Neurophysiological basis of respiratory discomfort improvement by mandibular advancement in awake OSA patients

Abstract

Patients with obstructive sleep apneas (OSA) do not complain from dyspnea during resting breathing. Placement of a mandibular advancement device (MAD) can lead to a sense of improved respiratory comfort (“pseudo‐relief”) ascribed to a habituation phenomenon. To substantiate this conjecture, we hypothesized that, in non‐dyspneic awake OSA patients, respiratory‐related electroencephalographic figures, abnormally present during awake resting breathing, would disappear or change in parallel with MAD‐associated pseudo‐relief. In 20 patients, we compared natural breathing and breathing with MAD on: breathing discomfort (transitional visual analog scale, VAS‐2); upper airway mechanics, assessed in terms of pressure peak/time to peak (TTP) ratio respiratory‐related electroencephalography (EEG) signatures, including slow event‐related preinspiratory potentials; and a between‐state discrimination based on continuous connectivity evaluation. MAD improved breathing and upper airway mechanics. The 8 patients in whom the EEG between‐state discrimination was considered effective exhibited higher Peak/TTP improvement and transitional VAS ratings while wearing MAD than the 12 patients where it was not. These results support the notion of habituation to abnormal respiratory‐related afferents in OSA patients and fuel the causative nature of the relationship between dyspnea, respiratory‐related motor cortical activity and impaired upper airway mechanics in this setting.

Full text

Physiological Reports. 2024;12:e15951.
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1 of 11
https://doi.org/10.14814/phy2.15951
wileyonlinelibrary.com/journal/phy2
Received: 5 October 2023
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Revised: 23 January 2024
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Accepted: 31 January 2024
DOI: 10.14814/phy2.15951
ORIGINAL ARTICLE
Neurophysiological basis of respiratory discomfort
improvement by mandibular advancement in awake
OSApatients
RémiValentin1,2,3
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Marie- CécileNiérat1
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NicolasWattiez1
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OlivierJacq1
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MaxensDecavèle1,4
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IsabelleArnulf2,5
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ThomasSimilowski1,6
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ValérieAttali1,2,3
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided
the original work is properly cited.
© 2024 The Authors. Physiological Reports published by Wiley Periodicals LLC on behalf of The Physiological Society and the American Physiological Society.
1INSERM, UMRS1158
Neurophysiologie Respiratoire
Expérimentale et Clinique, Sorbonne
Université, Paris, France
2Hôpital Pitié- Salpêtrière, Département
R3S, Service des Pathologies du
Sommeil (Département R3S), AP- HP,
Groupe Hospitalier Universitaire
APHP- Sorbonne Université, Paris,
France
3Institut de Biomécanique Humaine
Georges Charpak, École Nationale
Supérieure des Arts et Métiers, Paris,
France
4Service de Médecine Intensive et
Réanimation (Département R3S),
Groupe Hospitalier Universitaire
APHP- Sorbonne Université, Paris,
France
5Paris Brain Institute (ICM), Sorbonne
Université, Paris, France
6Hôpital, Pitié- Salpêtrière, Département
R3S, AP- HP, Groupe Hospitalier APHP-
Sorbonne Université, Paris, France
Correspondence
Rémi Valentin, Sorbonne Université,
INSERM, UMRS1158 Neurophysiologie
Respiratoire Expérimentale et Clinique,
91, bd de l'hôpital, 75013 Paris, France.
Email: remi.valentin@ensam.eu
Funding information
APHP; Institut Carnot APHP
Abstract
Patients with obstructive sleep apneas (OSA) do not complain from dyspnea
during resting breathing. Placement of a mandibular advancement device
(MAD) can lead to a sense of improved respiratory comfort (“pseudo- relief”)
ascribed to a habituation phenomenon. To substantiate this conjecture, we
hypothesized that, in non- dyspneic awake OSA patients, respiratory- related
electroencephalographic figures, abnormally present during awake rest-
ing breathing, would disappear or change in parallel with MAD- associated
pseudo- relief. In 20 patients, we compared natural breathing and breathing
with MAD on: breathing discomfort (transitional visual analog scale, VAS- 2);
upper airway mechanics, assessed in terms of pressure peak/time to peak (TTP)
ratio respiratory- related electroencephalography (EEG) signatures, including
slow event- related preinspiratory potentials; and a between- state discrimina-
tion based on continuous connectivity evaluation. MAD improved breathing
and upper airway mechanics. The 8 patients in whom the EEG between- state
discrimination was considered effective exhibited higher Peak/TTP improve-
ment and transitional VAS ratings while wearing MAD than the 12 patients
where it was not. These results support the notion of habituation to abnormal
respiratory- related afferents in OSA patients and fuel the causative nature of
the relationship between dyspnea, respiratory- related motor cortical activity
and impaired upper airway mechanics in this setting.
KEYWORDS
dyspnea, electroencephalography, neurophysiology, OSA, respiratory drive

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1
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INTRODUCTION
Patients suffering from obstructive sleep apneas (OSA) do
not complain of dyspnea during awake resting breathing,
notwithstanding abnormalities in upper airway mechanics
representing an inspiratory load (Attali etal., 2019). Yet,
despite this absence of respiratory complaints, the place-
ment of a mandibular advancement device (MAD), known
to improve upper airway mechanics (Gakwaya etal.,2014),
can lead to a sense of improved respiratory comfort (Attali
etal.,2019), hereafter termed “pseudo- relief”. The inten-
sity of this sensation correlates with the degree of me-
chanical improvement brought about by the MAD (Attali
etal.,2019). This phenomenon has been interpreted as re-
sulting from habituation to the respiratory sensations that
would typically be associated with the respiratory- related
brain processing of OSA- related abnormal respiratory af-
ferents or the corresponding compensatory mechanisms.
Indeed, OSA patients have an increased drive to breathe
(Mezzanotte et al., 1992; Saboisky et al., 2007; Steier
etal.,2010) and exhibit a respiratory- related activation of
the cerebral cortex visible under the form of slow preinspi-
ratory potentials (PIPs) (Launois etal.,2015), two circum-
stances generally associated with dyspnea.
Respiratory habituation has been described experi-
mentally (Subhan etal.,2003; Von Leupoldt etal.,2011;
Wan etal.,2009) and hypothesized to proceed from down-
regulation of the insular cortex (Stoeckel etal.,2015; Von
Leupoldt et al., 2011) or impaired somatosensory pro-
cessing (Davenport etal.,2000; Fauroux etal.,2007) as
it exists in OSA patients (Donzel- Raynaud et al., 2009;
Grippo etal.,2011). Demonstrating respiratory habitua-
tion in OSA patients would require showing first that a
neurophysiological phenomenon usually associated with
dyspnea can be evidenced in the absence of dyspnea and
second that this phenomenon disappears in response to
an intervention associated with “pseudo- relief”.
Based on the presence of PIPs in certain patients with
OSA (Launois etal.,2015) and on the association of PIPs
with dyspnea in certain clinical contexts like amyotrophic
lateral sclerosis (Georges etal.,2016) or mechanical venti-
lation in critically ill patients (Decavèle etal.,2023; Raux
etal.,2019), we hypothesized that MAD- associated respi-
ratory “pseudo- relief ” would relate with MAD- associated
changes in respiratory- related cortical activity.
We assessed the electroencephalography (EEG) activ-
ity by using two techniques: (1) detection of preinspira-
tory activity (PIP) and (2) an EEG classifier approach that
assess global connectivity changes (Grosselin etal.,2018;
Hudson etal.,2016; Navarro- Sune etal.,2017). In patients
under mechanical ventilation an area under the receiver
operating characteristic curve (ROC) area under the curve
(AUC) of 0.7 or more on the EEG classifier, was associated
with the convergent relief of dyspnea and disappearance
of PIPs after optimization of ventilatory parameters (Raux
etal.,2019).
2
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MATERIALS AND METHODS
2.1
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Participants
We included 20 patients (4 women, median age 58 years
[49–66], a body mass index (BMI) 26 kg/m2 [24–31]).
Patients with a BMI ≥ 35 were excluded of study. They had
no history of neurological or other respiratory disorders,
no intake of psychotropic medications and no previous
UA surgery. All had moderate to severe OSA character-
ized by an apnea hypopnea index (AHI) of 32 [28–48]
events/h and a score at the Epworth somnolence scale
(Epworth sleepiness scale, ESS; 0–24) before treatment
of 11 [9–15]. All were treated for 3 months or more by a
custom- made MAD (Narval CC®, Resmed Ltd, France)
titrated by a dental specialist. The MAD treatment was
considered as optimal, based on symptoms control on
ESS: 6 [5–7] (reduction of 6 [3–8] p < 0.001) and residual
AHI 6 [3–14] (reduction of 23 [16–30]; p < 0.001). This
study was conducted after legal and ethical approval by
the Comité de Protection des Personnes Ile- de- France VI—
Pitié- Salpêtrière (ID RCB: 2013- A00158- 37). Participants
received information on the purpose and procedures of
this study and provided written consent to participate.
2.2
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Experimental protocol
Participants were instructed to stop their MAD treat-
ment 10 days before this experimental evaluation. The
whole experiment was done while awake. Patients were
sitting down on an inclinable chair, in a 45 degrees semi-
recumbent position, legs in decline position and with a
cervical collar maintaining neck in neutral position. Once
settled in a comfortable position, patients were instructed
to score their breathing sensations on a visual analog scale
(VAS) (see below).
We equipped them with a 32 electrodes EEG cap
(Acticap, Brain Products, Germany) connected to an
EEG preamplifier (V- Amp, Brain Products, Germany)
from which the signals were digitized at 2000 Hz.
Simultaneously, a nasal canula recorded ventilatory sig-
nal by differential pressure transduction (DP15 Pressure
Sensor ADInstruments, NZ), digitalized at 200 Hz
(Powerlab 16/30, ADInstruments, NZ).
We recorded two breathing conditions, each lasting
20 min, one without MAD (natural breathing), the second
while wearing the MAD.

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2.3
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Breathing discomfort
Before EEG acquisition, patients were asked to answer
the trigger question “do you feel breathing discomfort
(yes/no)” at rest. Independently from the answer to this
trigger question they were asked to rate their breathing
discomfort using two VASs under natural breathing and
MAD conditions. The VAS- 1 assessed breathing dis-
comfort on a nongraduated 100 mm visual analog scale
anchored by “no breathing discomfort” at the left end
and “intolerable breathing discomfort” at the right end
(results expressed in % full scale). The VAS- 2 consisted
on a “transitional” evaluation of the change in breath-
ing discomfort before and after wearing MAD, on a
nongraduated 100 mm scale anchored from “extreme
deterioration” at the left end to “extreme improvement”
on the right end, with a middle marker to indicate “no
change” (results expressed in % of middle marker to ex-
tremes with “+” sign for improvement and “−” sign for
deterioration) (Attali etal.,2019).
2.4
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Breathing pattern
The breathing pattern was extracted from the nasal pres-
sure signal and inspiratory onsets were marked using an
automatic trigger, visual artifacts were rejected manually
(Figure1a). None participant had predominant/perma-
nent mouth breathing. The breathing mode (nasal or
mouth) was monitored visually and on the nasal pres-
sure signal; artifacts due to intermittent mouth breathing,
were removed during analysis. We assessed peak pressure
at inspiration (Peak) defined by local maximum of nega-
tive pressure between two inspiratory onsets and time to
peak (TTP) defined by the time from inspiration onset to
maximum pressure peak. Peak pressure at inspiration re-
flects ventilation maximum flow and should increase if
UA critical closing pressure was improved by mandibular
advancement. TTP as an estimation of inspiratory time
should decrease with the reduction of obstruction while
wearing MAD (Voskrebenzev et al., 2018). Therefore,
composite parameter Peak/TTP should increase whether
mandibular advancement would improve breathing sig-
nal amplitude (Peak) or slope (TTP) (Figure1b).
2.5
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Respiratory- related cortical
activity
2.5.1
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Riemannian EEG classifier
As described in details elsewhere (Grosselin et al., 2018;
Hudson etal.,2016; Navarro- Sune etal.,2017), an EEG clas-
sifier based on Riemannian geometry was used to compare
FIGURE  Schematic representation of the experimental setup and data analysis process. (a) Electroencephalography (EEG) was
recorded using a 32 electrodes cap synchronized with nasal pressure sensor. (b) Each breathing cycle was marked at local maximum
pressure amplitude (Peak) to calculate time to peak (TTP) from inspiratory onset. Peak/TTP ratio was calculated to appreciate a
modification of breathing cycle time and amplitude. (c) Modification of EEG connectivity was assessed by area under the curve (AUC) of
EEG classifier based on Riemannian geometry. An AUC >0.7 was considered as significative modification of EEG activity. (d) EEG was
segmented in inspiratory epochs and were averaged after artifact rejection. Algorithm detected preinspiratory potentials (PIP) within 1.5 s
before inspiratory onset.

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EEG recordings and estimate the performance of the classi-
fication to detect a modification in EEG signature—which is
the reflection of a change in brain state—between two con-
ditions (Grosselin etal.,2018; Hudson etal.,2016; Navarro-
Sune etal.,2017; Raux etal.,2019). The classifier was first
trained on natural breathing EEG matrices serving as refer-
ence to perform classification. Then the classifier compared
EEG covariance matrices obtained during breathing with
MAD and calculated the average deviation from the natu-
ral breathing distribution to estimate the rejection threshold
indicating a significant change in cortical activity (Mason &
Graham, 2002). Classification performance was evaluated
by a cross- validation process: the “natural breathing” period
was divided into 10 equal EEG segments and comparisons
between 9 of these segments and the data of the “MAD”
condition were repeated 9 times to take all combinations
into account. The results were plotted as ROC curves and
the prediction AUC of 1 and 0.5 indicated perfected and ran-
dom discrimination, respectively (Figure1c). An AUC ≥0.7
outcome was considered as satisfactory to identify a cortical
activity modification (Raux etal.,2019; Taytard etal.,2022).
2.5.2
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Preinspiratory potentials
According to the method previously described inspira-
tory time- locked segments were averaged for both condi-
tions (Georges et al., 2016; Launois et al., 2015; Nguyen
etal.,2018; Raux etal.,2007; Tremoureux, Raux, Hudson,
etal.,2014). Before data treatment, we used the inspiratory
markers for EEG segmentation from −2.5 s before each in-
spiratory marker to 1 s after. Data was resampled to 250 Hz.
We used semi- automatized artifact rejection (EEG gradient
≥5 μV/ms; EEG amplitude ≥50 μV) and visual validation to
preprocess EEG data. An in- house computational algorithm
based on time window and amplitude of EEG signal preced-
ing inspiratory onset identified presence (PIP+) or absence
(PIP−) of PIP either on Cz or Fz electrodes using Matlab
(Mathworks Inc, USA) (Figure1d). PIP+ Patients during
natural breathing were retained to identify PIP modifica-
tion profiles: PIP− while wearing MAD (PIP correction)
and PIP+ while wearing MAD (PIP persistence).
2.6
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Statistical analysis
All statistics analyses were performed using Prism 9 ©
(GraphPad Software, USA). As all variables did not follow
a normal distribution, the data was summarized in terms
of their median and interquartile interval. Comparison of
clinical features and breathing parameters between natu-
ral breathing and breathing with MAD was realized using
Wilcoxon signed rank tests for paired data. Congruence
between EEG classification and PIP correction after wear-
ing MAD was assessed by Fischer's exact test. Then, patients
with an AUC ≥0.7 on the EEG classifier were compared to
patients with an AUC <0.7 on relative change in Peak (% of
change), TTP (% change), Peak/TTP (% of change), VAS- 2 (%
of scale), using a Mann–Whitney test for unpaired samples.
In addition, we performed a sensitivity analysis in patients
exhibiting a PIP+ during natural breathing and in whom the
two EEG index provided congruent results, namely either
PIP disappearance when breathing with MAD associated
with a Riemannian classifier AUC ≥0.7 or PIP persistence
when wearing the MAD associated with a Riemannian clas-
sifier AUC <0.7. These two subgroups were compared in
terms of MAD- associated changes in Peak (% of change),
TTP (% change), Peak/TTP (% of change) and VAS- 2 (% of
scale), using a Mann–Whitney test for unpaired samples.
Differences were considered statistically significant for p
values below 0.05 (Figure2).
3
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RESULTS
3.1
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Breathing discomfort
None of the participants spontaneously responded «yes»
to the trigger question “do you feel breathing discomfort?”
at inclusion. Nevertheless, the VAS- 1 scale median score
was 3 [0%–12%] during natural breathing and 0 [0%–5%]
with MAD (−2 [−3.5 to 0], p = 0.011). The MAD- associated
change in breathing comfort on the VAS- 2 transitional
scale was 26 [2%–56%], with 11 patients out of 20 report-
ing change over 20%.
3.2
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Breathing pattern
Compared to natural breathing, breathing with MAD
was associated with significantly higher values of Peak
amplitude (from 14 [10–28] to 17 [10–37] mV, p = 0.002)
and Peak/TTP ratio (from 31 [15–45] to 34 [14–57] mV/s
p = 0,006) There was no significant change in TTP (0.7
[0.6–1] to 0.8 [0.6–1] s, p = 0.29) or breathing frequency
(14 [12–18] to 14 [11–18] cycles/min, p = 0.43).
3.3
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Respiratory- related cortical activity
3.3.1
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Riemannian EEG classifier
We observed a change in cortical connectivity between
natural breathing and MAD conditions with a median
AUC on the EEG classifier of 0.68 [0.61–0.80] and an AUC
≥0.7 for eight patients (40%) (Figure3a).

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VALENTIN etal.
FIGURE  Results of one patient regarding preinspiratory potentials (PIP) detection and electroencephalography (EEG) classifier.
(a)Average inspiratory epochs on Cz and Fz electrodes were divided in five windows of 0.5 s (red lines), preinspiratory activity was
identified by automatic detection of amplitude and latency before inspiratory onset. During natural breathing, the presence of PIP for this
patient is characterized by the slow negative shift around −0.5 s which cannot be found while breathing with mandibular advancement
device (MAD). (b) On the left, covariance matrices are computed from electrode1 to 32 signals and 1 to N 5 s windows to capture the
spatiotemporal dynamics of the EEG between natural breathing and breathing with MAD. In the middle, covariance matrices based on the
Riemannian distance between EEG signals of both conditions was used to evaluate the ability of the classifier to detect a change in brain
state using the receiver operating characteristics curve (ROC). On the right, a boxplot depicts the performance of the classifier to separate
the two conditions in terms of area under the curve (AUC) (the box delineates the interquartile range of the AUC centered on median value,
the whiskers correspond to the extreme values).
FIGURE  Electroencephalography (EEG) classifier area under the curve (AUC) and congruence with preinspiratory potential (PIP)
between rest breathing and while wearing mandibular advancement device (MAD). (a) Boxplot centered on median with interquartile
range, whiskers represent maximum and minimum values of EEG classification performance: receiver operating characteristics curve (ROC)
area under the curve (AUC). An AUC ≥0.7 was considered as significative for a modification of EEG activity. (b) After EEG classification
(AUC ≥0.7 in black and AUC <0.7 in gray), considering (PIP+) presence or (PIP−) absence at baseline rest condition, we described various
profiles of PIP modification while wearing MAD (−to−, −to+, +to−, +to+). Patients with baseline PIP and PIP modification congruent with
EEG classification profile («AUC <0.7/PIP+ to +» and «AUC ≥0.7/PIP+ to −» in plain line) were retained for further analysis.

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3.3.2
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Preinspiratory cortical activity
Fourteen patients (70%) exhibited PIPs during natural
breathing (of which six had an AUC ≥0.7) (Figure3b),
which disappeared when wearing MAD in six cases (P+
to −, PIP correction: of which five had an AUC ≥0.7)
(Figure3b) and persisted in the eight remaining cases
(P+ to +, PIP persistence: of which one had an AUC ≥0.7)
(Figure3b). PIP modification was congruent with global
connectivity (AUC <0.7 and P+ to +; n = 7 OR AUC ≥0.7
and P+ to −; n = 5) for 12 of the 14 patients exhibiting
PIP during normal breathing (patients in plain line on
Figure3a) (p = 0,025).
3.3.3
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Comparison of patients with AUC
≥0.7 and AUC <0.7 on EEG classifier
Patients with AUC ≥0.7 (n = 8) and AUC <0.7 (n = 12)
were comparable for age (58 [52–65] vs. 60 [49–66] years,
p = 0.69), sex ratio (2/6 vs. 2/10 female/male ratio, p = 1)
and BMI (28 [26–31] vs. 26 [24–28] kg/m2, p = 0.38).
Patients with AUC ≥0.7 had higher dyspnea VAS- 2 tran-
sitional score (49 [9%–75%]) than patients with AUC <0.7
(11 [0%–35%]; p = 0.03). We also observed higher changes
in Peak (26 [19%–41%] vs. 10 [0%–28%]; p = 0.03) and Peak/
TTP (25 [18%–53%] vs. 3 [−12% to 14%]; p = 0.002) than pa-
tients with AUC <0.7 (Figure4).
3.3.4
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Sensitivity analysis based on PIP and
EEG classifier congruence
The comparison between five patients congruently show-
ing PIP correction while breathing with MAD and an
AUC ≥0.7 (among the 8 AUC ≥0.7 patients, Figure3b)
and seven patients congruently showing PIP persistence
while breathing with MAD and an AUC <0.7 (among
the 12 AUC <0.7 patients, Figure3b). The comparison of
natural breathing and breathing when wearing the MAD
showed significantly higher changes regarding Peak/TTP
(20 [15%–39%] vs. −3 [−13% to 9%] change, p = 0.005)
and dyspnea VAS- 2 transitional score (72 [20%–80%] vs.
4 [0%–34%], p = 0.034) for the “AUC ≥0.7 and PIP correc-
tion” group (Figure5).
4
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DISCUSSION
In line with our hypothesis, this study shows that patients
with OSA who do not complain from dyspnea at rest and
who report the largest pseudo- relief in response to man-
dibular advancement exhibit concomitant EEG changes
similar to the changes previously reported in response
to dyspnea- relieving interventions, for example after
adjustments of ventilator settings in dyspneic mechani-
cally ventilated critically ill patients (Raux et al., 2019).
This provides a clear mechanistic argument in favor of
FIGURE  Relative change in breathing parameters while wearing mandibular advancement device (MAD) considering
Electroencephalography (EEG) classifier and preinspiratory potential modification. In order to compare the ability of EEG classifier to
identify patients with modification of breathing parameters while wearing MAD, we realized comparison for relative change in breathing
parameters between 8 «area under the curve (AUC) ≥0.7» (in black) versus 12 «AUC <0.7» (in gray) participants. Percentage of change
(% change) was calculated as the relative difference between baseline and while wearing MAD. Peak was the average local maximum of
inspiratory pressure curve; time to peak (TTP) was the average time between inspiratory onset and local maximum of inspiratory pressure
curve; Peak/TTP was the ratio reflecting inspiratory amplitude of pressure and inspiratory time; VAS- 2 was the score on transitional
breathing discomfort scale before and after wearing MAD. Boxplot centered on median, interquartile range, whiskers represent maximum
and minimum values.

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habituation as the explanation of the absence of dyspnea
in spite of abnormal respiratory mechanics OSA patients.
This is also an additional argument for the causative
nature of respiratory- related EEG abnormalities in the
pathogenesis of dyspnea (Decavèle et al.,2023; Georges
etal.,2016; Raux etal.,2019).
4.1
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General notions about the EEG
approaches used
The two EEG approaches that we used to compare the
natural breathing and the MAD breathing differ in their
principle. The EEG classifier based on Riemannian ge-
ometry provides a global cortical connectivity analysis
(i.e. including motor, premotor, somatosensory cortical
areas and deep cortical areas) without specific reference
to breathing. Interpreting an EEG change detected by this
technique as respiratory in origin can only result from a
contextual analysis. In the present case, natural breath-
ing and MAD breathing differed in terms of respiratory
mechanics and breathing comfort, which makes it rea-
sonable to assign the EEG connectivity changes identi-
fied to a respiratory origin. On the other hand, the PIP
approach focuses on time- locked, cortical preparation of
inspiration (Macefield & Gandevia,1991). Thepresence
of PIPs is interpreted as bearing witness to an increased
drive to breathe involving the supplementary motor area
(SMA) (Raux etal.,2007) in addition to the baseline tonic
activity of SMA (Laviolette et al., 2013) and the auto-
matic control originating from the brainstem (Del Negro
et al., 2018). PIPs are generally not observed in healthy
subjects during natural breathing outside voluntary inspi-
ration or speech (Tremoureux, Raux, Ranohavimparany,
etal.,2014). They are therefore considered as the sign of
a cortico- subcortical “cooperation” to maintain ventila-
tion in the presence of a defective automatic breathing
control (Fink,1961), and of respiratory loading in healthy
subjects (Raux etal.,2007) and in patients with respira-
tory disease (Georges et al., 2016; Nguyen et al., 2018;
Tremoureux, Raux, Hudson, et al., 2014). The presence
of PIPs, pointing at activation of the SMA, has been as-
sociated with dyspnea in certain circumstances (Georges
et al., 2016; Hudson et al., 2016; Morawiec et al., 2015;
Raux etal.,2019). Yet dyspnea occurs concomitantly with
the activation of a much larger brain network, involving
projections to the sensory cortex and integration in the
limbic cortex (Farb etal.,2013) including cingulate cor-
tex (Straus etal.,1997), posterior insula (Farb etal.,2013),
and connection between posterior insula and thalamus
(Farb etal.,2013). This should make the EEG classifier ap-
proach sensitive for the detection of dyspnea modulation
FIGURE  Relative change in breathing parameters while wearing mandibular advancement device (MAD) within preinspiratory
potential (PIP)+ patients during rest breathing, considering electroencephalography (EEG) classifier and PIP modification. Patients
exhibiting PIP during rest breathing were classified regarding both EEG classifier performance [area under the curve (AUC) ≥0.7] and
modification of PIP while wearing MAD. In order to compare the ability of EEG classifier to identify patients with modification of breathing
parameters while wearing MAD, we realized comparison for relative change in breathing parameters between 5 «AUC ≥0.7/PIP+ to −» (in
black) versus 7 «AUC <0.7 and PIP+ to +» (in gray) participants. Percentage of change (% change) was calculated as the relative difference
between baseline and while wearing MAD. Peak was the average local maximum of inspiratory pressure curve; time to peak (TTP) was the
average time between inspiratory onset and local maximum of inspiratory pressure curve; Peak/TTP was the ratio reflecting inspiratory
amplitude of pressure and inspiratory time; VAS- 2 was the score on transitional breathing discomfort scale before and after wearing MAD.
Boxplot centered on median, interquartile range, whiskers represent maximum and minimum values.

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(Raux etal.,2019). In our patients, this is supported by
the association of VAS- 2 score with the EEG classifier
performances.
4.2
|
Significance of results
In this series, the detection of PIPs in 14 out of 20 pa-
tients confirms our previous observations in awake OSA
patients (Launois etal.,2015, 2020). The presence of PIP
suggests a wake- related cortical adaptation to the intrinsic
load at UA level, to improve the stabilizing activity of the
pharyngeal dilator muscles and prevent obstructive events
(Launois etal.,2015, 2020). MAD- associated changes in
PIPs and EEG classifier performances were congruent
for 12 of the 14 PIP+ patients (86%) and for 15 patients in
all patients (75%). In the five noncongruent patients, we
observed a PIP modification in spite of an AUC <0.7 in
three patients and an AUC ≥0.7 without PIP modification
in two patients. PIP modification while AUC <0.7 could
be explained by difference of nature between PIP analysis
(amplitude analysis centered premotor cortical area and
time- locked on inspiration onset) (Georges etal., 2016;
Launois etal.,2015; Nguyen etal.,2018; Raux etal.,2007;
Tremoureux, Raux, Hudson, etal.,2014), and EEG classi-
fier (covariance analysis of global connectivity) (Grosselin
etal.,2018; Hudson etal.,2016; Navarro- Sune etal.,2017;
Raux etal.,2019). Therefore, a modification of PIP ampli-
tude solely located around premotor areas could be less
detectable by the classifier approach than low amplitude
changes occurring in several cortical areas. Similarly,
AUC ≥0.7 without PIP modification can be explained by
low decrease of PIP amplitude but significant change in
synchrony of premotor preparation network for inspira-
tion. PIP could thus be the “visible top” of the connectiv-
ity changes induced by MAD. For the sake of consistency,
we performed a sensitivity analysis in patients in whom
the two EEG approaches were congruent. We observed
similar results between this conservative approach and
the main analysis, namely an improvement in breathing
pattern and breathing comfort in patients with AUC ≥0.7.
This suggests that the EEG classifier approach alone is
reliable to detect MAD- associated changes in respiratory
cortical activity. Of note, those of our patients who exhib-
ited congruent EEG changes were those in whom the larg-
est pseudo- relief and the largest changes in respiratory
pattern were observed.
4.3
|
Study limitations
We have included patients treated with MAD for 3 months
or more, but to avoid a potential “residual” effect of
MAD, patients were instructed to stop their MAD treat-
ment 10 days before the evaluation. We showed a similar
prevalence of PIP than in the study of Launois etal which
included non- treated patients (Launois etal.,2015). Of
note, MAD is a symptomatic and not a curative treat-
ment. Consequently, while awake when the patient is
not wearing the MAD, the mechanical properties of their
upper airways are not improved and this may induce a
respiratory- related cortical activity in the form of a PIP.
We recognize that a longitudinal evaluation of the effect of
a MAD treatment on cortical activity and “pseudo- relief”
constitute a perspective of this work.
We acknowledge that the absence of a control group
implies a conservative interpretation of the results, how-
ever we are confident that our results support a relation be-
tween upper airway mechanics, breathing sensations and
brain connectivity in patients with obstructive sleep apnea
syndrome (OSAS). The present study was designed on the
basis of two previous studies which had included controls.
The first study showed that the prevalence of PPI was sig-
nificantly higher in patients with OSAS (60% in severe
OSAS and 30% in mild to moderate), than in the control
group (less than 10%) (p = 0.0336) (Launois et al., 2015).
The second study showed that only patients with OSA
showed an improvement in respiratory comfort when
wearing a MAD while awake, and that this improvement
was related to the severity of the abnormalities in upper
airway mechanics. (Attali etal., 2019). We acknowledge
that insufficient technical sensitivity could explain the im-
perfect homogeneity of our observations among patients.
This could also be due to undetected phenotypic hetero-
geneity among the participants to our study especially re-
garding age which is positively related to OSAS prevalence
(Bixler etal.,1998). The choice to exclude patients with a
BMI superior to 35 Kg/m2 was made to be consistent with
previous studies (Attali etal.,2019; Launois etal.,2015).
We also acknowledge that further work is needed to better
characterize the brain changes associated with MAD in pa-
tients with OSA of which the EEG is only a partial reflec-
tion. For example, functional resonance imaging would
be necessary to determine whether the pseudo- relief ob-
served in our patient only proceeds from the mechanical
improvement- related suppression of the compensatory
cortical activation (as suggested by the experimental study
of MAD in inspiratory loading by Hashimoto etal. (2006),
or if it also involves the activation of the specific dyspnea-
relief network described by Peiffer etal. (2008). Finally,
although our study does bring a mechanistic argument for
habituation as the explanation of the absence of dyspneic
complaints in patients with OSA, it does not elucidate the
mechanisms of this habituation. It would be interesting
to confront the EEG responses to MAD to the alterations
in somatosensory processing of respiratory stimuli that

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VALENTIN etal.
exists in OSA patients (Donzel- Raynaud etal.,2009) and
that could contribute to blunting respiratory sensations.
5
|
CONCLUSIONS AND
PERSPECTIVES
There is emerging evidence that inspiratory loading is
concurrent not only with respiratory- related cortical ac-
tivation, but also with impaired cognitive performances
(Taytard etal.,2022). Interferences between cognition and
respiratory- related cortical activity has also been described
in the absence of dyspnea in patients with congenital central
alveolar hypoventilation (CCAH) (Sharman et al., 2014;
Taytard etal.,2023) who are known to rely on their cer-
ebral cortex to maintain ventilation during wakefulness in
spite of a defective breathing automaticity (Tremoureux,
Raux, Hudson, et al., 2014). Respiratory- related cortical
activation in patients with OSA could contribute to OSAS-
associated impairment of cognition (Jordan et al., 2014)
and of other centrally modulated functions such a balance
and gait (Clavel etal.,2020; Degache etal.,2016). In the
present study not only do we confirm that respiratory-
related cortical activity is a reality in OSA patients, but we
also show that this activity can be suppressed by as simple
a mean as MAD. Therefore, our study justifies to assess the
immediate cognitive effects of MAD (or any other means
to suppress respiratory- related cortical activity) in OSA, in
addition to the more classically studied cognitive effects of
the long- term treatment of OSA.
AUTHOR CONTRIBUTIONS
RV, MCN, OJ, MD and VA contributed to design and
conception of the work, acquisition, analysis or inter-
pretation of data, NW, IA and TS contributed to design
of the work, analysis and interpretation of the data. All
authors contributed to drafting and revisiting of the
manuscript. All authors approved final version of the
manuscript and all persons who qualify as author are
listed.
ACKNOWLEDGMENTS
The authors are grateful to Dr jean Baptiste Kerbrat,
Dr Deborah Fellous, Dr David Clerigues- Bosch, mem-
ber of AP- HP, Groupe Hospitalier Universitaire APHP-
Sorbonne Université, Hôpital Pitié- Salpêtrière, Service
de Stomatologie et Chirurgie maxilla- Faciale for the help
with patient recruitment.
FUNDING INFORMATION
VA is the recipient of a grant “poste d'accueil APHP/Arts
et Métiers ParisTech”, Délégation à la Recherche Clinique
et à l'Innovation (DRCI), Assistance Publique Hôpitaux de
Paris (APHP). RV was supported by a grant « Inter Carnot
», Institut Carnot for his PhD doctorate.
CONFLICT OF INTEREST STATEMENT
RV, MCN, NW, OJ declared no link of interest. MD re-
ported no link of interest related to the study. Outside the
submitted work he reported congress registration fees
from ISIS Medical. IA, reported no link of interest related
to the study. Outside the submitted work she took part in
an advisory board of IDORSIA in 2020. TS reported no
link of interest related to the study. Outside the submitted
work he reported personal fees for consulting and teach-
ing activities from ADEP Assistance, AstraZeneca France,
Chiesi France, KPL consulting, Lungpacer Inc., OSO- AI,
TEVA France, Vitalaire, all outside the submitted work.
VA had no link of interest related to the study. Outside the
study, she took part in an advisory board of BIOPROJET
in 2021.
DATA AVAILABILITY STATEMENT
All original data from which graphical and/or tabular
summary data is generated is archived and fully available
to The Journal upon reasonable request.
ETHICS STATEMENT
This study was conducted after legal and ethical ap-
proval by the Comité de Protection des Personnes Ile- de-
France VI – Pitié- Salpêtrière (ID RCB: 2013- A00158- 37).
All methods were conducted in strict adherence to the
relevant guidelines and the Code of Ethics of the World
Medical Association (Declaration of Helsinki). Prior to
participation, the study subjects provided written in-
formed consent.
ORCID
Rémi Valentin https://orcid.org/0000-0001-8192-6048
Valérie Attali https://orcid.org/0000-0001-5444-9223
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How to cite this article: Valentin, R., Niérat,
M.-C., Wattiez, N., Jacq, O., Decavèle, M., Arnulf,
I., Similowski, T., & Attali, V. (2024).
Neurophysiological basis of respiratory discomfort
improvement by mandibular advancement in
awake OSA patients. Physiological Reports, 12,
e15951. https://doi.org/10.14814/phy2.15951