effect of stimulus
type (Fig. 4A–C).
In the MLR, mean amplitudes of the Na and Pa components
were tested for deviance-related modulations at the electrodes Fz,
FCz, Cz, FC3 and FC4. No significant differences for the stimulus
type were revealed. Visual inspection of the waveforms showed
that the response to deviants and standards diverged at the
transition from the Na to the Pa component (Fig. 5 and 6A,D),
which became visible in the difference waveform (deviant-
standard), peaking at 24 ms after stimulus onset (see Fig. 5 and
6A). An ANOVA comparing the mean voltages of deviant and
standard responses in the latency window around the peak of this
deflection (21 to 27 ms) over the electrodes Fz, FCz, Cz, FC3 and
FC4 was significant for the stimulus type (F(1,22)=10.686,
p,.01). The difference consisted in a more negative response to
deviants in comparison to standards. Post-hoc tests resulted in
significant differences (Fig. 5) at the electrodes Fz (t(22)=23.342,
p,.05), FCz (t(22)= 23.385, p,.05) and FC3 (t(22)= 24.178,
p,.01). Testing for differences in standard and control mean
voltages (21 to 27 ms) over the electrodes Fz, FCz, Cz, FC3 and
FC4 resulted in a significantly stronger response to the control
than to the standard stimulus (Fig. 6C,D; F(1,22)=9.727, p,.01).
This difference was significant at Fz (t(22)= 23.610, p,.05), FCz
(t(22)= 23.154, p,.05) and FC3 (t(22)= 23.385, p,.05). No
significant differences were found for deviant and control
responses neither at latencies of the deviant-standard difference
waveform nor at latencies of the deviant-control difference
waveform (17 to 23 ms; Fig. 6B). Comparison of peak latencies
revealed a significant difference for the Na peak latency between
standards and controls at electrode Fz (z=22.801, p,.05) with
the control showing longer latencies (Fig. 6C).
A small MMN was elicited, that is the response to deviants was
more negative than the standard response with a maximal
difference at 173 ms after stimulus onset at the electrode FCz.
The comparison of mean amplitudes (1582188 ms) at the
electrode FCz revealed a significance (t(22)=22.130, p,.05).
Mean amplitudes of deviant and control stimuli, however, did not
differ significantly from each other.
The objective of this study was to investigate whether MMN-
like deviance-related modulations in response to intensity deviants
were present in the MLR and ABR of the human AEP. The main
finding was that at the transition from the Na to the Pa component
of the MLR, at circa 24 ms from stimulus onset, click sounds of
lower intensity that occurred in the role of deviants elicited a
negative deflection compared to click sounds with the same
physical intensity occurring in the role of standards.
MMN can be elicited pre-attentively by louder as well as by
softer intensity deviants [2,25,29232] and peaks at approx.
Figure 2. ABRs to the control stimuli. A. Single-subject recording to control stimuli of 70 dB SL at FCz. ABR components are labeled with Roman
numerals. B. Grand-average response (N=23) to the control stimuli of 10 to 70 dB SL at FCz. C, D. Mean Wave V peak amplitudes (C) and latencies
(D) at FCz in response to the control stimuli presented at 20 to 70 dB SL. Error bars indicate +/- 1 standard error. Significant differences between
adjacent control stimuli are indicated with an asterisk (p,0.05).
Intensity Deviants Modulate the MLR
PLoS ONE | www.plosone.org4December 2011 | Volume 6 | Issue 12 | e28522
200 ms after stimulus onset . Our results suggest that in
addition to intensity MMN, the detection of intensity deviants is
reflected at much shorter latencies in the time range of the MLR,
at the transition of the Na to the Pa component. The generators of
the Na component are suggested to lie in the primary auditory
cortex and the Pa component possibly has several sources in the
primary, belt and parabelt regions [20221,33]. This finding for
intensity deviants is in agreement with recently reported
modulations of the MLR triggered by frequency  and
location  deviants. On the one hand, Grimm et al. 
reported that frequency deviants elicited a more negative Nb
component than standard and control stimuli of a controlled
oddball paradigm. Given that the AEPs for clicks presented at
40 dB SL recorded in our study only revealed the components Na
and Pa, specific comparisons to Grimm et al. ’s results cannot be
drawn and the possible existence of deviance-related modulations
in the time range of the Nb and Pb components triggered by
deviant intensities cannot be ruled out. On the other hand, an
enhanced Pa component in response to broadband noise
frequency deviants of a controlled oddball experiment was
observed by Slabu et al. . Furthermore, concerning sound
location, it was shown that sounds presented from an infrequent
location elicit an enhanced Na component . Thus, the
processing of location and intensity deviants appears to be
reflected at earlier latencies than the processing of frequency
Besides fast deviance-related modulations in the MLR, deviant
detection at single- and multi-unit levels beginning at latencies of
about 20 ms  is supported by several animal studies. These
studies reported neurons in the auditory regions of the midbrain,
thalamus and cortex exhibiting strong SSA to repetitive stimuli
and restoration of their firing rates when a deviant stimulus
occurred. This phenomenon has been mainly observed for
frequency deviants [627,13219], but in a handful of studies,
the processing of intensity deviants was tested as well. Ulanovsky
et al.  found that in the cat primary auditory cortex, louder
Figure 3. MLRs to the control stimuli. A, B. Grand-average AEP (N=23) filtered for the MLR in response to control stimuli of 10 to 30 dB SL (A)
and 40 to 70 dB SL (B) at Fz. C,D. Mean peak amplitudes (C) and latencies (D) of the Na component in response to the control stimuli of 20 to 70 dB
SL at the electrode Fz (N=18). Error bars indicate +/- 1 standard error. Significant differences between adjacent control stimuli are indicated with an
Table 1. Mean latencies, latency ranges, and mean
amplitudes of the MLR components Na, Pa, Nb and Pb,
elicited by the control stimulus presented at an intensity of
70 dB SL. N=18.
MLR componentsNa PaNbPb
Mean latency [ms] (SEM) 18.4 (.26)30.0 (.87) 44.9 (1.39)61.94 (1.56)
Latency range [ms]16–20 24–3734–59 53–76
Mean amplitude [ mV] (SEM) 2.77 (.08) .60 (.07)
2.81 (.07) .86 (.08)
Standard errors of mean (SEM) are given in parentheses.
Intensity Deviants Modulate the MLR
PLoS ONE | www.plosone.org5December 2011 | Volume 6 | Issue 12 | e28522
intensity deviants triggered an increased firing rate compared to
standard stimuli, but softer did not (cf. discussion of Farley and
colleagues ). This was confirmed by Farley et al. , who
recorded from the primary auditory cortex of the awake rat.
According to Pe ´rez-Gonza ´lez et al. , already neurons in the IC
of the rat exhibit SSA and an enhancement in the firing rate in
response to intensity deviants. Furthermore, in the midbrain of the
barn owl, SSA and enhanced response to deviant intensities was
detected . Importantly, the data of this later study suggests that
a release from SSA is not only triggered by a louder novel stimulus,
but also by a weaker stimulus following a sequence of 10 repetitive
stimuli. However, at the cellular level, results regarding softer
intensity deviants are contradictory and more detailed investiga-
tion concerning this matter is required.
The relationship between MMN and SSA, as two measures of
the enhanced responsiveness to deviant stimuli, has not been
clarified yet and there are constraints in comparing the effects of
intracranial cellular recordings to scalp evoked potentials, as the
latter are a composed signal reflecting the concurrent activity of
many different neural populations. A bridge between cellular
responses and scalp-measured responses is provided by evoked
local field potentials (eLFPs), which were recorded simultaneously
with cellular responses in a frequency oddball paradigm from the
rat auditory cortex , and more specifically, from the rat
primary auditory cortex . Similar to the increased response
measured at the cellular level, the first negative deflection of the
eLFP showed an enhanced response to deviants compared to
standards [18,24], with the difference wave peaking at approx.
25 ms after stimulus onset .
A significant difference between the deviant and control ERP
was not observed in this study. The control condition was
implemented because there might exist an amplitopicity in the
auditory cortex , that is, a systematical encoding of
intensity similar to the tonotopic organization. This would imply
that an enhanced response to the deviant compared to the
standard could be explained by refractoriness of the neurons
responding to the standard stimulus and the recruitment of ‘‘fresh’’
neurons when responding to the deviant. However, the control
condition, as it is applied in this study, may overcontrol for
refractoriness , because the neurons that respond to the
deviant stimuli might be more refractory than the neurons
responding to the control stimuli, as the constant activation
elicited by the standard stimulus could also fatigue the neighboring
neural population responding to the deviant. This effect has been
demonstrated by Taaseh et al.  who examined the detection of
frequency deviants by means of eLFP and multi-unit activity
recordings in the rat auditory cortex. They showed that, on the
one hand, comparison of the deviant response and the response to
a control stimulus embedded in a control condition, where the
frequency separation between the control stimuli is narrower than
the one between deviant and standard stimuli in the oddball
condition, results in a stronger neural response to the deviant than
to the control stimulus. On the other hand, responses to the
deviant are not stronger than responses to a control stimulus that is
embedded in a control condition where the frequency separation
between the different control stimuli is the same as it is between
deviant and standard stimulus in the oddball condition. Especially
in the experimental design used in the present study, it is likely that
the neural population responding to the softer deviant is also
activated during the presentation of the louder standard stimulus
since louder stimuli activate a wider neural region in the auditory
cortex than softer stimuli . This might dispel the notion that
fresh neurons are recruited during presentation of the deviant
stimulus when it is softer in intensity than the standard. Likewise it
is suggested that when using a softer deviant, the MMN comprises
no activation from the N1 generator process, as the N1 generator
process should be attenuated compared to its activation by the
louder standard stimulus . Assuming this, the enhanced MLR
response to softer deviants observed in our study could be
interpreted as the reflection of a sensory novelty processing rather
than a release from refractoriness. Additionally, the fact that
intensity deviants elicited a differential response compared to the
standards not at the peak of any particular MLR waveform, but at
the transition of the Na to the Pa waveform, provides further
support in favor of a ‘‘genuine’’ deviance-related response. One
may speculate that such an additional neuroelectric activity might
be elicited by a specific neural population showing an enhanced
activation (in terms of a release from SSA) at a latency that is
independent or delayed compared to the neuronal population’s
activity giving rise to the specific MLR waveforms.
The consistent and reliable analysis of sounds reflected by AEP
components is nicely expressed in the ABRs to the stimuli of the
Figure 4. ABRs to standards, deviants and controls. Grand-
average response (N=23) to deviants and standards (A), deviants and
controls (B) and standards and controls (C) at FCz. The grey shaded
bars denote the time window of the mean amplitudes used for
Intensity Deviants Modulate the MLR
PLoS ONE | www.plosone.org6 December 2011 | Volume 6 | Issue 12 | e28522
control condition. Sound intensity is consistently modulating Wave
V, which is systematically increasing in amplitude and systemat-
ically decreasing in latency with increasing stimulation intensity as
it has already been shown in seminal studies (; for a
review, see ). Nonetheless, to the authors’ opinion, it is worth
depicting this relationship using up-to-date plotting techniques
here, most importantly to show that it is possible to obtain
excellent data quality by recoding only 1,248 trials per stimulus
type. This is revealed by the flat baseline and the low threshold of
Wave V (which is already elicited from stimulation with 10 to
20 dB SL on).
Wave V of the ABR showed no differences in mean
amplitude or latency between the stimulus types deviant,
standard and control, which is consistent with the results of
the study by Slabu et al.  on broadband noise frequency
deviants. The absence of a deviance-related modulation in the
ABR was expected, as it reflects the first volley of activations at
auditory stations up to the IC . Additionally, it is
characteristically consistent and analyzes sounds quickly and
reliably . The subcortical neurons that exhibit sensitivity to
deviant auditory stimuli in animals are mostly located in non-
primary subdivisions of the thalamus and the IC [7,13214].
These non-primary portions are innervated by dense top-down
projections  whereas primary regions are part of the
afferent pathway [42,44]. ABRs, however, reflect activity from
the afferent auditory pathway , which might explain why
no deviance-related modulations in the ABR have been found
in the present and previous studies.
There was only a small MMN elicited for comparison of
deviant and standard; and no difference was observed for
comparison of deviant and control. This is probably due to
characteristics of the sequences’ design, which were tailored to
record ABRs, MLRs and LLR responses simultaneously. First,
click sounds, which were used to elicit ABR and MLR
components, are not optimal to elicit MMN . Second, the
usage of a rather short and random SOA with a mean of 300 ms
might have led to the small MMN because the temporal
probability of deviants increases with decreasing SOA. This
leads to a decline of MMN amplitude .
The feature which differentiates the deviant from the standard
stimuli in this study was sound intensity. Regarding the perception
of sound intensity it has to be considered that the perceived
intensity of a sound depends on the sound duration, because a
temporal integration of loudness over the first hundreds of
milliseconds takes place . As the used stimuli in this study
were click sounds with a very short duration of 100 ms, temporal
integration of loudness does not contribute to their loudness
perception. This raises the question if the detection of intensity
deviants for stimuli with a longer duration is based on an
additional, later comparison mechanism which takes into account
the temporal integration of loudness and would only be reflected at
later latencies of the AEP that is by MMN.
In summary, our results confirm the idea that the detection of
deviant and contextual novel sounds is a pervasive property of the
auditory system. It has so far been shown that frequency, location
and intensity deviants are automatically detected in the first 40 ms
from stimulus onset and additionally in the later processes reflected
by MMN. The existence of auditory novelty detection at early
stages is supported by animal studies, which suggest that even at
the subcortical level, stimulus feature changes are encoded by
single neurons. The distinction between standard and novel or
deviant sounds is an essential cognitive ability as it is important e.g.
for auditory attention and the perception of sounds that signal a
harmful situation. Therefore, the exact understanding of the
novelty detection pathway is not only an important step in the
exploration of the cognitive system, but can also contribute to
successful diagnosis of cognitive dysfunctions and the development
of their treatments.
Figure 5. Deviance-related changes in the MLR. Grand-average response (N=23) at FCz, FC3 and Fz elicited by deviants and standards. The
grey shaded fields mark the time window of the mean amplitudes used for statistics. The difference waveforms reveal a negative displacement of the
response to deviants compared to the one to standards.
Intensity Deviants Modulate the MLR
PLoS ONE | www.plosone.org7 December 2011 | Volume 6 | Issue 12 | e28522
We thank Amalia Gual de Torrella for laboratory assistance.
Conceived and designed the experiments: HA SG CE. Performed the
experiments: HA. Analyzed the data: HA. Contributed reagents/
materials/analysis tools: SG CE. Wrote the paper: HA. Correction of
the manuscript: SG CE. Design of software scripts: SG.
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