Sanne Floor Campfens
email: s.f.campfens@student.utwente.nl

Maria Papaiordanidou

DEMAR David Guiraud

An activation model of motor response and H-reflex under FES

In this work a model is presented that can improve the estimation of muscle activation under electrical stimulation. The model includes not only the motor recruitment but also the H-reflex recruitment, which is, at the lower stimulation levels, responsible for a larger exerted force than expected based on only motor recruitment. In the model it is assumed that recruitment curves are sigmoid shapes, that there is no difference between motor units and no specific recruitment order. The model is fitted to the measured recruitment curves of two healthy volunteers and shows good fits, with R 2 values above or around 0.95. The next goal is to use this improved activation model in combination with a force estimating muscle model in order to enhance the accuracy of the force estimation

Introduction

Functional electrical stimulation (FES) can provide a mean to restore human functions in various ways; pacemakers, cochlear implants and deep brain stimulation are just some examples. When the descending paths in motor control are lost, FES can provide a way to restore movement with the use of the bodies own actuators: the muscles. Given the highly complex and nonlinear nature of muscles, models have been developed to improve the performance of FES systems. Structure based models can predict the behaviour of the muscles and limbs as well as give meaningful parameters regarding the muscles of interest [START_REF] Makssoud | Mathematical muscle model for functional electrical stimulation control strategies[END_REF]. This model consists of several blocks representing different aspects of the stimulation: the activation, the mechanical behaviour and geometrical properties [START_REF] Makssoud | Mathematical muscle model for functional electrical stimulation control strategies[END_REF]. Control of the exerted force of a muscle under FES is often performed based on recruitment of increasing numbers of motor units, either rate coding is also possible but this is included in fewer models [START_REF] Bobet | Can muscle models improve FESassisted walking after spinal cord injury?[END_REF]. An accurate recruitment function is thus needed in the activation block of a structure based model. At this point one important phenomenon is not taken into account in the estimation of motor unit recruitment under FES: the presence of the Hoffmann reflex (H-reflex).

The H-reflex is present at the lower stimulation intensities and produces a higher force than what would be expected based on the motor response. It makes the estimation of exerted force at the low stimulation intensities inaccurate and does not represent what is actually happening. This H-reflex also prevents from accurately identifying the recruitment curves. This paper proposes a model for motor unit recruitment which does take into account the H-reflex and uses the EMG signal for the identification of both contributions: the H-reflex and the direct motor activation. This activation model can thus be used in the muscle model presented in [START_REF] Makssoud | Mathematical muscle model for functional electrical stimulation control strategies[END_REF]. Preliminary experiments show that this model enables to explain accurately the activation level measured and thus, in comparison with the conventional activation models, is able to predict more accurately the activation of the muscle induced by both phenomena.

Activation model

The activation model consists of separate functions to describe the motor recruitment and the H-reflex recruitment. It also describes the extinction of the Hreflex contribution with increasing motor response.

Motor and reflex recruitment

It is known that motor recruitment is well described by a sigmoid function. This accounts both for the relation between activation and stimulation amplitude as for the relation between activation and pulse width [START_REF] Devanne | Inputoutput properties and gain changes in the human corticospinal pathway[END_REF][START_REF] Crago | Modulation of muscle force by recruitment during intramuscular stimulation[END_REF]. Recently it has been shown that a sigmoid shape is also the best fit for the ascending part of the H-reflex recruitment curve [START_REF] Klimstra | A sigmoid function is the best fit for the ascending limb of the Hoffmann reflex recruitment curve[END_REF]. The function to describe the sigmoid recruitment function has the following general shape:

( ) [ ] s c c c A - ⋅ + = 3 2 1 exp 1 (2.1)
In this function A is the number of recruited motor units, s the stimulation input (amplitude or pulse width) and c 1 , c 2 and c 3 constants that alter the pla-teau, steepness of the sigmoid and the stimulation needed for 50% recruitment respectively. The descending part of the H-reflex recruitment curve is more complicated. The simplest explanation for the extinction of the H-reflex is that the reflexive activity is blocked by collisions with the antidromic action potentials induced in the motor neurons by the stimulation. This means that a function to describe the reflexive activation of motor units also requires the motor recruitment as an input.

Regarding the extinction of the H-reflex several assumptions have to be made in order to estimate the collisions: 1) There is a homogeneous motor unit pool. 2) A motor unit has an equal chance of being recruited in either the motor response or the H-reflex.

3) Motor recruitment and H-reflex recruitment are mutually independent. Under these assumptions the expected portion of the motor units recruited in the H-reflex that collides with the motor response, can be calculated. With M and H the normalised number of motor units in the motor response and H-reflex respectively, the expected overlap between the motor recruitment and the H-reflex recruitment (COL) is given by:

COL H M = ⋅ (2.
2) The number of motor units activated in the H-reflex (H*) is than given by: ( )

* 1 H H COL H M = - = - (2.3)

Structure of the activation model

The form in which the motor recruitment and H-reflex recruitment can be used in a model is given in Figure 1 Figure 1 Structure of the activation model.

From the stimulation parameters (amplitude or pulse width) the motor response recruitment (M) and the Hreflex recruitment (H) are calculated. From this the portion of H that actually results in muscle contraction is calculated (H*). H* reaches the muscle slightly later than the direct motor response does, so a time delay is added. Finally the both pathways are added giving the activation (α) of the muscle as a result of the stimulation.

In the blocks the functions of equations (2.1) and (2.3) are implemented, the formulas to calculate the M and H* become:

( )

2 3 1 1 exp M cm cm s =   + ⋅ -   (2.4) ( ) ( ) 1 2 3 * 1 1 exp ch H M ch ch s = ⋅ -   + ⋅ -   (2.5)
With this model the activation that is used in the mechanical part of the muscle model will contain both the motor response activation and the H-reflex activation. Identification of the parameters of the recruitment functions can be achieved based on the amplitudes of the M-wave and the H-wave in the EMG signal.

3 Model identification

Method

Recruitment curves were determined for two subjects to test the proposed activation model. Subjects were seated on a chair with their right foot fixed on a calibrated dynamometric pedal (Captels, St-Mathieu de Treviers, France). Transcutaneous stimulation was applied to the tibial nerve by bipolar electrodes. A cathode electrode was placed in the popliteal fossa, a 50 cm 2 anode electrode was placed on the knee at the patella. Stimulation was delivered in the form of rectangular monophasic pulses with durations of 200 µs by a constant current stimulator (DS7AH, Digitimer Ltd., Hertfordshire, UK). For EMG measurements bipolar surface Ag/AgClelectrodes were placed on the muscle belly of the medial gastrocnemius. Signal acquisition of the force and differential EMG signal was done with a sample frequency of 2048 Hz by the Biopac MP100 (Biopac Systems, Inc., Santa Barbara, CA). Single pulses were delivered with increasing amplitude in steps of 10 mA to identify the motor threshold and the maximum recruitment. From the maximum recruitment, stimulation amplitude was again reduced; this time in steps of 2 mA to get a higher resolution in the recruitment curve. The procedure was performed once.

From the EMG data the M-waves and H-waves were identified for all stimulation amplitudes. The amplitudes of both M-waves and H-waves were determined as the peak to peak amplitudes. All amplitudes were normalized to the maximal M-wave amplitude. Stimulation amplitude was normalised to the lowest stimulation amplitude needed to induce a maximal Mwave. For each simulation the peak force of the twitch was determined.

Using the MATLAB curve fitting toolbox the recruitment functions for motor response activation (M) and H-reflex activation (H*) are fitted to the measured Mwave and H-wave amplitudes. Normalised wave amplitude and normalised activation are assumed to be interchangeable. Goodness of fit is assessed based on the fraction variance accounted for (R 2 ).

Results

The recruitment curves of the motor response had the typical sigmoid shape for both subjects. The H-reflex recruitment curves showed the expected increase at the lower stimulation amplitudes, followed by a decrease when the motor response is getting larger.

Peak force increased with increasing stimulation amplitude. At the low stimulation amplitudes the force increases faster than what would be expected by looking at the motor recruitment curve. At these levels the H-reflex also contributes to the exerted force. This can be seen in Figure 2 The activation model was fitted to the data. The data and fitted recruitment curves are shown in Figure 3 As can be seen in the plot, the fitted function follows the measured data closely. This is also visible in the high R 2 values: The average R 2 value for the 4 fitted recruitment curves (motor recruitment and H-reflex recruitment for each subject) is 0.9731. For the motor response recruitment curves the average R 2 is 0.9916.

For the H-reflex recruitment curves the average R 2 is 0.9545.

Discussion

The aim of this study was to develop an activation model which can be used in combination with a struc-ture based muscle model. Including not only the motor response in the activation but also the H-reflex is important because the H-reflex is responsible for most of the force at the lowest stimulation intensities. Not including the H-reflex in the activation will result in an underestimation of the exerted force at those stimulation intensities.

The model fits that are made using the proposed model follow the measured recruitment curves closely. Something which is also reflected in the high fraction variance accounted for in both the motor response recruitment curves and the H-reflex recruitment curves. From these fits it can be concluded that the proposed activation model can be used to give a better estimation of the muscle activation induced by electrical stimulation. This activation model is based on some assumptions regarding the recruitment order and reason of the extinction of the H-reflex. Physiologically seen these assumptions may not be completely valid. But regarding the quality of the current model fits and the increase in model complexity that a more physiological recruitment order would mean, the assumptions made here can be justified. Future work includes the testing of the proposed activation model in combination with the complete muscle model and comparing the force predictions with the new and the old activation model. The assumption is then that the new model should give a better force estimation especially at the low stimulation intensities when the H-reflex has the largest contribution to the exerted force.

Figure 2

 2 Figure2Normalised data of one of the subjects: peak force and wave amplitude. In the lower graph the black dots represent the H-wave. The peak force shows a strong increase just above the motor threshold.

Figure 3

 3 Figure 3 Recruitment curves fitted to the measured data of one of the subjects. The black line and dots represent the H-reflex.

5

Literature


Lucien Schwab

Pierre-Etienne Allain

Louise Banniard

Nicolas Mauran

Denis Lagrange

Alexandre Fafin

Marc Gély

Maxime Hermouet

Guillaume Jourdan

Sebastien Hentz

30-MHz Optomechanical Vibrating Sensor: Towards High Bandwidth / Ultrasensitive Measurements

niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

130-MHz OPTOMECHANICAL VIBRATING SENSOR: TOWARDS HIGH BANDWIDTH / ULTRASENSITIVE MEASUREMENTS

Lucien Schwab 1 , Pierre-Etienne Allain 2 , Louise Banniard 3 , Nicolas Mauran 1 , Denis Lagrange 1 , Alexandre Fafin 3 , Marc Gely 3 , Maxime Hermouet 3 , Guillaume Jourdan 3 , Sébastien Hentz 3 , Ivan Favero 2 and Bernard Legrand 1 1 CNRS, University of Toulouse, LAAS-CNRS, Toulouse, FRANCE 2 Matériaux et Phénomènes Quantiques, Univ. Paris Diderot, CNRS UMR 7162, Paris, FRANCE 3 Univ. Grenoble Alpes, CEA, LETI, 38000 Grenoble, FRANCE [START_REF] Brugger | Micromachined atomic force microprobe with integrated capacitive read-out[END_REF][START_REF] Algre | MEMS Ring Resonators for Laserless AFM With Sub-nanoNewton Force Resolution[END_REF]. As fabrication technological processes developed, sensors' dimensions were shrunk in NEMS, looking for a twofold advantage: higher sensitivity and higher bandwidth, enabled by scaling laws and frequency increase. However, displacement transduction schemes usually at play in MEMS, like the capacitive one, are generally not applicable to NEMS [START_REF] Roukes | Nanoelectromechanical systems face the future[END_REF]. Thanks to different integrated transduction means, NEMS have however proven their effectiveness in many sensing fields providing for example, 43 MHz cantilevers, piezoresistive nanowire gauges detected, for gas chromatography [START_REF] Arcamone | VLSI silicon multi-gas analyzer coupling gas chromatography and NEMS detectors[END_REF] and chemisorptive mass sensing with piezoresistive metal film detection of a 127 MHz cantilever resonance [START_REF] Mo Li | Ultra-sensitive NEMS-based cantilevers for sensing, scanned probe and very high-frequency applications[END_REF].

To reach mechanical frequencies greater than the MHz, another path followed is to exploit bulk or inplane modes instead of shrinking dimensions of cantilever beams resonating on flexural modes. This idea was applied for ring-shaped force sensors [START_REF] Legrand | Multi-MHz micro-electro-mechanical sensors for atomic force microscopy[END_REF], achieving a 13 MHz breathing mode frequency record in AFM probes with a novel capacitive detection scheme based on microwave reflectometry, allowing high-bandwidth measurements without compromises on the femtometer resolution.

To go further, one needs to increase the frequency even higher and seek for higher displacement sensitivity to keep a reasonable signal-to-noise ratio due to the decrease in amplitude when the mechanical frequency raises. Consequently, force sensors vibrating above 100 MHz with picometer amplitudes imply once more drastic constraints on usual integrated electromechanical transduction schemes and locks are met in terms of measurement resolution [START_REF] Ekinci | Electromechanical Transducers at the Nanoscale: Actuation and Sensing of Motion in Nanoelectromechanical Systems (NEMS)[END_REF], calling for a change in transduction mean.

Concurrently, quantum experiments at mesoscale [START_REF] Rivière | Optomechanical sideband cooling of a micromechanical oscillator close to the quantum ground state[END_REF] pushed understanding and engineering capability of optomechanical transduction at play in whispering gallery mode (WGM) resonators. This growing interest lead to III-V material integrated sensors resonating above 100 MHz with ultimate motion sensitivity down to 10 -17 m.Hz -0.5 [START_REF] Ding | High Frequency GaAs Nano-Optomechanical Disk Resonator[END_REF]. This technology was successfully applied to scanning probe technique [START_REF] Liu | Wide cantilever stiffness range cavity optomechanical sensors for atomic force microscopy[END_REF] and transferred to silicon photonics and very large scale integration facility in the last years [START_REF] Hermouet | Ultra sensitive optomechanical microdisk resonators with very large scale integration process[END_REF].

To address the need in resonating devices for physical sensing applications with unprecedented performances, namely higher frequency, bandwidth and sensitivity, we present the design, fabrication and first characterization of a fully integrated, optically sensed, resonating sensor based on cavity optomechanics fabricated using a VLSI silicon photonics platform. The 130 MHz-frequency resonator presented hereafter offers an exquisite detection limit of 4.10 -16 m.Hz -0.5 and a measurement bandwidth of 130 kHz, being ruled by the relaxation time.

OPTOMECHANICAL SENSOR DESIGN

The sensor consists in a 20 µm diameter ring WGM optical cavity (Fig. 1a) standing in air on a 1-µm-high pedestal with three anchoring spokes. An optical waveguide evanescently couples the 1.55 μm laser light in and out the optical mode. The ring is designed from the mechanical point of view to reach a 134 MHz first order breathing mode that is simulated by finite element method (FEM) with a gom=7. 8 10 18 Hz/m optomechanical factor. For applications in mass or force sensing, one needs to seek the location of the lowest effective mass or stiffness of the resonator. This is reached at a location of the resonance mode shape where the vibration amplitude is maximal (See Fig. 1c). For the device presented in this study, effective mass and stiffness are calculated by FEM to be 6.10 -14 kg and 40 000 N/m respectively at a point of maximum of vibration.

Principle of operation of the optomechanical device is as follows. Mechanical breathing motion of the resonator during its vibration modulates the cavity optical length and thus its optical transmission. This benefits from sensitivity enhancement by the WGM optical quality factor Qopt=60 000. Gap distance between the coupling waveguide and the ring cavity and dimensions of the sensor were designed to maximize the contrast times optical quality factor product.

FABRICATION

The ring sensor is fabricated using VLSI silicon photonics SOI technology on a 200 mm wafer. First, a deep UV lithography step defines the grating couplers enabling top-injection and collection of laser light, respectively in and out of the chip. Then a variable shape beam lithography step defines the ring sensor structure. The patterned silicon structural layer (SiTop) is 220 nm thick on top of a 1-µm thick buried oxide layer (BOx). The BOx layer is then critically timed-etched with vapor-HF in order to form the pedestal on which the sensor is finally standing on. Main steps of the fabrication process and SEM picture of the resulting sensor are depicted in figure 2.

Table 1: Main characteristics of various MNEMS resonating sensors

Ring sensor [START_REF] Legrand | Multi-MHz micro-electro-mechanical sensors for atomic force microscopy[END_REF] Simple-clamped beam [START_REF] Ouerghi | Polysilicon Nanowire NEMS fabricated at low temperature for above IC NEMS mass sensing applications[END_REF] Simple-clamped beam [

CHARACTERIZATION SET-UP

Experimental characterizations are performed in air. A lock-in amplifier (LIA) allows frequency characterization of the sensor (Fig. 3). Laser light is topinjected with fibers in the silicon chip via grating couplers optimized for optical C-band operation. Polarization controllers ensure that light is injected in the ring matching coupling polarization. A 1500-1600 nm tunable laser allows to match optical modes of the ring cavity. Transmitted light, modulated by the resonator motion, is then collected by a 1.2 GHz bandwidth photodiode. Because of thermo-optic effect, the laser wavelength is blue-detuned which could enhance resonance through optical back-action. Injected power was thus limited to 1mW to prevent from this enhancement effect.

RESULTS & DISCUSSION

Thermomechanical (Brownian) motion is resolved (Fig. 4), at fm=130.6 MHz with a 3% difference with simulated breathing mode frequency, and Qm=1 000 in air. Air fluid dissipation hinders the intrinsic mechanical Q-factor that would be obtained in vacuum, expected to be Qm_vac=10 000 from numerical calculations. Brownian motion detection, routinely enabled by optomechanical transduction, is calibrated in two different ways. First, we use the equipartition theorem (See "Thermomechanical noise displacement" formula in Table 1) which yields a 7.10 -16 m.Hz -0.5 displacement noise density at the mechanical resonance frequency. The measured value, calibrated from the parameters of the detection chain, gives a 12.10 -16 m.Hz -0.5 value. The small discrepancy is within the uncertainty of the detection chain parameters and gains. Using this latter calibration value, the limit of detection of the measurement set-up is estimated to be below 4.10 -16 m.Hz -0.5 . By assuming an operation of the device in driven mode, a 63 dB SNR could be attained for a vibration amplitude of 1 pm, which is better than for other devices in the same frequency range as presented in Table 1. Thanks to its high mechanical resonance frequency, our optomechanical sensor reaches a bandwidth of 130 kHz in air, ruled by the f/Qm ratio, still competitive with regards to other resonating sensors (Table 1).

CONCLUSION

An optomechanical ring resonator, mechanical frequency being up to 130 MHz, is fabricated using VLSI silicon photonics technology and characterized with an exquisite 4.10 -16 m.Hz -0.5 detection limit, allowing clear resolution of the thermomechanical motion. Those exquisite performances put high-bandwidth sensing along with femtometer displacement resolution within grasp.

Figure 1 :

 1 Figure 1: (a) Device schematic highlighting the main dimensions of the tested sensor structure: Rext = 10 μm, Rped = 1.5 μm, Wring = 500 nm, Wspk = 100 nm, Wtaper = 475 nm and dgap = 300 nm. (b) Optical and (c) mechanical finite element modeling of the optomechanical sensor, consisting in a 20 µm diameter silicon ring with 3 spokes anchoring to a 1-µm high pedestal, allowing mechanical motion. Electrical field amplitude and displacement resonance mode are respectively simulated. The optical and mechanical resonance wavelength and frequency are λ=1.55 μm and fm_simulated=134 MHz respectively, scale bars: 5 µm.

Figure 2 :

 2 Figure 2: (a) Main fabrication steps of the optomechanical sensor. The silicon layer SiTop in which the optomechanical sensor is patterned is 220 nm thick. The 1-µm thick buried oxide layer (Box) is then etched to let only a 3 µm diameter pedestal for the sensor to stand on. (b) Colorized SEM image of the resulting optomechanical sensor featuring the coupling waveguide (plain red) and the optical cavity (dotted red). Scale bar: 20 µm.

Figure 3 :

 3 Figure 3: (a) Set-up used for experimental characterisations. Laser light evanescently couples to the device. Laser light exiting the sensor then carries the mechanical resonance motion. Sensing signal from the photodiode is processed by a lock-in amplifier acting as a spectrum analyzer. (b)Table of the main equipment used to acquire the measurement data displayed in this manuscript.

Figure 4 :

 4 Figure 4: (Blue) Brownian motion of the optomechanical resonator measured at 1-Hz bandwidth. Resonance frequency is fm=130.6 MHz. The sensor's quality factor attains Qm=1000 in air. The signal is calibrated via detection chain. (Red) Brownian motion theory given by the equipartition theorem with same noise floor. The 1.7 factor between theoretical and measured noise amplitude is within detection parameters uncertainty.

ACKNOWLEDGEMENTS

This work was supported by the French National Research Agency (ANR) under the research project OLYMPIA, grant ANR-14-CE26-0019 and by the Délégation Générale de l'Armement (DGA).

CONTACT

Lucien Schwab, lschwab@laas.fr


Xavier Benarous
email: xavierbenarous@gmail.com

Cosmin Iancu

Jean-Marc Guilé
email: guile.jean-marc@chu-amiens.fr

Angèle Consoli
email: 5angele.consoli@aphp.fr

David Cohen
email: david.cohen@psl.aphp.fr

Missing the forest for the trees? A high rate of motor and language impairments in Disruptive Mood Dysregulation Disorder in a chart review of inpatient adolescents

Keywords: disruptive mood dysregulation disorder, chronic irritability, hospitalization, language disorder, communication disorder, learning disabilities, motor disorder, developmental coordination disorder, cognitive impairments, depressive disorder

INTRODUCTION:

Youths with severe and persistent irritability have a particularly high rate of school failures and learning difficulties. The aim of this study was to determine whether inpatient adolescents with Disruptive Mood Dysregulation Disorder (DMDD) have more motor and/or language impairments compared to patients with other psychiatric disorders.

METHODS:

A retrospective chart review of all consecutive cases admitted in two adolescent inpatient units between January 2017 and December 2018 was conducted (N=191). All patients received multi-disciplinary clinical and developmental assessments. For a subtest of subjects, additional standardized tests were used to document motor and language impairments. In this clinical chart 53 adolescents with a DMDD (mean age 13.6 ± 1.5, min 12, max 16, 70% males) were compared to patients with a major depressive disorder (MDD, n=64, mean age 15.3 ± 1.6, 52% males) and patients with a non-mood disorder (NMD, n=61, mean age 14.4 ± 1.55, 59% males).

RESULTS: Among inpatients with DMDD, 71% had an associated motor and/or language disorder, with combined forms in around two-thirds of cases. Compared to youths with MDD, participants with DMDD were more likely to have an associated developmental coordination disorder (67% vs. 22%, OR=4.7) and a written language disorder (35% vs. 10%, OR=4.6).

While 31% of inpatients with DMDD had an associated communication/oral language disorder, this rate was not statistically different from those observed in the MDD group (11%, OR=3.2).

The frequencies of motor and language impairments were not statistically different between participants in the DMDD group and in the NMD group.

CONCLUSION:

The high rate of motor and written language disorders found in DMDD patients may partly account for their academic difficulties. Such finding, if confirmed, supports systematic screening of motor and written language impairments in youths with chronic irritability and suggests remediation potential.

INTRODUCTION

1.1.General information about DMDD

The Disruptive Mood Dysregulation Disorder (DMDD) is a childhood-onset psychiatric disorder newly included in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) [START_REF]Diagnostic and Statistical Manual of Mental Disorders, 5th Edition[END_REF]. Youths with DMDD suffer from having a chronically irritable mood associated with repeated temper outbursts disproportionate for the developmental level. While the prevalence of DMDD is around 0.8-3.3% in the general population, it is overrepresented in mental health care services, with rates between 8% and 31% across sites [START_REF] Vidal-Ribas | The Status of Irritability in Psychiatry: A Conceptual and Quantitative Review[END_REF]. Such a discrepancy is not very surprising as irritability, the core symptom of DMDD, is one of the most common reasons caregivers bring youths to outpatient treatment [START_REF] Yeh | Why are we here at the clinic? Parent-child (dis)agreement on referral problems at outpatient treatment entry[END_REF].

1.2.School impairments in DMDD patients

A high level of impairments in school functioning was constantly reported in youths with DMDD in community-based and clinical studies [START_REF] Althoff | Disruptive Mood Dysregulation Disorder at Ages 13-18: Results from the National Comorbidity Survey-Adolescent Supplement[END_REF][START_REF] Copeland | Prevalence, comorbidity, and correlates of DSM-5 proposed disruptive mood dysregulation disorder[END_REF][START_REF] Axelson | Examining the proposed disruptive mood dysregulation disorder diagnosis in children in the Longitudinal Assessment of Manic Symptoms study[END_REF][START_REF] Benarous | Are youths with disruptive mood dysregulation disorder different from youths with major depressive disorder or persistent depressive disorder[END_REF][START_REF] Margulies | Will disruptive mood dysregulation disorder reduce false diagnosis of bipolar disorder in children?[END_REF]. Margulies et al. [START_REF] Margulies | Will disruptive mood dysregulation disorder reduce false diagnosis of bipolar disorder in children?[END_REF] noted that children with DMDD are eight times more likely to report any problem with his/her teachers and nine times more likely to be suspended from school compared to healthy children. Other reports have shown that youths with DMDD have lower academic performance compared to youths with other psychiatric disorders [START_REF] Althoff | Disruptive Mood Dysregulation Disorder at Ages 13-18: Results from the National Comorbidity Survey-Adolescent Supplement[END_REF][START_REF] Copeland | Prevalence, comorbidity, and correlates of DSM-5 proposed disruptive mood dysregulation disorder[END_REF][START_REF] Axelson | Examining the proposed disruptive mood dysregulation disorder diagnosis in children in the Longitudinal Assessment of Manic Symptoms study[END_REF][START_REF] Benarous | Are youths with disruptive mood dysregulation disorder different from youths with major depressive disorder or persistent depressive disorder[END_REF]. The academic difficulties reported by children with DMDD sometimes persist into adulthood. Copeland et al. [START_REF] Copeland | Adult diagnostic and functional outcomes of DSM-5 disruptive mood dysregulation disorder[END_REF] showed that young adults who received a diagnosis of DMDD at age 10 were about twice as likely to fail to receive a high school diploma and to not go to college compared to those with another childhood-onset psychiatric disorder.

Several factors may affect the level of school functioning in youths with DMDD. School problems may be directly related to child's symptoms. For example, irritability and associated behaviors (e.g., reactive aggressive behavior) could affect the child's relationships with teachers and others schoolmates which could result in persisting conflicts within the classroom making it difficult to ensure a secure and supportive learning environment. Other co-occurring factors associated with DMDD could influence academic success in these patients, such as parental psychiatric problems [START_REF] Benarous | Are youths with disruptive mood dysregulation disorder different from youths with major depressive disorder or persistent depressive disorder[END_REF], a high rate of psychosocial adversity and socio-economic difficulties [START_REF] Althoff | Disruptive Mood Dysregulation Disorder at Ages 13-18: Results from the National Comorbidity Survey-Adolescent Supplement[END_REF], or comorbid psychiatric/developmental disorder [START_REF] Copeland | Prevalence, comorbidity, and correlates of DSM-5 proposed disruptive mood dysregulation disorder[END_REF][START_REF] Benarous | Definition and features of depressive disorder in children and adolescents[END_REF]. Among these factors, the cooccurrence of developmental/learning disabilities are particularly worth identifying in these patients as they represent treatable conditions resulting in educational improvement when adequately addressed.

1.3.Learning/developmental difficulties in youths with chronic irritability

Surprisingly, few studies have examined the relationship between DMDD and developmental/learning disorders except for attention deficit disorder [11]. Preliminary evidence for a possible association between DMDD and learning disabilities was gained from case-series [START_REF] Carlson | Rages--what are they and who has them?[END_REF], chart-review studies [START_REF] Benarous | Are youths with disruptive mood dysregulation disorder different from youths with major depressive disorder or persistent depressive disorder[END_REF][START_REF] Tufan | Sociodemographic and Clinical Features of Disruptive Mood Dysregulation Disorder: A Chart Review[END_REF] and epidemiological study [START_REF] Althoff | Disruptive Mood Dysregulation Disorder at Ages 13-18: Results from the National Comorbidity Survey-Adolescent Supplement[END_REF]. In a large cross sectional community-based study conducted in 6,483 adolescents, [START_REF] Althoff | Disruptive Mood Dysregulation Disorder at Ages 13-18: Results from the National Comorbidity Survey-Adolescent Supplement[END_REF] found that parents of adolescents with DMDD symptoms were 1.7 times more likely to report a history of learning difficulties in their child compared to parents of children with an anxiety disorder, a bipolar disorder or an attention deficit disorder. Carlson et al. [START_REF] Carlson | Rages--what are they and who has them?[END_REF] reported that among inpatients those with any rages were 5.5 times more likely to present a learning/language disorder compared to those without (83% vs. 47%). As noted by the authors, the lack of awareness of learning/developmental disabilities in patients with chronic emotional dysregulation may represent a missed opportunity to provide remediation interventions and ultimately to gain clinical improvement.

Previous studies have shown that youths with chronic irritability performed poorer in stop-signal task, a psychological task measuring motor inhibition, compared to children with other psychiatric disorders [START_REF] Hoeksma | Emotion regulation and the dynamics of feelings: a conceptual and methodological framework[END_REF][START_REF] Deveney | Neural recruitment during failed motor inhibition differentiates youths with bipolar disorder and severe mood dysregulation[END_REF]. Whether difficulties in other components of motor skill (e.g., fine motor skill, imitation, visuo-spatial abilities) exist in youths with chronic irritability has never been investigated. Children with poor motor skills may be more likely to experience chronic negative mood, in particular in school, in response to repeated learning difficulties or peer rejection [START_REF] Mammarella | Anxiety and Depression in Children With Nonverbal Learning Disabilities, Reading Disabilities, or Typical Development[END_REF]. However, for children with poor motor skills and depressed mood the exclusion from certain activities involving motor cooperation could result in missed opportunities to refine their emotional regulation strategies in an extra-familial context [START_REF] Xavier | Children's synchrony and rhythmicity in imitation of peers: toward a developmental model of empathy[END_REF].

Motor remediation or interventions enhancing participation with peers could be useful in this context to break the vicious circle of rejection, depressed mood and poor emotional regulation.

Several lines of research suggest that language difficulties are worth investigating in youths with chronic irritability. Child language delays and behavior problems, especially those involving poorly regulated anger, have been found to be associated both in clinical and nonclinical samples [START_REF] Baker | Attention deficit disorder and speech/language disorders[END_REF][START_REF] Cohen | Emotion regulation, language ability, and the stability of preschool children's peer play behavior[END_REF][START_REF] Irwin | The social-emotional development of "late-talking" toddlers[END_REF]. Longitudinal studies have shown direct evidence for relations among growth in language skills, decline in anger reactivity, and increase in self-regulatory strategy use [START_REF] Chow | Does oral language underpin the development of later behavior problems? A longitudinal meta-analysis[END_REF][START_REF] Roben | Longitudinal relations among language skills, anger expression, and regulatory strategies in early childhood[END_REF]. In the same way, several interventions that teach children to use words to deal with frustration or to improve emotional categorization have shown a positive impact on socioemotional competence [START_REF] Izard | Accelerating the development of emotion competence in Head Start children: effects on adaptive and maladaptive behavior[END_REF][START_REF] Ornaghi | Enhancing social cognition by training children in emotion understanding: a primary school study[END_REF].

As reading and writing are involved in almost all learning activities in schools, difficulties in these domains could contribute to the high rate of academic failure observed in youths with DMDD. The emergence of reading and writing skills involves the integrity of several acquired competences in language (e.g., phonological awareness) and motor domains (e.g., visuo-spatial, fine motor skill). It is therefore likely that difficulties in one of these domains could affect reading/writing performances.

1.4.Aims of the study

We used a retrospective chart review to determine the frequencies of motor and/or language developmental difficulties in inpatients with DMDD. Such developmental difficulties were measured in three ways: (i) the frequency of parent-reported delay and/or abnormal development in the domain considered, (ii) the frequency of associated diagnoses of developmental coordination disorder, communication/oral language disorder, and written language disorder and, (iii) the description of the detailed motor and/or language tests performed in a subset of patients prior or during the hospitalization. Inpatient adolescents with DMDD were compared to inpatients with Major Depressive Disorder without DMDD (MDD group) and to inpatients with non-mood disorder without DMDD (NMD, mainly psychotic and severe neurodevelopmental disorders). We hypothesized that the rate of developmental motor and language disorders would be higher in the DMDD group compared to the MDD group. No apriori-hypothesis was made for the difference between the DMDD and the NMD groups. We expected that DMDD youths would show impairments in multiple developmental domains, i.e., many of these patients having a combined form of developmental impairments in line with the observation provided by Carlson et al. [START_REF] Carlson | Rages--what are they and who has them?[END_REF]. Using an exploratory approach, the difficulties in several components of motor and language abilities were examined in the subsample of DMDD patients who had standardized tests:

-For motor development we paid particular attention to perceptive and motor abilities involved in the development of children's socio-emotional competence: motor imitation involved in contingent early-interaction with caregivers and later with peers [START_REF] Decety | A social neuroscience perspective on clinical empathy[END_REF][START_REF] Nadel-Brulfert | The Social Function of Reciprocal Imitation in 2-Year-Old Peers[END_REF]; fine motor ability [START_REF] Mendes | Fine motor ability and psychiatric disorders in youth[END_REF], and visuo-spatial skill involved in cognitive perspective-taking [START_REF] Xavier | Children's synchrony and rhythmicity in imitation of peers: toward a developmental model of empathy[END_REF].

-For oral language development, we examined specifically the semantic component of spoken language (vocabulary understanding), considering the relation between lexical enrichment and emotional regulation competencies reported [START_REF] Vallotton | Use Your Words: The Role of Language in the Development of Toddlers' Self-Regulation[END_REF][START_REF] Cole | The role of language in the development of emotion regulation[END_REF]. While other aspects of language typically affected in communication/oral language disorder such as phonological awareness and syntax were also examined, the pragmatic component of language was not.

-For written language, we in particular examined the speed and the quality of the reading and the writing, regarded to be strong predictors for school performances [30,[START_REF] Launay | Evaléo 6-15: batterie d'évaluation du langag écrit et oral[END_REF].

METHODS

2.1.Study design and setting

Data from the medical records of all patients hospitalized between January 1, 2017 to December 31, 2018 in the two adolescent units of the child and adolescent psychiatric department of a tertiary university care center were extracted (N = 191). Two researchers (a psychologist and a resident in psychiatry) used a 72-item computerized questionnaire to extract relevant information based on all clinical and paramedical charts available. All data was crosschecked by the senior psychiatrist who directly cared for each adolescent. The inter-rater reliability of the chart review instrument based on the analysis of ten randomly selected files was good (κ = .80). The data collected encompassed (i) socio-demographic characteristics, (ii) clinical features and symptom severity, (iii) developmental history and associated medical conditions, (iv) school functioning and psychosocial factors. The levels of functioning and symptom severity were assessed using questionnaires routinely used in the units: the Children-Global Assessment of Functioning scale (C-GAF) [START_REF] Jones | A brief mental health outcome scale-reliability and validity of the Global Assessment of Functioning (GAF)[END_REF], the Clinical Global Impressions-Severity scale (CGI-S), and the CGI-Improvement Scale (CGI-I) [START_REF] Busner | The clinical global impressions scale: applying a research tool in clinical practice[END_REF]. The study followed general recommendations for retrospective chart review [START_REF] Gearing | A Methodology for Conducting Retrospective Chart Review Research in Child and Adolescent Psychiatry[END_REF]. This project was designated as IRB exempt due to its retrospective design, patient de-identification, and the use of routine questionnaires.

2.2.Participants

We used a two-step procedure for the diagnostic of DMDD. Firstly, we carefully reviewed all charts searching for symptoms of chronic irritability (i.e., persistent irritable mood and/or anger feeling and/or impulsive/reactive/hostile aggressive behavior, and/or temper tantrums, for at least 12 months). We also examined the list of patients who required seclusion and/or intra-muscular treatment during the study period. Secondly, clinical data of inpatient adolescents positively screened were abstracted using a specific instrument based on the criteria for the temper dysregulation disorder with dysphoria, a research entity developed by the DSM-5 Task Force prior to the publication of the final DMDD criteria [START_REF]Justification for temper dysregulation disorder with dysphoria[END_REF]. Each item was endorsed as present or absent or unknown. The final diagnostic was endorsed only if participants matched all diagnostic criteria, including duration criteria, cross-domain impairment, and age of onset (Table S1). The psychometric properties of this ad-hoc diagnostic section for DMDD were explored in another sample of 12 to 15 year-old outpatients (internal validity Chronbach's α=0.90, test-retest reliability κ =.87) [36]. All other diagnoses were based on discharge diagnoses and follow the DSM-5 formulation [START_REF]Diagnostic and Statistical Manual of Mental Disorders, 5th Edition[END_REF].

[Insert Figure 1 about here]

Measurements

All patients hospitalized in the adolescent units received a multidimensional psychiatric and developmental assessment based on repeated family interviews, clinical interviews and observations of participants in various contexts, including in the hospital school center.

Standardized assessments performed prior to the hospitalization were systematically collected and reread.

In-depth motor assessment encompassed four standardized tests ascertaining different components of motor activity:

-The Movement Assessment Battery for Children 2nd edition (MABC-2) is a comprehensive measurement of motor skills used for the detection of movement difficulty in children [START_REF] Henderson | MovementAssessment BatteryforChildren, 2ndEdn[END_REF] or as a diagnostic tool for developmental coordination disorder [START_REF] Wagner | Factorial validity of the Movement Assessment Battery for Children-2 (age band 2)[END_REF]. The test comprises 11 items grouped in 3 subtests: Manual Dexterity, Aiming and Catching, and Balance. The raw scores are converted to percentile rank: a score between the 6th and 15th percentile represents a risk of having a movement difficulty and a score at or below the 5th percentile represents significant movement difficulty. Psychometric properties are good and MABC-2 AB3 version was standardized for youths between 3-16 years.

-The Developmental Test of Visual Perception, 2nd edition (DTVP-2) is a comprehensive visual-perceptual evaluation [START_REF] Hammill | Developmental Test of Visual Perception, Second Edition (DTVP-2)[END_REF] which encompasses eight subtests that measure different visual perceptual and visual-motor parameters. The raw scores are calculated as the sum of each subtest, which can be converted into percentiles. Sums of standard scores can be converted to two composite quotients: the motor-reduced visual perception quotient (visual-cognitive aspect) and the visual-motor integration quotient (visual-motor aspect). Psychometrics properties of the DTPV-2 are good [START_REF] Hammill | Developmental Test of Visual Perception, Second Edition (DTVP-2)[END_REF]40], and the scores were standardized for youths between 4-10 years.

-The Manual and Digital Gnosopraxia Test (EMG) is a specific measure of manual praxis based on gesture imitation for hands and digits [START_REF] Vaivre-Douret | Subtypes of developmental coordination disorder : research on their nature and etiology[END_REF]. This is a modified version of Bergès, Lézine [START_REF] Bergès | Test d'imitation de gestes[END_REF]. A total composite score is based on success rate for gesture imitation and motor planification.

-The Brief assessment of writing skill in adolescent (BHK-ado) [30] is a French adaptation for adolescents of the BHK test created by Hamstra-Bletz [43]. The test consists of a copy of a standardized test during five minutes on a blank paper. Analyses of writing ability is based on nine items measuring the quality of the writing and speed.

Psychometric properties were assessed in a French sample of adolescents [START_REF] Soppelsa | BHK Ado[END_REF].

In-depth language assessment encompassed several tests ascertaining different components of language activity. For oral language, phonological skill was measured based on the performances at two items (repetition of the logatom, suppression of the last phonem) of the Evaluation des Fonctions cognitives et des Apprentissages (EDA) [START_REF] Billard | L'EDA : Évaluation Des fonctions cognitives et Apprentissages[END_REF]. Syntax and morphology skills were ascertained based on two items of the EDA (syntax understanding, sentence completion). The semantics component of oral language was assessed in two ways: with two items of the EDA for the receptive domain (lexical understanding, picture designation) and with the Peabody Picture Vocabulary Test (PPVT) [START_REF] Dunn | Peabody Picture Vocabulary Test, Fourth Edition[END_REF] for the expressive domain. Different tests were used for the assessment of written language. Reading skills were ascertained with the LMC-R test [47], the L2MA-2 test [48], Odédys 2 [49] or Evaléo 6-15 [START_REF] Launay | Evaléo 6-15: batterie d'évaluation du langag écrit et oral[END_REF]. Writing skills were based on two items of the EDA (dictation and text transcription), Alouette-R test [START_REF] Lefavrais | L[END_REF] or the Batterie d'Evaluation de la Lecture et de l'Orthographe (BELO) test [51]. The choice of the appropriate test was left to the speech therapist.

The indication for performing additional tests (e.g., sensory-processing, attentional, logicomathematic) was discussed case-by-case during weekly multidisciplinary meetings (including two child psychiatrists, a psychologist, a motor therapist, a speech therapist and two schoolteachers). The scores at the different tests were standardized based on the scores of typically developing same-age adolescents' performances such as provided by manuals. Results were reported as Standard Deviation (SD) or percentile. Standard errors have been transformed in confidence intervals to facilitate the interpretation of the results. When several standardized assessments were available, only the last one was reported.

2.4.Statistical analyses

For the description of the sample, ANOVA or Kruskall-Wallis tests were used to compare quantitative variables and Chi-squared or Fisher's exact tests for qualitative variables, depending on assumptions validity. Quantitative variables were described using mean and standard deviation and qualitative variables using number and percentage of occurrences. Odd-Ratios (OR) were presented with their confidence intervals and Cramer's ɸ (Phi) correlation coefficients for effect sizes.

To document the association between motor impairments and DMDD, a Fisher's exact test was used to compare the proportions of inpatient adolescents with developmental coordination disorder between the DMDD group, the MDD group, and the NMD group. A similar analysis was performed to compare the proportions of parent-reported delays in motor development between the DMDD, MDD, and NMD groups. Univariate analyses were used to describe the results of the battery of motor tests conducted in the subset of inpatients with DMDD who had in-depth motor assessment (n=24).

To document the association between language impairments and DMDD, a Fisher's exact test was used to compare the proportions of inpatient adolescents with communication/oral language disorder and written language disorder between the DMDD group, the MDD group, and the NMD group. A similar analysis was performed to compare the proportions of parentreported delays in language development between the DMDD, MDD, and NMD groups.

Univariate analyses were used to detail the results of the battery of language tests conducted in the subset of inpatients with DMDD who had in-depth language assessment (n=29).

Analyses were run on R 3.4.0 and a p-value less than 0.05 was considered significant.

Applying the Bonferroni correction for planned comparisons for the first two aims of the study this p-value was divided by 15. The corrected threshold for statistical significance was therefore 0.0038. We proceeded to subgroups analyses to determine whether the rates of developmental motor and language disorders differed in DMDD patients with regards to the ADHD status (Table S2).

RESULTS

3.1.Description of the sample

Among the 191 inpatient adolescents consecutively admitted during the study period, 67 were positively screened for chronic irritability and 53 matched all criteria for DMDD. All inpatients with chronic irritability without DMDD (n=14, Mean age 14.4 ± 1.9, 64% males) had severe neurodevelopmental conditions and/or chronic psychiatric disorders (intellectual disability n=11, autistic spectrum disorder n=4, organic neurological disorder n=7, schizophrenia disorder n=2, bipolar disorder n=3, chronic tic disorder n=1).

As presented in Table 1, inpatients with DMDD were mostly boys and were younger than inpatients in the MDD and NMD groups. The most frequent psychiatric disorders associated with DMDD were disruptive behavioral disorder, anxiety disorder and attention deficit disorder. The C-GAF score at admission, the CGI-S score, and the CGI-I score were not statistically different among the three groups.

[Insert Table 1, about here]

3.2.Motor developmental difficulties

In our clinical chart, 67% of the DMDD inpatients had an associated developmental coordination disorder which represents 80% of those who had in-depth motor assessment (23/29) and 20% of those who did not (5/24). The rate of developmental coordination disorder was higher in the DMDD group than in the MDD group (OR= 4.66 95% CI: 2.09, 10.41, ɸ = .32, p < .001) but was not statistically different from the NMD group (OR= 1.76 95% CI: 0.84, 3.70, ɸ = .29, p= .559) (Table 2). The frequency of parent-reported delay and/or abnormal motor development was higher in the DMDD group compared to the two other groups.

Inpatient adolescents with DMDD who had in-depth motor assessment had problematic scores in tests measuring fine motor skills such as the EMG manual imitation score and the subscore of the MABC-2 for manual dexterity. They had scores in the normal range for the tests ascertaining gross motor skills (i.e., the MABC-2 total score) and visuo-spatial skills (i.e., the DTVP-2) and scored low in the BHK-ado, a test of graphism and writing ability.

[Insert Table 2, about here]

[Insert Table 3, about here]

Language developmental difficulties

In our clinical chart, 31% of the DMDD inpatients had an associated communication/oral language disorder; this represent 47% of those who had in-depth language assessment (11/24) and 0% of those who did not (0/29). Considering corrected p-value, the rate of communication/oral language disorder was not statistically different between the DMDD and the MDD groups (OR= 3.21 95% CI: 1.20, 8.61, ɸ = .22, p= .019) or between the DMDD and the NMD group (OR= 1.61 95% CI: 0.67, 3.84, ɸ = .15, p= .367) (Table 2). Parent-reported delay and/or abnormal language development were not statistically different among the three groups.

As presented in Table 4, inpatients with DMDD who had in-depth language assessment had low scores in tests measuring phonological awareness (repetition of logatom, suppression of the last phonem), syntax and sematic expression (sentence completion, picture denomination).

However, tests measuring the receptive component of spoken language (lexical understanding, picture designation, syntax understanding) were in the normal range.

[Insert Table 4, about here] In our clinical chart, 35% of DMDD inpatients had a written language disorder; this represents 50% of those who had in-depth language assessment (12/24) and 11% of those who did not (3/29). The rate of written language disorder was higher in the DMDD group than in the MDD group (OR= 4.56 95% CI: 1.65, 12.64, ɸ = .59, p= .002) but not statistically different compared to inpatients in the NMD group (OR= 4.33 95% CI: 1.56, 12.02, ɸ = .58, p= .005) (Table 2).

Inpatients with DMDD who had in-depth language assessment had scores in tests measuring reading ability and writing skill between -1 and -2 SD (Table 4).

Combined developmental difficulties

Around 71% of inpatients with DMDD had an associated motor and/or language developmental disorder. A combined form of motor and/or language disorders concerns almost 46% inpatients with DMDD which is higher than in the MDD and NMD groups (Table 2). Only two subjects with DMDD had a written language disorder without also having a communication/oral language disorder.

DISCUSSION

4.1.Interpretation of the main finding

We found a very high rate of developmental motor and language disorders in inpatients with DMDD (71%) compared to inpatients with MDD or NMD (respectively, 28% and 36%). As a comparison, a 7% rate of learning disabilities was reported among the DMDD youths in the chart-review of 6-17-year-old inpatients conducted by Tufan et al. [START_REF] Tufan | Sociodemographic and Clinical Features of Disruptive Mood Dysregulation Disorder: A Chart Review[END_REF]. A 19% rate of learning disabilities was reported in DMDD patients in a Canadian 7 to17-year-old outpatient sample particularly enriched in mood disorders, although this rate was not statistically different from subjects with major depressive disorder (11%) [START_REF] Benarous | Are youths with disruptive mood dysregulation disorder different from youths with major depressive disorder or persistent depressive disorder[END_REF]. This finding should be interpreted in the light of the risk of sampling bias. Most of the participants' hospitalizations were planned to provide a second opinion and adequate treatments for severe forms of psychiatric disorders. This may explain why this sample is particularly enriched in complex forms of psychiatric and developmental disorders. In addition, our department includes an expert center for learning disabilities which had referred some patients. Furthermore, only adolescents were included in this research, unlike previous studies reporting the rate of learning disabilities in all DMDD patients [START_REF] Tufan | Sociodemographic and Clinical Features of Disruptive Mood Dysregulation Disorder: A Chart Review[END_REF][START_REF] Carlson | Rages--what are they and who has them?[END_REF][START_REF] Benarous | Are youths with disruptive mood dysregulation disorder different from youths with major depressive disorder or persistent depressive disorder[END_REF]. By doing that, we may have selected a sample of particular severity as many prepubertal children with DMDD have only a transitory course of symptoms [START_REF] Axelson | Examining the proposed disruptive mood dysregulation disorder diagnosis in children in the Longitudinal Assessment of Manic Symptoms study[END_REF] Several competing hypotheses could explain the high rate of co-occurrence between motor and/or language disorders and DMDD. Aberrancies in the motor and language domains could co-occur with irritability i) because they increase the frequency of frustrating events, in particular academic failure and difficult peer-relations [START_REF] Mammarella | Anxiety and Depression in Children With Nonverbal Learning Disabilities, Reading Disabilities, or Typical Development[END_REF][START_REF] Roben | Longitudinal relations among language skills, anger expression, and regulatory strategies in early childhood[END_REF], ii) because they are associated with delay in emotion-regulation skills [START_REF] Mendes | Fine motor ability and psychiatric disorders in youth[END_REF][START_REF] Chow | Does oral language underpin the development of later behavior problems? A longitudinal meta-analysis[END_REF], or iii) due to shared risk factors [START_REF] Benarous | Are youths with disruptive mood dysregulation disorder different from youths with major depressive disorder or persistent depressive disorder[END_REF]52]. The results presented here do not allow us to distinguish between these three possibilities.

In our research we found that youths with DMDD had low scores in motor tasks testing motor imitation and fine motor skills. In contrast, balance and visuo-spatial skills were in the normal range. Such findings, while preliminary, are interesting considering the role of imitation in the emergence of young children's socio-emotional competence [START_REF] Nadel-Brulfert | The Social Function of Reciprocal Imitation in 2-Year-Old Peers[END_REF]. Difficulties in imitating facial emotion has been also associated with impairments in emotional recognition [START_REF] Wood | Fashioning the Face: Sensorimotor Simulation Contributes to Facial Expression Recognition[END_REF] and poor emotional awareness [START_REF] Trevisan | Alexithymia, but not autism spectrum disorder, may be related to the production of emotional facial expressions[END_REF], two difficulties reported in DMDD patients [START_REF] Vidal-Ribas | The Status of Irritability in Psychiatry: A Conceptual and Quantitative Review[END_REF]. The relatively good performance of DMDD in visuo-spatial tasks should be interpreted with caution, considering a possible ceiling effect for the DTVP-2 test, as the normative scores were extracted from a children sample.

We found that almost a third of DMDD patients had an associated communication/oral language disorder. However, using a more stringent criteria for statistical significance the difference between the patients with DMDD and the two other clinical control groups were no longer significant. In-depth language assessment tests showed that the subsample with DMDD and oral language impairments were particularly affected in the expressive domain of language (e.g., ascertained with the PPVT test) while they had scores in the normal range for the receptive domain (lexical understanding, picture denomination of the EDA test). This reflects the importance of considering not only the theoretical knowledge of youths' vocabulary but also how the lexical terms are actually used in everyday situations in youth with emotional problems and oral language impairments [55]. Suboptimal scores in other components of spoken language skills (i.e., phonology, syntax) were consistent with the relations reported between these components and early behavioral problems [56].

As the content of many therapeutic interventions for emotional disorders in adolescents are delivered orally (e.g., structured psychotherapies, group interventions, psychoeducation, family-focused interventions), a low level of oral language competence may also be worth identifying in youths with DMDD as it could moderate the response to therapeutic interventions. It remains to be seen whether interventions focusing on enhancing verbal emotional expression that proved effective in improving socio-emotional competence in children [START_REF] Izard | Accelerating the development of emotion competence in Head Start children: effects on adaptive and maladaptive behavior[END_REF] could be successfully applied to DMDD patients with difficulties in oral language skills. Youths with DMDD were particularly impaired in reading and writing competency (i.e., BHK-ado, dictation, text transcriptions) in line with our initial hypothesis. Nearly one third of DMDD patients had a written language disorder, and the lowest scores in standardized language tests were observed for tasks ascertaining reading and writing skills. In addition to the difficulties in phonology reported in DMDD subjects here, DMDD patients may be affected in several cognitives domains involved in the reading process such as attention [START_REF] Vidal-Ribas | The Status of Irritability in Psychiatry: A Conceptual and Quantitative Review[END_REF] and inhibition [START_REF] Hoeksma | Emotion regulation and the dynamics of feelings: a conceptual and methodological framework[END_REF][START_REF] Deveney | Neural recruitment during failed motor inhibition differentiates youths with bipolar disorder and severe mood dysregulation[END_REF]. Logically, the combination of reading/spelling difficulties and fine motor/graphism problems (i.e., as ascertained by the item Manual Dexterity of the MABC-2) in DMDD subjects results in poor writing performance This is particularly true for DMDD patients, as many of them have combined forms of learning/developmental disorders. The difficulties in text transcription based on visual or auditory informations could affect all learning activities, accounting for the low level of academic achievement observed in DMDD patients [START_REF] Althoff | Disruptive Mood Dysregulation Disorder at Ages 13-18: Results from the National Comorbidity Survey-Adolescent Supplement[END_REF][START_REF] Copeland | Prevalence, comorbidity, and correlates of DSM-5 proposed disruptive mood dysregulation disorder[END_REF][START_REF] Axelson | Examining the proposed disruptive mood dysregulation disorder diagnosis in children in the Longitudinal Assessment of Manic Symptoms study[END_REF][START_REF] Benarous | Are youths with disruptive mood dysregulation disorder different from youths with major depressive disorder or persistent depressive disorder[END_REF][START_REF] Margulies | Will disruptive mood dysregulation disorder reduce false diagnosis of bipolar disorder in children?[END_REF] .

4.2.Limitations

First, and as previously mentioned, this sample reflects adolescents referred in a tertiary university care referral center. How these findings apply to adolescents with less severe symptoms remains to be studied. A non-irritable ADHD sample might have been also worth including as a comparison group to account for the confounding effect of ADHD. Second, this chart-review study may be prone to a measuring bias, due to missing or incomplete charts.

Standardized assessments were only performed in a subgroup of non-randomly selected patients resulting in a possible sampling bias and an overestimation the rates of motor and language impairments. To limit this risk, the link between DMDD and developmental motor and language disorders was estimated by combining different measures: rates of DSM-5 psychiatric disorders, parent-reported information, and profile of impairments based on standardized tests in subsets of patients. Third, the diagnostic of DMDD was set up retrospectively on the basis of the temper dysregulation with dysphoria disorder whose diagnostic criteria differ slightly from DMDD. The use of this proxy diagnostic procedure was regarded as acceptable as all patients with temper dysregulation with dysphoria would match the less stringent DMDD criteria.

4.3.Clinical and research implications

If confirmed, this work will support the use of standardized screening assessment for developmental difficulties in help-seeking populations of adolescents with DMDD. Further studies would help to elucidate how difficulties in motor and language domains play a role in the propensity to anger reaction and temper outbursts observed in DMDD youths. For example, longitudinal studies of preschool children with repeated assessment of developmental steps, anger reactivity and behavioral measures could provide opportunities to understand the temporal interplay between these dimensions. Such studies may contribute to the development of promising therapeutic opportunities to reduce the academic difficulties of youths with DMDD.

4.4.Conclusion

In the current study, we found that a vast majority of inpatient youths with DMDD presented an associated diagnosis of developmental motor and written language disorders. Most of these adolescents with DMDD had combined forms of developmental impairments. Considering the current lack of therapeutic opportunity for DMDD youths, awareness of these associated conditions could be beneficial. Clinicians and researchers should remain careful that behavioral expressions of anger do not distract them from the bigger picture of developmental impairments in DMDD patients. 2 All subjects with communication/oral language disorder had reading difficulties. The difference between a mixed language disorder (oral + written) and the sequela of communication/oral language disorder on reading or writing abilities require further analyses not presented here. The reaction is grossly out of proportion in intensity or duration to the situation or provocation.

LIST OF ABBREVIATIONS USED:

and

The responses are inconsistent with developmental level.

B

The temper outbursts occur, on average, three or more times per week C1 Nearly every day, the mood between temper outbursts is persistently negative (irritable, angry, and/or sad).

C2

The negative mood is observable by others (e.g., parents, teachers, peers). D Criteria A-C have been present for at least 12 months. Throughout that time, the person has never been without the symptoms of Criteria A-C for more than 3 months at a time.

E

The temper outbursts and/or negative mood are present in at least two settings (at home, at school, or with peers) and must be severe in at least in one setting.

F

Chronological age is at least 6 years (or equivalent developmental level).

G

The onset is before age 10 years.

H

There has never been a distinct period lasting more than 1 day during which the full symptom criteria, except duration, for a manic or hypomanic episode have been met.

I

The behaviors do not occur exclusively during the course of a Psychotic or Mood Disorder (e.g., Major Depressive Disorder, Dysthymic Disorder, Bipolar Disorder) and are not better accounted for by another mental disorder (e.g., Pervasive Developmental Disorder, post-traumatic stress disorder, separation anxiety disorder)

Diagnostic procedure:

A DMDD diagnosis was positively endorsed if the subjects presented at least eleven positive answers to the diagnostic criteria described above. The final formulation for DMDD diagnostic criteria (1) are similar to those developed for TDDD [START_REF] Gearing | A Methodology for Conducting Retrospective Chart Review Research in Child and Adolescent Psychiatry[END_REF] except for two changes:

(i) the mood between the temper outbursts is persistently irritable or angry most of the day in DMDD. In TDDD the item was endorsed positively if the mood was angry, irritable and/or sad. (ii)

A new exclusion criterion was introduced for DMDD 'The symptoms are not attributable to the physiological effects of a substance or to another medical or neurological condition'.

Figure 1 .

 1 FIGURES CAPTIONS Figure 1. Flow-chart of the sample

Table 1 .

 1 Description of the subjects with DMDD, MDD and non-mood disorder

		DMDD (n=53)	MDD (n=64)	NMD (n=61)	p-value
	Socio-demographic characteristics
	Gender, female, n (%)	16 (30%)	31 (48%)	25 (41%)	.134 †
	Age (y) (mean ±SD)	13.58 ± 1.49 a	15.33 ±1.65 b	14.42±1.55 b	<.001 † † † **
	Socio-economic status, high and middle, n (%)	31 (59%)	51 (80%)	48 (79%)	.017 †
	School functioning and psychosocial factors
	Prior grade repetition, n (%)	15 (28%)	13 (20%)	9 (15%)	.204.201 † †
	School non-attendance above 3 months, n (%)	24 (45%)	32 (51%)	20 (33%)	.118.139 † †
	School adaptations, n (%)	36 (68%)	29 (46%)	31 (51%)	.050 †
	Special educational facilities, n (%)	14 (26%) a	6 (10%) b	7 (12%) b	.025.030 † † *
	Foster care placement, n (%)	17 (32%) a	7 (11%) b	4 (7%) b	<.001 † † **
	Home educative
	assistance/report to child-	32 (60%) a	19 (30%) b	27 (44%) ab	.004 † **
	protection agencies, n (%)
	Developmental history and medical conditions associated
	Complicated pregnancy, n (%)	13 (32%) a	16 (25%) a	5 (9%) b	.022.020 † † *
	Acute fetal distress, n (%)	11 (26%)	12 (19%)	7 (13%)	.226.349 † †
	Neurological disorder, n (%)	9 (17%) ab	4 (6%) b	13 (22%) a	.045.035 † † *
	Chronic somatic condition (non-neurological), n (%)	29 (55%)	21 (33%)	24 (40%)	.054 †
	Comorbid psychiatric disorders, %
	ADHD	23 (43%) a	4 (6%) b	5 (8%) b	<.001 † † **
	ASD	3 (6%)	3 (5%)	14 (23%)	.001
	ANX	29 (55%)	37 (58%)	23 (38%)	.057.061 † †
	ASD	3 (6%) b	3 (5%) b	14 (23%) a	.003 † † **
	DBD	36 (68%) a	6 (9%) b	11 (18%) b	<.001 † † **
	ED	1 (2%)	5 (8%)	1 (2%)	.226 † †
	ID	0 b	9 (14%) a	13 (22%) a	<.002001 † † **
	SPD	0 b	3 (5%) b	22 (36%) a	<.001 .004 † † **
	STRDTSD	16 (30%)	13 (20%)	23 (38%)	.100 † †
	TTS	5 (9%)	1 (2%)	6 (10%)	.084 † †
	Number of psychiatric
	diagnoses at discharge (mean	2.7 ±0.99 a	2.09 ±0.94 b	1.52 ±0.65 c	<.001 † † † **
	±SD)
	Severity and treatment
	response
	History of admission in inpatient structure, n (%)	33 (62%) a	29 (45%) ab	18 (30%) b	.002 † **
	C-GAF at admission (mean ±SD)	38.17 ±10.69	38.44 ±11.68	36.44 ±14.41	.422 † † †
	C-GAF at discharge (mean ±SD)	58.30 ± 10.59	62.52 ± 13.15	60.23 ±13.33	.091 † † †

Table 2 .

 2 Prevalence of motor and language impairments in the DMDD, MDD and NDM groups

				Comparisons
	DMDD	MDD	NMD	between the
	(n=53)	(n=64)	(n=61)	3 groups
				p-value 1

Note:

† Chi-2 test; † † Fisher exact test; * indicates p <.05. ** indicates p < .01. a-b Means in a row without a common superscript letter differ (p < .05). 1 Statistical comparisons between each group (DMDD vs. MDD, and DMDD vs. NMD) are presented in the plain text.

Table 3 .

 3 Detailed motor difficulties in the subset of DMDD patients with in-depth motor assessments (n=29/53) Standardized scores in same-age non-clinical sample were provided by the manuals for each test. MABC-2: Movement Assessment Battery for Children 2nd edition (Henderson 2007), EMG: Manual and Digital Gnosopraxia Test (Vaivre-Douret 2011), DTVP-2: Developmental Test of Visual Perception 2nd edition (Hammill 1993), BHK-ado: Brief assessment of writing skill in adolescent (Charles 2003) ** Scores in the problematic or pathologic ranges

		Mean performance of DMDD youths
	Tests	compared to standardized scores in
		non-clinical population *
	Gross motor skills
	MABC-2: Manual dexterity	14 th percentiles, 95% CI [13, 15] **
	MABC-2: Aiming and Catching	36 th percentiles, 95% CI [34, 38]
	MABC-2: Balance	27 th percentiles, 95% CI [25, 28]
	MABC-2 : total score	18 th percentiles, 95% CI [16, 20]
	Fine motor skills
	EMG : Manual imitation	-1.4 SD, 95% CI [-1.5, -1.3] **
	EMG : Digital imitation	+0.1 SD, 95% CI [0.0, 0.2]
	Visuo-spatial skills
	DTVP-2: Motor-reduced visual perception quotient	63 th percentiles, 95% CI [61, 65]
	DTVP-2: Visual-motor integration quotient	48 th percentiles, 95% CI [45, 50]
	Graphism
	BHK-ado, SD	-1.8 SD, 95% CI [-2.0, -1.7] **
	Note:

*

Table 4 .

 4 Detailed language difficulties in the subset of DMDD patients with in-depth language assessments (n=24/53) Standardized scores in same-age non-clinical sample were provided by the manuals for each test. EDA[START_REF] Billard | L'EDA : Évaluation Des fonctions cognitives et Apprentissages[END_REF], PPVT: Peabody Picture Vocabulary Test[START_REF] Dunn | Peabody Picture Vocabulary Test, Fourth Edition[END_REF]), LMC-R[START_REF] Khomsi | BLI : Batterie de lecture informatisée[END_REF]). ** Scores in the problematic or pathologic ranges

		Mean performance of DMDD
	Tests	youths compared to standardized
		scores in non-clinical population *
	Spoken language : phonology
	EDA : Repetition logatom	-0.3 SD, 95% CI [-0.5, -0.1]
	EDA : Suppression of the last phonem	-1.4 SD, 95% CI [-1.6, -1.2]
	Spoken language : syntax and morphology
	EDA : Syntax understanding	-0.7 SD, 95% CI [-0.8, -0.6]
	EDA : Sentence completion	-1.0 SD, 95% CI [-1.3, -0.7]
	Spoken language : semantics
	EDA : Lexical understanding	69 th percentiles, 95% CI [56, 82]
	EDA : Picture designation	40 th percentiles, 95% CI [37, 43]
	PPVT : Picture denomination	-2.0 SD, 95% CI [-2.3, -1.8]
	Written language : reading
	Reading regular words	-1.5 SD, 95% CI [-1.7, -1.3]
	Reading irregular words	-2.0 SD, 95% CI [-2,3, -1.8]
	Reading pseudo-words	-2.2 SD, 95% CI [-2.5, -2.0]
	Written language : writing
	Dictation	-1.4 SD, 95% CI [-1.6, -1.2]
	Text transcription	-1.6 SD, 95% CI [-1.8, -1.4]
	Note:

*

Table S1 .

 S1 Algorithm for the diagnosis of DMDD in the current studyA1The temper outbursts are manifest verbally and/or behaviorally, such as in the form of verbal rages, or physical aggression towards people or property A2

	Diagnostic criteria:	Clinical description:

  TableS2Subgroups analyses to compare the rate of motor and language impairments in DMDD with and without associated ADHD

		DMDD/	DMDD/
		ADHD+	ADHD-	p-value
		(n=22)	(n=31)
	Any developmental motor or language disorders, n (%)	18 (86%)	15 (62%)	.013
	Communication/oral language disorder	9 (41%)	7 (23%)	.152
	Written language disorder	8 (36%)	9 (29%)	.573
	Developmental coordination disorder	14 (63%)	14 (45%)	.184
	Two combined motor or language disorders *	7 (33%)	7 (29%)	.452
	Three combined motor or language disorders	4 (19%)	4 (17%)	.597