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fnhum-16-1028897 January 2, 2023 Time: 14:46 # 1
TYPE Original Research
PUBLISHED 10 January 2023
DOI 10.3389/fnhum.2022.1028897
OPEN ACCESS
EDITED BY
A. M. Barrett,
United States Department of Veterans
Affairs, United States
REVIEWED BY
Binke Yuan,
South China Normal University, China
Satoshi Maesawa,
Nagoya University Graduate School
of Medicine, Japan
*CORRESPONDENCE
Pablo R. Kappen
p.kappen@erasmusmc.nl
SPECIALTY SECTION
This article was submitted to
Speech and Language,
a section of the journal
Frontiers in Human Neuroscience
RECEIVED 26 August 2022
ACCEPTED 21 December 2022
PUBLISHED 10 January 2023
CITATION
Kappen PR, van den Brink J, Jeekel J,
Dirven CMF, Klimek M,
Donders-Kamphuis M,
Docter-Kerkhof CS, Mooijman SA,
Collee E, Nandoe Tewarie RDS,
Broekman MLD, Smits M,
Vincent AJPE and Satoer D (2023) The
effect of musicality on language
recovery after awake glioma surgery.
Front. Hum. Neurosci. 16:1028897.
doi: 10.3389/fnhum.2022.1028897
COPYRIGHT
© 2023 Kappen, van den Brink, Jeekel,
Dirven, Klimek, Donders-Kamphuis,
Docter-Kerkhof, Mooijman, Collee,
Nandoe Tewarie, Broekman, Smits,
Vincent and Satoer. This is an
open-access article distributed under
the terms of the Creative Commons
Attribution License (CC BY). The use,
distribution or reproduction in other
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original author(s) and the copyright
owner(s) are credited and that the
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academic practice. No use, distribution
or reproduction is permitted which
does not comply with these terms.
The effect of musicality on
language recovery after awake
glioma surgery
Pablo R. Kappen1*, Jan van den Brink1, Johannes Jeekel2,
Clemens M. F. Dirven1, Markus Klimek3,
Marike Donders-Kamphuis1,4, Christa S. Docter-Kerkhof4,
Saskia A. Mooijman1, Ellen Collee1,
Rishi D. S. Nandoe Tewarie5, Marike L. D. Broekman5,6,
Marion Smits7,8,9, Arnaud J. P. E. Vincent1and Djaina Satoer1
1Department of Neurosurgery, Erasmus University Medical Center, Rotterdam, Netherlands,
2Department of Neuroscience, Erasmus University Medical Center, Rotterdam, Netherlands,
3Department of Anesthesiology, Erasmus University Medical Center, Rotterdam, Netherlands,
4Department of Speech and Language Pathology, Haaglanden Medisch Centrum, The Hague,
Netherlands, 5Department of Neurosurgery, Haaglanden Medisch Centrum, The Hague,
Netherlands, 6Department of Neurosurgery, Leiden University Medical Center, Leiden, Netherlands,
7Department of Radiology & Nuclear Medicine, Erasmus University Medical Center, Rotterdam,
Netherlands, 8Medical Delta, Delft, Netherlands, 9Brain Tumor Center, Erasmus MC Cancer Institute,
Rotterdam, Netherlands
Introduction: Awake craniotomy is increasingly used to resect intrinsic brain
tumors while preserving language. The level of musical training might affect
the speed and extend of postoperative language recovery, as increased
white matter connectivity in the corpus callosum is described in musicians
compared to non-musicians.
Methods: In this cohort study, we included adult patients undergoing
treatment for glioma with an awake resection procedure at two neurosurgical
centers and assessed language preoperatively (T1) and postoperatively at three
months (T2) and one year (T3) with the Diagnostic Instrument for Mild Aphasia
(DIMA), transferred to z-scores. Moreover, patients’ musicality was divided into
three groups based on the Musical Expertise Criterion (MEC) and automated
volumetric measures of the corpus callosum were conducted.
Results: We enrolled forty-six patients, between June 2015 and September
2021, and divided in: group A (non-musicians, n= 19, 41.3%), group B (amateur
musicians, n= 17, 36.9%) and group C (trained musicians, n= 10, 21.7%). No
significant differences on postoperative language course between the three
musicality groups were observed in the main analyses. However, a trend
towards less deterioration of language (mean/SD z-scores) was observed
within the first three months on the phonological domain (A: −0.425/0.951
vs. B: −0.00100/1.14 vs. C: 0.0289/0.566, p-value = 0.19) with a significant
effect between non-musicians vs. instrumentalists (A: −0.425/0.951 vs. B +C:
0.201/0.699, p= 0.04). Moreover, a non-significant trend towards a larger
volume (mean/SD cm3) of the corpus callosum was observed between the
three musicality groups (A: 6.67/1.35 vs. B: 7.09/1.07 vs. C: 8.30/2.30, p= 0.13),
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with the largest difference of size in the anterior corpus callosum in non-
musicians compared to trained musicians (A: 3.28/0.621 vs. C: 4.90/1.41,
p= 0.02).
Conclusion: With first study on this topic, we support that musicality
contributes to language recovery after awake glioma surgery, possibly
attributed to a higher white matter connectivity at the anterior part of
the corpus callosum. Our conclusion should be handled with caution and
interpreted as hypothesis generating only, as most of our results were not
significant. Future studies with larger sample sizes are needed to confirm our
hypothesis.
KEYWORDS
music, neuro-oncology, neuroplasticity, corpus callosum, aphasia, brain tumors
Introduction
Awake craniotomy is increasingly used to resect intrinsic
brain tumors (specifically for diffuse low-grade gliomas)
while preserving language. This technique has improved over
time, with the development of intraoperative protocols for
awake tumor resection (De Witte et al.,2015). Despite these
improvements, intraoperative mapping and language testing
do not always ensure complete maintenance of the patient’s
linguistic abilities. Due to slow tumor growth, diffuse low grade
glioma patients typically suffer from mild aphasia preoperatively
which often temporarily deteriorates after tumor resection
(Duffau et al.,2003;Satoer et al.,2014). In the year after surgery,
most patients recover to their baseline level whereas others
remain to suffer from this further language decline in the long-
term (Satoer et al.,2014). This can be attributed to differences
in neuroplasticity in language networks, but it is unclear which
factors and to what degree these affect postoperative language
recovery (Kiran and Thompson,2019).
The literature suggests that musical training might affect
the course of postoperative language recovery (Merrett et al.,
2013). Both language and music require complex hierarchical
processing systems that share features, such as pitch, rhythm,
timbre, and syntactic structure (Besson and Schön,2001).
Recent fMRI data suggested that some brain regions, associated
with language functioning (e.g., Broca and Wernicke’s areas),
are also activated during music processing (Maess et al.,2001;
Levitin and Menon,2003;Abrams et al.,2011).
Higher degree of organization of language structures
between lobes (i.e., frontal and temporal) or hemispheres
through the corpus callosum have been described in musicians
(Schlaug et al.,1995a,2009). This has provided ground for
music-induced language therapy, such as Melodic Intonation
Therapy (MIT), in patients with severe aphasia (Schlaug et al.,
1995a,2009;Omigie and Samson,2014).
Some experimental studies show that musical training can
improve language function (in a so-called transfer of learning) in
healthy participants (Besson and Schön,2001). However, there is
currently no evidence in the literature to support the hypothesis
that musical training-related brain changes might also have a
beneficial effect on language following brain surgery (Omigie
and Samson,2014).
Hence, we conducted a study in which we hypothesize
a better recovery of language in musical patients after
awake glioma surgery as compared to non-musical patients.
Moreover, we hypothesize that this possible beneficial effect
may be explained by contralateral compensation through the
corpus callosum.
Materials and methods
Study population
The consecutively included cohort consisted of adult
patients, who underwent an awake resection between June 2015
and September 2021 at the Erasmus MC, University Medical
Center Rotterdam (EMC) or at the Haaglanden Medisch
Centrum the Hague (HMC), and received an extensive language
assessment before (baseline; T1) and at least one time point
after surgery (3 months; T2 and/or 1 year; T3). These centers
consider awake surgery in case of left-sided tumors, right-
sided tumors with left handedness or involvement of the
sensory-motor regions or in case of prior speech deficits with
or without language location confirmed by functional fMRI.
Moreover, an awake craniotomy procedure is only considered
if we deem this feasible for the particular patient. Patients
that were operated for a recurrent glioma, non-native Dutch
speakers (defined as unfamiliar with the Dutch language before
the age of 8 years), patients known with neurodegenerative
diseases affecting language (e.g., dementia) or with a WHO
grade 4 astrocytoma or glioblastoma, were excluded. Patients
were additionally excluded for the volumetric analysis in case
of tumor involvement in the corpus callosum.
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Study design and data extraction
Data on musicality were prospectively collected through a
questionnaire and retrospectively complemented with available
language and clinical data.
Musicality
The Musical Expertise Criteria (MEC) are based on years
of musical training and intensity and define a musician based
on the “six-year rule” of training (Lamont,2002;Lotze et al.,
2003;Weijkamp and Sadataka,2017;Zhang et al.,2018).
A questionnaire was developed, based on the MEC, in which
points were allocated to the patient, leading to final group
formation; non-musicians (group A), amateur musicians (group
B), and trained musicians (group C, Supplementary Appendix
A). Additional information on musicality was assessed such
as the onset age of playing the instrument/vocals, type of
instrument and whether music was played after the operation.
Linguistic data
Language data were retrospectively extracted as language
was already monitored with the Diagnostic Instrument for Mild
Aphasia (DIMA) as part of standard of clinical care at baseline
(T1) and at least one time point after surgery (3 months;
T2 and/or 1 year; T3) (Satoer et al.,2022). The DIMA is a
tool, developed and validated in Dutch to evaluate suspected
mild aphasia in patients with glioma (Satoer et al.,2022). It
consists of six subtests and assesses language production and
comprehension in the following linguistic domains: phonology,
semantics and (morpho-) syntax. Moreover, data from a non-
linguistic cognitive test for visual attention and mental flexibility
(Trail Making Test/TMT A, B, and BA) were extracted (Llinas-
Regla et al.,2017).
Clinical data
Clinical data were extracted consisting of demographic
data (age, sex, education years and level based on the Verhage
scale, handedness), disease specifications (histopathology,
localization), and treatment specifications (completeness
resection, complications, adjuvant treatment) (Verhage,
1964a,b;Reitan,1989).
Volumetry
To measure the size of the corpus callosum we analyzed the
most recent structural brain magnetic resonance imaging (MRI:
1.5 or 3.0 Tesla GE Healthcare) before the awake craniotomy,
using <1.0 mm slide with T1 weighted imaging parameters. Two
researchers (P.K./J.B.), blinded for the outcome on musicality
at the time of measurement, first divided the corpus callosum
in seven subregions according to the Witelson classification
(Witelson and McCulloch,1991). Afterward, volumes (in
cubic centimeters/cm3) for each subregion were measured
with Brainlab’s Synthetic Tissue Model (Brainlab Digital OR,
München, Germany). In this model each anatomical structure
is first detected and then adapted to a gray-scale image model.
Tissue-class specific gray value simulation is compared with
meta information from datasets and afterward quantitatively
and qualitatively validated. This software is CE marked and
already widely applied for guidance during neurosurgical
procedures. Sub-group analyses were conducted for sex and
onset/duration of musical training, as differences in corpus
callosum volumes have been described in these factors (Schlaug
et al.,1995a;Lee et al.,2003). For the volume lesion analysis
we used the pre-operative coronal, sagittal and transversal T2
weighted FLAIR MRI images and conducted volumetric analysis
with Brainlabs’ smart brush (see Supplementary Appendix B
for further Technical Background).
Statistical analysis
The raw DIMA and TMT scores (A, B, and BA) were
transferred into z-scores corrected for age and years of
education, in order to facilitate comparisons. For each of
the corpus callosum subregions, an inter-rater agreement was
calculated with the interclass correlation coefficient (ICC).
Corpus callosum region volumes were compared between
groups based on the raw (cm3) and corrected measurements
(corpus callosum volume divided by total brain volume).
The three musicality groups and language or corpus
callosum volumes were visually evaluated and statistically
compared with an ANOVA in case of parametric data and a
Kruskal–Wallis test in case of non-parametric data. Normality
was tested with the Shapiro–Wilk test. Correlations between
musical training, size of corpus callosum, and course of
postoperative language were conducted with the Pearson’s
product-moment correlation. For all analyses significance (p-
value, significant in case of 0.05 or less), and for correlation
coefficient (r), degrees of freedom (df) were illustrated.
We were unable to conduct a priori sample size calculation,
as we were unsure which effect size was expected as this is
the first study evaluating the effects of musicality on language
recovery after awake glioma surgery. Hence, achieved power
was computed (1-β) on post-hoc analyses in case of visually
observed non-significant outcomes using G∗Power version 3.1
(Faul et al.,2009). All other statistical analyses were conducted
using R (version 4.1.1).
Results
Musicality and demographic data
We consecutively included 46 patients, in the period
between June 2015 and September 2021, at the EMC (n= 39) and
HMC (n= 7). Patients were divided into three groups based on
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musicality: non-musician (A: n= 19, 41.3%), amateur musician
(B: n= 17, 36.9%), and trained musicians (C: n= 10, 21.7%).
The mean (SD) age at the time of craniotomy was 39.6 (12.0)
years; 18 women (39.1%) and 40 (87.0%) right-handed patients
(Table 1). Higher education level was observed in 24 (52.2%)
patients, with mean (SD) number of years of education of 14.8
(2.47). Gross total resection of the tumor was achieved in 20
(56.5%) patients. Intra-operative complications were reported in
4 (8.7%) patients; one patient had an arterial bleeding which was
coagulated and three other patients had intra-operative seizures
during mapping.
Adjuvant therapy within one year was administered in 16
(65.2%) patients. Histopathology revealed WHO grade 2 glioma
in 39 (84.8%) patients and tumor localization was right-sided
in 20 (43.5%) patients. None of the baseline characteristics
differed significantly among groups, except for right sided
tumor localization, which was more common in group C
(p= 0.02).
Trail Making Test (mean/SD z-scores) were 0.289/1.13–
1.00/1.62 (average to high average) and were similar between
the three groups. In musical patients, the mean/SD age of
starting to play an instrument was 13.1/8.44 years (group B)
and 12.0/4.59 years (group C), with a mean/SD total of hours of
playing music of 535/743 (group B) and 5020/3890 (group C).
Primary outcome: Musicality vs.
language
Our main analyses comparing musicality and postoperative
course of language were not statistically significant (Figure 1,
Table 2, and Supplementary Appendix C). An overall decrease
of language performance (mean/SD z-value) was observed
within the first three months (T1 vs. T2) in our included cohort
(n= 44, −0.255/0.966, Table 2), which was not different between
the three groups (A: −0.411/0.865 vs. B: −0.0947/1.18 vs. C:
−0.227/0.779, p= 0.45).
Within the first 3 months (T1 vs. T2), patients with more
musical experience tended to recover better in the phonologic
domain on the non-word repetition subtest (A: −0.425/0.951
vs. B: −0.001/1.14 vs. C: 0.028/0.566, p= 0.19, effect size:
0.233, 1-β= 0.26) and the sentence repetition subtest (A:
−0.202/0.683 vs. B: 0.036/1.92 vs. C: 0.125/1.32, p= 0.44, effect
size = 0.09, 1-β= 0.08), and recover less on the syntactic
domain in the sentence completion subtest (A: 0.031/2.09 vs.
B: −0.048/0.46 vs. C: −0.531/1.45, p= 0.86, effect size = 0.127,
1-β= 0.11). However, these differences were not significant.
In the period of 3 months to 1 year (T2 vs. T3) a decrease of
language performance (z-value mean/SD) was observed (n= 27,
−0.246/0.947), which was not different between the groups (A:
−0.178/1.19 vs. B: −0.265/0.818 vs. C: −0.260/1.07, p= 0.90),
but a beneficial effect of non-musicality was found in the word
repetition subtest (phonologic domain, A: 0/0 vs. B: 0.393/2.30
vs. C: 0.568/1.71, p= 0.86, effect size = 0.19, 1-β= 0.18). Post-hoc
analyses revealed a maximum achieved power (1-β) of 26%.
Sub-analyses within the musicians (B and C), comparing
instrument players (n= 21) with singers (n= 7) revealed
worse language performance of singers within the first 3 months
(0.0428/0.837 vs. −0.729/1.44, p= 0.21), in the compound
word repetition subtest (phonologic domain, −0.248/0.776 vs.
−1.77/2.33, p= 0.03) and the semantic subtest (0/0.968 vs.
−0.990/0.949, p= 0.01). Excluding singers from the main
analyses revealed a significant effect within the first three
months (T1 vs. T2) on the non-word repetition subtest
(phonologic domain) when comparing non-musicians vs.
instrumentalist musicians (A: −0.425/0.951 vs. B and C:
0.201/0.699, p= 0.039).
Secondary outcome: Musicality vs.
corpus callosum
Volumetric corpus callosum measurements were obtained
from 39 patients: inter-class correlation showed good to
excellent inter-observer agreement (ICC = 0.77–0.99) for each
corpus callosum region. No statistically significant difference
was observed between the musicality groups and the corpus
callosum volumes (Figure 2 and Table 3).
A trend of effect of musicality on corpus callosum volume
(mean/SD cm3) was observed (A: 6.67/1.35 vs. B: 7.09/1.07 vs.
C: 8.30/2.30, p= 0.13) which diminished after correcting for
total brain volume (A; 0.756/0.128 vs. B: 0.763/0.091 vs. C:
0.837/0.221, p= 0.63).
Sub-analyses in sex and subregion revealed the largest
difference in the anterior corpus callosum of male non- vs.
trained musicians (A: 3.28/0.621 vs. C: 4.90/1.41, p= 0.05).
No trend was observed in women nor in the posterior
corpus callosum. Size of corpus callosum (mean/SD cm3) was
not significantly larger in patients that started playing their
instrument before their tenth life year (7.33 vs. 7.84, p= 0.81).
A linear correlation was visually observed, but not
statistically confirmed, between volume of corpus callosum and
postoperative language course (T1 vs. T3, t= 0.79, df = 22,
p-value = 0.43) and between the total hours of playing and
corpus callosum volume (t= 1.57, df = 18, p-value = 0.13,
Figure 3).
Discussion
In this cohort study, we evaluated the effect of musicality on
the course of post-operative language recovery following awake
glioma surgery. We did not find a significant difference between
musicality, corpus callosum size and postoperative course of
language performance after awake glioma surgery in our main
analysis. This could point into the direction that there is no
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TABLE 1 Baseline characteristics.
A. Non-musician
N= 19
B. Amateur musician
N= 17
C. Trained musician
N= 10
P-Value
Demographic data
Age (mean/SD)138.8 (11.7) 40.3 (14.3) 39.6 (9.31) 0.92
Female sex (n/%) 9 (47.4%) 6 (37.5%) 3 (27.3%) 0.61
Higher education (n/%)26 (31.6%) 12 (70.6%) 6 (60.0%) 0.06
Education years (mean/SD) 14.1 (2.27) 15.1 (2.42) 15.5 (2.83) 0.17
Right handedness 16 (84.2%) 14 (82.4%) 10 (100%) 0.38
Disease and surgical specifics
High grade tumor (n/%) 1 (5.3%) 5 (29.4%) 1 (10.0%) 0.12
Right sided localization (n/%) 5 (26.3%) 7 (41.2%) 8 (80.0%) 0.02
Lesion volume (mean/SD cm3) 31.4 (19.2) 49.2 (31.7) 36.5 (28.0) 0.20
Gross total resection (n/%) 7 (36.8%) 8 (47.1%) 5 (50.0%) 0.74
Intra-operative complications (n/%) 1 (5.3%) 1 (5.9%) 2 (20.0%) 0.36
Adjuvant treatment (n/%)35 (26.3%) 9 (52.9%) 2 (20.0%) 0.13
Cognitive function4
TMT A (mean/SD) 0.889 (1.63) 1.24 (1.64) 0.810 (1.68) 0.63
TMT B (mean/SD) 0.611 (0.918) 0.318 (1.73) 0.660 (0.862) 0.97
TMT BA (mean/SD) 0.358 (1.21) 0.288 (1.19) 0.160 (0.937) 0.97
Musical specifications5
Main instrument –
Singing 4 (23.5%) 2 (20%)
Instrument – 15 (88.2%) 10 (100%) 0.46
Start age main instrument (mean/SD) – 13.1 (8.44) 12.0 (4.59) 0.78
Start instrument under 10 years (n/%) 10 (58.8%) 3 (30.0%) 0.15
Total hours of playing (mean/SD)6– 535 (743) 5020 (3890) <0.001
1Age at awake craniotomy.
2Finished high level secondary education or university degree.
3Received adjuvant therapy, including chemotherapy (i.e., temozolomide) or radiotherapy, until 1 year after surgery.
4Trail making test; z values.
5P-values were calculated between the amateur and trained musicians. +Mean hours per day ×years (×365) playing.
correlation between musicality and language recovery. However,
the lack of evidence could also be attributed to our limited
sample size, as our power (1-β) concerning possible trends did
not exceed 26%. Future studies with larger sample size could
confirm our findings.
Although most findings did not reach significance, we did
observe a significant beneficial effect, after excluding the vocal
musicians, in two phonological subtests in patients with a
musical background compared to non-musicians. The observed
effect in our study related to musicality and phonology is
not unexpected as the phonologic system and music share
a common hierarchical structure (e.g., syllabic and grouping
structure, prosody and melody). In the phonological subtests
existing words and non-words had to be repeated, including a
correct phonological form (including syllables and phonemes),
stress patterns and pitch. Musical expertise increases sensitivity
to pitch changes which allows musicians to detect subtle
variations of pitch, rhythm, and harmony within musical
phrases faster, and more accurately than non-musicians (Besson
et al.,1994;Koelsch et al.,2002;Bidelman and Krishnan,
2010). This enhanced sensitivity to acoustic features might
allow musicians to construct more elaborated perceptions of the
speech signal, referred to as transfer effects, than non-musicians.
This transfer effect was supported by a study showing that
musicians were more sensitive than non-musicians to abstract
phonological representations (consonant or vowel changes; e.g.,
baìn/zaìn) derived from the processing of acoustic parameters
(Marie et al.,2011). This, in turn, can facilitate stages of speech
processing, leading to higher scores on the phonologic language
tests (Besson et al.,1994).
As our patients were asked to focus their attention during
the test, one could argue that the beneficial results of musicians
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FIGURE 1
Postoperative language course vs. musicality. An overall decrease of language performance (mean/SD z-value) was observed within the first
three months (T1 vs. T2) in our included cohort (n= 44, –0.255/0.966) but patients with more musical experience tended to recover better on
the non-word repetition subtest (phonologic domain) (A: –0.425/0.951 vs. B: –0.001/1.14 vs. C: 0.028/0.566, p= 0.19) and the sentence
repetition subtest (phonologic domain) (A: –0.202/0.683 vs. B: 0.036/1.92 vs. C: 0.125/1.32, p= 0.446).
TABLE 2 DIMA scores vs. musicality.
Baseline (T1) vs. after 3 months (T2) After 3 months (T2) vs. after 1 year (T3)
A.
Non-musician
B. Amateur
musician
C. Trained
musician
A.
Non-musician
B. Amateur
musician
C. Trained
musician
Overall
DIMA −0.411 (0.865) −0.0947 (1.18) −0.227 (0.779) −0.260 (1.07) −0.265 (0.818) −0.178 (1.19)
Days* 68.3 (18.8) 73.6 (33.4) 67.2 (39.1) 347 (77.3) 297 (110) 353 (70.5)
Phonology
Word repetition −0.293 (1.20) −0.510 (1.86) 0 (0) 0.568 (1.71)0.393 (2.30)0 (0)
Compound
repetition
−0.308 (1.83) −0.805 (1.66) −0.214 (0.642) 0 (1.45) −0.224 (0.806) 0.385 (0.861)
Non-word repetition −0.425 (0.951)1−0.00100 (1.14)10.0289 (0.566)10.279 (1.63) 0.0768 (0.582) 0.199 (0.445)
Sentence repetition −0.202 (0.683)10.0359 (1.92)10.125 (1.32)1−0.318 (0.631) 0.426 (1.59) 0.226 (0.505)
Semantic
Semantic tests −0.470 (1.32) −0.225 (1.20) −0.234 (0.703) −0.234 (1.27) 0.162 (1.04) 0 (0)
Syntaxis
Sentence completion 0.0316 (2.09)1−0.0484 (1.46)1−0.531 (1.45)1−1.09 (2.46) −1.37 (1.96) −1.01 (4.43)
All values are mean (SD) Z scores, calculated from a healthy population (n= 211) based on age (cutoff 55 years) and Education years (cutoff 12 years). T1; baseline/before surgery, T2;
3 months after surgery, T3; 1 year after surgery. *Mean (SD) days from craniotomy to T2/T3. 1Beneficial trend observed between musicality and language. Detrimental trend observed
between musicality and language.
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FIGURE 2
Corpus callosum regions vs. musicality per sex. CC, corpus callosum. Sub-analyses in sex and subregion revealed the largest trend in the
anterior corpus callosum of male non- vs. trained musicians (A: 3.28/0.621 vs. C: 4.90/1.41, p= 0.05). No trend was observed in women nor in
the posterior corpus callosum.
TABLE 3 Corpus callosum measurements vs. musicality.
A. Non-musician
N= 17
B. Amateur musician
N= 13
C. Trained musician
N= 9
P-Value
Overall (n = 39)
Corpus callosum 6.67 (1.35) 7.09 (1.07) 8.30 (2.30) 0.13
Anterior corpus callosum 3.17 (0.551) 3.16 (1.12) 4.34 (1.41) 0.06
Posterior corpus callosum 3.49 (0.878) 3.42 (1.03) 3.93 (1.17) 0.52
Male (n = 23)
Corpus callosum 7.08 (1.42) 7.54 (0.995) 9.23 (2.18) 0.12
Anterior corpus callosum 3.28 (0.621) 3.66 (0.723) 4.90 (1.41) 0.05
Posterior corpus callosum 3.79 (0.905) 3.83 (0.433) 4.30 (1.13) 0.66
Female (n = 16)
Corpus callosum 6.21 (1.19) 6.36 (0.808) 6.44 (1.26) 0.13
Anterior corpus callosum 3.05 (0.468) 2.37 (1.27) 3.23 (0.432) 0.70
Posterior corpus callosum 3.16 (0.762) 2.76 (1.41) 3.18 (1.01) 0.78
All volume measures are in mean/SD cubic centimeter (cm3). Patients with tumor involvement in the corpus callosum were excluded. Anterior corpus callosum: rostrum, genu, rostral
body and anterior body. Posterior corpus callosum: posterior body, isthmus and splenium.
on language tests reflect a general effect of attention. However,
data from a non-linguistic cognitive test for visual attention
and mental flexibility (Trail Making Test) revealed average to
high scores, which did not differ between groups. Moreover,
electro-encephalogram studies tackled this issue by showing
similar attention between both musicians and non-musicians
while conducting several language tests (Courchesne et al.,
1975;Squires et al.,1975;Escera et al.,2000). Our findings on
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Kappen et al. 10.3389/fnhum.2022.1028897
FIGURE 3
Correlation hours of playing vs. volume of corpus callosum vs. language. A linear correlation was visually observed, but not statistically
confirmed, between volume of corpus callosum and postoperative language course (T1 vs. T3, t= 0.79, df = 22, p-value = 0.43) and between
the total hours of playing and corpus callosum volume (t= 1.57, df = 18, p-value = 0.13).
phonology are clinically relevant as its prognostic relation to the
quality of verbal communication at the long run were already
demonstrated in aphasic patients after stroke (El Hachioui et al.,
2013). The phonological subtests included, among other tests,
non-word and sentence repetition; these two tests are important
to address as they enable us to distinguish lexical from non-
lexical processes. Additional to the classic theory, in which a
lesion in the arcuate fasciculus leads to conduction aphasia
(Wernicke,1874), recent studies suggest that a word-repetition
impairment may be explained by a “dual-route” model: a
dorsal language stream which is dedicated to phonological
processing (non-lexical: ability to link sound to articulation),
and a ventral stream which is dedicated to semantic processing
(lexical: linking sound to meaning) (Moritz-Gasser and Duffau,
2013). Therefore, it is important to monitor subtle changes in
phonological production (e.g. word repetition) as an indicator
for the overall quality of language processing (Sierpowska
et al.,2017). Moreover, future language rehabilitation could be
targeted at the phonological level in glioma patients with a
musical background. The advantage of musicality on phonology
between three months and one year was less prominent:
restoration of language in the non-musical population may
have reduced the beneficial effect of music induced alternative
compensatory pathways for language recovery.
We did not expect the worse performance in the syntactic
domain in the trained musicians compared to the non-
musicians. In the literature a paradox is found on syntactic
relations in music and language. Cases of dissociations have
been described with impaired perception of harmonic relations
in music (i.e., amusia) with no signs of aphasia or, inversely,
language impairment with spared musical abilities (Griffiths
et al.,1997;Peretz et al.,1997,2003;Ayotte et al.,2000,
2002). On the other hand, associations have been described on
neuroimaging studies showing early right anterior negativity
(associated with harmonic processing) in Broca’s area (Maess
et al.,2001). Patel (2003) tackled this paradox by proposing
the ‘shared syntactic integration resource hypothesis’ in which
linguistic and musical syntax share certain syntactic integration
processes that apply over different domain-specific syntactic
representations. The syntactic subtest involved completion of
the sentence with words that would fit within the context,
which also touches upon semantic performance. Therefore, the
decrease of syntactic scores in the trained musician group may
have been attributed to damage to domain-specific semantic
representations rather than a problem with syntactic integration
processes, which is expected to be enhanced in this sub-group.
A trend toward a larger corpus callosum, predominantly
anteriorly, in trained musical patients compared to non-musical
patients was observed. Anterior corpus callosum connects
frontal structures; it has been suggested that the intense
bimanual motor training of musicians, such as when playing
a string instrument, could play an important role in the
development of more and thicker myelinated transcallosal fibers
(Schlaug et al.,1995a). This difference was mostly found in men,
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Kappen et al. 10.3389/fnhum.2022.1028897
which confirms a prior study conducted by Lee et al. (2003).
A pre-existing sex-based difference in brain symmetry was
hypothesized by these researchers. Less brain symmetry, thus
more functional lateralization, is observed in smaller corpus
callosum volumes (Keenan et al.,2001). There are reports
of women showing increased symmetry compared with men;
the authors speculate that female musicians might not show
a significant change in lateralization after repetitive bimanual
motoric movement and therefore no effect on corpus callosum
size (Dorion et al.,2001;Lee et al.,2003).
A paper on musicality and corpus callosum size reported
an increased size for those musicians who commenced music
training prior to seven years of age, which was confirmed by
a number of papers since that time (Schlaug et al.,1995b;
Ozturk et al.,2002;Lee et al.,2003). We were not able to
assess this correlation as the trained musicians in our cohort
started playing their instrument at an older age. There seemed
to be a trend between the hours of musical training and the
size of the corpus callosum, however this was not statistically
confirmed. A longitudinal study investigating the influence
of musical training on brain structure in children found a
significant relationship between the amount of practice and the
degree of structural change in the corpus callosum (Schlaug
et al.,2005).Future studies should therefore not just consider
when musicians start to train, but also how long and how much
they train.
We observed a linear trend between the size of the
corpus callosum, hours of musical training and postoperative
language recovery. Musical patients may benefit from higher
white matter connectivity in the corpus callosum, contributing
to functional reorganization toward the contralateral side
(Schlaug et al.,1995b;Amunts et al.,1997;Gaser and Schlaug,
2003;Lotze et al.,2003;Han et al.,2009;Hyde et al.,
2009;Pantev and Herholz,2011;Wu et al.,2013). Melodic
Intonation Therapy (MIT), a rehabilitation technique using
melodic intoning and rhythm to restore language, has been
demonstrated to be beneficial in improved functional language
in stroke patients with severe aphasia (Hurkmans et al.,2012).
A current debate in the aphasia literature concerns whether
this occurs due to contralateral hemisphere or ipsilateral
perilesional compensation (Van Der Meulen et al.,2016).
Presently, it is thought that contralateral activation occurs
commonly in the post-acute phase, with a return to ipsilateral
perilesional activation over the following months (Saur et al.,
2006). Our results create some substantiation for contralateral
compensation in the (sub-)acute phase through the corpus
callosum. As our results were less clear after three months post-
surgery, future studies could focus on the connectivity of the
ipsilateral arcuate fasciculus and the role over time between
musicians and non-musicians (Schlaug et al.,1995b;Amunts
et al.,1997;Gaser and Schlaug,2003;Lotze et al.,2003;Han
et al.,2009;Hyde et al.,2009;Pantev and Herholz,2011;
Wu et al.,2013).
Strengths and limitations
This is the first study supporting that musicality contributes
to language recovery after awake glioma surgery possibly due
to increased neuroplastic properties in language networks. This
is relevant as increased knowledge on factors contributing to
language recovery can be used in clinical practice to inform
the patients on their prognosis and could even aid in the final
decision-making when considering surgery. There are some
limitations to discuss: the first and most important issue is that
most of our findings were not statistically significant, which
may be due to our limited sample size as our power did not
exceed 26%. Our conclusions should therefore be interpreted to
generate new hypotheses. Second, patients in the musical group
had a higher level of education, which could have contributed
to a better cognitive reserve, also described as ‘brain reserve
capacity’. According to these models, the threshold of brain
damage necessary to bring about a given deficit is more quickly
reached in individuals with less cognitive training due to less
brain reserve capacity (Gehring et al.,2011;Omigie and Samson,
2014;Stern and Barulli,2019). However, we tend to tackle
this by showing a similar cognitive level at baseline. Moreover,
language scores were corrected for education level and age.
Second, tumor in the right hemisphere was more often observed
in the musical group which could be a confounding on language
performance, considering that language is often lateralized in
the left hemisphere. However, we argue that this does not
influence our results as prior research found that hemispheric
lateralization does not affect language performance on the
DIMA scale in glioma patients (Mooijman et al.,2021;Satoer
et al.,2022).
Future studies
Future studies with a larger sample size should confirm our
findings, and might be able to correct for the above-described
confounding variables. Second, imaging techniques such as
diffuse tensor imaging (DTI) and functional MRI (e.g., with
language and musical (intonation) tests) before and after surgery
could be linked to the course of postoperative language recovery
to identify the role of contra- and ipsilateral compensation
over time (Mendez Orellana et al.,2014). Last, quality of life
questionnaires may be added to assess the true impact of subtle
language differences between musical and non-musical patients
after glioma surgery.
Conclusion
This is the first study supporting that musicality contributes
to language recovery after awake glioma surgery due to
increased neuroplastic properties in language networks,
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Kappen et al. 10.3389/fnhum.2022.1028897
especially in instrumentalists. This may be partly attributed
to a higher white matter connectivity at the anterior part
of the corpus callosum developed during repetitive bimanual
musical training, which might have contributed to functional
reorganization toward the contralateral side. Our conclusion
should be handled with caution and interpreted as hypothesis
generating only, as most of our results did not reach statistical
significance. Future studies with larger sample sizes are needed
to confirm our hypothesis.
Data availability statement
The raw data supporting the conclusions of this article will
be made available by the authors, without undue reservation.
Ethics statement
Ethical approval for this study (MEC-2020-0351) was
provided by the Ethical Committee of the Erasmus Medical
Center, Rotterdam (Chairperson Prof. Dr. H. W. Tilanus) on
the 23rd of March 2020 and of the Haaglanden Medical Center
(MEC 2021-055, Chairperson Dr. D. Horbach) on the 6th of July
2021. The patients/participants provided their written informed
consent to participate in this study.
Authors contributions
PK and DS conceived the study idea, interpreted the data,
and wrote the first draft of the manuscript. PK coordinated the
research protocol. PK and JB extracted the data and analyzed the
radiologic data. JB, JJ, CD, MK, MD-K, CD-K, SM, EC, RN, MB,
MS, AV, and DS critically revised the manuscript. All authors
have seen and approved the final version of the manuscript being
submitted.
Acknowledgments
We would like to thank Naomi Legius (Master student
Linguistics) for helping in conceiving the study idea and writing
the first draft of the protocol.
Conflict of interest
The authors declare that the research was conducted in the
absence of any commercial or financial relationships that could
be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the
authors and do not necessarily represent those of their affiliated
organizations, or those of the publisher, the editors and the
reviewers. Any product that may be evaluated in this article, or
claim that may be made by its manufacturer, is not guaranteed
or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found
online at: https://www.frontiersin.org/articles/10.3389/fnhum.
2022.1028897/full#supplementary-material
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