Antonin Lavigne

Benoît Gilquin

Thomas Gehin

Vincent Jousseaume

Marc Veillerot

Yann Chevolot

Magali Phaner-Goutorbe

Christelle Yeromonahos
email: christelle.yeromonahos@ec-lyon.fr

Thomas Géhin

Effects of Silane Monolayers on Lysophosphatidylcholine (LysoPC) Detection by Desorption Ionization on Silicon Mass Spectrometry (DIOS-MS) in Solution and Plasma

Keywords: Desorption ionization on silicon mass spectrometry, Silane monolayer, Porous silicon, Lysophosphatidylcholine, Blood plasma, Time-of-flight secondary ion spectrometry, Sepsis

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Introduction

Several metabolites, such as amino acids and fatty acids, are biomarkers of a large range of inflammatory diseases. Indeed their blood concentrations are highly correlated to the type and to the stage of the illness. [1][START_REF] Wang | Correlation of Serum Hepcidin Levels with Disease Progression in Hepatitis B Virus-Related Disease Assessed by Nanopore Film Based Assay[END_REF][START_REF] Long | Metabolite Biomarkers of Type 2 Diabetes Mellitus and Pre-Diabetes: A Systematic Review and Meta-Analysis[END_REF] Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-ToF MS), a soft ionization process, is widely used to detect and analyse high molecular weight species with a very high sensitivity, as low as few ng/mL. [START_REF] Zenobi | Ion Formation in MALDI Mass Spectrometry[END_REF][START_REF] Dreisewerd | The Desorption Process in MALDI[END_REF] However, in the case of low molecular weight molecules, like metabolites, matrix peaks induce an important background noise that can interfere with the analyte peaks and limit their signal-tonoise (S/N) ratio. Moreover, to allow MALDI-ToF MS detection of metabolites from blood samples, long pre-treatment protocols of blood samples are required to remove abundant high molecular weight species. These limitations may induce artefacts and prevent the use of MALDI-ToF MS for the rapid detection of blood metabolites, as required for instance in the case of sepsis diagnosis.

In this context, a set of surface-assisted laser desorption ionization-MS (SALDI-MS) methods, which are matrix free strategies, has been developed. [START_REF] Sunner | Graphite Surface-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry of Peptides and Proteins from Liquid Solutions[END_REF] These techniques use the nanostructuration of the substrate to desorb and ionize analytes. Even though, for now, no consensus has been found on the exact mechanism involved [START_REF] Müller | Surface-assisted Laser Desorption/Ionization Mass Spectrometry Imaging: A Review[END_REF] , it is well established that the substrates need a strong absorbance in the UV region, a low heat capacity and a reduced thermal conductivity to allow the desorption and the ionization of the analytes. [START_REF] Picca | Mechanisms of Nanophase-Induced Desorption in LDI-MS. A Short Review[END_REF] Several type of nanostructured substrates, such as gold [START_REF] Duan | On-Plate Desalting and SALDI-MS Analysis of Peptides with Hydrophobic Silicate Nanofilms on a Gold Substrate[END_REF][START_REF] Fournelle | Minimizing Visceral Fat Delocalization on Tissue Sections with Porous Aluminum Oxide Slides for Imaging Mass Spectrometry[END_REF] , silver [START_REF] Baquer | An Open-Source Tool for Matrix-Related Peak Annotation in Mass Spectrometry Imaging and Its Application to Silver-Assisted Laser Desorption/Ionization[END_REF][START_REF] Lauzon | Development of Laser Desorption Imaging Mass Spectrometry Methods to Investigate the Molecular Composition of Latent Fingermarks[END_REF] and alumina [START_REF] Fournelle | Minimizing Visceral Fat Delocalization on Tissue Sections with Porous Aluminum Oxide Slides for Imaging Mass Spectrometry[END_REF][START_REF] Baquer | An Open-Source Tool for Matrix-Related Peak Annotation in Mass Spectrometry Imaging and Its Application to Silver-Assisted Laser Desorption/Ionization[END_REF][START_REF] Kuwata | DIUTHAME Enables Matrix-free Mass Spectrometry Imaging of Frozen Tissue Sections[END_REF] , have been used in SALDI-MS due to their optical properties. Carbon-based nanostructure [START_REF] Kim | Synergistic Effect of Graphene Oxide/MWCNT Films in Laser Desorption/Ionization Mass Spectrometry of Small Molecules and Tissue Imaging[END_REF][START_REF] Abdelhamid | A Method to Detect Metal-Drug Complexes and Their Interactions with Pathogenic Bacteria via Graphene Nanosheet Assist Laser Desorption/Ionization Mass Spectrometry and Biosensors[END_REF] and silicon [START_REF] Guinan | Comparison of the Performance of Different Silicon-Based SALDI Substrates for Illicit Drug Detection[END_REF][START_REF] Budimir | The Use of Desorption/Ionization on Porous Silicon Mass Spectrometry for the Detection of Negative Ions for Fatty Acids[END_REF][START_REF] Jemere | Matrix-Free Laser Desorption/Ionization Mass Spectrometry Using Silicon Glancing Angle Deposition (GLAD) Films: Matrix-Free LDI-MS Using Silicon GLAD Films[END_REF][START_REF] Trauger | High Sensitivity and Analyte Capture with Desorption/Ionization Mass Spectrometry on Silylated Porous Silicon[END_REF][START_REF] Zhou | Salt Segregation and Sample Cleanup on Perfluoro-Coated Nanostructured Surfaces for Laser Desorption Ionization Mass Spectrometry of Biofluid Samples[END_REF][START_REF] Dupré | Investigation of Silicon-Based Nanostructure Morphology and Chemical Termination on Laser Desorption Ionization Mass Spectrometry Performance[END_REF][START_REF] Singh | Engineering Matrix-Free Laser Desorption Ionization Mass Spectrometry Using Glancing Angle Deposition Films: Matrix-Free LDI Using GLAD Films[END_REF] have also been reported.

Desorption Ionization On Silicon-MS (DIOS-MS), first introduced by Wei et al. [START_REF] Wei | Desorption-Ionization Mass Spectrometry on Porous Silicon[END_REF] , is one of these technics using the porosity of porous silicon substrate for the ionization of the analytes, decreasing drastically the background noise in the metabolite mass range (0-1000 Da) compared to MALDI-ToF MS. Also, by tuning the size of the pores, it is possible to sterically exclude high molecular weight species from the sample, avoiding long pre-treatment protocols. [START_REF] Bouamrani | Mesoporous Silica Chips for Selective Enrichment and Stabilization of Low Molecular Weight Proteome[END_REF][START_REF] Wang | Rapid Liquid-Phase Microextraction of Analytes from Complex Samples on Superwetting Porous Silicon for Onsite SALDI-MS Analysis[END_REF] This would, for instance, prevent the need of several solvents for the extraction of high molecular weight molecules [START_REF] Yang | Detection of Serum Phospholipids by Microchannel-Integrated Black Phosphorus-Assisted Laser Desorption/Ionization Mass Spectrometry[END_REF][START_REF] Gao | N-Phosphorylation Labeling for Analysis of Twenty Natural Amino Acids and Small Peptides by Using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry[END_REF] or the labelling of the analytes of interest with more easily ionisable molecules [START_REF] Gao | N-Phosphorylation Labeling for Analysis of Twenty Natural Amino Acids and Small Peptides by Using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry[END_REF] for human sample analysis. So, DIOS-MS seems to be promising for the metabolite detection in a clinical diagnosis context.

Silane molecules are widely used to functionalize the surface of bio-analytical devices. [START_REF] Lecot | Impact of Silane Monolayers on the Adsorption of Streptavidin on Silica and Its Subsequent Interactions with Biotin: Molecular Dynamics and Steered Molecular Dynamics Simulations[END_REF][START_REF] Lecot | Curious Binding Energy Increase between the Receptor-Binding Domain of the SARS-CoV-2 Spike Protein and Angiotensin-Converting Enzyme 2 Adsorbed on a Silane Monolayer from Molecular Dynamics Simulations[END_REF][START_REF] Lecot | Arrangement of Monofunctional Silane Molecules on Silica Surfaces: Influence of Alkyl Chain Length, Head-Group Charge, and Surface Coverage, from Molecular Dynamics Simulations, X-Ray Photoelectron Spectroscopy, and Fourier Transform Infrared Spectroscopy[END_REF][START_REF] Lecot | Effects of the Chemical and Structural Properties of Silane Monolayers on the Organization of Water Molecules and Ions at Interfaces, from Molecular Dynamics Simulations[END_REF][START_REF] Wang | Surface Chemical Reactions on Self-Assembled Silane Based Monolayers[END_REF] In addition, silane monolayers allow to prevent from uncontrolled oxidation porous silicon surfaces and allow to improve the DIOS-MS limit of detection (LoD) of specific metabolites. [START_REF] Iakab | Silicon-Based Laser Desorption Ionization Mass Spectrometry for the Analysis of Biomolecules: A Progress Report[END_REF] For instance, amino-silane monolayers, with hydrophilic head groups, were shown to be well suited for the specific detection of hydrophilic molecules, whereas hydrophobic monolayers were shown to improve the detection of any molecules whatever their hydrophobicity. [START_REF] Trauger | High Sensitivity and Analyte Capture with Desorption/Ionization Mass Spectrometry on Silylated Porous Silicon[END_REF] Also, Guinan et al. have shown that tridecafluoro-1,1,2,2-tetrahydrooctyldimethylchlorosilane (F 13 ) onto porous silicon enhances the detection of cocaine and methadone from water, down to 100ng/mL. [START_REF] Guinan | Comparison of the Performance of Different Silicon-Based SALDI Substrates for Illicit Drug Detection[END_REF] Moreover, scarce studies have shown that silanized porous silicon surfaces enable the detection of specific metabolites from complex human fluids, without any pre-treatments of the sample: a drop of fluid is deposited on the silanized porous silicon surface, high molecular weight species are washed from the surface with solvent, and then metabolites are analysed by DIOS-MS. In particular, Alhmoud et al. have shown, using this protocol, that porous silicon surfaces functionalized with F 13 allow methadone detection from saliva, urine, and plasma for patients treated with this drug. [START_REF] Alhmoud | Surface-Assisted Laser Desorption/Ionization Mass Spectrometry Using Ordered Silicon Nanopillar Arrays[END_REF] Consequently, it is hypothesized that silane monolayers provide a better selective metabolite adsorption, desorption, and/or ionization. Nevertheless, to the best of our knowledge, the effects of the alkyl chain length of the silane molecules on the DIOS-MS detection of metabolites have never been investigated. Also, even if it is well established that the presence of pores is essential to get a DIOS-MS signal, the effects of the location of the metabolites (inside the pores or on the surface outside the pores) on the DIOS-MS signal have never been studied. Finally, there is only one previous study, the one of Alhmould et al., which has shown the possibility to detect a specific metabolite from plasma without any pre-treatment of the sample.

Lysophosphatidylcholine (LysoPC) is a biomarker for most of inflammatory diseases that is very well detected by mass spectrometry in model solutions. 1,[START_REF] Park | MALDI-TOF Mass Spectrometry Based on Parylene-Matrix Chip for the Analysis of Lysophosphatidylcholine in Sepsis Patient Sera[END_REF] The present study investigates the effects of two different silane monolayers on the LysoPC detection by DIOS-MS in solution and in plasma. The two silane molecules studied are n-propyldimethylmetoxysilane (named CH 3 short in this study) and octadecyldimethylmetoxysilane (named CH 3 long) (Table 1).

Those silane molecules are monovalent, they have different alkyl chain lengths, and they were self-assembled in monolayers on porous silicon surfaces (pores of 10 nm in diameter and 1 µm in depth). The effects of the silanes monolayers, and of the bare silicon substrate, on the LysoPC detection from solution, were correlated both to the chemical properties of LysoPC and to its location inside/outside the pores. Then, the possibility of detecting LysoPC, by DIOS-MS, from a drop of plasma, using silanized porous silicon substrate without any pre-treatment of the sample, is demonstrated. Gas Phase Chemical Surface Functionalization. The porous silicon substrates were cleaned by ozone/ultraviolet treatment at room temperature under an oxygen flow for 30 minutes. Next, the substrates were placed in a vacuum chamber at 150°C for 30 minutes and then allowed to cool at room temperature under nitrogen atmosphere. 100 µL of silane were injected in the reaction chamber and put under vacuum while the temperature was gradually increased to 150°C. After one hour of silanisation, the chamber was pumped for 15 minutes, then the substrates were allowed to cool under nitrogen atmosphere until room temperature was reached.

Finally, the samples were washed for 10 minutes in THF and 10 minutes in ultrapure water.

LysoPC preparation. For LysoPC detection in solution, LysoPC was dissolved in a solution of chloroform/methanol (2:1 v/v) at 1 mg/mL. For LysoPC detection in plasma, LysoPC was spiked in plasma at 50 µg/mL and 500 µg/mL. Spiked plasma was prepared from a solution of LysoPC at 10 mg/mL in chloroform/methanol (2:1 v/v).

DIOS-MS Analysis. DIOS mass spectra were obtained using an UltrafleXtreme MALDI-TOF/TOF (Bruker Daltonics) equipped with a laser (355 nm). The silicon substrates were held on a modified MALDI target plate using copper tape. Ions were detected in reflectron positive (RP) or reflectron negative (RN) ion mode at ± 20 kV accelerating potential. The laser was set on the large size with a grid voltage of 100 % for RP and RN ion modes. The m/z range was 10-800 Da. A 1 µL droplet of the solution, or of the spiked plasma, was deposited on the surface for 1 min. In the case of the plasma samples, the surface was washed with water, one minute after plasma deposition. The washing was done by pipetting 5 µL of ultrapure water on the surface. Surface imaging was performed using the FlexImaging 3.0 software (Bruker Daltonics) with a spatial resolution of 200 µm (40 spots per droplet in solution and 100 spots per droplet in plasma). For each spot, 500-satisfactory laser shots were averaged to obtain a mass spectrum.

The spectra were analysed using the FlexAnalysis Bi 3+ ion gun operation at 15 keV was used as the primary probe for analysis (rastered area 80 × 80 μm 2 ). For depth profiling, sputtering was performed using Cs + ions at low energy (500 eV, rastered area 400 × 400 μm 2 ). Spectra were normalized using the intensity of the [START_REF] Lecot | Arrangement of Monofunctional Silane Molecules on Silica Surfaces: Influence of Alkyl Chain Length, Head-Group Charge, and Surface Coverage, from Molecular Dynamics Simulations, X-Ray Photoelectron Spectroscopy, and Fourier Transform Infrared Spectroscopy[END_REF] Si -ions in the silicon bulk region.

Results and Discussions

LysoPC detection in solution

LysoPC was firstly studied alone in solution, to identify its m/z characteristic peaks in DIOS-MS, and to investigate the effects of silane monolayers on its detection. Firstly, in the absence of matrix, no signal was obtained using non porous substrates (bare silicon, silanized silicon or even the classical stainless steel MALDI target plate).

The spectra obtained in RP ion mode, using the two silanized porous surfaces and the bare porous silicon surface, are presented in Figure 1 phosphocholine-related ion (phosphocholine + CH 2 ) respectively. [START_REF] Chughtai | Mass Spectrometry Images Acylcarnitines, Phosphatidylcholines, and Sphingomyelin in MDA-MB-231 Breast Tumor Models[END_REF] The main fragment is the one at 86.0 m/z, whatever the surface studied. The silanized surfaces lead to higher intensities, for each fragment peak, than the bare silicon surface. Moreover, the highest intensities are mainly obtained in the case of the CH 3 short monolayer. Indeed the relative intensities for the peaks at 86.0 m/z, 104.0 m/z, 184.1 m/z, and 198.2 m/z are 1, 0.31, 0.18, 0.12 respectively (in the case of the CH 3 short monolayer), 0.77, 0.24, 0.07, 0.17 respectively (in the case of the CH 3 long monolayer), and 0.46, 0.12, 0.17, 0.04 respectively (in the case of the bare silicon substrate).

To explain these results, the location of LysoPC, inside/outside the pores of the three different substrates, was investigated by depth profiling ToF-SIMS analysis of the P -ion (characteristic of LysoPC, 30.9682 amu) along the pores. Our ToF-SIMS spectra (Figure 2) demonstrate a significantly higher intensity of P -ions inside the pores of the bare silicon substrate and inside the pores functionalized with the CH 3 short monolayer than inside the pores functionalized with the CH 3 long monolayer. This result suggests that the trapping of LysoPC inside the pores improves the effective local and direct ionization of LysoPC molecules, leading to fragment peaks with high intensity in DIOS-MS analysis. In the case of silicon substrates functionalized with long alkyl chains silane, LysoPC molecules remain outside the pores and are indirectly ionized thanks to the transfer of the laser energy accumulated inside the pores. So, even if the laser energy transfer to the surface is sufficient to get a signal, a higher signal is obtained through local ionization when the molecules are trapped inside the pores. Also, LysoPC is a highly hydrophobic zwitterionic molecule containing two functional groups that are charged at pH 7 (a quaternary ammonium positively charged and a phosphate negatively charged in the phosphocholine side of the molecule), as shown in Figure 3. Consequently, it seems reasonable to assume that the positively charged groups of LysoPC will be more easily fragmented when

LysoPC is adsorbed on the CH 3 short monolayer than on the negatively charged bare silicon surface, explaining the lower intensity of fragment peaks on the bare silicon surface than on CH 3 short modified porous silicon. On the contrary to fragment peaks, the peak at [M+H] + has a higher intensity on the CH 3 long monolayer and on the bare silicon surface than on the CH 3 short monolayer. This result could be explained by an improved desorption of the entire LysoPC molecules outside the pores of hydrophobic substrates (case of CH 3 long monolayer), as well as from the pores of hydrophilic surfaces (case of bare silicone surface), than from the pores of hydrophobic substrates (case of CH 3 short monolayer).

In RN ion mode, depicted in Figure 4 [START_REF] Pulfer | Electrospray Mass Spectrometry of Phospholipids[END_REF] The intensity of these fragments is higher on the CH 3 long monolayer than on the CH 3 short monolayer and on the bare silicon surface. Indeed, the relative intensities of the peaks at 79.0 m/z, 123.1 m/z, 153.1 m/z, and 283.6 m/z are 0.28, 0.02, 0.03, 0.01 respectively (in the case of the CH 3 short monolayer), 0.61, 0.08, 0.24, 0.38 respectively (in the case of the CH 3 long monolayer), and 0.34, 0.07, 0.04, 0.02 respectively (in the case of the bare silicon substrate). These results suggest that LysoPC trapping inside the pores strongly decreases the detection signal. Thus, it could be more difficult to extract the negatively charged fragments from the pores than the positively charged fragments. Moreover, the larger the fragments, the more difficult it will be to extract them. Indeed, the largest fragment (at 283. S1-S3). Total ion current (TIC) normalization is used. S1-S3). TIC normalization is used.

LysoPC detection from Blood Plasma

LysoPC is present in plasma under physiological conditions at 26µg/mL. [START_REF] Drobnik | Plasma Ceramide and Lysophosphatidylcholine Inversely Correlate with Mortality in Sepsis Patients[END_REF] To assess its DIOS-MS detection, 50µg/mL and 500µg/mL of LysoPC were spiked in plasma, and mass spectra of the spiked plasma were compared to the ones of the unmodified plasma. It ensures that the panel of fragments analysed is related to the ones of LysoPC.

Spiked plasma was firstly investigated in RN ion mode, since this mode is expected to yield a lower signal background than the RP ion mode. It should be noted that, after plasma deposition, no peak was detected (Figure S4) if the samples were to be analysed as deposited. Several washing protocols were evaluated on the CH 3 short monolayer surface: one, three, and ten water droplets (5 µL) were pipetted one time on the surface (1x1, 3x1, 10x1 protocols) ; two, three, and five water droplets (5 µL) were pipetted five times on the surface (2x5, 3x5, 5x5 protocols)

; and five water droplets (5 µL) were pipetted two times on the surface (5x2 protocol). The 3. For all surfaces, no peaks are detected above 300 m/z. Moreover, the CH 3 short monolayer leads to the highest intensity for most of the LysoPC fragments (the relative intensities of the peaks at 79.0 m/z and 123.1 m/z are 2.46*10 -2 and 2.50*10 -3 respectively on CH 3 short, and 3.28*10 -3 and 1.80*10 -3 respectively on the bare silicon substrate), except the one at 153.1 m/z that has a slightly higher intensity on the bare porous silicon (1.52*10 -2 on CH 3 short and 2.13*10 -2 on the bare silicon substrate). No significant peak was observed on the CH 3 long monolayer. The absence of signal on the CH 3 long monolayer could be explained by the removal of LysoPC molecules, which are mainly outside the pores, during the water washing (using the 5x5 protocol as well as any other protocol). In the case of the CH 3 short monolayer and of the bare silicon surface, LysoPC molecules trapped into the pores are protected from washing. Indeed, ToF-SIMS profiling analysis have shown that the presence of P -ions along the pores is not impacted by water washing (Figure S7). Figure 6 presents the peaks of LysoPC fragments detected in RN ion mode, in plasma with and without spiking of LysoPC (spiking at 50µg/mL and at 500µg/mL) on the CH 3 short monolayer, by using the 5x5 washing protocol. Same fragments of LysoPC are detected in the spiked plasma as in the unmodified plasma, with higher intensity in the spiked plasma. Indeed, the relative intensities of the peaks at 79.0 m/z, 123.1 m/z, and 153.1 m/z are 8.00*10 -2 , 1.61*10 -2 , 6.59*10 -2 respectively in the 500µg/mL spiked plasma, 2.46*10 -2 , 2.50*10 -3 , 1.52*10 -2 respectively in the 50µg/mL spiked plasma, and 1.13*10 -2 , 1.67*10 -3 , 8.61*10 -3 respectively in the unmodified plasma (Table 4). These results demonstrate the possibility to detect LysoPC in the unmodified plasma sample, by using the CH 3 short monolayer, in RN ion mode. Also, as demonstrated in Figure 5, no significant peak is observed above 300 m/z and adducts are not detected.

Nevertheless, a fragment peak attributed to the silane molecules is observed, with high relative intensity (5.00*10 -2 on CH 3 short, and 3.30*10 -2 on the bare silicon substrate). In the context of clinical diagnosis, it could be relevant to maximize the number of LysoPC fragments analysed (for sensitivity optimization). Consequently, the possibility to detect LysoPC in RP ion mode using the CH 3 short monolayer was investigated. Mass spectra of the unmodified plasma on the CH 3 short monolayer in the RP ion mode, by using the 5x5 washing protocol, is presented 4). Also, no signal is obtained above 300 m/z, adducts and substrates are not detected. These results demonstrate the possibility to detect LysoPC in the unmodified plasma sample, by using the CH 3 short monolayer, both in RP and in RN ion modes. This method might be used to detect the drastic decrease in phospholipids concentration in case of sepsis diagnosis.

Conclusions

The DIOS-MS detection of LysoPC, both in solution and in plasma, is demonstrated through the analysis of LysoPC fragments. The use of porous silicon substrate is essential to get a signal.

Also, porous silicon substrates chemically modified by silane monolayers lead to higher signal intensity than bare porous silicon substrates.

In solution, the signal background, is shown to be lower in RN ion mode than in RP ion mode, both by using chemically functionalized substrates and bare silicon substrates. Moreover, in RN ion mode LysoPC molecules outside the pores are better detected than the ones trapped inside the pores.

On the contrary, in plasma, water washing of the surface, after plasma deposition, is required for LysoPC detection. Consequently, only LysoPC molecules trapped inside the pores are detected by DIOS-MS in plasma. Indeed, no signal is obtained by using plane silicon surfaces, or porous surfaces functionalized with long alkyl chain silane monolayers which prevent LysoPC trapping inside the pores, whatever the washing protocols used. The CH 3 short monolayer is demonstrated to be well suited for the detection, in RN ion mode, of LysoPC molecules which are physiologically present in unmodified plasma samples. In addition, this monolayer allows the detection of LysoPC fragments also in RP ion mode. Moreover, the detection does not require any pre-treatment of plasma samples. Thus, porous silicon surfaces functionalized with CH 3 short monolayer could be highly promising for clinical diagnosis of sepsis, an inflammatory disease partly characterized by a drastic decrease in blood phospholipids, in few minutes, from a drop of plasma. Further investigations of the effect of

  3.4 software (Bruker Daltonics) for peaks detection. The mass spectra of each spot are averaged to determine the peak intensities. To evaluate the error bars, spots are randomly divided in two sets, and mass spectra are averaged inside each set. The difference in peak intensity between the two half sets of data corresponds to the error bars. Time of flight -secondary ions mass spectrometry (ToF-SIMS) profiling. High resolution mass depth profiles were acquired by ToF-SIMS (ToF-SIMS V from ION-TOF). A bunched

  6 m/z) is poorly detected on the CH 3 short monolayer (relative intensity 0.01) and on the bare silicon surface (relative intensity 0.02), while the smallest fragment (at 79.0 m/z) is detected (relative intensities 0.28 and 0.34 on CH 3 short and on the bare silicon substrate respectively), and the intermediate fragments (at 123.1 m/z and 153.1 m/z) are slightly detected (relative intensities 0.02 and 0.03 respectively on CH 3 short and 0.07 and 0.04 respectively on the bare silicon substrate).Consequently, for the detection of LysoPC from a model solution, the CH 3 short and the CH 3 long monolayers are more promising than the bare silicon surface, since these monolayers lead to the highest fragment peak intensities (in RP and RN ion mode respectively). Moreover, in model solution, the RP ion mode should be privileged since it allows the detection of LysoPC at [M+H] + contrary to the RN ion mode. However, the RN ion mode allow to decrease the background signal in comparison to the RP ion mode. Consequently, in the following, the RN ion mode was used to investigate the effect of silane monolayers on the detection of LysoPC in plasma.

Figure 1 :

 1 Figure 1: DIOS mass spectra of LysoPC in RP ion mode, alone in solution at 1 mg/mL using

Figure 2 .

 2 Figure 2. Depth profiling of Si -and P -ions by ToF-SIMS on porous silicon functionalized by

Figure 3 .

 3 Figure 3. Location of the positively and negatively charged fragments of LysoPC detected in

Figure 4 .

 4 Figure 4. DIOS mass spectra of LysoPC in RN ion mode, alone in solution at 1 mg/mL using

5 .

 5 normalized intensity of each fragment peak obtained in RN ion mode, for the different washing protocols are presented in Figures S4-S6. The 5x5 protocol seems to be the best compromise when considering the intensity improvement of the four fragments. Mass spectra of the spiked plasma on the three different surfaces studied in the RN ion mode, by using the 5x5 washing protocol, are presented Figure The relative intensities for each fragment peak are presented in Table

Figure 7 .

 7 Figure 7. The 86.0 m/z and the 184.1 m/z fragments are detected (relative intensities 1.93*10 -

Figure 5 .

 5 Figure 5. DIOS mass spectra in RN ion mode of plasma spiked with LysoPC (at 50 µg/mL)

Figure 6 .Figure 7 .

 67 Figure 6. DIOS mass spectra in RN ion mode on the CH 3 short monolayer at (a) 79.0 m/z, (b)

Table 1 :

 1 Developed formula of the silane molecules used in this study.

Silane name Structural formula CH 3 short CH 3 long 1. Material and methods Chemical and Reagents. Porous

  silicon substrates were purchased from SiLiMiXT (Tours,

	France). Pores (10 nm in diameter and 1 µm in depth) were obtained through electrochemical
	etching of silicon substrates (150mm in diameter, type P, 10-20 mOhms.cm, and 508 µm in
	thickness). The silane molecules were purchased from ABCR (Karlsruhe, Germany). LysoPC
	molecules were obtained from Avanti Polar Lipid (reference #855775P). The solvents
	(tetrahydrofuran 99% (THF), methanol, ethanol and chloroform) and the plasma (reference
	#P9523-1ml) were obtained from Sigma-Aldrich.

Table 2 .

 2 Those peaks correspond to the PO 3 -, O 3 P(CH 2 ) 2 O -, CH 3 CH(OH)CH 2 PH 2 O 4 -, and CH 3 (CH 2 ) 16 COO -fragments respectively.

, no peak is detected at [M-H] -(522.3 m/z). However, several fragments are visible, mainly at 79.0 m/z, 123.1 m/z, 153.1 m/z, and 283.6 m/z. Their relative intensities are presented in

Table 2 .

 2 Relative intensities of the LysoPC fragment peaks, in RP and RN ion modes, in solution, for the different surfaces studied. Error bars are below 10% (calculated from two half sets of data).

				RP ion mode			RN ion mode
	m/z	86.0	104.0	184.1	198.2	524.3	79.0	123.1	153.1	283.6
	CH 3 short	1	0.31	0.18	0.12	0.01	0.28	0.02	0.03	0.01
	CH 3 long	0.77	0.24	0.07	0.17	0.03	0.61	0.08	0.24	0.38
	bare silicon	0.46	0.12	0.17	0.04	0.02	0.34	0.07	0.04	0.02

Table 3 .

 3 Relative intensities of the LysoPC fragment peaks, in RN ion mode, in spiked plasma

	(50µg/mL), for the different surfaces studied. No peaks are detected by using CH 3 long, and no
	peaks are detected at 283.6 m/z. Error bars are below 10% (calculated from two half sets of
	data). (Spectra are in Figure 5)
			RN ion mode -spiked plasma (50µg/mL)
	m/z	79.0	123.1	153.1	283.6
	CH 3 short	2.46*10 -2	2.5*10 -3	1.52*10 -2	_
	CH 3 long	_	_	_	_
	bare silicon 3.28*10 -3	1.80*10 -3	2.13*10 -2	_

Table 4 .

 4 Relative intensities of the LysoPC fragment peaks, for the CH 3 short monolayer, in

RN ion mode in unmodified plasma, in spiked plasma at 50µg/mL, in spiked plasma at 500µg/mL, and in RP ion mode in unmodified plasma. No peaks are detected at 283.6 m/z in RN ion mode, and no peaks are detected at 104.0 m/z and at 198.2 m/z in RP ion mode. Error bars are below 10% (calculated from two half sets of data). (Spectra are in Figures

5-7) CH 3 short m/z 79.0 123.1 153.1 283.6 RN ion mode -unmodified plasma

	1.13*10 -2	1.67*10 -3	8.61*10 -3	_
	RN

ion mode -spiked plasma (50µg/mL)

	2.46*10 -2	2.5*10 -3	1.52*10 -2	_
	RN

ion mode -spiked plasma (500µg/mL)

	Page 17 of 28	The Journal of Physical Chemistry
			8.00*10 -2	1.61*10 -2	6.59*10 -2	_
	m/z		86.0	104.0	184.1	198.2
	RP ion mode -unmodified plasma	1. 93*10 -2	_	9.88*10 -3	_
		ACS Paragon Plus Environment

ACKNOWLEDGMENT

A. L. is grateful to the ANR PORIDG, of the French Agence Nationale de la Recherche, for funding his Ph.D. fellowship.

Funding Sources

This work was supported by the Young Researcher ANR PORIDG project, grant ANR-18-CE09-0006 of the French Agence Nationale de la Recherche.

AUTHOR INFORMATION

Corresponding Author

*Email: christelle.yeromonahos@ec-lyon.fr

Author Contributions

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.


Benjamin Mathieu
email: benjamin.mathieu@univ-amu.fr

Antonin Abillama

Simon Moré

Catherine Mercier

Martin Simoneau

Jérémy Danna

Laurence Mouchnino

Jean Blouin

SEEING OUR HAND OR A TOOL DURING VISUALLY-GUIDED ACTIONS: DIFFERENT EFFECTS ON THE SOMATOSENSORY AND VISUAL CORTICES

Keywords: Electroencephalography, Proprioception, Sensory conflict, Vision, Sensory gating, Body representation

The processing of proprioceptive information in the context of a conflict between visual and somatosensory feedbacks deteriorates motor performance. Previous studies have shown that seeing one's hand increases the weighting assigned to arm somatosensory inputs. In this light, we hypothesized that the sensory conflict, when tracing the contour of a shape with mirrorreversed vision, will be greater for participants who trace with a stylus seen in their hand (Hand group, n=17) than for participants who trace with the tip of rod without seen their hand (Tool group, n=15). Based on this hypothesis, we predicted that the tracing performance with mirror vision will be more deteriorated for the Hand group than for the Tool group, and we predicted a greater gating of somatosensory information for the Hand group to reduce the sensory conflict. The participants of both groups followed the outline of a shape in two visual conditions. Direct vision: the participants saw the hand or portion of a light 40 cm rod directly. Mirror Vision: the hand or the rod was seen through a mirror. We measured tracing performance using a digitizing tablet and the cortical activity with electroencephalography.

Behavioral analyses revealed that the tracing performance of both groups was similarly impaired by mirror vision. However, contrasting the spectral content of the cortical oscillatory activity between the Mirror and Direct conditions, we observed that tracing with mirror vision resulted in significantly larger alpha (8-12 Hz) and beta (15-25 Hz) powers in the somatosensory cortex for participants of the Hand group. The somatosensory alpha and beta powers did not significantly differ between Mirror and Direct vision conditions for the Tool group. For both groups, tracing with mirror vision altered the activity of the visual cortex: decreased alpha power for the Hand group, decreased alpha and beta power for the Tool group. Overall, these results suggest that seeing the hand enhanced the sensory conflict when tracing with mirror vision and that the increase of alpha and beta powers in the somatosensory cortex served to reduce the weight assigned to somatosensory information.

The increased activity of the visual cortex observed for both groups in the mirror vision condition suggests greater visual processing with increased task difficulty. Finally, the fact that the participants of the Tool group did not show better tracing performance than those of the Hand group suggests that tracing deterioration resulted from a sensorimotor conflict (as opposed to a visuo-proprioceptive conflict).

Introduction

Hands and fingers can be moved with extraordinary precision, notably when interacting with the external world. To successfully control movements with high spatial constraints, the brain uses two main sources of feedback: visual and somatosensory. Although these feedbacks first reach highly sensory-specific areas of the brain (e.g., the primary visual and somatosensory areas), they rapidly converge at common integrative areas (e.g., posterior parietal cortex; see [START_REF] Murray | The neural bases of multisensory processes[END_REF] for a review). Importantly, the great adaptability of the sensorimotor system enables visual and somatosensory information to be spatially (and temporally) congruent. In other words, we see our hand where we feel it, and we feel our hand where we see it. This sensory congruence is a keystone of our fine hand motor skills.

There are instances, however, where the congruence between hand visual and somatosensory feedbacks is altered, such as when using a microscope or magnifying lenses. In this context, motor performance is disrupted, most probably because the sensorimotor system is fed with conflicting visual and proprioceptive information [START_REF] Starch | A demonstration of the trial and error method of learning[END_REF]). An interesting support for this hypothesis was provided by [START_REF] Balslev | Enhanced accuracy in novel mirror drawing after repetitive transcranial magnetic stimulation-induced proprioceptive deafferentation[END_REF] who showed that a reduction of hand proprioception induced by repetitive transcranial magnetic stimulations (rTMS) of the somatosensory cortex, decreased the detrimental effect of incongruent visual feedback on movement performance. In this novel visuomotor environment, the suppression of somatosensory information would help reduce the sensory conflict, thereby improving motor performance. Note that the results reported by [START_REF] Balslev | Enhanced accuracy in novel mirror drawing after repetitive transcranial magnetic stimulation-induced proprioceptive deafferentation[END_REF] are also in line with studies

showing that mirror-reversed vision has little impact on the motor performance of patients suffering from a loss of proprioception who trace the contour of a shape [START_REF] Lajoie | Mirror drawing in a deafferented patient and normal subjects: Visuoproprioceptive conflict[END_REF][START_REF] Miall | Evidence for stronger visuo-motor than visuoproprioceptive conflict during mirror drawing performed by a deafferented subject and control subjects[END_REF].

Previous studies therefore provide clear evidence that processing proprioceptive information is pernicious for controlling movements in the context of a conflict between visual and proprioceptive feedbacks. The question nevertheless remains as to whether the intensity of this conflict is modulated by the possibility/impossibility of seeing the effector from which the conflicting proprioceptive inputs arise. For instance, because the hand muscles are endowed with proprioceptive receptors, the sensory conflict could be enhanced when our hand is visible compared to when we can only see a manipulated tool (e.g., a rod) in a context in which the tool is not incorporated into body representations (for tool embodiment, see [START_REF] Cardinali | Tool-use induces morphological updating of the body schema[END_REF][START_REF] Martel | Tool-use: An open window into body representation and its plasticity[END_REF][START_REF] Sposito | Extension of perceived arm length following tool-use: Clues to plasticity of body metrics[END_REF]. Indeed, with the sight of the hand, the brain receives visual and somatosensory hand afferents that can be (more or less) directly compared.

This context could ameliorate detection of the sensory mismatch, and could also increase the strength of the sensory mismatch. In this light, it is worth noting that seeing one's body part has been shown to facilitate the processing of the somatosensory inputs [START_REF] Ackerley | Seeing your foot move changes muscle proprioceptive feedback[END_REF][START_REF] Kennett | Noninformative vision improves the spatial resolution of touch in humans[END_REF][START_REF] Longo | Vision of the body modulates processing in primary somatosensory cortex[END_REF][START_REF] Taylor-Clarke | Vision modulates somatosensory cortical processing[END_REF], 2004;[START_REF] Zhou | Visuo-tactile cross-modal associations in cortical somatosensory cells[END_REF].

This sensory facilitation is known to target cutaneous [START_REF] Kennett | Noninformative vision improves the spatial resolution of touch in humans[END_REF][START_REF] Taylor-Clarke | Vision modulates somatosensory cortical processing[END_REF] and proprioceptive [START_REF] Ackerley | Seeing your foot move changes muscle proprioceptive feedback[END_REF] inputs. One possible underlying mechanism would be that, by association, the visual cue activates the internal representation of somatosensory stimulus (see Zhou & Foster, 2002). Accordingly, we might expect a greater sensory conflict when tracing the contour of a shape with a hand-held stylus than with a rod, which is an external object not linked to our somatosensory system and which is therefore devoid of somatosensory attributes.

Here, we tested this prediction by comparing the precision with which healthy human participants traced the contour of a shape with either a stylus (Hand group) or with the tip of a rod (Tool group) in two visual conditions: direct and mirror-reversed vision (i.e., Direct and Mirror conditions, respectively). Based on the hypothesis of a greater sensory conflict when seeing the hand, the tracing performance should be greater for the Tool group than for the Hand group in the Mirror condition. Predictions can also be made regarding the activity of the somatosensory cortex for the Hand and Tool groups when tracing with incongruent visual feedback. Indeed, [START_REF] Bernier | Direct evidence for cortical suppression of somatosensory afferents during visuomotor adaptation[END_REF] have observed that participants tracing a shape with incongruent visual feedback (participants saw their moving hand through an inclined mirror) exhibited a suppression of somatosensory inputs compared to when they were tracing with direct vision. In their study, the somatosensory suppression was evidenced by the decreased evoked potentials within the somatosensory cortex following the electric stimulations of the median nerve at the wrist. Functionally, this suppression of somatosensory information would reduce the sensory conflict (as for the rTMS over the somatosensory cortex, [START_REF] Balslev | Enhanced accuracy in novel mirror drawing after repetitive transcranial magnetic stimulation-induced proprioceptive deafferentation[END_REF]. Supporting the hypothesis that the sight of the hand increases the visuo-proprioceptive conflict, a gating of somatosensory inputs was not observed by [START_REF] Lebar | On the neural basis of sensory weighting: alpha, beta and gamma modulations during complex movements[END_REF] when the incongruent hand visual feedback was provided through a 3-mm dot (i.e., devoid of somatosensory attributes). In this visual context, [START_REF] Lebar | On the neural basis of sensory weighting: alpha, beta and gamma modulations during complex movements[END_REF] found a decreased power of beta oscillations (15-25 Hz) in the somatosensory cortex which, on the contrary, reflected greater cortical activity (see [START_REF] Kilavik | The ups and downs of beta oscillations in sensorimotor cortex[END_REF] for a review on cortical beta oscillations).

Because alpha and beta band powers are inversely related to the levels of excitability (alpha) and processing (beta) of the somatosensory and visual cortices [START_REF] Anderson | Attentional modulation of the somatosensory mu rhythm[END_REF][START_REF] Cheyne | Neuromagnetic imaging of cortical oscillations accompanying tactile stimulation[END_REF][START_REF] Pfurtscheller | Event-related EEG/MEG synchronization and desynchronization: basic principles[END_REF], we predicted that only the Hand group would show greater alpha (8-12 Hz) and beta (15-25 Hz) powers in the somatosensory cortex when tracing with mirror-reversed vision compared to a context with direct vision.

Method

Participants

Thirty-four volunteers participated to the study. They all had normal or corrected-to-normal vision and were right-handed according to Edinburgh Handedness Inventory (mean laterality score: 77.15 ± 15.4). Informed written consent was obtained before running the experiment.

The protocols and procedures were in accordance with the 1964 Declaration of Helsinki and were approved by the CERSTAPS ethic committee. The experiment lasted ~2 hours.

Procedure

The participants were seated in a darkened room in front of an irregular small shape (see Fig. 1) laid on a digitizing tablet. The shape was printed in white on a black background, and was lit by small LEDs directly above the tablet. It was made of 16 thin (0.5 mm) straight lines and 1 curved line whose lengths varied between 8 and 36 mm (total perimeter 36.7 cm). We deliberately chose a complex template (i.e., with many corners) as it has been shown to increase the complexity of the mirror-drawing task [START_REF] Miall | Evidence for stronger visuo-motor than visuoproprioceptive conflict during mirror drawing performed by a deafferented subject and control subjects[END_REF]. The task consisted of tracing the outline of this shape as precisely as possible with a digitizing stylus (weight 18 grams). The participants of the Hand group (n = 17; 8 women; mean age: 23.7 ± 3.7 years) held the stylus in their right hand. The participants of the Tool group (n = 17) held in their right hand the extremity of a light aluminum rod (40 cm, 17 grams) on the opposite end of which the stylus was firmly fixed. The data of 2 participants had to be discarded because of technical problems.

Thus, for the Tool group, the analyses were performed on 15 participants (8 women, mean age:

23.9 ± 2.8 years).

Participants of both groups followed the shape in two visual conditions. In the Direct condition (see Fig. 1A, right panel), the participants of the Hand group could directly see their hand while the participants of the Tool group could see only about the most extreme half of the rod (see Fig. 1B). For this latter group, vision of the arm and the hand was occluded with a black shield. In the Mirror condition, a mirror (Comair Cabinet Executive mirror, diameter 28 cm) was located to the front left of the participant with an inclination of 45 ° relative to the subject's frontal plane (Fig. 1A, right panel). In this condition, only the hand (Hand group) or the extremity of the rod (Tool group) could be seen through the mirror. For both groups, direct vision of the right upper limb was occluded with a black shield. (i.e., alpha, beta), the signal computed between 2 s and 9 s after the imperative go signal (i.e., at 0 s) was expressed as a change of power (dB) with respect to a 2-s mean window baseline recorded before the start tracing signal.

Participants of each group performed 40 trials of 18 s duration in both the Direct and Mirror conditions. The temporal organization of every trial is depicted in Figure 1C. At the beginning of each trial, due to software-related constraints, the tip of the stylus had to be held ~5 cm above the digitizing tablet. For the first trial, all participants held the stylus above the position on the shape indicated by an arrow in Figure 1A. For the subsequent trials, the participants held the stylus above the position reached at the end of the previous trial. For each trial, with the stylus at these starting positions, the participants sent the verbal message "ready" to the experimenter. Then, on hearing a beep, the participants had to lower the tip of the stylus onto the tablet and to hold the hand and stylus at this position (even if inadvertently the stylus was not on the intended point on the shape). A second beep issued 8 s after the first one served as an imperative signal to start tracing the contour of the shape. A final beep occurring 10 s after the second indicated the end of the trial. All trials were thus composed of a 8 s static phase and of a 10 s dynamic phase. The small size of the shape allowed participants of both groups to perform the tracing using only finger and wrist movements. The participants were instructed that whenever the stylus (or tip of the rod) left the outline of the shape, they should bring it back to the point where it left the shape before continuing the tracing. Participants were required to hold the stylus (Hand group) or the rod (Tool group) with a minimal force and to perform very slow movements. An experimenter demonstrated suitable tracing speeds prior to the experiment and corrective instructions were provided between trials when necessary. Slow movements reduced the muscular activation and the speed of the ocular pursuit which can both contaminate EEG recordings. Offline analyses showed that the mean tracing velocities for the Hand group were 0.54 ± 0.21 cm/s (Direct vision) and 0.47 ± 0.12 cm/s (Mirror vision), and for the Tool group, 0.50 ± 0.11 cm/s (Direct vision) and 0.49 ± 0.11 cm/s (Mirror vision). A 2 x 2 ANOVA did not reveal neither a significant effect of Vision (F1,31 = 2.77; p > 0.05) and of Group (F1,31 = 0.03; p > 0.05), nor a significant Vision x Group interaction (F1,31 = 1.72; p > 0.05).

Our goal was to investigate the effect of seeing one's hand on the processing of somatosensory information in the context of incongruence between visual and somatosensory feedbacks. Therefore, several elements of the experimental protocol aimed to limit adaptation to the sensory incongruence. The shape had a complex geometry, and the participants had to start their tracing from the position reached in the previous trial in order to avoid an overly repetitive pattern of the layout. The exposure duration to the sensory conflict was only of 6'40'' (i.e., 40 (trials) x 10 s (dynamic phase duration)). Moreover, after every 5 trials, participants were asked to directly watch their hand moving freely (without the rod, for the Tool group).

For reasons of homogeneity between the conditions, this procedure was also followed in the Direct condition.

Participants of both groups were first tested in the Direct condition. Note that contrary to protocols specifically designed to investigate the modification of the internal representation of the body when using tools (e.g., lengthening of the represented arm length, [START_REF] Martel | Tool-use: An open window into body representation and its plasticity[END_REF], the present protocol incorporated features to minimize such modifications in the Tool group (e.g., time-break with a view of the hand moving without the tool every 5 trials).

Data acquisition and processing

Behavior

The X and Y coordinates of the tip of the digitizing stylus were recorded using a Wacom Intuos 4L tablet (spatial resolution of <1mm, 100 Hz recording frequency). The tracing performance was assessed by computing a distance/segment index (referred to as distance ratio) (as in [START_REF] Law | Neural correlates for task-relevant facilitation of visual inputs during visually-guided hand movements[END_REF][START_REF] Lebar | On the neural basis of sensory weighting: alpha, beta and gamma modulations during complex movements[END_REF][START_REF] Miall | Evidence for stronger visuo-motor than visuoproprioceptive conflict during mirror drawing performed by a deafferented subject and control subjects[END_REF] which corresponded to the ratio between the total distance covered by the tip of the stylus and the total length of all drawn segments. The closer this ratio was to 1, the more accurate was the tracing. We also computed the number of reversals in direction when the participants traced the contour of the shape (as in [START_REF] Bernier | Direct evidence for cortical suppression of somatosensory afferents during visuomotor adaptation[END_REF][START_REF] Lajoie | Mirror drawing in a deafferented patient and normal subjects: Visuoproprioceptive conflict[END_REF]). This was done by calculating and then averaging the number of zero-line crossing in the X and Y velocity of the tracing. The smaller the number of zero-line crossing, the smoother the tracing.

As it can be seen in Figure 2, both assessments of the tracing performance showed substantial performance deterioration in the Mirror condition for both the Hand and Tool groups. However, performance improved across the first 20 trials before reaching a plateau. In this light, all analyses (i.e., performance, EMG, EEG) were performed using the first 20 EEG artifact-free trials (see below). This series of trials is more likely to better characterize crossmodal conflict between visual and sensorimotor inputs.

Electromyography (EMG)

The activity of the muscles acting on the wrist and fingers of the right arm was recorded to control for potential large differences of EMG activities between group and vision conditions.

This verification is particularly relevant in the context of the present study because the decrease of proprioceptive inflow to the somatosensory cortex, which is normally observed during movements [START_REF] Rushton | Gating of somatosensory evoked potentials during different kinds of movement in Man[END_REF][START_REF] Seki | Gating of sensory input at spinal and cortical levels during preparation and execution of voluntary movement[END_REF], is heighten during strong muscle contractions [START_REF] Staines | Movement-induced gain modulation of somatosensory potentials and soleus Hreflexes evoked from the leg I. Kinaesthetic task demands: I. Kinaesthetic task demands[END_REF].

EMG activity was recoded using a Bortec AMT-8 system (Bortec Biomedical, Calgary, Canada; 250 Hz sampling frequency). We recorded the activity of the flexor of the thumb (flexor pollicis brevis) and the first dorsal interosseous muscles, which are both involved in the precision grip. These activities were recorded bipolarly with Ag-AgCl electrodes placed 2 cm apart after cleaning the skin with alcohol. Activity of the flexor and extensor muscles of the wrist was recorded with electrodes placed over the wrist extensor bundle (top of the arm) and over the flexor bundle (bottom of the arm). With this wide configuration, both flexion and extension of the wrist can be recorded with a single pair of electrodes (see Criswell & Cram, 2011, p. 311). An electrode placed above the right epicondyle was used to reference all EMG recordings.

As expected, due to the slow speed of the tracing, the EMG recordings showed tonic activities without clear burst pattern. To compare the EMG activity across groups and conditions, we rectified and integrated the 3 sets of EMG data over both the static phase (-3.5 s to -1.5 s) and the dynamic phase (2 s-9 s) for each valid trial (i.e., without EEG artifact). The integrals (i.e., iEMG) obtained in the dynamic phase were expressed as a percentage of the iEMG obtained in the static phase. Then, we computed the mean % iEMG of the 3 set of EMG data for each group (Hand, Tool) and vision condition (Direct, Mirror).

Electroencephalography (EEG)

EEG activity was recorded continuously using a cap of 64 Ag/AgCl electrodes at a 1024 Hz sampling frequency (ActiveTwo system, Biosemi, Amsterdam, The Netherlands). The activities recorded by electrodes placed near each external canthus, and electrodes placed below and above the left eye were used to detect blinks and saccades. The EEG data were preprocessed using BrainVision Analyzer2 software (Brain Products, Gilching, Germany). EEG signals were referenced against the average of the activities recorded by all electrodes. The effect of ocular artifacts on the EEG recordings, related to blink and saccades, was reduced using the method of [START_REF] Gratton | A new method for off-line removal of ocular artifact[END_REF].

For each vision condition, the EEG data were segmented and synchronized with respect to the occurrence of the beep which indicated the beginning of the dynamic phase. Note that due to very slow tracing movements, this segmentation could not be made using kinematic (e.g., tracing onset) or EMG data within a reasonable temporal margin of error. The recordings were visually inspected and epochs still presenting artifacts were rejected. These trials were replaced by those occurring between the 20 th and 27 th trials, so that 20 epochs were analyzed for each participant (see Table 1 for the number of trials rejected within the first 20 trials for each participant and each condition).

Table 1. Number of trials that were selected between the 20th and the 27th trials for each participant and condition.

Hand group Participant # 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Direct vision 1 1 0 2 0 0 0 1 4 4 0 1 1 0 0 1 4 Mirror vision 2 1 1 3 1 1 3 0 3 5 4 4 5 1 3 0 5

Tool group Participant # 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Direct vision 0 2 1 0 0 4 4 3 2 0 2 0 0 4 3 Mirror vision 0 4 1 1 1 0 5 4 0 5 2 3 2 3 0

We used Brainstorm software to estimate the cortical sources of the EEG signals [START_REF] Tadel | Brainstorm: a user-friendly application for MEG/EEG Analysis[END_REF]. The inverse problem was resolved using the minimum-norm technique and unconstrained dipole orientations. A boundary element method (symmetric BEM, [START_REF] Gramfort | OpenMEEG: opensource software for quasistatic bioelectromagnetics[END_REF] was used to compute the forward models on the anatomical MRI Colin 27 brain template (15,000 vertices) from the Institut Neurologique de Montréal. We opted for a model with three realistic layers (scalp, inner skull, and outer skull) which yields more accurate solutions compared to a simple three concentric spheres model [START_REF] Sohrabpour | Effect of EEG electrode number on epileptic source localization in pediatric patients[END_REF].

Single-trial EEG data were transformed in the time-frequency domain using the Hilbertfilter method. This method is particularly suited for long times-series such as those analyzed in the present study [START_REF] Cohen | Analyzing neural time series data: Theory and practice[END_REF]. The analyses of the time frequency distribution were performed in the source space. We extracted the amplitude envelope (i.e., power) of alpha (mean 8-12 Hz, steps of 0.5 Hz) and beta (mean 15-25 Hz, steps of 1 Hz) bands over both the static and dynamic phases of the trials. For each frequency band, the power computed during the dynamic phase was normalized with respect to the static baseline period (-3.5 to -1.5 s) and then averaged, for each group and condition, between all trials over the 2-9 period after the imperative go ("beep") signal (see Fig. 4). The selected baseline time window was deliberately chosen away from the beep indicating the onset of the static phase, at which time the participants had to lower the stylus on the digitizing tablet (event that was most likely followed by the cognitive appraisal of the stylus landing position). We indistinctly considered increases of alpha and beta band power as a neurophysiological signature of a gating of somatosensory and visual inputs. Decreases of these low and medium frequency bands rather reflecting a facilitation of these sensory inputs. The analyses were limited to the left hemisphere because it receives somatosensory inputs from the arm that the participants used to perform the tracing task (i.e.

right arm), and because its posterior region is highly responsive to vision of hands and tools [START_REF] Bracci | Dissociable neural responses to hands and non-hand body parts in human left extrastriate visual cortex[END_REF][START_REF] Bracci | Closely overlapping responses to tools and hands in left lateral occipitotemporal cortex[END_REF].

Specific analyses were performed to get insight into the dynamics of the visual feedbackrelated changes of alpha and beta band powers in the somatosensory and visual cortices. This was done by first identifying from the BEM mesh, and for each participant, the vertex within the somatosensory or visual cortex that exhibited the strongest significant effect (i.e., smallest negative t value or greatest positive t value, see fig. 4) when contrasting the sources of the baseline-normalized alpha and beta band powers estimated in the Direct and Mirror conditions (group analyses, see statistical analyses below). Then, the alpha and beta band powers computed at this vertex in the Mirror condition were extracted from -3.5 s to 9 s, where 0 s indicates the imperative signal to start the tracing movement. Two ways were used to express the time courses of alpha and beta band changes. We computed the mean baseline-normalized power between participants and computed, for each participant, the cumulative integral of the baselinenormalized power. Monotonic increasing or decreasing of the cumulative integral indicates that the increase or decrease of power is preserved throughout the tracing. This computation provides smoother data than the baseline-normalized power and is particularly relevant for appraising the between-participants variability.

The EEG data recorded in the electrode space was also transformed in the time-frequency domain using the Hilbert-filter method. This transformation was performed after applying a spatial filter (surface Laplacian, [START_REF] Perrin | Spherical splines for scalp potential and current density mapping[END_REF]; order term of the Legendre polynomial=10, smoothing=1e-5, m=4) thereby increasing the topographical selectivity by filtering out volumeconducted potentials [START_REF] Law | Neural correlates for task-relevant facilitation of visual inputs during visually-guided hand movements[END_REF][START_REF] Nunez | Electric Fields of the Brain[END_REF]. Analyzing the spectral content of the EEG signals recorded at C3 and C5 electrodes allowed to directly compare, between the Hand and Tool groups, the effect of tracing with mirror-reversed vision on the alpha and beta band powers over the somatosensory cortex (i.e. the key region for testing the effect vision of the hand on somatosensory processes). Indeed, as shown in Fig. 4, electrodes C3 and C5 respectively overlay the left primary (SI) and secondary (SII, upper bank of the Sylvian fissure) somatosensory cortices.

Statistical analyses

For each Group and Vision conditions, the evolution of the tracing-related variables (i. For each group, we assessed the effect of the sensory incongruence on the topography and amplitude of the normalized alpha and beta band power by contrasting the sources of alpha and beta band powers estimated in the Direct and Mirror conditions using t-tests (significance threshold p < 0.05, uncorrected).

Finally, to directly compare the effect of the sensory incongruence on somatosensory alpha and beta band powers between the Hand and Tool groups, we subtracted for both the C3 and C5 electrodes and for all participants of each group, the normalized power computed in the Mirror condition from the normalized power computed in the Direct condition. These differences allowed us to cancel out activities strictly related to the control of a hand-held stylus or of a hand-held tool. The differences (hereafter referred to as ΔMirror-Direct) computed in the Hand and Tool groups were submitted to independent t-tests (significance threshold p < 0.05).

Results

Tracing performance

The evolution of the distance/segment index and of the number of zero speed crossing throughout the 40 trials are shown in Figure 2 for both the Hand and Tool groups. Overall, the participants of both groups accurately traced the shape with Direct vision but substantially decreased their tracing accuracy with mirror-reversed vision. Figure 2 shows improvement in tracing performance over the first 20 trials before reaching a relative stable plateau, suggesting that the sensory conflict was perceived greater in the first half of the trials. Because our main goal was to compare the response of the somatosensory cortex when tracing a shape in the context of a visuo-proprioceptive conflict, all behavioral and electrophysiological analyses presented below pertained to the first 20 trials (see methods for exceptions). The distance/segment index was significantly greater in the Mirror (mean: 1.41 ± 0.48) than in the Direct (mean: 1.02 ± 0.04) conditions (main effect of Vision: F1,31 = 63.65; p < 0.001; η 2 = 0.68). For this variable, the ANOVA did not reveal a significant effect of Group (F1,31 = 0.78; p > 0.05), but revealed a significant Vision x Bin interaction (F1,31 = 6.89; p < 0.001; η 2 = 0.19). Post-hoc analyses confirmed the decrease of the distance ratio over the trials with mirror-reversed vision, but more importantly, they showed that the distance ratio computed in the last series of 5 trials (i.e., bin no. 4) was still significantly greater than the distance ratio computed in all bins of the Direct condition (all ps < 0.05).

The number of zero speed crossing was also significantly greater in the Mirror (mean:

13.44 ± 5.04) than in the Direct (8.92 ± 3.68) conditions (main effect of Vision: F1,31 = 44.04; p < 0.001). For this variable, the ANOVA did not reveal neither a significant effect Group (F1,31 = 1.51; p > 0.05), nor a significant Vision x Bin interaction (F1,31 = 2.38; p > 0.05).

EMG recordings

Figure 3 shows the iEMG, computed from the recordings of the forearm and hand muscles during the tracing, normalized to the iEMG computed before starting the tracings. The figure

shows that the iEMG was ~200-300% greater during the tracing compared the static period.

The ANOVA revealed that the normalized iEMG was significantly greater in the Mirror condition (mean: 278% ± 40) than in the Direct condition (mean: 257% ± 34) (F1,31 = 11.05; p < 0.005; η 2 = 0.29). However, the effect of Group (F1,31 = 2.26; p > 0.05), the interaction between Vision and Group (F1,31 = 1.31; p > 0.05) and the interaction between Vision and Bin (F1,31 = 0.12; p > 0.05) were not significant. Therefore, if different spectral contents of cortical neural oscillations were to be found between the Hand and Tool groups, they would unlikely result from different muscular activities (see [START_REF] Staines | Movement-induced gain modulation of somatosensory potentials and soleus Hreflexes evoked from the leg I. Kinaesthetic task demands: I. Kinaesthetic task demands[END_REF] for the effect motor contractions amplitude on the gating of somatosensory inputs). The increased hand muscle activities observed with mirror-reversed vision could be due to the greater number of reversals in direction when tracing the contour of the shape with incongruent vision (Fig. 3). On the other hand, the absence of a significant effect of Group on the iEMG indicates that the rod (weight = 17 grams) was not heavy enough to have an impact on the EMG recordings. These electrodes overlay the left somatosensory cortex (i.e., contralateral to the tracing hand).

EEG data

The signals recorded at these electrodes were used to compare the effect of the visual conditions (i.e., Direct, Mirror) between the Hand and Tool groups (see Fig. 5).

EEG data: Somatosensory cortex

For the Hand group, alpha band power was significantly greater when tracing with mirrorreversed vision in areas identified by the source analyses as the primary (SI) and the secondary (SII, i.e. upper bank of the Sylvian fissure) somatosensory cortices (Fig. 4a). Beta band power was also significantly greater with incongruent visual feedback in SI (Fig. 4b). For the Tool group, alpha and beta band powers computed in the somatosensory cortex were strikingly alike between the Mirror and Direct conditions. The statistical map only revealed a significantly smaller alpha band power in a small area of SI (Fig. 4a).

Alpha and beta band powers recorded at C3 and C5 electrodes were also compared between Groups and Vision conditions over the same time windows as the analyses in the source space. These electrodes overlay the left postcentral region [START_REF] Koessler | Automated cortical projection of EEG sensors: anatomical correlation via the international 10-10 system[END_REF], see also Fig. 4) which was contralateral to the tracing hand. T-tests revealed that the ΔMirror-Direct beta (t(30) = 3.01; p < 0.01; d = 0.95) and the ΔMirror-Direct alpha (t(30) = 2.50; p < 0.01; d = 0.83) significantly differed between groups at electrode C3 and C5, respectively (Fig. 5).

Importantly, for the Hand group, the ΔMirror-Direct beta value (electrode C3) was positive (mean = 9.87 ± 12.77) and was significantly different from 0 (comparison to a standard (i.e., 0); p < 0.01). Likewise, for the Hand group, the ΔMirror-Direct alpha value (electrode C5) was positive (mean = 9.70 ± 18.79) and also significantly differed from 0 (p < 0.05). However, the ΔMirror-Direct alpha (C3) and the ΔMirror-Direct beta (C5) did not significantly differ between groups (t(30) = 0.93; p > 0.05 and t(30) = 1.23; p > 0.05, for C3 and C5, respectively).

For the Tool group, the ΔMirror-Direct alpha and beta bands computed at electrodes C3 and C5 did not significantly differ from zero (ps>0.05). None of these variables was significantly correlated with the performance variables (ps>0.5; Spearman's rank tests).

EEG data: Visual cortex

The power within alpha and beta bands computed in the medial visual cortex was also altered when tracing with mirror vision. In contrast to what was observed in the somatosensory cortex, the bias in the visual feedback led to decreases in alpha and beta band powers in visual areas (Fig. 4). This suggests a facilitation of visual feedback with mirror-reversed vision. However, the effect of the incongruent visual feedback on the neural oscillations appeared more pronounced for the Tool group than for the Hand group. Indeed, the statistical maps showed significant smaller power in the Mirror condition in regions estimated by sources analyses as the lingual gyrus (alpha), the medial parietal cortices (alpha) and the cuneus (beta). For the Hand group, the statistical maps only revealed significantly smaller beta band power in the cuneus (Fig. 4). Note that because the effects of mirror-reversed vision occurred in the medial visual cortex, the ΔMirror-Direct alpha and beta band powers could not be computed in the electrode space.

The contrast Mirror vs Direct condition also revealed smaller alpha band power in the Mirror condition for the Tool group in a region identified as the anterior precuneus cortex.

EEG data: dynamics of the changes of alpha and beta band powers

Figure 6 provides an estimate of the dynamics of the changes in alpha and beta band powers when the participants of the Hand and Tool groups traced the shape with mirror-reversed feedback. Band powers were extracted from vertices within areas showing significant contrasts between the Mirror and Direct conditions (i.e., SI, SII, cuneus, lingual gyrus, see Fig. 4). The figure shows that the increased in power observed in the somatosensory cortex (results obtained only for the Hand group) was more consistent in SII (alpha) than in SI (beta). Indeed, 14 out of 17 participants showed an increase of alpha band power in SII when they traced the shape in the Mirror condition while 10 participants showed an increased beta in SI. On the other hand, the decrease in alpha and beta band powers observed in the visual cortex, when tracing with mirror-reversed vision, was more robust in the Tool group compared to the Hand group; the power decreased in all participants except one.

Remarkably, the participant in the Tool group showing a larger increase in alpha band power during mirror vision, also had the greatest number of zero-line crossings in tracing velocity (i.e., worst tracing performer).

Together, these results are consistent with those issued from the statistical maps (Fig. 4) that showed i) for the Hand group, a greater cluster exhibiting significant increase in alpha band power sources localized in SII, and ii) for the Tool group, greater clusters exhibiting significant decreases of alpha and beta band powers in the visual cortex.

Discussion

We tested the hypothesis that the conflict between visual and arm proprioceptive inputs, when tracing the contour of a shape with mirror-reversed vision, is greater when participants see their hand during tracing. Contrasting the spectral content of the cortical oscillatory activity in conditions with and without incongruent visual feedback (respectively Mirror and Direct conditions), we observed increases of alpha and beta band powers in the somatosensory cortex when participants had vision of their hand when tracing with mirror vision (Hand group). In contrast, for participants tracing with the tip of a rod (i.e., without hand visual feedback, Tool group), alpha and beta band powers in the somatosensory cortex did not significantly differ between the Direct and Mirror conditions. There is a consensus that increases in alpha and beta band powers respectively correspond to a decrease in cortical excitability and processing [START_REF] Anderson | Attentional modulation of the somatosensory mu rhythm[END_REF][START_REF] Cheyne | Neuromagnetic imaging of cortical oscillations accompanying tactile stimulation[END_REF][START_REF] Kilavik | The ups and downs of beta oscillations in sensorimotor cortex[END_REF][START_REF] Pfurtscheller | Event-related EEG/MEG synchronization and desynchronization: basic principles[END_REF]. In this light, the changes of alpha and beta band powers observed in the somatosensory cortex imply a suppression of arm somatosensory information. The fact that only the participants of the Hand group showed a gating of arm somatosensory inputs with mirror vision suggests that seeing the hand enhanced the visuo-proprioceptive conflict. Altered visual feedback, however, deteriorated tracing performance similarly in both the Hand and Tool groups. The results showed by the participants of the Tool group suggest that their altered performance with mirror vision essentially stemmed from a sensory-motor conflict (rather than from a visuo-proprioceptive conflict, see below).

Moving our arm or an object when seen through a mirror creates a mismatch between the movement-related information carried by the visual and proprioceptive systems. Conceptually, this mismatch prevailed in the present experiment when the participants of both the Hand and Tool groups traced the shape with mirror vision. However, only the participants of the Hand group showed a suppression of somatosensory information (i.e., greater alpha and beta band powers in the Mirror condition). Functionally, the dynamic suppression of somatosensory information when performing goal-directed movement under incongruent visual inputs would reduce the sensory conflict [START_REF] Bernier | Direct evidence for cortical suppression of somatosensory afferents during visuomotor adaptation[END_REF][START_REF] Goldenkoff | Reversal of visual feedback modulates somatosensory plasticity[END_REF]. Within this framework, our results are then compatible with two non-mutually exclusive scenarios. One in which vision of the hand would enhance arm somatosensory information, thereby increasing the sensory conflict. This would be consistent with psychophysical studies showing enhanced processing of somatosensory information (from extraocular, neck and arm muscles) with visual feedback [START_REF] Becker | Perception of angular head position during attempted alignment with eccentric visual objects[END_REF][START_REF] Blouin | Visual signals contribute to the coding of gaze direction[END_REF][START_REF] Kennett | Noninformative vision improves the spatial resolution of touch in humans[END_REF][START_REF] Longo | Vision of the body modulates processing in primary somatosensory cortex[END_REF][START_REF] Taylor-Clarke | Vision modulates somatosensory cortical processing[END_REF], 2004;[START_REF] Zhou | Visuo-tactile cross-modal associations in cortical somatosensory cells[END_REF]. It would also be compatible with the greater sensitivity of the somatosensory cortex to peripheral somatosensory inputs reported in previous studies when the stimulated body area can be seen [START_REF] Forster | Vision and gaze direction modulate tactile processing in somatosensory cortex: Evidence from event-related brain potentials[END_REF][START_REF] Sambo | Viewing the body modulates neural mechanisms underlying sustained spatial attention in touch[END_REF][START_REF] Taylor-Clarke | Vision modulates somatosensory cortical processing[END_REF]. Another possibility is that the inter-sensory conflict increased for the Hand group because the source of the conflicting somatosensory inputs (i.e., the hand) could be seen, contrary to the Tool group. According to this hypothesis, the view of the hand would allow a more direct comparison between the visual and somatosensory mapping of the hand, and therefore a better detection of a sensory mismatch when controlling movements with incongruent visual feedback.

Our results point to an automatic covert processing of arm proprioceptive inputs induced by vision of the hand. In direct visual conditions, this covert processing might contribute to the high quality of our broad manual motor repertoire. In conditions with incongruent visual feedback, it would impair movement performance, thereby prompting the brain to decrease the weight of proprioception during the visual and somatosensory feedbacks integration. While converging evidence suggests that the prefrontal cortex has a key role for the downregulation of somatosensory inputs [START_REF] Bolton | Transient inhibition of the dorsolateral prefrontal cortex disrupts attention-based modulation of tactile stimuli at early stages of somatosensory processing[END_REF][START_REF] Della-Maggiore | Time course of changes in brain activity and functional connectivity associated with long-term adaptation to a rotational transformation[END_REF][START_REF] Haggard | Supplementary motor area provides an efferent signal for sensory suppression[END_REF][START_REF] Staines | Task-relevant modulation of contralateral and ipsilateral primary somatosensory cortex and the role of a prefrontal-cortical sensory gating system[END_REF], the mechanisms that enable the facilitation of these inputs through vision are not well understood. One possible mechanism is that by association, the visual information of the hand could activate the somatosensory inputs that it represents (see [START_REF] Zhou | Visuo-tactile cross-modal associations in cortical somatosensory cells[END_REF]. The bimodal cells, which respond to both visual and somatosensory inputs and which are found in several regions of the brain, could permit the visual inputs to play such a role. Moreover, a population of bimodal cells which have their tactile receptive field on the hand increases its firing rates when a visual stimulus appears near the hand [START_REF] Fogassi | Coding of peripersonal space in inferior premotor cortex (area F4)[END_REF][START_REF] Graziano | A bimodal map of space: somatosensory receptive fields in the macaque putamen with corresponding visual receptive fields[END_REF][START_REF] Rizzolatti | Afferent properties of periarcuate neurons in macaque monkeys. II. Visual responses[END_REF]see Maravita et al. 2003 for a review). This suggests that the tactile and visual receptive fields of these bimodal neurons are not merely retinotopic and, thereby, that the view of the whole hand could have contributed to increase the response of the somatosensory cortex to fingers somatosensory inputs (in the present study, tracing the shape essentially required movements of the fingers).

The fact that the participants of the Tool group did not show significant modulation of somatosensory alpha and beta powers when tracing with mirror vision suggests that vision of a self-moved tool does not enable such covert processing of proprioceptive information. In the present study, we did not control for change of the internal representation of the body when participants used the tool to trace the contour of the shape (e.g., lengthening of the represented arm length, [START_REF] Cardinali | Tool-use induces morphological updating of the body schema[END_REF][START_REF] Sposito | Extension of perceived arm length following tool-use: Clues to plasticity of body metrics[END_REF]see Martel et al., 2016 for a review).

However, our experiment was designed to minimize such modifications (e.g., participants

viewed their hand moving without the tool every 5 trials). The lack of alpha and beta power modulation in the Mirror condition for the Tool group indicates that the tool was unlikely incorporated into body representations. Further studies are needed to determine whether the view of the tool also leads to down-weighting of proprioception in the somatosensory cortex after tool embodiment.

The present sources analyses indicated that the dynamic control exerted by the brain over arm somatosensory information mainly occurred in SII, which is an important hub for processing somatosensory information [START_REF] Steinmetz | Attention modulates synchronized neuronal firing in primate somatosensory cortex[END_REF]. Our findings are then consistent with studies showing greater attention-related processes in SII than in SI [START_REF] Chapman | Independent controls of attentional influences in primary and secondary somatosensory cortex[END_REF][START_REF] Nelson | Activation in SI and SII; the influence of vibrotactile amplitude during passive and task-relevant stimulation[END_REF]. Importantly, SII is thought to contribute to the integration of proprioceptive inputs for the online motor control [START_REF] Eickhoff | Anatomical and functional connectivity of cytoarchitectonic areas within the human parietal operculum[END_REF][START_REF] Hinkley | Sensorimotor integration in S2, PV, and parietal rostroventral areas of the human Sylvian fissure[END_REF].

The sensory gating observed in SII areas then likely decreased the weight assigned to arm proprioceptive inputs when the participants of the Hand group controlled their movements with incongruent visual and proprioceptive feedbacks.

Although occurring outside our pre-defined region of interest (i.e., somatosensory area), we found significant decreases of alpha and beta powers in the occipital cortex when participants traced the shape with mirror-reversed vision. The effect of the incongruent visual feedback on the activity of the occipital cortex was therefore opposed to the effect observed in the somatosensory cortex for the Hand group (i.e., increased alpha and beta powers). The decrease in occipital alpha and beta band powers is consistent with a facilitation of visual inputs when performing movement under visuo-proprioceptive incongruence. This change in occipital alpha and beta powers corroborates brain imaging studies (e.g., EEG, fMRI) reporting increased activity in the occipital lobe when performing movements under discrepant visual feedback [START_REF] Law | Neural correlates for task-relevant facilitation of visual inputs during visually-guided hand movements[END_REF][START_REF] Lebar | On the neural basis of sensory weighting: alpha, beta and gamma modulations during complex movements[END_REF][START_REF] Limanowski | Neuronal correlates of continuous manual tracking under varying visual movement feedback in a virtual reality environment[END_REF][START_REF] Limanowski | Cortical beta oscillations reflect the contextual gating of visual action feedback[END_REF].

The changes in alpha and beta band powers observed in the occipital were more robust for the Tool than for the Hand groups. This observation might suggest that seeing a self-moved tool under incongruent visual feedback is a favorable context to create a visual attentional set, which increases visual brain activity (see [START_REF] Limanowski | Active inference under visuo-proprioceptive conflict: Simulation and empirical results[END_REF][START_REF] Limanowski | Precision control for a flexible body representation[END_REF].

On the other hand, for the Tool group, the shift of attention away from arm proprioception (and perhaps away from hand working space), and the absence of covert processing of arm proprioceptive inputs in the absence of hand visual feedback, might have reduced the weight of arm proprioceptive inputs when tracing the shape with direct visual feedback. According to this assumption, there would be no functional necessity to further downregulate arm somatosensory inputs when tracing with incongruent visual feedback. This could explain why, contrary to the Hand group, the Tool group showed similar somatosensory alpha and beta band powers between the Mirror and Direct conditions. Therefore, the present results could reconcile the apparent discrepancy between the suppression of somatosensory inputs reported by [START_REF] Bernier | Direct evidence for cortical suppression of somatosensory afferents during visuomotor adaptation[END_REF] when participants traced the contour of a shape while seeing their hand through an inclined mirror (as in the present study) and the reduction of somatosensory beta band power (i.e., increased processing) reported by [START_REF] Lebar | On the neural basis of sensory weighting: alpha, beta and gamma modulations during complex movements[END_REF] when the incongruent hand visual feedback was provided using a digitized dot image.

Our source analyses estimated the cuneus (for the Hand and Tool groups) and the lingual gyrus (for the Tool group) as the origin of the occipital decrease of alpha and beta band powers in the Mirror condition. These medial visual areas are known to encode space in an allocentric frame of reference [START_REF] Chen | Allocentric versus egocentric representation of remembered reach targets in human cortex[END_REF][START_REF] Committeri | Reference frames for spatial cognition: different brain areas are involved in viewer-, object-, and landmark-centered judgments about object location[END_REF][START_REF] Ruotolo | Neural correlates of egocentric and allocentric frames of reference combined with metric and non-metric spatial relations[END_REF]. In this frame of reference, the body (including the hand) and the objects of the environment would be encoded relative to each other within a retinal map (i.e., object-based coding of space) (Burgess et al., 2004;[START_REF] Galati | The neural basis of egocentric and allocentric coding of space in humans: A functional magnetic resonance study[END_REF][START_REF] Paillard | Cognitive versus sensorimotor encoding of spatial information[END_REF]. Such visual representation of space would be largely independent of somatosensory inputs [START_REF] Ambrosini | Behavioral investigation on the frames of reference involved in visuomotor transformations during peripheral arm reaching[END_REF][START_REF] Blouin | Reference systems for coding spatial information in normal subjects and a deafferented patient[END_REF][START_REF] Medendorp | Behavioral and cortical mechanisms for spatial coding and action planning[END_REF]. Accordingly, our results suggest that controlling the motion of the hand or of a tool with incongruent visual feedback enables the use of an allocentric reference frame. The fact that the Tool group showed stronger between-subjects consistency regarding the decreased alpha and beta band powers in the medial visual cortex implies that the manipulated tool was selectively encoded with an object-based frame of reference. The observation that the only participant of the Tool group who showed a strong increase in alpha band power in the Mirror condition (see Fig. 6D) was the worst tracing performer provides evidence that this frame of reference was more relevant for controlling arm movements in this novel visuomotor environment than somatosensory-based egocentric reference frames.

Moreover, the finding of both increase and decrease of visual beta band power when the participants of the Hand group traced with mirror vision supports the suggestion that the selection of the frames of reference is subject and context dependent [START_REF] Bernier | Human posterior parietal cortex flexibly determines reference frames for reaching based on sensory context[END_REF]Bridgeman, 1991;Byrne & Henriques, 2013). The enhanced object-based coding of space for the Tool group in the Mirror condition is also supported by the decreased alpha band power observed in the anterior precuneus with mirror vision. Indeed, this medial area of the parietal cortex has been shown to selectively encode the motor goal in visual coordinates [START_REF] Bernier | Human posterior parietal cortex flexibly determines reference frames for reaching based on sensory context[END_REF].

We reasoned that because tools are devoid of somatosensory attributes, the visuoproprioceptive conflict should be less perceived for the Tool group. Accordingly, we predicted better performance for the Tool than for the Hand groups in conditions with incongruent visual feedback. Behavioral analyses rather revealed that the tracing performance of both groups was similarly impaired with mirror vision. A likely explanation is that the performance degradation showed by the Tool group mainly resulted from a sensorimotor conflict (rather than from a visuo-proprioceptive conflict). During visually-guided movements, this conflict would result from the incongruence between the actual visual feedback and the predicted visual feedback issued from the motor commands (Brun et al., 2020;[START_REF] Miall | Evidence for stronger visuo-motor than visuoproprioceptive conflict during mirror drawing performed by a deafferented subject and control subjects[END_REF][START_REF] Shadmehr | Error correction, sensory prediction, and adaptation in motor control[END_REF]. Similar conflict could have emerged between the predicted and the actual somatosensory feedbacks. In our study, the hand motor commands when manipulating the tool might have enabled these sensory predictions. Most likely, the visuomotor conflict also degraded the tracing performance of the Hand group. However, the fact that for the Tool group, the incongruence between visual and somatosensory feedbacks had no significant impact on the somatosensory alpha and beta band powers suggests that the visuomotor conflict had only negligible effect on the activity of the somatosensory cortex.

Conclusion

We found that the control of tracing movement under incongruent visual and somatosensory information was associated with an increased alpha (8-12 Hz) and beta (15-25 Hz) band powers in the somatosensory cortex if participants had visual feedback of their hand. This modulation of alpha and beta activities, which suggested reduced proprioception, was not found if participants traced the shape with the tip of a rod without seeing their hand. Taken together, our findings are in line with a covert processing of arm somatosensory information induced by vision of the hand. This covert processing would have a detrimental effect on movements that are controlled under incongruent visual and proprioceptive feedbacks, and would prompt the brain to exert a control over somatosensory information. A challenging goal of further studies would be to determine the mechanisms responsible for the facilitation and inhibition of the somatosensory inputs and to identify the network involved. The present results suggest that the processing of arm somatosensory inputs during the control of goal-directed hand movements differs largely between conditions where hand visual feedback is available and conditions where the hand cannot be seen. This could explain results from previous studies (e.g., [START_REF] Clower | Selective use of perceptual recalibration versus visuomotor skill acquisition[END_REF][START_REF] Norris | Prism adaptation of reaching is dependent on the type of visual feedback of hand and target position[END_REF] showing that the sensorimotor adaptation to prismatic displacement is greater when the participants can see their hand than when the participants see their hand in a more abstract form (e.g., digitized dot, video).

Figure 1 .

 1 Figure 1. A. Schematic representation of the experimental set-up used in the Direct (left panel) and the Mirror (right panel) conditions with a participant of the Hand group. B. Sketches of the visual feedback available during the tracing for the participants of the Hand (left) and Tool (right) groups. The starting position is indicated by the arrows. C. Temporal organization of the

  e., distance/segment index, number of zero speed crossing, iEMG) over the first valid 20 trials was assessed by computing their mean values over 4 bins of 5 consecutive trials. These variables were submitted to separate 2 (Group: Hand, Tool) x 2 (Vision: Direct, Mirror) x 4 (Bin: Bin1-5, Bin6-10, Bin11-15, Bin16-20) analyses of variance (ANOVA), with repeated measurements on the Vision and Bin factors. Significant effects were further analyzed using Newman-Keuls posthoc tests. The alpha level was set at 0.05 for all statistical contrasts. The normal distribution of data for each variable was confirmed by Kolmogorov-Smirnov tests.

Figure 2 .

 2 Figure 2. Mean tracing performance over the course of the 40 trials for the Hand group (A) and the Tool group (B). The trials are pooled into 8 bins of 5 consecutive trials. Left panels: The tracing performance is expressed as the average total distance covered by the pen per segment completed in every trial (distance/segment index). Right panels: Number of reversals in direction of the stylus as expressed by the average number of zero-line crossings on the velocity profiles per trial. Error bars: standard error of the mean.

Figure 3 .

 3 Figure 3. Baseline-normalized iEMG for the Hand and Tool groups computed in the Direct and Mirror conditions.

Figure 4

 4 Figure4shows the statistical maps of alpha and beta band power resulting from the contrast Mirror vs Direct conditions for both the Hand and Tool groups. Warm colors indicate that alpha and beta band powers were significantly greater in the Mirror condition than in the Direct condition. If observed in sensory areas, warm colors would therefore reflect a relative decrease in weight assigned to the inputs pertaining to these areas when tracing with mirror-reversed vision. Cold colors indicate the opposite pattern. In the grey regions of the statistical maps, the power of alpha and beta was not significantly different between the Mirror and Direct conditions. Remarkably, the significant differences resulting from the contrasts Mirror vs Direct conditions were largely circumscribed to the somatosensory and visual areas for the Hand group, and to visual areas for the Tool group.

Figure 4 .

 4 Figure 4. Statistical maps (source space, left hemisphere) of alpha (A) and beta (B) powers resulting from the contrast Mirror vs Direct conditions for both the Hand (left panels) and Tool (right panels) groups. The position of the C3 and C5 electrodes are shown on the side views.

Figure 5 .

 5 Figure 5. Results of the t-tests comparing, between the Hand and Tool group, the ΔMirror-Direct (alpha and beta, expressed in signal units 2 /Hz) computed at electrode C3 (A) and electrode C5 (B). These electrodes overlay the left sensorimotor cortex (see Fig.4). The significant effect of Group was preserved at electrode C3 (t(25) = 3.25; p < 0.005) and at electrode C5 (t(24) = 3.18; p < 0.005) when performing the tests after removing the outliers.

Figure 6 .

 6 Figure 6. Time course of the baseline-normalized alpha and beta powers. For each participant, the powers (signal units 2 /Hz) were extracted from vertices within areas showing, for either the Hand or the Tool group, significant contrasts between the Mirror and Direct conditions (see Fig. 4). The red traces represent the between-participants mean powers. The black traces represent the cumulative integral of the baseline-normalized power computed for each participant. The arrows indicate the start tracing signal. It should be noted that the different graphs have different scales.

Acknowledgments

We thank Marie Fabre, Aurélie Grandjean and Chloé Sutter for their help at various stages of this research project. We also thank Franck Buloup for developing the software Docometre used for data acquisition, Marcel Kaszap for developing the software Analyse used for data processing.

Declarations of interest: none

Funding: this research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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