All content in this area was uploaded by Lars Rogenmoser on Feb 04, 2021
Content may be subject to copyright.
All content in this area was uploaded by Lars Rogenmoser on Jan 06, 2021
Content may be subject to copyright.
Auditory aversion in absolute pitch possessors
, H.Charles Li
, Lutz J€
Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
Department of Medicine, University of Fribourg, Fribourg, Switzerland
Department of Psychology, University of Zurich, Zurich, Switzerland
University Research Priority Program (URPP), Dynamics of Healthy Aging, University of Zurich, Zurich,
Received 30 March 2020
Reviewed 9 June 2020
Revised 7 August 2020
Accepted 9 November 2020
Action editor Gus Buchtel
Published online 5 December 2020
Absolute pitch (AP) refers to the ability of identifying the pitch of a given tone without
reliance on any reference pitch. The downside of possessing AP may be the experience of
disturbance when exposed to out-of-tune tones. Here, we investigated this so-far unex-
plored phenomenon in AP, which we refer to as auditory aversion. Electroencephalography
(EEG) was recorded in a sample of AP possessors and matched control musicians without
AP while letting them perform a task underlying a so-called affective priming paradigm:
Participants judged valenced pictures preceded by musical primes as quickly and accu-
rately as possible. The primes were bimodal, presented as tones in combination with visual
notations that either matched or mismatched the actually presented tone. Both samples
performed better in judging unpleasant pictures over pleasant ones. In comparison with
the control musicians, the AP possessors revealed a more profound discrepancy between
the two valence conditions, and their EEG revealed later peaks at around 200 ms (P200) after
prime onset. Their performance dropped when responding to pleasant pictures preceded
by incongruent primes, especially when mistuned by one semitone. This interference was
also reﬂected in an EEG deﬂection at around 400 ms (N400) after picture onset, preceding
the behavior responses. These ﬁndings suggest that AP possessors process mistuned
musical stimuli and pleasant pictures as affectively unrelated with each other, supporting
an aversion towards out-of-tune tones in AP possessors. The longer prime-related P200
latencies exhibited by AP possessors suggest a delay in integrating musical stimuli, un-
derlying an altered afﬁnity towards pitchelabel associations.
©2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC
BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
*Corresponding author. Department of Medicine, University of Fribourg, Chemin du Mus
ee 8, 1700, Fribourg, Switzerland.
E-mail address: firstname.lastname@example.org (L. Rogenmoser).
Available online at www.sciencedirect.com
Journal homepage: www.elsevier.com/locate/cortex
cortex 135 (2021) 285e297
0010-9452/©2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://
Absolute pitch (AP), the ability to identify the chroma of a
tone without the aid of any reference (Takeuchi &Hulse,
1993), is sparsely distributed in the population (approximate
<1%) but yet bears phylogenetic and ontogenetic signiﬁcance:
The phylogenetic argument relies on the fact that hearing
with a preference for absolute over relational cues appears to
be conserved in humans (Levitin &Rogers, 2005) given that
songbirds fail to demonstrate octave generalization while
experiments conﬁrm this particular skill in rhesus monkeys
(Cynx, 1993;Wright, Rivera, Hulse, Shyan, &Neiworth, 2000).
Some ontogenetic evidence suggest that humans prefer ab-
solute auditory cues during early infancy, shifting towards a
preference for relational ones as they mature (Saffran &
Griepentrog, 2001; for a contradictory ﬁnding see Plantinga
&Trainor, 2005). A genetic component in combination with
speciﬁc learning factors such as early music engagement and
exposure to language, and possibly the presence of a partic-
ular brain anatomy prevent the maturation-related decline in
the ability of processing pitches absolutely and thus account
for AP acquisition (Deutsch, Henthron, Marvin, &Xu, 2006;
Gregersen, Kowalsky, Kohn, &Marvin, 1999,2001). Similar to
the successful language acquisition that requires early lan-
guage exposure during a child’s development (Newport,
1990), AP may only emerge on condition that music engage-
ment takes place during a critical period, a maturational
stage at which cognitive processing still functions in a rather
unidimensional mode and the brain is still highly malleable
and responsive to environmental inputs (Chin, 2003;Russo,
Windel, &Cuddy, 2003). As a result, adult AP possessors
show an increased left-sided asymmetry of the planum
temporale (Keenan, Thangaraj, Halpern, &Schlaug, 2001;
ancke, Huang, &Steinmetz, 1995;Wilson, Lusher,
Wan, Dudgeon, &Reutens, 2009), which is likely due to the
reduced size on the right side (Keenan et al., 2001;
Wengenroth et al., 2013). This structural asymmetry might
create a functional dominance directing auditory stimuli to
categorization centers within the left temporal lobe such as
the superior temporal sulcus (J€
ancke, Langer, &H€
Loui, Li, Hohmann, &Schlaug, 2010). A further brain structure
related to AP is the posterior dorsal frontal cortex. This brain
region might potentially drive conditional associative mem-
ory and, in the context of AP, be responsible for the process
underlying the association between categorized pitches and
verbal labels or other sensorimotor codes (Zatorre &Beckett,
1989;Zatorre, Perry, Beckett, Westbury, &Evans, 1998). In AP
possessors, within this left-sided frontotemporal network an
interplay is detectable even at rest in electroencephalography
(EEG) recordings (Elmer, Rogenmoser, Ku
2015), suggesting functional optimization that may enable
the automatic nature of AP. Furthermore, right-sided net-
works comprising auditory and non-auditory structures have
been reported (Kim &Kn€
osche, 2016,2017;Wengenroth et al.,
2013), possibly mediating AP perception (Wengenroth et al.,
2013). Automaticity is, however, accompanied by the difﬁ-
culty in suppression, as many studies using interference
tasks have demonstrated, revealing a drop in identiﬁcation
performance under incongruent trial conditions among AP
possessors (Akiva-Kabiri &Henik, 2012;Itoh, Suwazono,
Arao, Miyazaki, &Nakada, 2005;Rogenmoser, Arnicane,
ancke, &Elmer, 2020;Schulze, Mueller, &Koelsch, 2013;Ziv
&Radin, 2014). Further studies revealed that in comparison
to non-AP (NAP) participants, AP possessors are disadvan-
taged in recognizing transposed melodies or in identifying
musical intervals within out-of-tune contexts (Miyazaki,
1993;Miyazaki &Rakowski, 2002). AP possessors incur more
cognitive load for processing out-of-tune tones, this certain
sensitivity towards mistuned tones increasing the later the
onset of musical training takes place during childhood
(Rogenmoser, Elmer, &J€
ancke, 2015). From an affective
perspective, this sensitivity is corroborated by anecdotal ev-
idence suggesting that AP possessors become agitated when
exposed to out-of-tune tones (Levitin &Rogers, 2005). Here,
we investigated this so-far unexplored phenomenon in AP,
which we refer to as auditory aversion. Understanding the
mechanisms underlying auditory aversion might advance
research on cognitive-affective development. It is further
crucial given that some AP possessors report a distortion in
frequency perception as a consequence of aging (Athos et al.,
2007;Vernon, 1977). Thus, aversion would no longer exclu-
sively be triggered externally by certain out-of-tune tones but
additionally internally by perceiving in-tune tones as out-of-
tune. In the present study, we measured the affective re-
actions in response to musical stimuli in a sample of AP
possessors and in one of matched control participants by
recording EEG during the performance of a task underlying an
affective priming paradigm (Fazio, 2001). This particular
paradigm has turned out to be promising in capturing the
automatic processing of emotional experiences (Fazio, 2001;
Klauer, 1997), even though semantic network effects (i.e.,
semantic priming) may contribute to the measurement (Eder,
Leuthold, Rothermund, &Schweinberger, 2012;Steinbeis &
Koelsch, 2008,2011). The affective priming procedure in-
volves the sequential presentation of two valenced stimuli,
namely the preceding so-called primes and the following so-
called targets. The task is to handle the targets whereby the
preceding primes are either affectively related or affectively
unrelated to them. It is well documented that affectively
unrelated prime-target pairs induce interference that varies
as a function of the extent of involved emotional experience
(Fazio, 2001). In EEG, this interference is reﬂected by a
negative-going deﬂection around 400 ms after target-onset,
which is referred to as the N400 (Kutas &Hillyard, 1980;
Steinbeis &Koelsch, 2008,2011;Zhang, Li, Gold, &Jiang, 2010).
EEG has an excellent time resolution and has been promising
in capturing the early perceptual and cognitive processes
underlying AP (Burkhard, Elmer, &J€
Sollberger, Meyer, &J€
ancke, 2013;Greber, Rogenmoser,
ancke, 2018;Rogenmoser et al., 2015). In the pre-
sent study, the participants were instructed to judge as
quickly and accurately as possible whether pictures (targets)
were either pleasant or unpleasant by pressing one of two
response buttons. In the experimental condition, these tar-
gets were preceded by musical stimuli (primes) which were
bimodal, comprising visually presented notations in combi-
nation with auditorily presented tones. The auditory
cortex 135 (2021) 285e297286
counterpart either matched the notations (congruent) or
deviated from them (incongruent) in a higher semitone (i.e.,
sharp) or quarter-tone. Based on the assumption that out-of-
tune tones trigger aversion in AP possessors, we predicted an
interference in the AP possessors’ response behavior
accompanied by a greater N400 deﬂection in conditions in
which the incongruent primes preceded pleasant targets.
2. Materials and methods
We report how we determined our sample size, all data ex-
clusions (if any), all inclusion/exclusion criteria, whether in-
clusion/exclusion criteria were established prior to data
analysis, all manipulations, and all measures in the study.
Inclusion (i.e., possession or non-possession of AP) and
exclusion criteria (i.e., history of neurological, psychiatric and
audiological disorders) were established a priori. The open
source software G*Power (Faul, Erdfelder, Lang, &Buchner,
2007) was used to estimate the sample sizes required for the
detection of within-between interaction effects.
Twenty-one AP possessors (14 males) and 21 matched NAP
control musicians (13 males) participated in this study. The
two samples were comparable regarding age (t
P¼.428, d¼.25), general cognitive capability (t
P¼.502, d¼.21) as measured by the ShipleyeHartford Retreat
Scale (Shipley, 1940), and comparable regarding the distribu-
tion of handedness (one left-hander in each sample) and of
the sexes (Х
¼.10, P¼.747). Both AP and NAP participants
commenced their musical training at a comparable age range
¼1.64, P¼.106, d¼.51) and trained for a comparable
number of hours per day (t
¼.45, P¼.656, d¼.14) and years
in total (t
¼.11, P¼.910, d¼.04). Across both samples, the
participants were comparably skilled in music performance,
as conﬁrmed using pitch and rhythm discrimination tasks
underlying psychophysical adaptive staircase procedures
(Fujii &Schlaug, 2013;Loui, Alsop, &Schlaug, 2009). Regarding
pitch discrimination, the minimum detectable frequency dif-
ference around the center frequency of 500 Hz was measured.
The two samples performed at comparable pitch discrimina-
tion thresholds (t
¼1.18, P¼.244, d¼.36). Regarding rhythm
discrimination (i.e., Beat Interval Test (Fujii &Schlaug, 2013)),
sequences of 21 woodblock tones with varying interval
lengths were presented. The sensory threshold for discrimi-
nating temporal changes as well as the performance in tap-
ping in synchrony while adapting to temporal changes were
measured. The two groups performed at comparable rhythm
discrimination thresholds (t
¼.011, P¼.992, d¼.00) and
with a comparable tapping synchronization ability (t
P¼.507, d¼.21). The values on characteristics and musical
background are reported in Table 1.
All participants gave written informed consent, and the
study was approved by the institutional review board of Beth
Israel Deaconess Medical Center. No part of the study pro-
cedures or analyses was pre-registered prior to the research
2.2. Absolute pitch (AP) veriﬁcation
AP was conﬁrmed using an established pitch-labeling test
(Keenan et al., 2001) in which 52 trials were presented. Each trial
contained one computer-generated sine wave tone (500-ms
duration with a 50-ms rise and decay time) with a funda-
mental frequency covering one octave from 370 Hz (F#3) to
739.97 Hz (F#4) in the equal-tempered Western scale. The par-
ticipant’s task was to label each pitch by writing down the letter
name on an answer sheet upon hearing each tone. The inter-
tone interval was 2 sec. Semitone errors were counted as
incorrect responses. The AP possessors performed (% correct
responses) considerably better on this test (mean correct: 94.15,
SD ¼10.05) than the NAP participants (mean correct 5.77,
SD ¼6.26; t
¼34.21, P¼3.08 10
,d¼10.56). NAP partici-
pants did not perform better than chance level (8.33%;
¼1.89, P¼.075). The individual scores are depicted in Fig. 1.
2.3. Experimental task and stimulus material
To measure the participants’ affective reaction in response to
musical stimuli, EEG was recorded during performance of a
task underlying an affective priming paradigm. In this task,
the participants were instructed to judge as quickly and
accurately as possible whether pictures (targets) preceded by
musical stimuli (primes) were either pleasant or unpleasant
by pressing one of two response buttons. The targets were 144
pictures (see Appendix) taken from the International Affective
Picture System (Lang, Bradley, &Cuthbert, 2008) on the basis
of normative ratings (9-point scales) regarding the two affec-
tive dimensions of valence (1 ¼most unpleasant; 9 ¼most
pleasant) and arousal (1 ¼most calm; 9 ¼most aroused). Half
of the picture collection was pleasant (M¼7.60, SD ¼.41) while
the other was unpleasant (M¼2.66, SD ¼.79; t
,d¼7.82), but across both valences the pic-
tures were controlled for arousal (unpleasant pictures:
M¼5.59, SD ¼.71; pleasant pictures: M¼5.41, SD ¼.95;
¼1.33, P¼.185, d¼.21). The preceding primes were
Table 1 eCharacteristics and data on the musical
background of both samples.
Age (years) 22.38 (4.86) 23.47 (3.94)
Cognitive capability (IQ scores) 115.24 (8.62) 113.47 (8.22)
Age at commencement of musical
6.14 (2.44) 7.43 (2.60)
Practice intensity (hours per day) 2.92 (1.82) 2.67 (1.79)
Duration of musical training (years) 16.24 (5.70) 16.05 (5.08)
Pitch discrimination threshold (Hz) at
4.89 (5.43) 7.55 (8.77)
Rhythm; perceptual discrimination
1.53 (1.72) 1.54 (3.01)
Rhythm; tapping synchronization
1.61 (3.56) 2.39 (4.03)
Listed are the means with the standard deviations in brackets. All
independent-samples t-test calculated for each variable revealed
values of P>.1. AP: Absolute pitch, NAP: non-absolute pitch.
cortex 135 (2021) 285e297 287
bimodal, comprising visually presented notations in combi-
nation with auditorily presented pure tones. The set of pre-
sented notations comprised the scale of 12 subsequent notes
ranging from F#4 to F5. The auditory counterpart either
matched the notations or deviated from them in a higher
semitone (sharp) or quarter-tone. The 144 targets were pre-
sented 4 times in total; once per each matching condition and
additionally once as control condition without any prime.
Since the tuning of the musical stimulus is expected to impact
the affective reaction exceptionally in AP participants, the
particular prime-target pairs in this experimental set-up
reﬂect either affectively unrelated or affectively related con-
ditions. Predicated on this constellation, 6 particular prime-
target pair conditions result (see Table 2), within which each
of the 12 scaled primes were paired 4 times with different
targets (72 times per valence). The prime-target pairs as well
as the order of trials were pseudorandomized. Each trial began
with a ﬁxation cross for gaze stabilization that was presented
for a duration of 500 ms. The following primes were presented
with a duration of 500 ms and the targets with one of 800 ms
while the prime-target interval was of 200 ms. The inter-trial
interval was jittered between 1000 and 1500 ms. The proced-
ure of one trial is illustrated in Fig. 2. The auditory stimuli
included 10 ms of fade-in/out phases and were delivered via
Sennheiser HD 205 headphones at the sound pressure level of
80 dB. The visual material was shown in the center of a PC
laptop monitor. Stimuli presentation and behavior recordings
were controlled by the software PsyTask. Before starting the
actual experiment, the participants were given 8 practice tri-
als to get familiar with the task.
2.4. EEG recording
EEG was recorded via 19 channels (Ag/AgCl electrodes, BEE
Medic GmbH) placed according to the “10e20”system with the
following electrode locations: Fp1, Fp2, F7, F3, Fz, F4, F8, T3, C3,
Cz, C4, T4, T5, P3, Pz, P4, T6, O1, O2. A further Ag/AgCl elec-
trode embedded in the cap horizontally centered between Cz
and Fz served as ground and two Ag/AgCl electrodes clipped
on both earlobes as reference. EEG recording was done with an
ampliﬁer (EEG NeuroAmp x23) and the ERPrec software. The
signal was recorded with a sampling rate of 500 Hz and a
bandpass ﬁlter of .1e100 Hz. Impedances were kept below 5 kU
using conductive gel (Elecro-Gel).
2.5. Data analyses
The conditions of our ethics approval do not permit public
archiving of anonymised study data. Readers seeking access to
the data should contact the ﬁrst or last author. Access will be
granted following completion of a formal data sharing agree-
ment. Legal copyright restrictions prevent public archiving of
the IAPS stimuli used in the current study which can be ob-
tained from (Lang et al. 2008), and see Appendix for stimulus
catalogue numbers. Presentation code, absent the IAPS stim-
uli, may be freely downloaded from https://osf.io/a6qfd.
Raw EEG data were imported into EEGLAB v.13.2.1 (Delorme &
Makeig, 2004), an open source toolbox running under MAT-
LAB. The data were down-sampled to 250 Hz, band-pass
ﬁltered at 1e20 Hz and re-referenced to the mean of the T3
and T4 electrodes. Epochs were created ranging from 200 to
500 ms after prime-onset and from 200 to 1000 ms after
target-onset, respectively. A baseline correction relative to the
200 to 0 ms pre-stimulus time period was applied. Epochs
contaminated by unsystematic artifacts were rejected. Sys-
tematic artifacts corresponding to non-cortical sources were
removed by using independent component analysis (Jung et
al., 2000). Condition-wise, event-related potentials (ERP)
were calculated by averaging the epochs belonging to the
respective condition. The central channels (F3, Fz, F4, C3, Cz,
C4, P3, Pz, P4) were pooled together. The maxima/minima
peak values and their timepoints (latencies) were extracted
Table 2 ePrime-target pair conditions.
1. Congruent prime þpleasant target
2. Incongruent prime (semitone) þunpleasant target
3. Incongruent prime (quarter-tone) þunpleasant target
4. Congruent prime þunpleasant target
5. Incongruent prime (semitone) þpleasant target
6. Incongruent prime (quarter-tone) þpleasant target
Fig. 1 ePitch-labeling performance. Depicted are the
individual scores (%) achieved by the participants with
absolute pitch (AP, blue circles, N¼21) and participants
without absolute pitch (NAP, red circles, N¼21) from the
pitch-labeling test. The dotted line represents the baseline
cortex 135 (2021) 285e297288
from the N100eP200 complex of the prime-induced ERPs. The
minima peak values and their latencies of the negative-going
deﬂection centered around 400 ms after target-onset (N400)
were extracted from the difference waves, calculated between
the two ERPs (affectively unrelatedeaffectively related)
belonging to the same matching condition. In case of the ERPs
induced by targets without preceding primes, minima values
and their latencies of the negative-going deﬂection centered
Fig. 2 eSchematic representation of the task. Each trial began with a ﬁxation cross (A) that was presented on the monitor for
500 ms, followed by a prime (B) for a duration of 500 ms. The prime was bimodal, comprising visually presented notations in
combination with auditorily presented pure tones via earphones. The auditory counterpart either matched the notations
(congruent) or deviated from them (incongruent) in a higher semitone or quarter-tone. Afterwards, the monitor turned blank
for 200 ms (C). Then, the target (D) followed, presented for 800 ms. The target was either a pleasant or an unpleasant picture
taken from the International Affective Picture System. The participants were instructed to indicate as quickly and accurately
as possible the valence of the target by pressing on either the right (pleasant) or left (unpleasant) mouse button. The next
trial followed after the monitor turned blank for a duration jittered between 1000 and 1500 ms (E).
cortex 135 (2021) 285e297 289
around 400 ms after target-onset were extracted from the
difference waves, subtracted from each other in both di-
rections (pleasanteunpleasant and vice versa).
2.5.2. Statistical analyses
The amplitudes and the latencies as well as the mean reaction
times (RT) and accuracy scores obtained from each condition
by each participant were imported into the SPSS software for
statistical analyses. The mean RTs as well as the accuracy
scores were subjected to three-way mixed analyses of vari-
ance (ANOVA) with group (AP, NAP) as between-factor and
two within-factors, namely “matching condition”with four
levels (no prime, congruent, incongruent semitone, incon-
gruent quarter-tone) and “valence”with two levels (pleasant,
unpleasant). The amplitudes and latencies of the ERPs (N100,
P200, N400) were subjected to two-way mixed ANOVAs with
group (AP, NAP) as between-factor and “matching condition”
as within-factor with three levels (congruent, incongruent
semitone, incongruent quarter-tone). The amplitudes and la-
tencies of the negative-going waves of the control difference
waves were subjected to independent-samples t-tests. Sta-
tistical analyses were adjusted for non-sphericity using
GreenhouseeGeiser Epsilon when equal variances could not
be assumed. Group-interaction effects were further inspected
with post-hoc analyses. The relation between group-speciﬁc
ERP ﬁndings and the AP scores achieved from the pitch-
labeling test were investigated using Pearson’s
productemoment correlations. Correlation analyses as well
as t-tests were run two-tailed. Effect size measures were
calculated; namely the Cohen’s dfor t-tests and Generalized
Eta Squared (h
) for ANOVAs.
3.1. Behavioral ﬁndings
The mean reaction times (RT) and accuracy scores achieved at
each condition by both samples are depicted in Fig. 3.Both
samples responded not only faster (F
¼.071) but also with higher accuracy (F
¼12.64, P¼9.87 10
¼.074) to unpleasant targets than
to pleasant ones. The matching condition of the primes had a
group-independent inﬂuence on the RT (F
¼.027). The two samples responded with
comparable RT, as no group effect (F
¼.06) or any group-interaction effects (matching x group:
¼1.31, P¼.265, h
¼.002; valence x group: F
¼2.42, P¼.128, h
¼.003) were revealed. Regarding the
accuracy scores, the two samples differed in general (group
¼4.10, P¼.050, h
¼.055) but differed also as
interaction with the matching condition (F
¼.012) and the valence factor (F
¼.026). Post-hoc pairwise comparisons (Bonferroni-
adjusted at the level of a¼.05for8paired-samplest-tests) of
the accuracy scores between the valences at all matching
conditions across both samples revealed a signiﬁcant differ-
ence only in the AP sample at the incongruent semitone con-
¼3.16, Bonferron i-adjusted P¼.039, d¼.69).
3.2. EEG ﬁndings
3.2.1. N100eP200 complex
The ERP induced by the primes are depicted in Fig. 4 and their
values are plotted in Fig. 5. Regarding the amplitude and the
latency of the N100, no group (amplitude: F
¼.014; latency: F
¼.41, P¼.526, h
¼.008), nor condition
differences (amplitude: F
¼2.89, P¼.061, h
¼2.35, P¼.102, h
¼.012) nor groupecondition in-
teractions (amplitude: F
¼2.748, P¼.070, h
¼.004) were found. Within the P200, AP
possessors peaked later than NAP participants (F
¼.093) but with comparable height (F
¼.008). TheP200 latencies correlated positively with
the participants’ AP scores achieved from the pitch-labeling test
¼.37, P¼.017; incongruent semitone: r
P¼.042; incongruent quarter-tone: r
¼.32, P¼.041). The
matching condition, however, had no impact on the P200
Fig. 3 ePerformances achieved from the affective priming task. The mean RTs (left) as well as the accuracy scores (right) are
depicted for each condition for the absolute pitch (AP, blue, N¼21) and the non-absolute pitch (NAP, red, N¼21) samples.
The solid lines present pleasant targets and the dashed lines present unpleasant targets. The bars depict standard errors.
Two-tailed Bonferroni-adjusted *P<.05.
cortex 135 (2021) 285e297290
¼.32, P¼.649, h
<.001) nor on the P200
¼1.02, P¼.366, h
¼.006), and nor did it interact
with the samples(amplitude: F
¼.59, P¼.531, h
¼.11, P¼.862, h
¼.001) in this regard.
The ERPs induced by the targets including the difference
waves calculated between the two valence factors referring to
each prime matching condition are depicted in Fig. 6. The
values of the difference waves are plotted in Fig. 7. The
negative-going deﬂection of the difference waves calculated
between the affectively related and affectively unrelated pair
conditions varied as a function of the matching condition
¼12.13, P¼1.03 10
¼12.73, P¼6.3 10
¼.178). No group
differences were found in the amplitudes (F
¼.024) nor in the latencies (F
¼.013). The latencies did not reveal a group-interaction
¼1.68, P¼.068, h
¼.048), whereas the
amplitudes did (F
¼5.10, P¼.013, h
effect was not impacted by the participants’ response
behavior, as their RTs did not correlate with the amplitudes;
neither in the AP (“un-/pleasant”x“congruent”:r
“un-/pleasant”x“incongruent quarter-tone”:.1 >r
.6) nor in the NAP group (“un-/pleasant”x“congruent”:r
P>.4; “un-/pleasant”x“incongruent semitone”:r
P>.9; “un-/pleasant”x“incongruent quarter-tone”:r
P>.07). The AP scores, however, correlated negatively with
the “incongruent semitone”amplitudes (r
and trended negatively with the “incongruent quarter-tone”
¼e.29, P¼.060) but correlated positively with
the “congruent”amplitudes (r
¼.31, P¼.044). Post-hoc
comparisons (Bonferroni-adjusted at the level of a¼.05 for 6
paired-samples t-tests) of amplitudes between all matching
conditions across both samples revealed signiﬁcant differ-
ences only in the AP possessors between the congruent and
incongruent semitone conditions (t
adjusted P¼5.88 10
,d¼1.64) and between the
congruent and incongruent quarter-tone conditions
¼3.20, Bonferroni-adjusted P¼.028, d¼1.14).
Independent-samples t-tests across the two samples revealed
a difference at the incongruent semitone condition (t
uncorrected P¼.023, d¼.73).
3.2.3. Control difference waves
Comparing the negative-going deﬂections of the difference
wave calculated by subtraction of the ERPs induced by the
unpleasant from the ERPs induced by the pleasant targets
revealed no group difference in amplitude (t
d¼.03) or latency (t
¼.14, P¼.891, d¼.04). Vice versa, the
negative-going deﬂections of the difference wave calculated
by subtraction of the ERPs induced by the pleasant from the
ERPs induced by the unpleasant targets revealed no group
difference in amplitude (t
¼1.18, P¼.244, d¼.37) or latency
¼.36, P¼.720, d¼.11). The amplitudes also did not
correlate with the AP scores (pleasanteunpleasant: r
P¼.714; unpleasantepleasant: r
¼.17, P¼.294). The ERPs
induced by the targets including the difference waves calcu-
lated between the two valence factors without preceding
primes are also depicted in Fig. 6. The values of the difference
waves are plotted in Fig. 7.
Fig. 4 eGroup-averaged ERPs in response to the primes. On top, the ERPs averaged across the absolute pitch (N¼21) and the
non-absolute pitch (N¼21) samples are displayed. Below, the respective current distribution of the scalps are displayed
derived from the peaks of the N100 (ﬁrst) and P200 (second).
cortex 135 (2021) 285e297 291
The participants processed the unpleasant pictures more
efﬁciently than the pleasant ones, as evident from the faster
and more accurate responses in the unpleasant target condi-
tions. These results mirror the well documented ﬁnding that
unpleasant stimuli induce stronger affective effects than
pleasant ones, supporting the idea that the processing system
is sensitized to aversion ( €
Ohman &Mineka, 2001). From an
evolutionary perspective, this system has adaptive value
given that it favors avoidance/defense over approach
response behavior. This discrepancy, referred to as negativity
bias in the literature, underlies the recruitment of the
subcortical route that involves the thalamus and amygdala,
leading to a more rapid orienting of attention when exposed
with aversive, potentially harmful events (Carreti
Tapia, &Hinojosa, 2001;Ito, Larsen, Smith, &Cacioppo, 1998;
Compared to NAP participants, the AP possessors judged
the targets with accuracy scores varying as function of the
prime-target pair condition. They underperformed strongest
in the condition in which the pleasant targets were preceded
by incongruent primes that were one semitone off. In line with
the behavioral results, the N400 amplitudes differed between
the two samples in dependence of the matching condition.
This interaction effect was due to the conditions in which the
primes were incongruent, particularly in terms of one semi-
tone. The interference in the response behavior together with
the N400 effects occurring in the conditions in which the
pleasant targets were preceded by incongruent primes
conﬁrm that the AP possessors processed these prime-target
pairs as affectively not in line with each other, supporting
an aversion towards out-of-tune tones in AP possessors.
Furthermore, these ﬁndings provide evidence that aversion is
experienced more intensely when detuning reaches one
semitone, possibly underlying the categorical nature of AP
(Harris &Siegel, 1975). Instead of relying on a sensory coding
strategy, AP has shown to rather be driven by a categorical
perception mechanism (Siegel, 1974). Within the critical in-
fantile period during which AP acquisition takes place,
Western pitchelabel associations are formed in units of
Fig. 5 eValues of the prime-induced ERPs. Plotted are the averaged amplitudes (top) and latencies (bottom) from the
absolute pitch (N¼21) and non-absolute pitch (N¼21) sample across all prime matching conditions. The bars depict
standard errors. A: N100. B: P200.
cortex 135 (2021) 285e297292
semitones, leading to a susceptibility speciﬁed for these highly
familiarized units. Thus, in comparison with within-
categorical violations (e.g., quarter-tone), between-categori-
cal violations (i.e., semitone) intensify the interference. In AP
possessors, detuning especially across semitone categories
not only impairs music performance (Miyazaki 1993,1995;
Miyazaki &Rakowski, 2002;Siegel, 1974) but also, as the pre-
sent ﬁndings suggest, affect the affective responses. These
ﬁndings are in line with the more general relation between
categorization difﬁculty (i.e., low ﬂuency processing) and
negative affect (Reber, Schwarz, &Winkielman, 2004). How-
ever, it shall be noted that here we only explored the affective
effects in response to a limited range of detuning degrees in
only one (i.e., sharp) direction by using an indirect measuring
approach. The advantage of the affective priming paradigm
lies in that it bypasses introspection and captures automatic
emotional responses outside of awareness (Bargh &Morsella,
2008;Fazio, 2001;Greenwald, Draine, &Abrams, 1996),
avoiding potential top-down biases. Nevertheless, the partic-
ipants were not asked to directly rate the primes. Thus,
further research is required to validate and generalize our
ﬁndings on auditory aversion covering also detuning degrees
in the “ﬂat”direction.
Regarding the maturational aspect of AP, these ﬁndings are
revealing given that they expand the interlinkage between AP
and other developmental conditions in which AP sometimes
co-exists; such as congenital synesthesia (Bouvet et al., 2014;
Gregersen et al., 2013;H€
anggi, Beeli, Oechslin, &J€
ancke, Rogenmoser, Meyer, &Elmer, 2012) and blindness
(Hamilton, Pascual-Leone, &Schlaug, 2004), autism spectrum
disorder (Bonnel et al., 2003;Brenton, Devries, Barton,
Minnich, &Sokol, 2008;Heaton, 2003;Heaton, Davis, &
e, 2008), Williams syndrome (Lenhoff, Perales, &
Hickok, 2001). A range of auditory abnormalities are reported
in Williams syndrome such as hyper- and odynacusis, audi-
tory allodynia or attraction to certain everyday life sounds
(Levitin, 2005;Levitin, Cole, Lincoln, &Bellugi, 2005). Likewise,
hyperacusis and hypersensitivity to certain, especially com-
plex, sounds have been described in autism spectrum disorder
(O’Connor, 2012;Rosenhall, Nordin, Sandstr€
Fig. 6 eGroup-averaged ERPs induced by the targets including the difference waves. The difference waves are calculated
between the two ERPs (affectively unrelatedeaffectively related) belonging to the same matching condition. In case of the
control condition (no primes), differences waves were calculated by subtracting the ERPs induced by the two targets from
each other in both directions (pleasant-unpleasant and vice versa). The current distributions derived from deﬂection-peak
of each difference curve are plotted as scalp maps. Absolute pitch (left; N¼21), non-absolute pitch (right; N¼21).
cortex 135 (2021) 285e297 293
Gillberg, 1999). Furthermore regarding common characteris-
tics, AP possessors have shown to exhibit more autistic traits
(Brown et al., 2003;Dohn, Garza-Villarreal, Heaton, &Vuust,
2012;Wenhart, Bethlehem, Baron-Cohen, &Altenmu
2019) and rather an “autistic-typical”cognitive style, namely
the processing of local information in expense of global ones
(Foxton et al., 2003;Mottron, Peretz, &Menard, 2000), which is
observable not only in the auditory but also in the visual
domain (Chin, 2003;Costa-Giomi, Gilmour, Siddell, &
Lefebvre, 2001;Wenhart &Altenmu
¨ller, 2019;Ziv &Radin, 2014). Imaging
studies pointed out that speciﬁc hyperfunctioning underlie
local hyperconnectivity between the involved areas in the
brain; a further overlapping feature not only documented in
AP but also synesthesia or other savant skills (Brauchli,
ancke, 2019;Elmer et al., 2015;H€
anggi et al., 2008;
ancke, Langer et al., 2012;Loui et al., 2010;Mottron et al.,
2013). A similar phenomenon to the AP-speciﬁc aversion
conﬁrmed in this study has been described in congenital
synesthesia, a condition that overlaps phenotypically and
genotypically with AP (Gregersen et al., 2013;Loui, Zamm, &
Schlaug, 2012a) and also co-occurs with autism (Bouvet et
al., 2014;Mottron et al., 2013;Neufeld et al., 2013). In
particular, synesthetes react aversively when exposed to
inducereconcurrent pairs mismatching their familiarized
idiosyncratic own (Callejas, Acosta, &Lupi
Beyond the interference reﬂected in the present data
pattern, the AP possessors showed overall poorer accuracy
scores speciﬁcally when judging pleasant pictures. A group
difference in mere affective visual processing, however, was
not supported by the EEG results, as the control difference
curves did not differ between the two samples. Thus, the
question raises to what extent AP possessors differ in affective
processing not limited to out-of-tune responses or beyond the
auditory dimension in general. As already mentioned, non-
auditory differences between AP and NAP participants have
been reported in visual cognition, such as in the ability for
spatial and binocular rivalry resolution (Costa-Giomi,
Gilmour, Siddell, &Lefebvre, 2001;Kim, Blake, Lee, &Kim,
2017). Worth mentioning, a further linkage between the vi-
sual system and AP is reﬂected in a higher incidence rate of AP
among congenitally blind (Hamilton et al., 2004). In the pre-
sent study, compared to NAP participants the AP possessors
exhibited longer P200 latencies in response to the auditory-
visual primes regardless of the matching condition. An ERP
modulation within this relatively early component has been
Fig. 7 eValues of the difference curves. Plotted are the group-averaged amplitudes (top) and latencies (bottom) extracted
from deﬂection at the N400 across all prime matching (A) and control (B) conditions. Absolute pitch (N¼21), non-absolute
pitch (N¼21). The bars depict standard errors. Two-tailed Bonferroni-adjusted ***P<.001, *P<.05, and unadjusted
cortex 135 (2021) 285e297294
ascribed to the intrinsic relevance of the stimulus and to af-
fective integration of multiple connotations (Carreti
e et al.,
2001;Spreckelmeyer, Kutas, Urbach, Altenmu
2006). Thus, the ﬁndings provide evidence that AP posses-
sors exhibit a delay in affectively integrating musical stimuli,
possible due to altered afﬁnity to them. In earlier studies, AP
possessors differed from NAP participants in brain activation
during music listening (Loui et al., 2012a) and in response to
the performance of an emotional rating task during music
listening (Loui et al., 2012a;Loui, Zamm, &Schlaug, 2012b). In
particular, AP possessors exhibited increased functional acti-
vation as well as greater functional interconnections with
strongest effects around the left superior temporal gyrus
including brain areas involved in multisensory integration as
well as in emotion and reward processing (Loui et al., 2012b).
Altogether, some previous studies (Loui et al., 2012a,2012b)
and the present ﬁndings suggest that the differences under-
lying the affective processing system in AP possessors may go
beyond auditory aversion.
This work was supported by the Swiss National Science
Foundation (P1ZHP1_158642, P2ZHP1_168587, P300P1_177744
to LR and 138668, 163149 to LJ) and the National Institute on
Deafness and Other Communication Disorders (RO1-
DC009823 to GS).
The catalog numbers for the pictures used in this study are as
Pleasant: 1440, 1460, 1463, 1510, 1600, 1710, 1750, 1920,
1999, 2040, 2045, 2050, 2058, 2070, 2071, 2080, 2091, 2150, 2151,
2160, 2165, 2170, 2208, 2209, 2216, 2260, 2274, 2311, 2332, 2340,
2341, 2345, 2347, 2395, 2550, 2660, 4622, 4660, 5470, 5480, 5600,
5621, 5629, 5829, 5830, 5833, 7200, 7230, 7330, 7502, 7580, 8030,
8080, 8158, 8170, 8178, 8179, 8180, 8185, 8186, 8190, 8200, 8206,
8210, 8370, 8400, 8420, 8470, 8490, 8496, 8499, 8501.
Unpleasant: 1033, 1110, 1111, 1120, 1202, 1220, 1271, 1274,
1280, 1930, 1931, 1932, 2053, 2095, 2120, 2205, 2490, 2590, 2661,
2717, 2750, 2800, 2811, 2900, 2981, 3005.1, 3015, 3030, 3064,
3071, 3100, 3140, 3160, 3181, 3220, 3225, 3230, 3300, 3301, 3350,
6020, 6021, 6520, 6555, 6563, 7380, 9006, 9007, 9008, 9040, 9042,
9043, 9075, 9102, 9140, 9182, 9183, 9265, 9301, 9320, 9325, 9373,
9405, 9490, 9530, 9561, 9570, 9571, 9582, 9584, 9592, 9594.
CRediT authorship contribution statement
Lars Rogenmoser: Conceptualization, Methodology, Software,
Formal analysis, Investigation, Data Curation,
WritingeOriginal Draft, WritingeReview &Editing, Visualiza-
tion, Funding acquisition. H. Charles Li: Software. Lutz J€
Resources, WritingeReview &Editing, Supervision, Funding
acquisition. Gottfried Schlaug: Resources, Data Curation,
WritingeReview &Editing, Supervision, Project administra-
tion, Funding acquisition.
Akiva-Kabiri, L., & Henik, A. (2012). A unique asymmetrical stroop
effect in absolute pitch possessors. Experimental Psychology,
Athos, E. A., Levinson, B., Kistler, A., Zemansky, J., Bostrom, A.,
Freimer, N., & Gitschier, J. (2007). Dichotomy and perceptual
distortions in absolute pitch ability. Proceedings of the National
Academy of Sciences, 104(37), 14795e14800.
Bargh, J. A., & Morsella, E. (2008). The unconscious mind.
Perspectives on Psychological Science, 3(1), 73e79.
Bonnel, A., Mottron, L., Peretz, I., Trudel, M., Gallun, E., &
Bonnel, A. M. (2003). Enhanced pitch sensitivity in individuals
with autism: A signal detection analysis. Journal of Cognitive
Neuroscience, 15(2), 226e235.
Bouvet, L., Donnadieu, S., Valdois, S., Caron, C., Dawson, M., &
Mottron, L. (2014). Veridical mapping in savant abilities,
absolute pitch, and synesthesia: An autism case study.
Frontiers in Psychology, 5, 106.
Brauchli, C., Leipold, S., & J€
ancke, L. (2019). Univariate and
multivariate analyses of functional networks in absolute
pitch. NeuroImage, 189, 241e247.
Brenton, J. N., Devries, S. P., Barton, C., Minnich, H., & Sokol, D. K.
(2008). Absolute pitch in a four-year-old boy with autism.
Pediatric Neurology, 39(2), 137e138.
Mullane, J., Bernier, R., …Folstein, S. E. (2003). Autism-
related language, personality,andcognitioninpeoplewith
absolute pitch: Results of a preliminary study. Journal of
Autism and Developmental Disorders, 33(2), 163e167.
Burkhard, A., Elmer, S., & J€
ancke, L. (2019). Early tone
categorization in absolute pitch musicians is subserved by the
right-sided perisylvian brain. Scientiﬁc Reports, 9, 1419.
Callejas, A., Acosta, A., & Lupi
nez, J. (2007). Green love is ugly:
Emotions elicited by synesthetic graphene-color perceptions.
Brain Research, 1127(1), 99e107.
e, L., Mercado, F., Tapia, M., & Hinojosa, J. A. (2001).
Emotion, attention, and the “negativity bias”, studied through
event-related potentials. International Journal of
Psychophysiology, 41(1), 75e85.
Chin, C. S. (2003). The development of absolute pitch: A theory
concerning the roles of music training at an early
developmental age and individual cognitive style. Psychology of
Music, 31(2), 155e171.
Costa-Giomi, E., Gilmour, R., Siddell, J., & Lefebvre, E. (2001).
Absolute pitch, early musical instruction, and spatial abilities.
Annals of the New York Academy of Sciences, 930, 394e396.
Cynx, J. (1993). Auditory frequency generalization and a failure to
ﬁnd octave generalization in a songbird, the European starling
(Sturnus vulgaris). Journal of Comparative Psychology, 107(2),
Delorme, A., & Makeig, S. (2004). EEGLAB: An open source toolbox
for analysis of single-trial EEG dynamics including
independent component analysis. Journal of Neuroscience
Methods, 134(1), 9e21.
Deutsch, D., Henthorn, T., Marvin, E., & Xu, H. (2006). Absolute
pitch among American and Chinese conservatory students:
Prevalence differences, and evidence for a speech-related
critical period. The Journal of the Acoustical Society of America,
Dohn, A., Garza-Villarreal, E. A., Heaton, P., & Vuust, P. (2012). Do
musicians with perfect pitch have more autism traits than
musicians without perfect pitch? An empirical study. PLoS
One, 7(5), Article e37961.
Eder, A. B., Leuthold, H., Rothermund, K., & Schweinberger, S. R.
(2012). Automatic response activation in sequential affective
cortex 135 (2021) 285e297 295
priming: An ERP study. Social Cognitive and Affective
Neuroscience Electronic Resource, 7(4), 436e445.
Elmer, S., Rogenmoser, L., Ku
¨hnis, J., & J€
ancke, L. (2015). Bridging
the gap between perceptual and cognitive perspectives on
absolute pitch. The Journal of Neuroscience: the Ofﬁcial Journal of
the Society for Neuroscience, 35(1), 366e371.
Elmer, S., Sollberger, S., Meyer, M., & J€
ancke, L. (2013). An
empirical reevaluation of absolute pitch: Behavioral and
electrophysiological measurements. Journal of Cognitive
Neuroscience, 25(10), 1736e1753.
Faul, F., Erdfelder, E., Lang, A. G., & Buchner, A. (2007). G*Power 3:
A ﬂexible statistical power analysis program for the social,
behavioral, and biomedical sciences. Behavior Research
Methods, 39(2), 175e191.
Fazio, R. H. (2001). On the automatic activation of associated
evaluations: An overview. Cognition &Emotion, 15(2), 115e141.
Foxton, J. M., Stewart, M. E., Barnard, L., Rodgers, J., Young, A. H.,
O’Brien, G., & Grifﬁths, T. D. (2003). Absence of auditory “global
interference”in autism. Brain, 126(12), 2703e2709.
Fujii, S., & Schlaug, G. (2013). The Harvard Beat Assessment Test
(H-BAT): A battery for assessing beat perception and
production and their dissociation. Frontiers in Human
Neuroscience, 7, 771.
Greber, M., Rogenmoser, L., Elmer, S., & J€
ancke, L. (2018).
Electrophysiological correlates of absolute pitch in a passive
auditory oddball paradigm: A direct replication attempt.
eNeuro, 5(6). ENEURO.0333-18.2018.
Greenwald, A. G., Draine, S. C., & Abrams, R. L. (1996). Three
cognitive markers of unconscious semantic activation. Science,
Absolute pitch: Prevalence, ethnic variation, and estimation
of the genetic component. American Journal of Human
Genetics, 65(3), 911e913.
Gregersen, P. K., Kowalsky, E., Kohn, N., & Marvin, E. W. (2001).
Early childhood music education and predisposition to
absolute pitch: Teasing apart genes and environment.
American Journal of Human Genetics, 98(3), 280e282.
Gregersen, P. K., Kowalsky, E., Lee, A., Baron-Cohen, S.,
Fisher, S. E., Asher, J. E., …Li, W. (2013). Absolute pitch exhibits
phenotypic and genetic overlap with synesthesia. Human
Molecular Genetics, 22(10), 2097e2104.
Hamilton, R. H., Pascual-Leone, A., & Schlaug, G. (2004). Absolute
pitch in blind musicians. Neuroreport, 15(5), 803e806.
anggi, J., Beeli, G., Oechslin, M. S., & J€
ancke, L. (2008). The
multiple synaesthete E.S. dneuroanatomical basis of
interval-taste and tone-colour synaesthesia. NeuroImage, 43(2),
Harris, G., & Siegel, J. (1975). Categorical perception and absolute
pitch. The Journal of the Acoustical Society of America, 57. S11.
Heaton, P. (2003). Pitch memory, labelling and disembedding in
autism. Clinical Psychology &Psychotherapy, 44(4), 543e551.
Heaton, P., Davis, R. E., & Happ
e, F. G. E. (2008). Research note:
Exceptional absolute pitch perception for spoken words in an
able adult with autism. Neuropsychologia, 46(7), 2095e2098.
Itoh, K., Suwazono, S., Arao, H., Miyazaki, K., & Nakada, T. (2005).
Electrophysiological correlates of absolute pitch and relative
pitch. Cerebral Cortex, 15(6), 760e769.
Ito, T. A., Larsen, J. T., Smith, N. K., & Cacioppo, J. T. (1998).
Negative information weighs more heavily on the brain: The
negativity bias in evaluative categorizations. Journal of
Personality and Social Psychology, 75(4), 887e900.
ancke, L., Langer, N., & H€
anggi, J. (2012). Diminished whole-brain
but enhanced peri-sylvian connectivity in absolute pitch
musicians. Journal of Cognitive Neuroscience, 24(6), 1447e1461.
ancke, L., Rogenmoser, L., Meyer, M., & Elmer, S. (2012). Pre-
attentive modulation of brain responses to tones in coloured-
hearing synesthetes. BMC Neuroscience, 13, 151.
Jung, T. P., Makeig, S., Humphries, C., Lee, T. W., McKeown, M. J.,
Iragui, V., & Sejnowski, T. J. (2000). Removing
electroencephalographic artifacts by blind source separation.
Psychophysiology, 37(2), 163e178.
Keenan, J. P., Thangaraj, V., Halpern, A. R., & Schlaug, G. (2001).
Absolute pitch and planum temporale. NeuroImage, 14(6),
Kim, S., Blake, R., Lee, M., & Kim, C. Y. (2017). Audio-visual
interactions uniquely contribute to resolution of visual
conﬂict in people possessing absolute pitch. PLoS One, 12(4),
Kim, S. G., & Kn€
osche, T. R. (2016). Intracortical myelination in
musicians with absolute pitch: Quantitative morphometry
using 7-T MRI. Human Brain Mapping, 37(10), 3486e3501.
Kim, S. G., & Kn€
osche, T. R. (2017). Resting state functional
connectivity of the ventral auditory pathway in musicians
with absolute pitch. Human Brain Mapping, 38(8), 3899e3916.
Klauer, K. C. (1997). Affective priming. European Review of Social
Psychology, 8(1), 67e103.
Kutas, M., & Hillyard, S. A. (1980). Event-related brain potentials to
semantically inappropriate and surprisingly large words.
Biological Psychology, 11(2), 99e116.
Lang, P., Bradley, M., & Cuthbert, B. (2008). International affective
picture system (IAPS): Affective ratings of pictures and instruction
manual. Technical report A-8. Gainesville, FL: University of
LeDoux, J. (1995). Emotion: Clues from the brain. Annual Review of
Psychology, 46, 209e235.
Lenhoff, H. M., Perales, O., & Hickok, G. (2001). Absolute pitch in
Williams syndrome. Music Perception, 18(4), 491e503.
Levitin, D. J., & Rogers, S. E. (2005). Absolute pitch: Perception,
coding, and controversies. Trends in Cognitive Sciences, 9(1),
Levitin, D. J. (2005). Musical behavior in a neurogenetic
developmental disorder: Evidence from Williams syndrome.
Annals of the New York Academy of Sciences, 1060, 325e334.
Levitin, D. J., Cole, K., Lincoln, A., & Bellugi, U. (2005). Aversion,
awareness, and attraction: Investigating claims of hyperacusis
in the Williams syndrome phenotype. Journal of Child
Psychology and Psychiatry, 46(5), 514e523.
Loui, P., Li, H. C., Hohmann, A., & Schlaug, G. (2010). Enhanced
cortical connectivity in absolute pitch musicians: A model for
local hyperconnectivity. Journal of Cognitive Neuroscience, 23(4),
Loui, P., Alsop, D., & Schlaug, G. (2009). Tone deafness: A new
disconnection syndrome? The Journal of Neuroscience, 29(33),
Loui, P., Zamm, A., & Schlaug, G. (2012a). Absolute pitch and
synesthesia: Two sides of the same coin? Shared and distinct
neural substrates of music listening. ICMPC Proceedings of the
International Conference on Music Perception &Cognition, 618e623.
Loui, P., Zamm, A., & Schlaug, G. (2012b). Enhanced functional
networks in absolute pitch. NeuroImage, 63(2), 632e640.
Miyazaki, K. (1993). Absolute pitch as an inability: Identiﬁcation of
musical intervals in a tonal context. Music Perception, 11(55),
Miyazaki, K., & Rakowski, A. (2002). Recognition of notated
melodies by possessors and nonpossessors of absolute pitch.
Perception &Psychophysics, 64(8), 1337e1345.
Miyazaki, K. (1995). Perception of relative pitch with different
references: Some absolute-pitch listeners can’t tell musical
interval names. Perception &Psychophysics, 57(7), 962e970.
Mottron, L., Bouvet, L., Bonnel, A., Samson, F., Burack, J. A.,
Dawson, M., & Heaton, P. (2013). Veridical mapping in the
development of exceptional autistic abilities. Neuroscience and
Biobehavioral Reviews, 37(2), 209e228.
Mottron, L., Peretz, I., & Menard, E. (2000). Local and global
processing of music in high-functioning persons with autism:
cortex 135 (2021) 285e297296
Beyond central coherence? Clinical Psychology &Psychotherapy,
Neufeld, J., Roy, M., Zapf, A., Sinke, C., Emrich, H. M., Prox-
Vagedes, V., …Zedler, M. (2013). Is synesthesia more common
in patients with Asperger syndrome? Frontiers in Human
Neuroscience, 7, 847.
Newport, E. (1990). Maturational constraints on language
learning. Cognitive Science, 14(1), 11e28.
Ohman, A., & Mineka, S. (2001). Fears, phobias, and preparedness:
Toward an evolved module of fear and fear learning.
Psychological Review, 108(3), 483e522.
O’Connor, K. (2012). Auditory processing in autism spectrum
disorder: A review. Neuroscience and Biobehavioral Reviews, 36(2),
Plantinga, J., & Trainor, L. J. (2005). Memory for melody: Infants
use a relative pitch code. Cognition, 98(1), 1e11.
Reber, R., Schwarz, N., & Winkielman, P. (2004). Processing
ﬂuency and aesthetic pleasure: Is beauty in the perceiver’s
processing experience? Personality and Social Psychology Review,
Rogenmoser, L., Arnicane, A., J€
ancke, L., & Elmer, S. (2020). The
left dorsal stream causally mediates the tone labeling in
absolute pitch. bioRxiv, 2020, 07.16.206284.
Rogenmoser, L., Elmer, S., & J€
ancke, L. (2015). Absolute pitch:
Evidence for early cognitive facilitation during passive
listening as revealed by reduced P3a amplitudes. Journal of
Cognitive Neuroscience, 27(3), 623e637.
Rosenhall, U., Nordin, V., Sandstr€
om, M., Ahls
en, G., & Gillberg, C.
(1999). Autism and hearing loss. Journal of Autism and
Developmental Disorders, 29(5), 349e357.
Russo, F. A., Windel, D. L., & Cuddy, L. L. (2003). Learning the
“Special Note”: Evidence for a critical period for absolute pitch
acquisition. Music Perception, 21(1), 119e127.
Saffran, & Griepentrog, G. J. (2001). Absolute pitch in infant
auditory learning: Evidence for developmental reorganization.
Developmental Psychology, 37(1), 74e85.
Schlaug, G., J€
ancke, L., Huang, Y., & Steinmetz, H. (1995). In vivo
evidence of structural brain asymmetry in musicians. Science,
Schulze, K., Mueller, K., & Koelsch, S. (2013). Auditory stroop and
absolute pitch: An fMRI study. Human Brain Mapping, 34(7),
Shipley, W. C. (1940). A self-administering scale for measuring
intellectual impairment and deterioration. The Journal of
Psychology, 9(2), 371e377.
Siegel, J. A. (1974). Sensory and verbal coding strategies in
subjects with absolute pitch. Journal of Experimental Psychology,
Spreckelmeyer, K. N., Kutas, M., Urbach, T. P., Altenmu
¨ller, E., &
¨nte, T. F. (2006). Combined perception of emotion in
pictures and musical sounds. Brain Research, 1070(1), 160e170.
Steinbeis, N., & Koelsch, S. (2008). Comparing the processing of
music and language meaning using EEG and fMRI provides
evidence for similar and distinct neural representations. PLoS
One, 3(5), e2226.
Steinbeis, N., & Koelsch, S. (2011). Affective priming effects of
musical sounds on the processing of word meaning. Journal of
Cognitive Neuroscience, 23(3), 604e621.
Takeuchi, A. H., & Hulse, S. H. (1993). Absolute pitch. Psychological
Bulletin, 113(2), 345e361.
Vernon, P. E. (1977). Absolute pitch: A case study. British Journal of
Psychology, 68(4), 485e489.
Wengenroth, M., Blatow, M., Heinecke, A., Reinhardt, J.,
Stippich, C., Hofmann, E., & Schneider, P. (2013). Increased
volume and function of right auditory cortex as a marker for
absolute pitch. Cerebral Cortex, 24(5), 1127e1137.
Wenhart, T., Bethlehem, R. A. I., Baron-Cohen, S., &
¨ller, E. (2019). Autistic traits, resting-state
connectivity, and absolute pitch in professional musicians:
Shared and distinct neural features. Molecular Autism, 10,20.
Wenhart, T., & Altenmu
¨ller, E. (2019). A tendency towards details?
Inconsistent results on auditory and visual local-to-global
processing in absolute pitch musicians. Frontiers in Psychology,
¨ller, E. (2019). Enhanced
auditory disembedding in an interleavedmelody recognition test
is associated with absolute pitch ability. Scientiﬁc Reports, 9,7838.
Wilson, S. J., Lusher, D., Wan, C. Y., Dudgeon, P., & Reutens, D. C.
(2009). The neurocognitive components of pitch processing:
Insights from absolute pitch. Cerebral Cortex, 19(3), 724e732.
Wright, A. A., Rivera, J. J., Hulse, S. H., Shyan, M., & Neiworth, J. J.
(2000). Music perception and octave generalization in rhesus
monkeys. Journal of Experimental Psychology. General, 129(3),
Zatorre, R. J., & Beckett, C. (1989). Multiple coding strategies in the
retention of musical tones by possessors of absolute pitch.
Memory &Cognition, 17(5), 582e589.
Zatorre, R. J., Perry, D. W., Beckett, C. A., Westbury, C. F., &
Evans, A. C. (1998). Functional anatomy of musical processing
in listeners with absolute pitch and relative pitch. Proceedings
of the National Academy of Sciences, 95(6), 3172e3177.
Zhang, Q., Li, X., Gold, B. T., & Jiang, Y. (2010). Neural correlates of
cross-domain affective priming. Brain Research, 1329, 142e151.
Ziv, N., & Radin, S. (2014). Absolute and relative pitch: Global
versus local processing of chords. Advances in Cognitive
Psychology, 10(1), 15e25.
cortex 135 (2021) 285e297 297