Baba I Camara
email: baba-issa.camara@univ-lorraine.fr

Abdoulaye Diouf

Hela Toumi

Diène Ngom

Vincent Felten

Jean-Franc ¸ois Masfaraud

Jean-Franc ¸ois Férard

J-F Masfaraud

J-F Férard

Estimation of deltametrin bio-accumulation kinetics and dynamics of effects on daphnia population

Keywords: DEBtox model, bayesian inference, risk assessment, pesticide contamination, long-term exposure

contamination effects on aquatic organisms, at individual or population level, are a real research problem. The models of Dynamic Energy Budget in toxicology (DEBtox) allowed to the possibility of

Introduction

Highly relevant in recent decades, understanding the use of environmental resources by individual organizations and the population-level consequences of these interactions is one of the major challenges in ecology (Johnson & al 2013 [22]). To this complexity of interactions is added the increase in the number of contaminants present in the environment. This is a serious problem of water contamination and a serious damage to organisms inhabiting their ecosystems. Among these contaminants, pesticides have raised significant social and scientific concerns all over the world [START_REF] Rodrigues | Determination of several pesticides in water by solid-phase extraction, liquid chromatography and electrospray tandem mass spectrometry[END_REF]. Their intensive use presents a serious potential hazard to both the environment and to human health, because their toxicity persistency results in their accumulation in organisms as they move up the food chain [START_REF] Chambers | Chemistry of organophosphorus insecticides[END_REF]. Deltamethrin is among the most effective pyrethroid [START_REF] Bradbury | Comparative toxicology of the pyrethroid insecticides[END_REF] and one of the most widely used insecticides. Depending on its concentration and the exposure duration, this insecticide has been shown to cause lethal and sublethal effects on aquatic invertebrates [START_REF] Gutiérrez | Deltamethrin-mediated toxicity and cytomorphological changes in the midgut and nervous system of the mayfly Callibaetis radiatus[END_REF][START_REF] Oliveira | Acute effects of deltamethrin on swimming velocity and biomarkers of the common prawn Palaemon serratus[END_REF][START_REF] Toumi | Investigation of differences in sensitivity between 3 strains of Daphnia magna (crustacean Cladocera) exposed to malathion (organophosphorous pesticide)[END_REF][START_REF] Xiu | Toxicity of the new pyrethroid insecticide, deltamethrin, to Daphnia magna[END_REF]. As response variables we considered a set of physiological and life history traits of the freshwater zooplankton Daphnia magna. In fact, daphnids have been routinely used where invertebrates in aquatic toxicology bioassays have been required [START_REF] Pereira | Gene transcription in Daphnia magna: effects of acute exposure to a carbamate insecticide and an acetanilide herbicide[END_REF]. They i) are small in size, ii) are simple to culture, iii) are easy to handle in the laboratory and iv) have a parthenogenetic mode of reproduction, leading to genetic uniformity [START_REF] Baird | Genetic variation in the response of Daphnia to toxic substances: Implications for risk assessment[END_REF]. D. magna has been selected for previous studies where acute and chronic bioassays have been conducted [START_REF] Barata | Role of B-esterases in assessing toxicity of organophosphorus (chlorpyrifos, malathion) and carbamate (carbofuran) pesticides to Daphnia magna[END_REF][START_REF] Barata | Biochemical factors contributing to response variation among resistant and sensitive clones of Daphnia magna Straus exposed to ethyl parathion[END_REF][START_REF] Guilhermino | Inhibition of acethylcholinesterase activity as effect criterion in acute tests with juvenile Daphnia magna[END_REF][START_REF] Toumi | Investigation of differences in sensitivity between 3 strains of Daphnia magna (crustacean Cladocera) exposed to malathion (organophosphorous pesticide)[END_REF]. The use of this species has allowed the assessment of deltamethrin's ecotoxic effects to be made using different endpoints, including survival, growth, reproduction and embryotoxicity [START_REF] Toumi | Investigation of differences in sensitivity between 3 strains of Daphnia magna (crustacean Cladocera) exposed to malathion (organophosphorous pesticide)[END_REF].

The idea is that concepts related to energy flow are used in studies at all levels of biological and ecological organization [START_REF] Nisbet | Models relating individual and population response to contaminants[END_REF]. Energy processes are important in determining the consequences of environmental stress, particularly in response to sub-lethal concentrations of contaminants, which generally affect assimilation and respiration rates. Numerous Dynamic Energy Budget (DEB) models have been developed to better understand how environmental changes would affect, for example, the growth, development, maintenance, reproduction and survival of certain populations (Gurney and Nisbet 1998 [20], Johnson & al. 2013 [22]). Nisbet et al 1997 [START_REF] Nisbet | Models relating individual and population response to contaminants[END_REF] defined an individual response model for exposure to toxic substances with three components: (i) a DEB model predicting growth and reproduction; (ii) a bioaccumulation model describing the exchange of toxic substances between the body and the environment and its distribution in the body; and (iii) a model of toxicant action. In addition, the inference of the life traits of these models is very complex in general. In the literature, many statistical models are currently too complex to fit using standard statistical methods, but can be adjusted using Bayesian computational methods (Link et al., 2002 [27, 28]). However, it can be reassuring that, in many cases, Bayesian inference gives numerical responses that closely match those obtained by conventional methods.

Johnson & al 2013 [START_REF] Johnson | Bayesian inference for bioenergetic models[END_REF] developed a rigorous methodology for modelling the link between unobservable underlying states and observable magnitudes and for parameter inference in a Bayesian framework. He examined how parameter estimation could be affected by poor specification of the food model, in particular by assuming a constant food level when the true underlying dynamics are variable. Still in the Bayesian context for parameter estimation, Delignette-Muller & al 2017 [START_REF] Delignette-Muller | Robust Fit of Toxicokinetic-Toxicodynamic Models Using Prior Knowledge Contained in the Design of Survival Toxicity Tests[END_REF] proposed a fully automated fitting procedure that extracts prior knowledge of model parameters from the design of the toxicity test (tested concentrations and time observation). They evaluated their procedure on three experimental datasets and over 300 simulations and showed that it provides robust model fits, both in the frequentist and Bayesian framework, with a better robustness of the Bayesian approach for ensembles of the sparsest data using the JAGS software via the R package rjags. Vogel & al 2016 [START_REF] Albert | Computationally efficient implementation of a novel algorithm for the General Unified Threshold Model of Survival (GUTS)[END_REF] presented a new algorithm and its rapid implementation in their R package, GUTS helping to overcome parameter inference as part of a survival model. They showed an example of a step-by-step application of calibrating their model and estimating uncertainty, making probabilistic predictions and validating their model with new data. A recent work, Philipp H Boersch-Supan & al., 2016 [START_REF] Philipp | deBInfer: Bayesian inference for dynamical models of biological systems in R[END_REF] demonstrated parameter inference for a DDE model of population growth in the pathogenic fungal pathogen Batrachochytrium dendrobatidis (Bd), which causes the amphibian disease chytridiomycosis (Rosenblum et al. 2010 [37]; Voyles et al. 2012 [42]).

In this paper, we illustrate the utility of Bayesian statistics for the inference of bioenergetic model parameters, taking advantage of our experimental results of Daphnia growth and reproduction modeling. The major goal of our study is the assessment of the threshold concentration above which there will be effects on the growth and reproduction of daphnids exposed to 5, 20, 40, 80 and 160 ng.L -1 doses of deltamethrin.

Materials and methods

Chronic ecotoxicity

Based on acute and chronic deltamethrin results found by Toumi et al. [START_REF] Toumi | Investigation of differences in sensitivity between 3 strains of Daphnia magna (crustacean Cladocera) exposed to malathion (organophosphorous pesticide)[END_REF], neonates daphnids (aged < 24 h) were exposed during 21 days to nominal sublethal concentrations from 18 to 300 ng L -1 . The daphnids were exposed individually in 60 mL glass beakers containing 50 mL of test solution, composed of LC-Volvic mixture culture medium with algae and deltamethrin at the diverse desired concentrations. Daphnids were fed a mixture of three algal species (5x10 6 P. subcapitata/daphnia/day, 2.5x10 6 D. subspicatus/daphnia/day, and 2.5x10 6 C. vulgaris/daphnia/day). Temperature was controlled at 20 o C, photoperiod was maintained as culture conditions at 16-8 h light-dark, the test solution (with food) was renewed every 2 days and a total of 10 replicates for the control and each treatment were prepared. The endpoints examined in this test were longevity, reproduction (daily number of neonates per survival female) and body length (measured at 0, 7, 14 and 21 days). Body length of daphnids was measured with the image analysis software Motic Image Plus 2.0 (Motic China Group Ltd, Xiamen, China), from the top of the head to the base of the tail spine.

Description of the model

In this study, we consider the maintenance model DEBtox developed in Goussen et al 2015 [START_REF] Goussen | Energy-based modelling to assess effects of chemicals on Caenorhabditis elegans: A case study on uranium[END_REF] for evaluating the long-term effects of the toxic compound called deltamethrin our test organism Daphnia magna. The choice made on this model is explained by the fact that in many recent studies fungal pathogens impact both growth and reproduction of test organisms(Goussen & al 2015 [START_REF] Goussen | Energy-based modelling to assess effects of chemicals on Caenorhabditis elegans: A case study on uranium[END_REF], Nisbet & al 1997 [START_REF] Nisbet | Models relating individual and population response to contaminants[END_REF], Kooijmann & al [START_REF] Kooijman | Dynamic Energy Budgets in Biological Systems[END_REF][START_REF] Kooijman | Analysis of toxicity test on Daphnia survival and reproduction[END_REF], Billoir & al 2008 [6]). Previous studies [START_REF] Biesinger | Effects of various metals on survival, growth, reproduction, and metabolism of Daphnia magna[END_REF][START_REF] Becker | Differential effects of phosphorus and fatty acids on Daphnia magna growth and reproduction[END_REF][START_REF] De Schamphelaere | Effects of chronic dietary copper exposure on growth and reproduction of Daphnia magna[END_REF][START_REF] Flaherty | Effects of pharmaceuticals on Daphnia survival, growth, and reproduction[END_REF][START_REF] Knops | Alterations of physiological energetics, growth and reproduction of Daphnia magna under toxicant stress[END_REF] have shown that the contaminant simultaneously impacts the growth and reproduction of Daphnia. These are the reasons that motivated our choice. Further details on model development for parameter inference can be found in (Goussen et al 2015 [START_REF] Goussen | Energy-based modelling to assess effects of chemicals on Caenorhabditis elegans: A case study on uranium[END_REF]). The maintenance model that we will apply to our data is the following system of three non-autonomous differential equations :

s f (l) = α 1 -1 + l 3 f l 3 -1 , (1)
s(C q ) = max(0, b(C q -NEC)), (2)
dC q dt = C k e (1 -s f ) f l -C q k e (1 -s f ) f l + d ln(l 3 ) dt , (3)
dl dt = r B [(1 -s f ) f -(1 + s(C q ))l], (4)
dR dt = R M 1 -l 3 p (1 + s(C q )) (1 -s f ) f l 2 g(1 + s(C q )) -1 + l g + (1 -s f ) f -l 3 p R Max -R R Max , (5)
Equation ( 3) represents dynamics of deltametrin concentration in the daphnia body. Equation (3) and equation ( 4) describe respectively de daphnia body growth dynamics and the reproduction dynamics in an environment contaminated by deltamethrin. The model parameter are S f the size-dependent ingestion limitation function, (1α)(-) the proportion of food available whatever the length, r B (days -1 ) the Von Bertalanffy growth rate, f (-) the actual ingestion rate divided by the maximal ingestion rate for a body size, R(#) the cumulated reproduction, R Max (#) the maximal cumulated reproduction, R M (#(days -1 )) the maximum reproduction rate, and g(-) the investment ratio. L(mm) represents the body length at time t; L 0 (mm) body length at birth (start of feeding in the DEB framework), L f (mm) body length at which the ingestion rate is half the maximum ingestion rate and L p (mm) the body length at puberty. All these length data are scaled by the maximal length L in f (mm) resulting in scaled parameters l; l 0 ; l f ; and l p (-). ke(days -1 ) is the elimination rate and C(ng.L -1 ) is the actual exposure concentration. b(L.ng -1 ) is the slope of the effect in the toxic stress function, s while NEC(ng.L -1 ) the no-effect concentration.

For the inference of the parameters of the model considered, the approach adopted is the Bayesian approach to statistics. Statistical inference is based on the posterior distribution, which expresses all that it knows about the parameters of a statistical model, taking into account the experimental data and existing knowledge (the a priori). In general, there are few large samples in ecology. Bayesian inference is a formidable asset for the treatment of ecological models. This is a fairly rigorous methodology for any sample size especially when it is small.

Statistical analyzes

The Bayesian inference of the parameters for the evaluation of allometry and reproduction has been implemented with R version 3.4.2 software [START_REF] Core | R: A language and environment for statistical computing[END_REF]. We used the vignette developed in Boersch-Supan et al., 2016 [START_REF] Philipp | deBInfer: Bayesian inference for dynamical models of biological systems in R[END_REF] requiring the loading R package deBInfer requiring the devtools libraries (Wickham & Chang 2016 [START_REF] Wickham | Devtools: Tools to make developing r packages easier[END_REF]). We have implemented the considered DEB model using the R package deSolve [START_REF] Soetaert | Solving Differential Equations in R: Package deSolve[END_REF]. More details on how to specify differential equations for this solver can be found in the documentation and thumbnails of the package (Soetaert & al., 2010 [23]).

Before estimating the parameters, we corrected our weekly growth data collected over 21 days. To do this, we have different doses of deltamethrin that we divide into concentration group. Using a succinct writing of the growth model ( 6) used in Ritz & Streibig, 2008 [39], we have set the relative daily size for each group.

L(t) = L ∞ [group] 1 -exp -K[group](t-t 0 [group]) (6)
Where group represents each of the deltamethrin doses. L ∞ [group] and K[group] are respectively the asymptotic average length, not the maximum length of the animal and the Brody coefficient for individuals of each pesticide concentration. t 0 [group] represents the initial time. Further details of von Bertalanffy Growth Functions can be found in [START_REF] Ogle | fishR Vignette-von Bertalanffy growth models[END_REF][START_REF] Ogle | Von Bertalanffy growth model vignette[END_REF].

The appropriate log-likelihood function for our data takes the form:

L (Y |θ ) = ∑ t ln 1 Ñt σ obs √ 2π exp - (ln Ñt -ln(N t + ε)) 2 2σ 2 obs (7)
where Ñt are the observations, and N t are the predictions of the DEB model given by the current MCMC sample of the parameters θ . In addition, ε is a small correction needed because the DE solution can be zero (or less, depending on the numerical precision) [START_REF] Johnson | Bayesian inference for bioenergetic models[END_REF]. ε should therefore be at least as large as the expected numerical precision of the solver. We chose ε = 10 -6 , which is of the same order as the default numerical precision of the default solver (deSolve :: ode with method = "lsoda"), but we found that the inference results were insensitive to this choice as ε ≤ 0.01. It is translated by an observation model function taking as input three data arguments, sim.data and samp, used by the MCMC procedure to transmit the data (as data.frame, that is to say indexed to using the $ operator and column names of the input data), the current state of the Markov chain (as the named vector), and the associated DE modeling solution (in as a class object of deSolve, indexed by the operator [ ] and the declared names of the state variables). We can access these entries to define the likelihood of the data. The battlehorse of the deBInfer package that executes the MCMC estimate is the function de mcmc. The progression of the MCMC procedure can be monitored using the cnt, plot and verbose options: Each iteration of the function will print information about the current state and, if plot = TRUE, the strokes of the strings will be plotted (Philipp H Boersch-Supan & al, 2016 [START_REF] Philipp | deBInfer: Bayesian inference for dynamical models of biological systems in R[END_REF]). It is important to note that for the inference results reported in this paper, the MCMC procedure was run for 13,000 iterations, which was worth about more than 24 hours on a computer with an Intel(R) Core processor(TM) i3-2350M CPU clocked at 2.30 GHz. The parameters to be inferred are

θ modele = (k e , NEC, α, b, f , R max , R M , r B , L p , L in f , L 0 , L f )
and possibly the standard deviations (sd.y i ) i=1,••• ,12 between observation data and dynamic model solutions. Prior distributions of the model parameters are summarized in the table [START_REF] Albert | Computationally efficient implementation of a novel algorithm for the General Unified Threshold Model of Survival (GUTS)[END_REF].

Results

The convergence of the MCMC runs to a stable joint posterior distribution was obtained after 18,000 iterations. The stationary chains of 18, 000 iterations in figure [START_REF] Barata | Role of B-esterases in assessing toxicity of organophosphorus (chlorpyrifos, malathion) and carbamate (carbofuran) pesticides to Daphnia magna[END_REF] revealed that our model (( 1)) was well fitted. Thus, we obtain the set of parameter values fitting the model [START_REF] Albert | Computationally efficient implementation of a novel algorithm for the General Unified Threshold Model of Survival (GUTS)[END_REF] to experimental data of daphnia deltamethrin exposure. The statistics (mean and standard deviation) of estimated parameters are summarized in figure [START_REF] Albert | Computationally efficient implementation of a novel algorithm for the General Unified Threshold Model of Survival (GUTS)[END_REF]. With the estimate parameter values, we computed model (1) outputs to confirm that the inference procedure actually retrieved the model. The figure (3) visualized in the same graphic, the posterior median trajectories and the experimental data of daphnia growth an cumulative reproduction for the six contaminated deltamethrin environment and during the 21 days of the experiment. Furthermore, the figure (4) illustrates custom plots by accessing the simulated trajectories inside the post traj object (the post sim list class is simply a nested list). From the posterior, we simulate

(-) log N (0; 1) 1 rw-unif c(5, 6)
Table 1 Prior distributions of the model parameters using the maintenance model [START_REF] Albert | Computationally efficient implementation of a novel algorithm for the General Unified Threshold Model of Survival (GUTS)[END_REF]. The normal distribution and log normal distribution of mean µ and standard deviation σ are respectively noted N (µ; σ ) and log N (µ; σ ) , and the uniform distribution between a and b is noted U [a; b]. I]c; d] denotes an interval censoring between c (excluded) and d. The three following variations can be considered: ind corresponding to proposals from the appropriate prior (independent proposals); rw as a normal distribution centered at the current value of the parameter (or a multivariate normal distribution if parameters were proposed jointly) and rw-unif a uniform distribution with limits proportional to the current value of the parameter (i.e., Unif[ a b x, b a x] where b > a and x is the current value) 500 trajectories of the DEB model while calculating at 95%HDI highest posterior density interval for the deterministic part of the model. The fitted model showed that chronic Delamethrin exposure effected on both D. magna growth and reproduction when the bio-accumulated deltamethrin exceeded the estimated threshold of NEC (No Effect Concentration) with mean value 5.849 ngL -1 and standard deviation 2.57. Furthermore, the estimated parameters allowed us to compute in figure [START_REF] Biesinger | Effects of various metals on survival, growth, reproduction, and metabolism of Daphnia magna[END_REF] the bio-accumulation kinetics in exposed daphnia bodies. Regardless of the 21-day exposure concentration, bioaccumulation kinetics presented increasing dynamics and also increased more rapidly with exposure concentration. Thus even at low dose of exposure, the rate of natural elimination did not completely detoxify the daphnids. At long-term exposure, this non-complete detoxification will lead to effects on daphnia. In addition, figure [START_REF] Biesinger | Effects of various metals on survival, growth, reproduction, and metabolism of Daphnia magna[END_REF] showed that daphnids exposed to more than 80 ngL -1 will accumulate in their body, in less than 21 days, a deltamethrin concentration higher than the NEC = 5.849 ng/L. The concentration of bio-accumulated deltamethrin exceeded the NEC from the 20th (respectively 17 th) day of exposure for daphnids exposed to 80 ngL -1 (respectively 160 ngL -1 ).

Figure [START_REF] Billoir | A Bayesian approach to analyzing ecotoxicological data[END_REF] showed the correlations between posterior estimated parameters of our model. The set of parameters consisting of daphnia physiological parameters of growth and reproduction but also parameters measuring the effects of exposure to deltamethrin, this correlation test (in fig ( 6)) allowed to better understand how deltamethrin affects the daphnia physiological parameters. In fact the parameter correlation plot revealed that the NEC was positively correlated with the killing rate b, the elimination rate k e and the body length at which the ingestion rate is half the maximum ingestion rate L f (mm). Figure ( 6) also revealed that the

Conclusion & Discussion

The present study estimated the effects of chronic deltamethrin exposure on daphnia growth and reproduction. For this purpose a laboratory experiment for data acquisition was run and Dynamic Energy Budget approach model analysis was used for data analysis. The daphnia physiologic parameters of growth and reproduction and parameters measuring deltamethrin effects (killing rate, elimation rate, NEC) were also estimated using Bayesian inference and the R's deBInfer package. The fitted model to our data gave us the kenetic of deltamethrin bio-accumulation dynamics and the time from which the NEC threshold is reached triggering the observed effects. Results also showed that in 21 days exposure the deltamethrin effects were mainly observed on exposed at concentration 80 ngL -1 or more. The computation of parameter correlation pair revealed the no-effect concentration NEC was positively correlated with the killing rate b, the elimination rate k e and the body length at which the ingestion rate is half the maximum ingestion rate L f (mm). This means that daphnia with hight NEC needed a higher elimination rate, needed more growth to reach the half maximum saturation and had a higher killing rate. The parameter correlation Fig. 2 MCMC chains plotting & summarizing computation also revealed that the investment rate g was positively correlated with Rm and Rmax, negatively correlated with NEC, b, and L f . This means that the higher was the investment ratio the lower were the no-effect concentration NEC, the killing rate b and daphnia had lower size at half maximum ingestion rate. Inversely, it also may main that in an environment with high contamination of deltamethrin, the daphnia investment ratio is lower while the killing rate and the NEC are higher. Thus, our estimation from the DEBtox model (model ( 1)) confirmed results in Toumi and al. [START_REF] Toumi | Investigation of differences in sensitivity between 3 strains of Daphnia magna (crustacean Cladocera) exposed to malathion (organophosphorous pesticide)[END_REF] that deltamethrin exposure resulted in a decrease of D. magna survival and reproduction rates with increasing concentrations of pesticide. Furthermore, daphnia with higher investment ratio had a higher maximum reproduction rate and a higher maximal cumulative reproduction rate. Results also highlighted that deltamethrin exposure modified the daphnia's allocation of energy for structural maintenance, reproduction or survival. These modifications of allocated energy, due to deltamethrin toxicity, depended on accumulated concentration and affected daphnia survival and reproduction. This may also mean that the deltamethrin elimination process became ineffective when the accumulated concentration exceeds a certain threshold. However, in these 21 days chronic exposure, data analysis didn't reveal deltamethrin effects on daphnia growth dynamics. Our experimental data and the DEBtox model analysis didn't show significant difference in growth dynamics between our control [START_REF] Reyes | Temporal variability of food determines the outcome of pesticide exposure in Daphnia[END_REF]) showed that pesticide effects on growth could be observed by varying the quality of food. However, more investigations like multi-generational exposures, varying exposure time are needed to determine the effect of deltamethrin on daphnia in terms of growth rate and population dynamics or to exhibit other complex interaction effects. However, more investigations like multi-generational exposures, varying exposure time are needed to determine the effect of deltamethrin on daphnia in terms of growth rate and population dynamics or to exhibit other complex interaction effects.

Fig. 1

 1 Fig. 1 Summary of parameter estimated parameter values of model (1)

Fig. 3

 3 Fig. 3 Median growth & reproduction fitting with 95% HDI

Fig. 5

 5 Fig. 5 Kinetics of deltamethrin bioacumulation in exposed daphania

Fig. 6

 6 Fig. 6 Parameter correlations plotting

Acknowledgments

The financial sponsors of this scientific work were French cooperation and the Grand Est region and UTIQUE, the Hubert Curien Partnership (PHC) Franco-Tunisian. We are very grateful for their financial support.


Arthur Abia
email: arthurabia@gmail.com

Loïc Caroux
email: loic.caroux@univ-tlse2.fr

Effects of Self-Selected Music and the Arousal Level of Music on User Experience and Performance in Video Games

Keywords: Game design, Player experience, Enjoyment, Musical preference, Game genre

Effects of self-selected music and the arousal level of music on user experience and performance in video games

Arthur Abia, Loïc Caroux

Introduction

Music has become an important part of everyday life. A growing number of studies has been therefore dedicated to it [START_REF] Krumhansl | Rhythm and pitch in music cognition[END_REF]. In the field of cognitive ergonomics, music study is mainly task-performance oriented. According to the literature [START_REF] Cassidy | The effect of background music and background noise on the task performance of introverts and extraverts[END_REF][START_REF] Furnham | The influence of musical distraction of varying complexity on the cognitive performance of extroverts and introverts[END_REF], music can be considered as an additional distraction, interfering with the completion of a task. The concept of distraction, refers here to the process of attention, as defined by Broadbent [START_REF] Broadbent | Perception and communications[END_REF]. In this model, attention is described as a cognitive filter, selecting and processing the most relevant information as well as inhibiting the other messages in goal-oriented tasks. According to this model, attention is a limited process. Processing stimuli during task execution or in the presence of external stimulus drains from the cognitive system of an operator or a user. Exposition to musical stimuli may then be detrimental performance-wise. However, in video games, soundtracks are a common part of the player experience. They have to be considered more than ambient stimuli and they are not used just as auditory feedback anymore [START_REF] Nacke | More than a feeling: Measurement of sonic user experience and psychophysiology in a first-person shooter game[END_REF]. The role of music in user experience in video games has received little attention in the literature. There is still much to discover about the impact of audio in video games. In particular, there is still a need for investigation of the effects of self-selected music and the arousal level of music on player experience.

The present study aimed to investigate the effects of music, and more specifically the effects of musical preference and the arousal level of music on user performance and user experience in a given task: playing video games. Based on the work of Cassidy and MacDonald [START_REF] Cassidy | The effects of music choice on task performance: A study of the impact of self-selected and experimenter-selected music on driving game performance and experience[END_REF], an experiment was designed to assess the effects of these music characteristics on player performance and player experience in different types of games.

Influence of Music on Human Behavior

Musical preference has been widely studied in the literature of psychology of art. According to Berlyne [START_REF] Berlyne | Aesthetics and psychobiology[END_REF], art can be expressed in terms of "aesthetics stimuli". The author suggested a theory in which the subjective experience of art, visually or auditory, may provoke a variation in arousal levels, both physiologically and psychologically. This variation of stimulation would be related to the characteristics of the experienced stimuli, such as their novelty, their complexity, or their tempo for example in the case of music. The preference one feels for any form of aesthetics stimulus would then be linked to the perceived degree of arousal.

Listening to music requires cognitive resources, music being a stimulus needing to be analyzed and processed. Konecni [START_REF] Konečni | Social interaction and musical preference[END_REF] studied the relation between musical preference and the listener's performance in a dual-task context. The author showed that the musical preference is influenced by the arousal provoked by music and also by the amount of cognitive resources available during the dual-task process. The more demanding a task is, the more intrusive a music is perceived, and the less it is appreciated.

The notion of musical preference is as well related to task performance. In a study conducted by Nantais and Schellenberg [START_REF] Nantais | The Mozart effect: An artifact of preference[END_REF], the participants performed significantly better a given task when they listened to a stimulus they like, may it had been Schubert or even a story narrated by Stephen King.

Influence of Music in Video Games

Further literature investigated the influence of music in human-computer interaction situations, and in particular in player-video game interaction. With the advances in technology, more and more studies have been published on video games and user experience. While most of them examine the visual aspect of the game interface (see [START_REF] Caroux | Player-video game interaction: A systematic review of current concepts[END_REF] for a review), a number of studies analyzed the auditory dimension of interactive games. For example, Nacke, Grimshaw and Lindley [START_REF] Nacke | More than a feeling: Measurement of sonic user experience and psychophysiology in a first-person shooter game[END_REF] have shown that the presence of sounds and/or music during gameplay was correlated to an increase of positive affects regarding subjective game experience and a decrease of negative ones. Several studies focused on the topic of musical preference. A study conducted by North and Hargreaves [START_REF] North | Music and driving game performance[END_REF] aimed to investigate the relation between music listening, musical preferences and performance in a concurrent task in a context of dual-task while playing a driving game. The authors found that the driving performance was lower when the participants had to listen to the high-arousal music while performing the concurrent task, due to a high cognitive workload. They also found that the driving performance was higher when the participants listened to the low-arousal music with no concurrent task. Finally, the authors reported higher ratings of music appreciation when there was no concurrent task to simultaneously perform. In line with Konecni [START_REF] Konečni | Social interaction and musical preference[END_REF], those results showed that musical preference in the context of task performance is related to the nature of the task, and to the cognitive resources available when listening.

More recent evidence of this phenomenon can be found in a study conducted by Cassidy and MacDonald [START_REF] Cassidy | The effects of music choice on task performance: A study of the impact of self-selected and experimenter-selected music on driving game performance and experience[END_REF]. The authors asked participants to perform a driving task in a video game. They were separated in 5 groups to compare several auditory conditions: no sound, car sounds alone, car sounds with the addition of self-selected music, car sounds with high-arousal music, and car sounds with low-arousal music. The authors found that the participants who had the opportunity to bring their own songs reported a higher level of appropriateness, lower levels of tension-anxiety, had a higher driving performance, and overall had a better user experience. They also found that the highest driving performance was found in the high-arousal music condition.

These studies showed that music is more than an additional information existing in the auditory dimension. It can be used as a tool to change levels of arousal as well as affects, thus having an effect in goal-oriented contexts. Depending on the task, one could allocate their preferences depending on the cognitive resources available. In the present study, those effects of music were investigated on a different type of material, to appreciate the external validity of previous studies.

The Present Study

The aim of the present study was to extend current knowledge of the effects of musical preference and arousal level of music on user experience and performance in video games. This investigation, in line with Konecni [START_REF] Konečni | Social interaction and musical preference[END_REF], aimed to measure the user experience and performance as well as taking into account the ecological choice of music self-selection according to the task to perform. Our experimental set up was based on the Cassidy and Macdonald's one [START_REF] Cassidy | The effects of music choice on task performance: A study of the impact of self-selected and experimenter-selected music on driving game performance and experience[END_REF]. The main differences are that, in the present study, enjoyment of players was measured with a specific questionnaire [START_REF] Fang | Development of an instrument to measure enjoyment of computer game play[END_REF], and that two different types of games were used, namely an action game and a puzzle game. Most of studies tended to focus on driving games [START_REF] North | Music and driving game performance[END_REF][START_REF] Brodsky | The effects of music tempo on simulated driving performance and vehicular control[END_REF]. With this in mind, our research tried to examine others contexts of video games to determine the external validity of past studies. The performance of players was measured in two distinct video games, as well as their subjective experience, several times under varying musical conditions for each session. There were three types of musical conditions: high-arousal music, low-arousal music and self-selected music. In this last condition, the music track was brought by the players. The user experience was measured using several existing questionnaires.

The following hypotheses were established on the basis of the previous literature described above. The first hypothesis was that the performance is overall better when participants are exposed to the music they select themselves in comparison to the other music conditions, for both types of games. The second hypothesis was that the subjective experience of players is better when exposed to self-selected music as compared to experimenter-selected music, for both types of games. The third hypothesis was selfselected music is more appreciated and perceived as more appropriate than other music conditions, for both types of games. The fourth hypothesis was that the player performance is better when high-arousal music is displayed during the action game than when low-arousal music is displayed, and vice-versa in the puzzle game. In a similar way, the fifth hypothesis was that high-arousal music is perceived as more appropriate in the action game than low-arousal music, and vice-versa in the puzzle game.

Methods

Participants

A total of 20 participants (10 women) from age 20 to 34 (M = 23.9, SD = 4.1) were recruited for the study. They were university students from various disciplines, recruited on a voluntary basis, with various gaming expertise.

Material

Music. The music tracks used in for the low-arousal and high-arousal conditions were selected from the study of Cassidy and MacDonald [START_REF] Cassidy | The effect of background music and background noise on the task performance of introverts and extraverts[END_REF] and prepared in advance. This choice allowed us to use an already empirically validated material. The different musical pieces used were "Distractions" from the album Simple Things (2002) of the band Zero 7 and "Attitude" from the album Roots (1996) of the band Sepultura. "Distractions" is a down-tempo music with a rhythm of 102 BPM and "Attitude" is a groove metal song with a rhythm of 155 BPM. Regarding the self-selected music, the participants were asked to choose a music before coming to the experimentation. They were asked to "choose a song they like, and that they would like to hear during the game session." Participants knew that the experiment was to play video games under several conditions, but they did not know the type of game in advance. Music was diffused with computer speakers.

Games. The selected video games were World of Goo (2D Boy, 2008) and Geometry Wars 3: Dimensions (Lucid Games, 2014). They were fairly recent and critically wellreceived. They were chosen for their typical genre-characteristics. World of Goo is a puzzle video game, where the goal is to assemble small creatures called "Goos" into structures, in order to lead them through an exit pipe. This game has a static environment, meaning that the situation on screen only moves when the players enter an input. Geometry Wars 3: Dimensions is an action video game, in which the player controls a spaceship and must earn the highest score possible by destroying enemies' spaceships. This game has a dynamic environment, meaning that the situation evolves independently from the players' action, and they have to adapt and react to it. For the action game, the instruction was to "destroy as many ships as possible while dying the least possible during 3 minutes" and for the puzzle game, it was to "finish the level as fast as possible using as few moves as possible". For this experimentation, only the music was manipulated. The original game sounds (coming from environment, enemies, effects, etc.) were not manipulated. They were always presented during the game sessions.

Questionnaire. The questionnaire was composed of items from the Fang et al.'s "instrument to measure enjoyment of computer game play" [START_REF] Fang | Development of an instrument to measure enjoyment of computer game play[END_REF], and from the study of Cassidy and MacDonald [START_REF] Cassidy | The effects of music choice on task performance: A study of the impact of self-selected and experimenter-selected music on driving game performance and experience[END_REF], which assesses the players' perception of music in a video game and their global play experience. The Fang et al.'s [START_REF] Fang | Development of an instrument to measure enjoyment of computer game play[END_REF] instrument aims to assess the level of enjoyment, by focusing on 3 dimensions affecting the user experience during gameplay: the affective aspect (related to emotions and feelings), the behavioral aspect (related to the behavior during the game session) and the cognitive aspect (related to the judgment of game elements by the player). We present only the affective dimension in the present paper. The questionnaire included 11 items (Table 1), which had to be rated on a 10-point Likert scale.

Table 1. Items used for the questionnaire.

Study of origin Dimension Item

Fang et al. [START_REF] Fang | Development of an instrument to measure enjoyment of computer game play[END_REF] Affective aspect of enjoyment 1. I feel unhappy when playing this game 2. I feel worried when playing this game 3. I feel happy when playing this game 4. I feel exhausted when playing this game 5. I feel miserable when playing this game Cassidy and MacDonald [START_REF] Cassidy | The effects of music choice on task performance: A study of the impact of self-selected and experimenter-selected music on driving game performance and experience[END_REF] Global experience 6. I felt distracted while playing 7. I enjoyed the game experience Music perception 8. I liked the music during playing 9. I felt the music was familiar 10. I felt the music was appropriate for the task 11. I found the music arousing

Design and Procedure

The type of music (low-arousal vs. high-arousal vs. self-selected) and the genre of game (action vs. puzzle) were manipulated as within-participants factors. Once recruited, participants did not know which type of video game they were going to play to. Depending on the sessions' order, the respective video game was presented to the participant, as well as the instructions. The order of the game sessions was counter-balanced. Controls, using keyboard and mouse only, were explained before proceeding. After a training session without any music presented, the experiment began. Each participant completed 6 game sessions. The experiment was segmented in two blocks of 3 sessions for each game, each session corresponding to a different music condition. The order of music conditions was also counter-balanced for each participant. After each session, participants had to fill the subjective experience questionnaires. After 3 sessions with the first game presented, participants were then presented the second game of the experiment, with the same procedure. The mean time of a game session was 2 minutes, without the time of completing the questionnaire.

Dependent Variables

Performance indicators used for the action game were the score and the number of destroyed enemies for each session. The elapsed time as well as the number of moves done for each session were used for the puzzle game. The subjective experience of the participants was assessed with the answers given for each item of the questionnaire.

Results

Performance

The performance indicators were analyzed separately for each game because they were not similar and thus not readily comparable. A repeated measures ANOVA was carried out to investigate the differences between the music conditions on defined performance indicators. The ANOVA carried out did not present any significant difference for the score nor for the number of deaths in the action game, and neither for the elapsed time nor for the number of moves in the puzzle game.

Questionnaire

Items of the questionnaires were analyzed with the two independent variables, namely the type of music and the type of game, as well as their interaction. Repeated measures ANOVAs were performed for all items of the questionnaires.

Affective Aspect of Enjoyment. For Item 3 "I feel happy when playing this game", the main effect of the type of music F(2,38) = 6.10, p < .01, η²p = .24 on the answers of participants, as well as the interaction between the type of music and the type of game, F(2,38) = 5.08, p < .01, η²p = .21, were significant. As shown in Figure 1, participants reported more positive affect when exposed to self-selected music compared to other types of music for both types of game. It was also observed that in the action game, participants reported more positive affect with the high-arousal music than the lowarousal music, and vice-versa for the puzzle game. For Item 2 "I feel worried when playing this game", there was a significant difference of the type of game F(1,19) = 4.96 , p < .05, η²p = .21 on the answers of participants, in the sense that the participants reported higher scores when playing the action game than the puzzle game. However, there were no significant difference between the types of music F(2,38) = 1.09, p = .35. The interaction between these two factors did not reach significance F(2,38) < 1, p = .85.

For the other items (1, 4 and 5), none of the observed differences were statistically significant neither for the type of game, nor for the type of music, or their interactions. 1, participants appreciated the most their self-selected music for both types of game. It was also observed that in the action game, participants appreciated more the low-arousal music in the puzzle game than in the action game. For Item 10, "I felt the music was appropriate for the task", there was a significant difference between the two types of music F(2,38) = 15.52, p < .001, η²p = .45 as well as an interaction between the type of music and the type of game F(2,38) = 9.54, p < .001, η²p = .33. Figure 1 shows that self-selected music was perceived as more appropriate than the other types of music, independently from the type of game. Moreover, high-arousal music was perceived as more appropriate in the action game than in the puzzle game, and vice-versa for the low-arousal music. The analysis did not reveal any significant differences between the types of games F(1,19) = .87, p = .36.

The results for Item 11 "I found the music arousing" revealed a significant difference between the type of music F(2,38) = 39.32, p < .001, η²p = .67 and the type of game F(1,19) = 8.16, p < .01, η²p = .30. There was also a significant interaction between the two variables F(2,38) = 3.57, p < .05, η²p = .16. As shown in Figure 1, self-selected music was perceived as more arousing than the other types of music for both types of game. Moreover, there was a significant difference of perceived arousal between higharousal and low-arousal music in the action game, but none in the puzzle game.

For Item 9 "I felt the music was familiar", there was a significant difference between the type of music F(2,38) = 70.54, p < .001, η²p = .79, in the sense that participants reported higher scores for the self-selected music than the other music conditions, but none for the type of game F(1,19) = 1.49, p = .24 or for the interaction of the two variables F(2,38) = 1.14, p = .33. Global Experience. Item 6 "I felt distracted while playing" showed a significant difference between the types of games F(1,19) = 10.70, p < .01, η²p = .36, in the sense that players reported higher scores when playing the puzzle game than the action game, but none for the type of music F(2,38) = 2.10, p = .14 or for the interaction of the two variables F(2,38) = 2.32, p = .112.

Item 7 "I enjoyed the game experience" also showed a significant difference between the types of games F(1,19) = 4.84, p < .05, η²p = .20, in the sense that players reported higher scores when playing the action game than the puzzle game, but none for the type of music F(2,38) = 2.20, p = .13 or for the interaction of the two variables F(2,38) = 1.23, p = .30.

Discussion

The first hypothesis was not supported. The results did not show any significant difference in the performance indicators defined in both video games. Those findings differ from those found by Cassidy and MacDonald [START_REF] Cassidy | The effects of music choice on task performance: A study of the impact of self-selected and experimenter-selected music on driving game performance and experience[END_REF]. Such results could be explained by the level of expertise of participants and the genre of games. Many studies only examined the effects of music in driving games [START_REF] Cassidy | The effects of music choice on task performance: A study of the impact of self-selected and experimenter-selected music on driving game performance and experience[END_REF][START_REF] North | Music and driving game performance[END_REF][START_REF] Brodsky | The effects of music tempo on simulated driving performance and vehicular control[END_REF]. The difference could be linked to the nature of the task. Playing a driving game requires skills acquired in real life, as compared to the skills required for playing a game like a FPS. Because of that, even if some participants are not considered as video game experts, their driving experience could play a role for the task. The second hypothesis was partially supported. The item 3 "Felt happy" of the questionnaire provided significant differences between self-selected music and the other conditions, in the sense that participants reported more positive affect when exposed to self-selected music, as compared to the other music conditions. Those results are in line with Cassidy and MacDonald's [START_REF] Cassidy | The effects of music choice on task performance: A study of the impact of self-selected and experimenter-selected music on driving game performance and experience[END_REF] findings. However, the analysis did not confirm any significant differences for the items related to the anxiety, distraction or overall user experience, namely items 2, 6 and 7. Even though those findings are not in line with previous work [START_REF] Cassidy | The effects of music choice on task performance: A study of the impact of self-selected and experimenter-selected music on driving game performance and experience[END_REF][START_REF] North | Music and driving game performance[END_REF], it can be supposed that only the affective aspect of the enjoyment was affected by the musical preference of participants. It is plausible that the length of our games sessions, being in average two minutes each, which was relatively short, played a role in those results. It can be then assumed that duration of gameplay has an effect on attentional and cognitive factors involved in the user experience.

The third hypothesis was supported. The musical preference effect found by Cassidy and MacDonald [START_REF] Cassidy | The effects of music choice on task performance: A study of the impact of self-selected and experimenter-selected music on driving game performance and experience[END_REF] was also present in this study, in the sense that self-selected music was the most favorite for participants. This reinforce the external validity of this effect.

The fourth hypothesis was not supported. Contrary to findings of the previous literature about driving games [START_REF] Cassidy | The effects of music choice on task performance: A study of the impact of self-selected and experimenter-selected music on driving game performance and experience[END_REF], player performance was not improved by the music that would be appropriate for the game genre.

The fifth hypothesis was supported. Interactions between the type of music and the type of game presented were observed regarding music perception (items 8 and 10) and the positive affect reported by the participants (item 3). The low-arousal music condition was linked to better perception and higher levels of positive affect than the higharousal music condition in the puzzle game, and the opposite for the action game. One could assume that what was observed was merely an aesthetics preference regarding the arousal levels of our material. Nevertheless, self-selected music and high-arousal music were both perceived as more arousing in the action game than in the puzzle game (item 11). This provides further evidence for an interaction between the musical stimuli and the environment presented to the participant. It may mean than the perception of an auditory environment could vary in function of a person's user experience. Such results underline the importance of investigating the effects of music on video games experience, to better understand the underlying mechanisms.

Conclusions and Outlook

In this paper, the effects of self-selected music and the arousal level of music on performance and subjective experience in video games were investigated. The findings suggested that participants rate self-selected music as more appropriate, more agreeable to listen to, more arousing, and linked to more positive affect, in both the action and the puzzle games. Our results share a number of similarities with Cassidy and MacDonald's [START_REF] Cassidy | The effects of music choice on task performance: A study of the impact of self-selected and experimenter-selected music on driving game performance and experience[END_REF] findings, notably about the musical preference effect and the link between self-selected music and positive affect. Although our study did not confirm previous results on the effects of music in video game performance, it highlighted interactions between the types of music presented and the types of game in user experience. The difference observed with the two types of games underline the importance of keeping in mind that video games do not follow a standard model when it comes to game experience, and each game will solicit different cognitive resources and trigger different behaviors depending on the players. This is part of what makes this field interesting to study, but also what raises many questions about the measurement of game experience [START_REF] Fang | Development of an instrument to measure enjoyment of computer game play[END_REF][START_REF] Jennett | Measuring and defining the experience of immersion in games[END_REF]. The hypotheses presented to explain the difference in findings from other studies [START_REF] Cassidy | The effects of music choice on task performance: A study of the impact of self-selected and experimenter-selected music on driving game performance and experience[END_REF] should be taken into account for future studies, in order to determine the interactions between audio and game experience. Not much is known about the auditory dimension in video games [START_REF] Caroux | Player-video game interaction: A systematic review of current concepts[END_REF].

With advances in technology, several video games now offer the possibility to customize the soundtrack, such as the Grand Theft Auto series (Rockstar Games) or Audiosurf 2 (Invisible Handbar, 2015). It is then worthwhile to consider that aspect of user experience during game development. Extending this practice other types of games, such as sports games or fighting games for example, would allow both developers to manipulate the level of arousal depending of the experience intended, and players to benefit from a more tailored game experience.

Fig. 1 .

 1 Fig. 1. Mean ratings for the items 3, 8, 10 and 11 for each type of game and type of music. The error bars represent standard errors.