Keywords
singing - auditory stimulation - temporal auditory area
Introduction
Auditory temporal processing is defined as perception of sound or alternation of sound
within a restricted time duration.[1] Temporal resolution ability allows us to detect small and sudden change in sound
stimuli. Good auditory temporal resolution ability is important for understanding
speech in noise in listeners with normal hearing, hearing aid users, individuals with
cochlear implant, and language disorder groups. Temporal processing is a fundamental
ability in the perception of both verbal and non-verbal stimuli.[2] Previous literature also reported the importance of temporal processing in the perception
of music, rhythm, periodicity, phoneme discrimination, duration discrimination, and
pitch discrimination.[3]
[4] According to Parbery et al[5], musical training and exposure enhances one's ability to code sudden change in stimuli.
Music is one of the most demanding cognitive and neural challenges, which requires
very precise and accurate timing of many actions, exact interval control of pitch
not involved in language, and producing sound in many different ways. Enhanced auditory
perception in musicians is likely to result from auditory perceptual learning during
several years of training and practice. Moreover, music contains fine modulation of
amplitude, frequency, and temporal aspects, which make the musicians experts in identifying
such su0062tle fluctuations. In recent literature of plasticity dependent on experience,
two studies explained some of the pre-requisites for inducing neuroplasticity, which
include complexity, intensity, and repetition of training.[6]
[7] Another voxel-based morphometric study by Abdul et al showed significantly increased
gray matter volume in musicians compared with non-musicians.[8] Results were positively correlated with years of music experience.[8] This study also showed the change due to musical training in middle and superior
cerebellar peduncle in trained musicians.[8]
Most trained and professional musicians are involved in intensive practice from many
years in terms of both intense and repetitive to attain a high level of expertise.
In case of vocal singers control of pitch is a complex biomechanical and aerodynamic
system. Researchers agree that the musician's ability to produce a precise pitch is
very important for the professional vocal musician. Literature also showed that accurate
pitch control is mainly dependent on auditory perceptual monitoring, proprioceptive
feedback of the laryngeal system and phonatory reflex systems.[9]
[10]
[11] Professional singers consistently control fundamental frequency and maintain targeted
pitch better than non-singers. Thus, there must be a better temporal resolution ability
and active auditory discrimination threshold in vocal musicians compared with non-musicians.
Many studies have focused on biological processing of auditory stimuli among musicians.[12]
[13]
[14] However, there is a lack of literature on temporal resolution and active auditory
discrimination skills in vocal musicians. The effect of musical training and experience
on temporal processing has not been studied using a combination of tasks i.e., duration
discrimination using pure tones, pulse train duration discrimination, and gap detection
threshold. Hence, the aim of the present study is to assess temporal resolution and
active auditory discrimination skill in vocal musicians.
Method
Participants
Two groups of subjects (15 experimental and 15 in the control group) within the age
range of 20–30 years participated in the study. The subjects with minimum professional
experience of 5 years of vocal musical exposure participated in experimental group.
Age-matched participants without any formal training of music qualified as non-musicians
(control group). All the participants provided informed written consent.
Participant Selection Criteria
All the participants were having normal hearing thresholds as defined by pure tone
thresholds of < 15 dBHL at 250 Hz, 500 Hz, 1000 Hz, 2000 Hz, 4000 Hz, and 8000 Hz.
Further, they had normal middle ear functioning, as revealed by the middle ear analyzer.
We used click-evoked auditory brainstem response (ABR) to rule out any retrocochlear
pathology. Participants who had any other otological, neuromuscular, and neurological
problem were excluded from the study based on structured case history.
Testing Environment
All the behavioral tests were performed in a sound treated room where noise levels
were in accordance with the guidelines in ANSI S3.1. The testing rooms were well illuminated
and air-conditioned for the comfort of the experimenter as well as of participants.
Procedure
Pure tone thresholds was obtained using a modified version of Hughson and Westlake
procedure across octave frequencies from 250, 500, 1000, 2000, 4000 Hz, and 8000 Hz
for air conduction and frequencies from 500, 1000, 2000, and 4000 Hz for bone conduction.[15] We used a middle ear analyzer to carry out tympanometry using a probe tone frequency
of 226 Hz and to obtain ipsilateral and contralateral acoustic reflexes thresholds
at 500 Hz, 1000 Hz, 2000 Hz, and 4000 Hz. We administered duration discrimination
using pure tone, pulse train duration discrimination, and gap detection threshold
tasks on both groups of participants to assess temporal resolution ability. Similarly,
differential limen of frequency tasks were given to both groups of participants to
assess active auditory discrimination skill with MATLab software using maximum likelihood
procedure technique through a calibrated headphone (Sennheiser Urbanite XL) attached
to a personal computer. The program provided feedback on the computer screen after
every response as to whether it was correct or incorrect. We considered an average
of three blocks as threshold. We adopted this procedure to obtain more precise and
reliable thresholds.
Duration Discrimination using Pure Tone
In duration discrimination using pure tone (1000Hz), we measured the minimum difference
in duration required to perceive the two otherwise identical stimuli, using maximum
likelihood procedure. The duration of the standard tone was 250 milliseconds. The
duration of the variable tone was changed based on response of the participants. We
used two alternative forced choice procedures in which the participants were asked
to indicate which tone was longer in duration.
Pulse Train Duration Discrimination
In pulse train duration discrimination, the standard stimulus consists of six 20 milliseconds
pulses of 1 KHz tone. These pulses are arranged in three pairs, with 40 milliseconds
of silence between each member of a pair and 120 milliseconds between pairs. The temporal
structure of the variable sequence is varied by increasing the separation between
members of each pair, with a corresponding decrease in the between-pair time and,
thus, a constant interval between the first tones in each of the successive pairs.
Thus, the first, third, and fifth tones are fixed in time, while the onsets of the
second, fourth, and sixth tones are delayed by a varying amount. The parameters that
varied adaptively were duration of gap within or between pairs of the variable stimulus
to make different rhythm from standard stimuli. The subject task was to identify odd
rhythm in a group of two standard and one variable stimuli.
Gap Detection Threshold
Gap detection threshold was assessed using 750 milliseconds of Gaussian noise with
gap in the center. Gap duration was varied according to listener performance using
maximum likelihood procedure. The noise had 0.5 milliseconds cosine ramps at the beginning
and end of the gap. In the three alternative forced choice task, the reference stimulus
was always a 750-millisecond white noise without gap, whereas the variable stimulus
contained a gap. We took the minimum gap duration required to perceive a gap in noise
as the threshold.
Differential Limen of Frequency
We assessed differential limens of frequency at 1000 Hz with the help of MATLab software
using the maximum likelihood procedure technique. Three number of blocks were taken
for differential limen of frequency. Each block contained 35 trials. We adopted three
alternative forced choice procedures for response. The clients were instructed to
discriminate highest pitch among three tones (250 milliseconds) presented one after
the other.
Statistical Analysis
We performed descriptive statistics to find out mean and standard deviation (SD) for
all tasks in vocal musicians and non-musicians. Independent t-test was done to compare between musicians and non-musicians for all task to check
any significant difference between groups.
Results
To analyze the data collected from vocal musicians and non-musicians, we performed
descriptive statistics and independent t-test using SPSS (version 17.0). The purpose of descriptive statistics was to find
out mean and standard deviation of all the tasks: duration discrimination using pure
tone, pulse train duration discrimination, gap detection threshold, and differential
limen of frequency ([Table 1]). Results revealed lower threshold for all tasks in vocal musicians compared with
non-musicians.
Table 1
Mean and standard deviation (SD) of duration discrimination using pure tone, pulse
train duration discrimination, gap detection threshold, and differential limen of
frequency
|
Pure Tone Duration Discrimination
|
Pulse train duration discrimination
|
Gap Detection Threshold
|
Differential Limen of Frequency
|
|
Mean
|
SD
|
Mean
|
SD
|
Mean
|
SD
|
Mean
|
SD
|
|
Vocal Musicians
|
23.13
|
10.16
|
19.30
|
5.29
|
1.81
|
0.39
|
5.86
|
1.64
|
|
Non-Musicians
|
38.93
|
13.18
|
35.17
|
13.76
|
2.47
|
0.48
|
10.33
|
1.34
|
Abbreviation: SD, standard deviation.
Independent t-test showed that vocal musicians have a significantly lower threshold compared with
non-musicians in duration discrimination using pure tone (t = −3.67; df = 28; p = 0.001), pulse train duration discrimination (t = −4.16; df = 28; p = 0.00), gap detection threshold (t = −4.06; df = 28; p = 0.00), and differential limen of frequency (t = −8.15; df = 28; p = 0.00).
[Fig. 1 ] shows error bar graph of duration discrimination threshold and pulse train duration
discrimination threshold for vocal musician and non-musicians. Similarly, [Fig. 2] and [Fig. 3] show error bar graph of gap detection threshold and differential limen of frequency,
respectively.
Fig. 1 Error bar graph of duration discrimination threshold and pulse train duration discrimination
threshold for vocal musician and non-musicians.
Fig. 2 Error bar graph of gap detection threshold for vocal musician and non-musicians.
Fig. 3 Error bar graph of differential limen of frequency for vocal musician and non-musicians.
Discussion
The main aim of the present study is to compare temporal resolution skills in vocal
musicians compared with non-musicians. The present study showed enhanced temporal
resolution ability in vocal musicians in comparison to non-musicians. The better performance
of musicians can be attributed to the fact that music exposure helps to develop auditory
pathways for detecting small change in auditory stimuli. Similarly, the current study
also showed better (lower) active discrimination threshold compared with non-musicians,
which indicates that musical training and experience has influenced and enhanced active
auditory discrimination skills in musicians. Our finding supports those in Fujioka
et al and Moreno et al, which reported enhancement of auditory processing with musical
training and exposure.[16]
[17] The effect of musical training and experience on temporal processing has not yet
been studied using combination of tasks (i.e., duration discrimination using pure
tones, pulse train duration discrimination, and gap detection threshold). The present
study showed that all these tests are equally sensitive in assessing enhanced temporal
resolution ability in musicians.
Duration Discrimination using Pure Train and Pulse Train Duration Discrimination
The current study showed lower threshold among vocal musicians for duration discrimination
using pure tone as well as for pulse train duration discrimination, which indicates
enhanced temporal resolution ability in musicians compared with non-musicians. This
outcome is in consonance with previous literature.[18]
[19] Güçlü et al investigated duration discrimination threshold in musicians and non-musicians
and reported that musicians had better duration discrimination threshold compared
with non-musicians.[18] The present study finding is similar with a study done by Sangamanatha et al, which
reported lower duration discrimination threshold (better) in children with musical
training and adults with musical training, when compared with children without any
musical training.[19]
Gap Detection Threshold
Result showed significantly lower gap detection threshold in vocal musicians compared
with non-musicians. Our results are well-supported by other researchers.[19]
[20]
[21]
[22] However, few studies showed no changes due to musical training.[23] Sangamanatha et al investigated gap detection threshold and reported that mean gap
detection thresholds were significantly lower for children with musical training and
adults with musical training, when compared with children without any musical training.[19] Similarly, Mishra, and Panda showed that Carnatic musical training has a significant
effect on temporal resolution ability in musicians assessed by gap detection threshold.[20] The present study's finding is in contrast with the study done by Monteiro et al,
which reported no significant difference in gap detection threshold between musicians
and non-musicians.[23]
Differential Limen of Frequency
The current study showed that musicians performed significantly better than non-musicians
in differential limen frequency. Threshold of differential limen of frequency for
musicians was significantly lower (better) than non-musicians. The finding revealed
that musicians have better “active auditory discrimination skill” than non-musicians.
Similar, this finding appears in previous literature.[24]
[25]
[26]
[27] Parbery et al compared frequency discrimination in musicians and non-musicians.[25] They reported that musicians have more fine-grained frequency discrimination. In
a similar line, Bidelman and Krishnan measured fundamental (F0) and first formant
(F1) frequency difference limens (DLs) in musicians and showed DLs 2 to 4 times better
than non-musicians.[26] In another study, Bidelman et al assessed fundamental frequency discrimination limen
between musicians and non-musicians.[27] They reported trained musicians having significantly better fundamental frequency
differential limen when compared with non-musicians. The findings of the current study
showed mean DLF for musicians was almost half of the DLF for non-musicians. This indicates
that musical training and experience has influenced and enhanced active auditory discrimination
skills in musicians.
Thus, musical training can be used to enhance temporal resolution skills and active
auditory discrimination skills in the clinical population, such as cases of temporal
processing deficit, learning disabilities, Parkinson's disease, schizophrenia, Alzheimer's
disease, children with developmental language disorder, and children with cochlear
implant.[28]
[29]
[30] Enhancement of temporal resolution ability and active auditory discrimination skills
due to musical training in these populations may result in the improvement of speech
perception.
Conclusion
The present study's outcome showed that vocal music training and experience enhances
temporal resolution skill and active auditory discrimination ability. These enhancements
may be due the fact that more efficient neural network and connections (neuroplasticity)
in vocal musicians results in a better threshold in duration discrimination tasks
as well as gap detection tasks. Results from the present study support further exploration
into the effectiveness of musical training on children with auditory processing disorder.
To conclude, musical training is useful in enhancing temporal resolution and active
auditory discrimination skills in normal hearing individuals.
