Learning Auditory Space: Generalization and Long-Term Effects

Abstract

Previous findings have shown that humans can learn to localize with altered auditory space cues. Here we analyze such learning processes and their effects up to one month on both localization accuracy and sound externalization. Subjects were trained and retested, focusing on the effects of stimulus type in learning, stimulus type in localization, stimulus position, previous experience, externalization levels, and time.
We trained listeners in azimuth and elevation discrimination in two experiments. Half participated in the azimuth experiment first and half in the elevation first. In each experiment, half were trained in speech sounds and half in white noise. Retests were performed at several time intervals: just after training and one hour, one day, one week and one month later. In a control condition, we tested the effect of systematic retesting over time with post-tests only after training and either one day, one week, or one month later.
With training all participants lowered their localization errors. This benefit was still present one month after training. Participants were more accurate in the second training phase, revealing an effect of previous experience on a different task. Training with white noise led to better results than training with speech sounds. Moreover, the training benefit generalized to untrained stimulus-position pairs. Throughout the post-tests externalization levels increased. In the control condition the long-term localization improvement was not lower without additional contact with the trained sounds, but externalization levels were lower.
Our findings suggest that humans adapt easily to altered auditory space cues and that such adaptation spreads to untrained positions and sound types. We propose that such learning depends on all available cues, but each cue type might be learned and retrieved differently. The process of localization learning is global, not limited to stimulus-position pairs, and it differs from externalization processes.

Full text

Learning Auditory Space: Generalization and Long-Term
Effects
Catarina Mendonça1,2,3*, Guilherme Campos4, Paulo Dias4, Jorge A. Santos3,5
1 Cluster of Excellence Hearing4all, Carl Von Ossietzky University of Oldenburg, Oldenburg, Germany, 2 Department of Signal Processing and Acoustics, Aalto
University, Espoo, Finland, 3 Centro Algoritmi, School of Engineering, University of Minho, Guimarães, Portugal, 4 Institute of Electronics and Telematics
Engineering, University of Aveiro, Aveiro, Portugal, 5 Department of Basic Psychology, University of Minho, Braga, Portugal
Abstract
Background: Previous findings have shown that humans can learn to localize with altered auditory space cues. Here
we analyze such learning processes and their effects up to one month on both localization accuracy and sound
externalization. Subjects were trained and retested, focusing on the effects of stimulus type in learning, stimulus type
in localization, stimulus position, previous experience, externalization levels, and time.
Method: We trained listeners in azimuth and elevation discrimination in two experiments. Half participated in the
azimuth experiment first and half in the elevation first. In each experiment, half were trained in speech sounds and
half in white noise. Retests were performed at several time intervals: just after training and one hour, one day, one
week and one month later. In a control condition, we tested the effect of systematic retesting over time with post-tests
only after training and either one day, one week, or one month later.
Results: With training all participants lowered their localization errors. This benefit was still present one month after
training. Participants were more accurate in the second training phase, revealing an effect of previous experience on
a different task. Training with white noise led to better results than training with speech sounds. Moreover, the
training benefit generalized to untrained stimulus-position pairs. Throughout the post-tests externalization levels
increased. In the control condition the long-term localization improvement was not lower without additional contact
with the trained sounds, but externalization levels were lower.
Conclusion: Our findings suggest that humans adapt easily to altered auditory space cues and that such adaptation
spreads to untrained positions and sound types. We propose that such learning depends on all available cues, but
each cue type might be learned and retrieved differently. The process of localization learning is global, not limited to
stimulus-position pairs, and it differs from externalization processes.
Citation: Mendonça C, Campos G, Dias P, Santos JA (2013) Learning Auditory Space: Generalization and Long-Term Effects. PLoS ONE 8(10): e77900.
doi:10.1371/journal.pone.0077900
Editor: Manuel S. Malmierca, University of Salamanca- Institute for Neuroscience of Castille and Leon and Medical School, Spain
Received May 15, 2013; Accepted September 13, 2013; Published October 22, 2013
Copyright: © 2013 Mendonça 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, provided the original author and source are credited.
Funding: This work was supported by the Portuguese Foundation for Science and Technology and FEDER, with the research grant SFRH/BD/36345/2007
and the funded projects PTDC/EEA-ELC/112137/2009, FCOMP-01-0124-FEDER-007560, FCOMP-01-0124-FEDER-022674 and PEst-OE/ECI/
UI4047/2011. 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: catarina.mendonca@uni-oldenburg.de
Introduction
Over the last decades, many scientific advances have
demonstrated the neural plasticity and experience-based
shaping of brain processes. Relearning auditory space from
new head-related auditory cues is one of such cases. To be
able to localize sounds, one must learn each sound position
cue, which is always shaped by one’s own head and torso, and
successively recalibrate to it through feedback. Alterations to
auditory space cues can take place as the head size changes
with age, through surgical means, with cochlear implants or
hearing aids, or when audition declines with aging [1,2].
Analyzing how humans learn to localize with altered auditory
cues will bring new insights on how the auditory space
representations are formed and adjusted throughout life, with
potential applications to hearing rehabilitation and auditory
assistive technologies [3–5].
Several studies have revealed that animals learn to localize
from altered sound cues. King and collaborators [1] recorded
responses of neurons in the ferret’s primary auditory cortex to
individualized and non-individualized virtual sound sources.
They found that the structure of the spatial response fields
changed significantly when non-individualized sounds were
presented. But, through intensive training, ferrets relearn to
localize sounds with altered cues [6,7]. In humans, altering
both ears with molds immediately impairs elevation localization.
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Elevation localization is mostly affected by cues provided by
the spectral shaping of the head and pinnae, rather than from
the cues due to differences in sound signals arriving at both
ears. Changing the shape of the pinnae dramatically affects
such spectral cues, thus impairing elevation localization. But by
wearing such molds for several weeks, accurate performance
is steadily reacquired [8]. Interestingly, when the subjects take
the molds off, their elevation localization accuracy remains
unchanged, despite having been trained in the new cues. Irving
and Moore [9] trained sound localization in humans hearing
with and without a unilateral earplug. With the plug inserted in
one ear the azimuth localization was impaired, due to its strong
dependence upon binaural cues, namely the difference in time
and level of the sounds arriving at both ears. Over 5 days
wearing the plug, azimuth localization continuously improved
and, upon plug removal, azimuth localization was again at the
pre-plug accuracy levels.
Studies on human auditory space adaptations have often
been conducted with head-related filters. Those filters can be
measured as a binaural impulse response for each source
position, known as Head Related Impulse Response (HRIR), or
by its Fourier transform, the Head Related Transfer Function
(HRTF). With those filters, it is possible to reproduce through
headphones the sound as it would be heard by a given person
or model. It is also possible to present the sound filtered by
someone else’s HRTFs, or any combination of these filters.
Wright and Zhang [10] reviewed the literature on auditory
localization learning with normal/individualized and altered/non-
individualized cues in human adults. With altered cues, partial
adaptation has been reported with a variety of cue
manipulations, such as altered interaural time difference. For
normal/individualized cues, significant improvement has only
rarely been observed. These findings point out that improving
localization accuracy with one’s own unaltered ears might not
always occur, mostly because one might already have reached
the optimal localization performance; but when altered sounds
are trained, learning might take place because the initial
performance is low.
To explore such learning potential, some training approaches
have been proposed to teach humans how to localize with non-
individualized head-related cues [11,12]. These training
approaches used highly complex real-time virtualization
systems that took advantage of the subject’s own head
movement and therefore provided vestibular and proprioceptive
cues, coupled with the audiovisual feedback of the virtual
environment. After several days of training, subjects improved
sound localization accuracy and this improvement lasted up to
one month [11] and seemed to generalize to other untrained
positions [12].
In a previous study [13] we addressed the learning of
auditory localization with non-individualized head-related
transfer functions in a simple setting. Using only passive
contact to static free-field sounds without head motion or
feedback did not result in any improvement in azimuth
localization accuracy. On the other hand, a short training
program, of less than one hour, involving active learning and
response feedback, significantly improved the localization in
both azimuth and elevation. These results revealed that
auditory space learning might occur much faster than
previously thought, and under much simpler conditions.
Interestingly, both in azimuth and in elevation, listeners were
trained in only 3 or 5 source positions, but improvement was
found for all in-between source positions in the after test,
suggesting some spatial generalization.
Some spatial learning generalization effects have been
suggested before [10], but they have never thoroughly been
analyzed or directly tested. Understanding such effects might
cast new insights on how the auditory spatial maps are formed
and recalibrated, how the brain learns to associate the sound
cues to positions in space, and how this association is
represented. We designed a longitudinal learning study to
assess the effects of time, stimulus type, previous experience,
and sound source position. We also assessed the quality of the
spatial sound experience by addressing externalization levels.
Non-individualized sounds are often felt as less spatial or less
compelling, typically being reported as felt inside the head or
between ears, rather than externalized. This additional
measure allowed us to better understand the quality of the
training process.
Methods
Overview
This study comprised several successive tests. In the main
condition, there was an elevation training experiment and an
azimuth training experiment. Each of them integrated a pre-
test, a training session, and five post-tests. In the control
condition there were also elevation and azimuth experiments,
but they only comprised the pre-test, training, and two post-
tests.
Participants
Twelve inexperienced subjects, aged 20 to 55 (33 on
average), participated in the main condition experiments. Due
to technical issues, namely a large number of missing records
in some sessions, only 10 subjects (20 to 55 – average 34)
were considered in the data analysis. The control condition
experiments involved nine subjects (19 to 22 - average 20),
divided into three equal-sized groups.
All participants had normal hearing, checked by standard
audiometric screening at 500, 750, 1000, 1500 and 2000 Hz,
with auditory thresholds below 15 dB HL, and none showed
interaural sensitivity differences above 5 dB HL. All the
experiments were conducted in accordance with the
Declaration of Helsinki and the resulting data were processed
anonymously.
Ethics statement
All the participants were informed about the purpose of the
experiments and provided written consent. The experiment was
approved by the ethics committee of the School of Psychology,
University of Minho. The experiment was conducted in
accordance with the principles stated in the 1964 Declaration of
Helsinki.
Learning Auditory Space
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Stimuli
The experimental stimuli were based on anechoic recordings
of speech (Portuguese word “atum” (tuna)), and on computer-
generated white noise, both with the duration of 3s. These
sound files were convolved with head-related impulse response
pairs corresponding to the simulated source position. The
HRIR set used, taken from the CIPIC database [14], was
measured on a manikin with constant distance of 1m between
the sound source and the center of the manikin’s head. The
actual stimuli, reproduced with a Realtec Intel 8280 IBA sound
card, were presented through a set of Etymotics ER-4B
MicroPro flat-response ‘in-ear’ earphones.
For the azimuth localization tests, ten source positions were
considered in the horizontal plane (i.e. at constant 0°
elevation), with azimuth ranging from front to right at 10°
intervals: 0° (front), 10°, 20°, 30°, 40°, 50°, 60°, 70°, 80°, and
90° (right).
The elevation localization training tests used the same
number of virtual source positions, now varying in elevation on
the median plane (fixed 0° azimuth) with the same 10° angular
spacing: 0° (front), 10°, 20°, 30°, 40°, 50°, 60°, 70°, 80°, and
90° (head top).
Procedure
Both azimuth and elevation experiments started with a pre-
training session test. In this pre-test, the speech and noise
stimuli were repeated ten times, with virtual source positions
chosen pseudo-randomly in the mentioned ranges. Participants
were asked to point the perceived source position on a touch
screen (see Figure 1 - top), on a continuum from front to right
in the azimuth experiment, and from front to top in the elevation
experiment. The vertical and horizontal axes in Figure 1
represented, respectively, the “front” (0°) and “right” (90°)
directions in the azimuth experiment and the “top” (90°) and
“front” (0°) directions in the elevation experiment. While
pointing in that continuum, participants were asked to also
report externalization levels. They were told that they should
respond in the orange area if they felt the sound more inside
the head, and in the blue area if the sound was felt outside the
head. They were told to respond in a continuum, inner border
being the most inside the head and outer border being 1 m
away from the head. Each trial lasted for 3 s, with a 2 s interval
between stimuli.
The participants then engaged in a training session in which
the virtual source was restricted to four angular positions (in
azimuth or elevation, depending on the experiment): 0°, 30°,
60° and 90° (represented by the white areas in Figure 1 -
bottom). In each experiment a part of the participants trained
with noise sounds, and the other part trained with speech
sounds.
The training followed the same steps as described in our
previous work [13]:
1 Active Learning: The participants were informed they had
five minutes to learn to identify source position and would be
tested afterwards. While training, they were allowed to choose
among the four source positions at will, by pointing at the
corresponding white area.
2 Passive Feedback: 3 s sounds positioned randomly at one of
the four possible options were played with an inter-stimulus
interval of 4 s. In each trial, the participants had to identify
source position by pointing the corresponding white area on the
touch screen. The correct answer was shown immediately after
each trial. The sounds were organized in sequences of 10. This
training stage continued until the number of correct answers
reached 80% (azimuth localization) or 70% (elevation
localization) for two consecutive sequences,.
Post-training tests were then carried out using exactly the
same stimuli and procedure of the pre-test. In the main
condition, there were five post-tests: 1) immediately after
training; 2) one hour later; 3) one day later, 4) one week later
and 5) one month later. In the control condition, there were only
two post-tests: 1) immediately after training and 2) either one
day, one week or one month later (i.e. skipping one, two or
three intermediate tests, respectively).
All participants took part in both the elevation and azimuth
experiments, but both experiment type and trained stimulus
type were counterbalanced. Therefore, part of the participants
trained elevation first and the other part trained azimuth first.
Part were trained in speech first and part were trained in noise
first. Subjects trained in azimuth using speech were trained in
elevation using noise; conversely, subjects trained in azimuth
using noise were trained in elevation using speech. There were
therefore 4 possible training orders. Here is an example of test
sequence in the main condition, for a subject who trained
elevation and speech first: 1) pre-test in elevation; 2) elevation
training with speech sounds; 3) post-test in elevation; 4) pre-
test in azimuth; 5) azimuth training with noise sounds; 6) post-
test in azimuth; 7) one hour later, post-test in elevation
immediately followed by post-test in azimuth; 8,9,10) similar
post-tests a day, week, and one month later.
In the main condition, three subjects trained elevation and
speech first, two trained azimuth and speech first, two trained
elevation and noise first and two trained azimuth and noise
first. Therefore, half participants started by training speech, half
by training noise; half started by training elevation and half by
azimuth. In the control condition, five subjects trained elevation
first and four trained azimuth first; five trained speech first and
four trained noise first (see Supporting Information S1 for a
map of participant distribution across conditions).
All experiments took place in a quiet room with black walls
and lights off.
Main Condition Results
This section presents the results of the azimuth and
elevation experiments. The results are presented under
different perspectives, resulting in five sub-sections: Training
Effect analyses the effect of training on localization accuracy,
and the influence of stimulus types on it. Experience Effect
looks into the influence of prior elevation training in azimuth
localization results and vice-versa. Stimulus Position analyses
localization performance as a function of source azimuth/
elevation. The Time Effect part observes the evolution of
localization performance along time, based on post-test data.
Learning Auditory Space
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Figure 1. Touch-screen interfaces. Interfaces used for pre- and post-tests (top) and training session tests (bottom).
doi: 10.1371/journal.pone.0077900.g001
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Finally, Externalization analyses the influence of time and
stimulus type on reported externalization levels.
Results are expressed in localization error and
externalization level. Localization error was computed as the
average Euclidean distance between the position of each
stimulus and the position of each corresponding response. It
was first computed trial by trial, in degree, and then averaged
according to the following variables to be analysed: by
participant (data not shown), by group, by experiment, by
stimulus type, by stimulus position, by test-session.
Externalization levels were computed from the participant’s
responses in a continuum between two colored areas, where
the inner area of the arc corresponded to sounds perceived
most inside the head, and the outer area of the arc
corresponded to sounds perceived most outside the head.
Pixel outputs were converted to a linear externalization scale,
where value 0 then represented a response at the inner border
of the arc, and value 100 corresponded to a response at the
outer border of the arc. Value 50 was defined at the color
border; this value represented the line between sounds
perceived inside and outside the head.
Azimuth experiment
Training effect. All ten participants took less than 20
minutes to reach the target localization accuracy. Four of them
started the passive feedback phase already at 80 percent
accuracy and only three took longer than 5 minutes. For those
three subjects, a decrease in accuracy was found over the first
trials of the passive feedback phase.
All subjects improved localization with training. Figure 2 (left)
shows mean localization errors before and after training.
In the pre-test there was a mean localization error of 21.3°,
while in the first post-test the mean error was reduced to 15.8°.
This difference is statistically significant in a t-test (t9=5.4,
p≤0.001).
Those who trained with white noise sounds achieved higher
accuracy levels than those who trained with speech.
Figure 2. Azimuth localization mean error. Mean error as a function of training (A) and stimulus type (B).
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Immediately after training, the mean error in azimuth for those
who trained with speech was 17.9°, while for those who trained
with noise it was 13.8°. Those who trained with speech
decreased on average 5.5° in speech localization error.
Interestingly, they also improved in noise localization, with a
7.0° reduction in error. In a similar way, those who were trained
with white noise decreased 4.7° in noise localization error, but
they also decreased 4.6° in speech error. Localization was
significantly better for both stimulus types after training
(speech: t9=6.4, p≤0.001; noise: t9=2.56, p≤0.05).
Experience effect. Half of the participants took part in the
elevation experiment first and, for this reason, were regarded
as experienced when they started the azimuth experiment.
Conversely, those who started by the azimuth experiment were
considered experienced in the elevation experiment.
Experienced participants indeed performed differently (see
Figure 2). They started with an error level of 19.0°, against
23.5° in the inexperienced group. After training, there was still a
small benefit, where experienced listeners had an error of 15.1°
and the inexperienced listeners had an error of 15.5°, but this
difference was not significant. Considering the localization error
prior to training both in the azimuth and in the elevation
experiment, there was a significant difference between
experienced and inexperienced groups (t9=13.21, p≤0.001).
Both experienced and inexperienced subjects had lower
localization errors in noise stimuli than in speech stimuli. The
experienced group had on average 16.6° of error for noise and
17.9° for speech sounds. The inexperienced group had 18.1°
for noise and 21.6° for speech. These results indicate better
localization accuracy for experienced listeners.
Time effect. Overall, there was a clear training benefit with
persistent effects over time. Before training, there was an
average localization error of 21.3°. Immediately after training,
the error was reduced to 15.8°, and then it remained stable at
the subsequent tests, with 16.5°, 16.0°, 15.1° and 14.7° values
one hour, one day, one week, and one month later,
respectively. Along time, localization errors were persistently
lower for noise stimuli than for speech stimuli, as depicted in
Figure 3.
In a factorial ANOVA, analyzing the effects of stimulus type
and test session, these differences were confirmed. The main
effect of test session was found to be significant (F1,5=6.42,
p≤0.001). In a post-hoc Sheffé analysis, it was found that such
differences were only significant between the pre-test session
and all others. None of the post-training test sessions differed
Figure 3. Average azimuth localization error with noise and speech stimuli along all experimental sessions (A) and
respective standard deviation (SD) values (B).
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significantly from the others. The main effect of stimulus type
was also significant (F1,5=10.45, p≤0.005), revealing that the
benefit of noise over speech as stimuli in the localization task
was consistent along time.
Stimulus position. Localization accuracy varied widely with
stimulus position. There was also a large variability among
subjects. The largest localization errors were found for the
10°-40° azimuth range, where results before training were not
statistically different from response at chance. The best
accuracy was found for frontal and lateral stimuli. As an
example, the average localization error for 0° azimuth was
21.2° before training and 10.98° after training. This difference is
statistically significant in a t-test (t9=2.8, p≤0.05). On the other
hand, localization error at azimuth 60°, also a trained position,
improved from 12.0° to 10.0°, a difference which was not
statistically significant. The stimulus positions for which
localization improved the most with training were 0°, 10° and
20°, with 10.2°, 8.0° and 5.9° absolute mean error reductions,
respectively. The positions for which localization improved the
least with training were 60°, 50° and 90°, with mean error
lowered by 2.0°, 3.0° and 3.2°, respectively. Result differences
were statistically significant for all source positions between 0°
and 50° (inclusive). Training reduced localization error for all
azimuths, including untrained ones, and the magnitude of error
reduction was not related to direct training. Therefore, the
training effect was not limited to the trained positions, and
many untrained positions improved more than trained ones.
Externalization. Overall, externalization levels were low. On
average, sounds were perceived mostly inside the head in the
first and second day (see Figure 4). There was a mean
externalization of 46 before training, 47 after training, 48 one
hour later and 48 one day later. But one week and one month
later mean externalization was 52. This might indicate a
tendency for greater externalization as listeners become
acquainted with the localization cues provided by non-
individualized HRTF sounds, but evolving at a slower pace
than localization accuracy. In paired-sample t-tests, results
showed that only the first and last sessions were statistically
different from each other (t9=-2.8, p≤0.01).
Externalization seemed to depend strongly on stimulus type.
The global externalization level for the noise sounds was 59,
against 40 for speech sounds, which indicates that noise
Figure 4. Externalization levels across time (A) and by stimulus type (B). Level of 50 represents the threshold between inside
the head (values under 50) and outside the head.
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sounds were mostly externalized, while speech was more often
perceived inside the head. This effect was significant in a t-test
(t9=2.1, p≤0.05).
Elevation experiment
Training effect. The outcomes of the elevation experiment
were very similar to those of the azimuth experiment. All
participants improved with training and all training sessions
lasted less than 20 minutes. In the pre-test, the mean
localization error was 29.3°, higher than that for azimuth.
Considering that a subject answering randomly would obtain a
mean localization error of 33°, this value was also close to
random levels. In the post-test, the error was 25.9°. This
difference is significant in a t-test (t9=3.39, p≤0.01). Those who
trained with speech sounds improved accuracy by an average
of 3.4°, while those who trained with noise improved by 5°.
Those who trained with noise improved in localizing speech
and vice versa, but the effect was not as strong as in the
azimuth case. Those who trained speech improved 6.7° in
speech localization, and only 3.2° in noise localization. Those
who trained noise improved 4.9° in noise and only 2° in
speech. On average, both speech and noise sounds were
localised more accurately after training, and those differences
are statistically significant (speech: t9=2.83, p≤0.05; noise:
t9=4.3, p≤0.005).
Experience effect. As previously analyzed in section 3.1.2,
experienced subjects performed statistically better in the pre-
test than inexperienced subjects. The mean error for
experienced listeners prior to training was 26.5°, while for
inexperienced listeners it was 30.2°. Again, this benefit was still
found after training, where inexperienced subjects had a mean
error of 26.3° against 24° of the experienced group. There
were, however, no accuracy differences by both trained and
untrained subjects in the localization of speech and noise
sounds prior to elevation training (Figure 5).
Figure 5. Elevation localization mean error. Mean error as a function of experience (A) and stimulus type (B).
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Time effect. The general tendency over time was similar to
that observed in the azimuth experiment, with a clear
improvement in localization with training and a stabilization
after that. Before training, the average localization error was
29.3°. Immediately after training, the average error was
reduced to 25.2° and stayed at 25.4°, 24.8°, 25.4° and 24.8° in
the subsequent test sessions. There were, however, no
relevant differences between noise and speech sound. On
average, the error was 25.7° for speech and 25.9° for noise.
In a factorial ANOVA for stimulus type and test session
effects on error levels, no significant stimulus type effect was
found (F1=1.01, n.s.). There was, however, a significant effect
of test session (F5=3.28, p≤0.01).
Stimulus position. As depicted in Figure 6, the error of
sound position estimation varied across elevation. The largest
localization errors prior to training were at higher elevations,
namely at 70°, 80° and 90°, with 36.7°, 44.3° and 59.9° mean
errors, respectively. All elevation estimates from 40° to 90°
were not different from random responses before training.
Conversely, the smallest localization errors prior to training
were at lower elevations, from 0° to 40°.
With training, most stimuli elevations were better localized.
There were statistically significant localization improvements in
elevations comprised between 40° and 90°. Interestingly, these
were the same elevations that were at chance level prior to
training.
Figure 6. Mean error (deg) in localization of sounds across elevation, before, immediately after, and one month after
training. Error bars represent ± one standard deviation. The symbol = above bars represents values that are not statistically
different from the response at random for that given position, in a t-test for mean difference. The symbol * represents statistically
significant differences between the pre- and post-test in a paired sample t-test.
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However, at three stimulus positions (0°, 10° and 20°), no
improvement was observed with training. It should be noticed
that these stimuli were already localized above chance before
training.
In a similar way to what was observed in the azimuth
experiment, the localization of some trained source positions
did not improve or improved less than some untrained
positions. This was the case of the 0° and 30° sounds, which
were trained but were not better localized in the post-tests. On
the other hand, there were several untrained source positions
for which localization accuracy improved significantly, namely
the 40°, 50°, 70° and 80°. These stimuli were among those with
the largest localization improvement after training. The largest
accuracy improvement, however, was observed for the 90°
sounds, where after training there was a 13.5° error reduction
and one month later there was still a 9.8° reduction.
Externalization. Externalization levels in the elevation
experiment were even lower than in the azimuth experiment.
Taking 50 as the threshold, externalization levels compatible
with outside-the-head sound perception only appeared in the
last session (Figure 7). In the first session, sounds were mostly
perceived inside the head (35.2) and values stayed quite stable
along the first 4 post-tests, despite a small value increase: 36.6
immediately after and 38.6, 40 and 37.8 respectively one hour,
one day and one week later. However, the one month post-test
showed an externalization level of 50.4. Indeed, only the pre-
test and the one month post-test results differed significantly in
a t-test analysis (t9= -2.8, p≤0.01).
Comparing stimulus types, noise again yielded more outside-
the-head estimations, although the mean values were still
under the cut point (46.8). Like in the azimuth experiment, the
speech sounds remained mostly inside the head, with very low
externalization levels (33.6). The difference in externalization
between noise and speech sounds was statistically significant
(t9=1.33, p≤0.01).
Control Condition Results
The control condition experiments were conducted to assess
the impact of all successive retesting sessions on the long-term
results. The effect of successive information retrieval on
memory is well known; information that is used more often is
less likely to be forgotten. Here, it was hypothesized that the
reason that listeners localized so accurately and had such
good externalization levels one month after the short training
Figure 7. Externalization levels in the elevation experiment across test sessions (A) and by stimulus type (B).
doi: 10.1371/journal.pone.0077900.g007
Learning Auditory Space
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session was because of successive retrieval of the trained
information.
Here we conducted a new set of experiments in azimuth and
elevation learning, where all procedures were kept the same
except for the post-test sessions. There were three
experimental groups: the one-day group, that was only retested
one day after training; the one-week group, that was tested one
week later; and the one-month group, only retested one month
after training. Therefore there were always a total of three test
sessions per group: the pre-test, the post-test immediately after
training, and the final post-test that varied across groups.
The results of these experiments are summarized in Figure
8.
Both in the azimuth and in the elevation experiments, the
average localization error decreased after training, but there
were different long-term effects of such training. In azimuths,
the average error reduction was of 3.1° immediately after
training. One day later, there was an error reduction of 4.7°,
while one week later it was 3.9° and one month later it was
2.4°. In elevations there was on average an improvement of
7.2° in localization accuracy immediately after training.
However, in the long term there were differences between
groups. The one-day group had an error reduction of 8.6°
comparing to the pre-test. The one-week had only a benefit of
2.1°, and the one-month group only had a benefit of 1.4°.
Unfortunately, since there were only three participants per
group, there was not enough sample size to conduct
meaningful statistical tests.
Regarding externalization there were also different effects
between the azimuth and the elevation experiment. In azimuth,
all groups increased externalization after training, but with
different patterns. The one-day group started with an average
Figure 8. Results of the control condition. Top graphics show localization error and bottom graphics display externalization
levels. Left shows azimuth results and right shows elevation results. Results are organized according to the three experimental
groups: one-day group was only retested one day after training; one-week group was retested only one week after; one-month was
retested one month later. Bars represent results before training, after training, and in the last post-test (a day, week or month later).
Error bars represent ±1 SD.
doi: 10.1371/journal.pone.0077900.g008
Learning Auditory Space
PLOS ONE | www.plosone.org 11 October 2013 | Volume 8 | Issue 10 | e77900

externalization level of 42 and increased to 50 immediately
after training and to 52 the next day. The one-week group also
increased steadily in azimuth externalization. They started with
a level of 45 and reached 47 after training and 49 one week
later. In the one-month group the results were not as clear.
They started with an average of 42, achieved 47 after training
and then reduced back to 45 one month later. In elevation,
externalization effects were even smaller. The one-day group
had a small externalization evolution, from 43 in the pre-test to
45 after training and 47 one day later. The one-week group
failed to reveal any long-term externalization effects, with a
level of 43 before training, 49 immediately after training, but
again 42 one week later. A similar effect was observed in the
one-month group: it started with a 45 externalization level and
increased to 49 after training, but was reduced to 43 one month
later. Such results might reveal the relevance of successive
contact with the new head related cues, namely for the learning
of sound elevation.
Discussion
The general scope of this work was to analyze the
generalizations in learning auditory localization with altered
head-related sound cues along time. It was expected that such
analysis would cast new insights on how the auditory spatial
maps are formed and recalibrated, how the brain associates
the sound cues to localizations in space, and how this
association is represented. For that purpose, subjects were
trained to localize speech or noise sounds in azimuth and in
elevation and retested at several time intervals until one month
later. We then analyzed the evolution of localization errors and
externalization levels along time.
All subjects improved with training both in azimuth and in
elevation. Some benefit was found for white noise sounds over
speech. In azimuth, both experienced and inexperienced
listeners had lower localization errors in noise than in speech.
These sounds were also consistently more externalized than
speech sounds. Such results are easily explained by the fact
that wideband noises carry much more spectral information,
and therefore more cues, for the learning/retrieving process.
Although such sounds are not as natural as human speech,
they might be preferable for training purposes and even to
provide more out-of-the-head experiences.
An unexpected effect of previous experience was also found.
Both in elevation and in azimuth, listeners localized significantly
better prior to training if they had been previously trained in the
other task. This result points to a first interpretation standing
from this study: the neural representation of the new head
related localization cues might take the form of a generic
congruent model, not a specific cue-to-location pair. As such,
totally untrained elements from the same head-related model
might still benefit from training.
This interpretation is consistent with the results regarding the
stimulus position. Indeed, both in the azimuth and in the
elevation experiments only four sound positions were trained.
Nevertheless, error reduction was found in many other stimuli
positions. Also, some untrained sounds positions had higher
error reductions than some trained ones. This result, congruent
with our previous findings [13], is consistent with the
interpretation that a global new head model is formed as
subjects learn to localize with the new cues. Localization errors
were also varied in continuums, namely after training: in
azimuth, they were higher in the intermediate area between
front and lateral positions; in elevation they were better in
higher positions and gradually became worse as they became
more frontal. This might outline a global congruent
representation of the new sound cues, which is formed from
some learned features and then mentally interpolated in a
consistent map. Shinn-Cunningham [15] proposed a similar
explanation for the adaptation to remapped auditory
localization cues. She proposed that subjects cannot adapt to
nonlinear rearrangements of localization cues. In spatial
adaptation subjects would learn to interpret a continuous
internal decision variable differently than normal; they do not
learn to associate discrete stimulus/response pairs.
The analysis of results along time also revealed some
interesting effects. The learning of the new head-related cues
had an enduring effect over time, both in azimuth and in
elevation. The benefits were still found one month after the
short training session. The fact that this new head-related map
is remembered for longer periods of time is consistent with
previous data on auditory remapping [8]. In that work, subjects
wore ear molds for nineteen days. By the end of such time they
had learned the new auditory map and were able to localize
sounds in elevation, but they were still as accurate as prior to
training in localizing with their own ears. Here subjects
continued wearing and localizing with their own ears, but kept
the representation of the new map for a period of one month. It
is therefore arguable that listeners can learn and use
simultaneous head-related maps, much like learning and using
simultaneous languages. But in light of the control condition
results it is arguable that some additional contact with the
learned cues helps maintain the new maps. This effect was not
the same for both azimuth and elevation. Azimuth space was
sustainably maintained up to one month after training without
any additional session, but elevation was gradually more
affected with longer periods between training and post-testing.
This outlines that possibly the new auditory map represents
binaural and monaural cues differently. Indeed, the differences
between azimuth and elevation processing in the brain are
related to the most prominent use of binaural cross correlation
for azimuth and of spectral cues for elevation. These results
might reveal different long-term encoding of both types of
signal.
The analysis of the externalization levels brings further
evidence at this level. Sounds were overall poorly externalized,
but such externalization improved with time. It took longer to
reach the external threshold for elevation than for azimuth,
again representing some differences in how the brain deals
with both cue types. Interestingly, although externalization
followed a similar evolution as localization accuracy, both
improving with time and being better achieved with the white
noise stimuli, it showed more cumulative effects. As such,
although localization results tended to stabilize with time,
externalization levels tended to improve with the successive
tests. In the control condition it was noticeable that the closer
Learning Auditory Space
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together the test sessions, the higher the impact on enhanced
externalization. It becomes therefore arguable that
externalization might be achieved with greater cue familiarity,
or, in the language analogy, it might be associated with greater
fluency or naturalness in using the second head-related spatial
map.
Finally, some issues regarding the training method and what
was effectively learned should be addressed. Did subjects
learn new head-related cues, or were they merely learning
sound features or cues? Firstly, it should be restated that
trained and tested stimuli were not the same. For each
experiment, subjects were trained in only one sound type, at
only 4 positions. They revealed benefits in another sound type
and in many other sound positions. So we can conclude that
subjects were not simply finding cues in the sounds when
learning them. There was also benefit just by participating in a
previous experiment. But from azimuth to elevation, only the 0°
was the same. No sound feature could be learned in all the
other sounds.
But were they learning the task? Indeed all participants were
inexperienced. It can be argued that benefits on localization
were simply due to adjusting to the task and response
interface. We don’t have enough information about those
processes to offer a conclusive response. But such adaptation
should happen within the first trials of the experiment and reach
a plateau very fast. In most psychophysical research, an
extremely short familiarization with experiments, with only a
handful of trials, is usually enough to discard such effects. In
this study, since we intended to avoid any previous experience,
no such experiment was run. In any case, in our previous work
with similar stimuli [13], there was such a control experiment.
No benefit was found from prolonged exposure to the task.
Performance in localization was constant throughout ten
experimental blocks of localization without feedback or training.
So task learning might not have played a relevant role in our
current findings. As a final remark, the training sessions
presented totally different task and different response
interfaces from the test-sessions. So it can be stated that
subjects were not trained in the task during the training
session. It was, however, precisely after the training sessions
that the largest improvements were found.
Here we argue that the improvement found after training was
mostly due to an adaptation to new, non-individualized HRTF.
We argue this based on previous evidence that training to
localize with one’s own HRTF leads to little or no
improvements, whereas localization accuracy with altered
HRTFs strongly benefits from training [10].
In any case, additional experiments should be run, with
alternative tasks or learning methods, to better understand the
underlying mechanisms of the data presented here. It would be
particularly interesting to compare these results to more implicit
learning tasks, where subjects would not be aware of the
purposes of the experiment. There are indeed other
approaches to training, with more implicit learning, like
audiovisual settings with motion or real-time systems allowing
for visual or vestibular feedback [8,9,11,12]. However, such
paradigms are very different in nature, often involving
multisensory processes, and are therefore hard to compare.
Conclusion
This study brought new insights on the learning and
generalization of auditory space. We found evidence that a
brief training session with only a selection of sounds leads to a
general improvement in the localization of trained and
untrained sounds in trained and untrained positions. These
effects are still observed one month after training.
Externalization levels are also increased by training, although
not directly related to localization accuracy levels. Information
retrieval might affect the long-term effects of training, namely
for localization in elevation. We conclude that sound
localization with altered cues is easily trained and subject to
generalization effects across sound type, space and time.
Supporting Information
Supporting information S1. Subject distribution across
experimental conditions.
(PDF)
Author Contributions
Conceived and designed the experiments: CM JAS. Performed
the experiments: CM. Analyzed the data: CM. Contributed
reagents/materials/analysis tools: GC PD JAS. Wrote the
manuscript: CM.
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