Alejandro Pérez
email: alejandro.perez@utoronto.ca

Guillaume Dumas

Melek Karadag

Jon Andoni Duñabeitia

Differential brain-to-brain entrainment while speaking and listening in native and foreign languages

Introduction

Verbal communication is associated with synchronous patterns of brain activity between the speaker and the listener [START_REF] Dai | Neural mechanisms for selectively tuning in to the target speaker in a naturalistic noisy situation[END_REF][START_REF] Jiang | Neural synchronization during face-to-face communication[END_REF][START_REF] Kawasaki | Inter-brain synchronization during coordination of speech rhythm in human-to-human social interaction[END_REF][START_REF] Kuhlen | Content-specific coordination of listeners' to speakers' EEG during communication[END_REF][START_REF] Liu | Measuring speaker-listener neural coupling with functional near infrared spectroscopy[END_REF][START_REF] Nozawa | Interpersonal frontopolar neural synchronization in group communication: An exploration toward fNIRS hyperscanning of natural interactions[END_REF][START_REF] Spiegelhalder | Interindividual synchronization of brain activity during live verbal communication[END_REF][START_REF] Tadic | Algebraic Topology of Multi-Brain Connectivity Networks Reveals Dissimilarity in Functional Patterns during Spoken Communications[END_REF]. This interbrain coupling seems to reflect the alignment between the processes of speech production and comprehension necessary for mutual understanding and successful communication [START_REF] Dikker | On the same wavelength: predictable language enhances speaker-listener brain-to-brain synchrony in posterior superior temporal gyrus[END_REF][START_REF] Schoot | What can we learn from a two-brain approach to verbal interaction[END_REF][START_REF] Stephens | Speaker-listener neural coupling underlies successful communication[END_REF]. Interestingly, in spite of the crucial importance of face-to-face interactions [START_REF] Jiang | Neural synchronization during face-to-face communication[END_REF], interbrain coupling also takes place in a turn-taking verbal exchange under conditions of no interpersonal visual contact [START_REF] Ahn | Interbrain phase synchronization during turn-taking verbal interaction-a hyperscanning study using simultaneous EEG/MEG[END_REF][START_REF] Pérez | Brain-to-brain entrainment: EEG interbrain synchronization while speaking and listening[END_REF]. In other words, successful verbal interaction is associated with brain-to-brain synchronization regardless of non-verbal communication. This indicates that, at least in healthy adults using their native language, a shared speech signal and the willingness to communicate are enough to elicit interbrain synchronization. This phenomenon has been termed brain-to-brain entrainment during speaking and listening (henceforth, B2B), and it has been suggested to result from the mutual neural entrainment mediated by the speech signal [START_REF] Pérez | Brain-to-brain entrainment: EEG interbrain synchronization while speaking and listening[END_REF].

Neural entrainment is a general mechanism by which brain oscillations adapt to the rhythm of regular stimulation [START_REF] Lakatos | Entrainment of neuronal oscillations as a mechanism of attentional selection[END_REF]. This way, and as a consequence of a series of predictive mechanisms, the upcoming stimuli in a time series will coincide with a specific predicted phase of the entrained oscillation, leading to an amplification of the neural response to expected stimulus and attenuation of those not expected [START_REF] Lakatos | Neuronal oscillations and multisensory interaction in primary auditory cortex[END_REF]. This mechanism seems particularly suited for the specific case of the quasi-rhythms of natural speech [START_REF] Ding | Cortical tracking of hierarchical linguistic structures in connected speech[END_REF], leading to the phenomenon referred to as brainentrainment to speech: the ongoing oscillatory rhythmic neural activity becomes synchronous, or entrains, to the slow temporal fluctuation (envelope) of acoustic verbal stimuli [START_REF] Ghitza | On the possible role of brain rhythms in speech perception: intelligibility of time-compressed speech with periodic and aperiodic insertions of silence[END_REF][START_REF] Giraud | Cortical oscillations and speech processing: emerging computational principles and operations[END_REF][START_REF] Luo | Phase patterns of neuronal responses reliably discriminate speech in human auditory cortex[END_REF]. Brain-entrainment to speech already starts at the speaker's side [START_REF] Magrassi | Sound representation in higher language areas during language generation[END_REF][START_REF] Pérez | Brain-to-brain entrainment: EEG interbrain synchronization while speaking and listening[END_REF] due to the monitoring of one's own speech and/or due to the generation of the internal representations (motor and linguistics) preceding verbal output [START_REF] Reznik | Lateralized enhancement of auditory cortex activity and increased sensitivity to self-generated sounds[END_REF]. Then, it takes place in the listener, linked to comprehension [START_REF] Peelle | Phase-locked responses to speech in human auditory cortex are enhanced during comprehension[END_REF]. Thus, at the basic physical level, B2B could be conceptualized as a situation in which one autonomous oscillator (speaker's brain) initiates an interaction (via speech) with another autonomous oscillator (listener's brain) leading to a mutual synchronization.

Albeit fostered and prompted by brain-entrainment to speech of the speaker and the listener, B2B not only occurs because of the joint entrainment to the speech envelope [START_REF] Dai | Neural mechanisms for selectively tuning in to the target speaker in a naturalistic noisy situation[END_REF]. The act of actively sharing relevant content through speech implies a form or partially disembodied interaction that goes beyond the physical verbal utterance [START_REF] Pérez | Brain-to-brain entrainment: EEG interbrain synchronization while speaking and listening[END_REF]. During purposeful verbal information exchange, people intend to convey and receive meaning, and in order to facilitate M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT 2 understanding and prediction of forthcoming speech, a form of mutual 'alignment' in attention to speech content is established between interlocutors (Friston & Frith, 2015a). The joint temporal fluctuations of attention resources associated with the timing and dynamics of the speech stream could be considered a type of joint attention neccesary for successful communication and also an emergent property of the interactive scenarios contributing to the B2B phenomenon [START_REF] Hari | Centrality of Social Interaction in Human Brain Function[END_REF]. In general, it could be stated that shared attention to the act of communication and brain-entrainment to speech are two entangled factors [START_REF] Alexandrou | The right hemisphere is highlighted in connected natural speech production and perception[END_REF][START_REF] Zion Golumbic | Mechanisms underlying selective neuronal tracking of attended speech at a "cocktail party[END_REF] playing a critical role in B2B. Here, the question under scrutiny is whether modulating linguistic contextual factors in a 'natural' manner influences the patterns of the interbrain coupling. Some linguistic contexts provide an ecologically valid scenario modulating the two mentioned factors. For instance, foreign language contexts represent a natural circumstance where intelligibility is hampered and the cognitive cost of producing and comprehending the language is higher than in native language contexts [START_REF] Pérez | Differential oscillatory encoding of foreign speech[END_REF], thus requiring enhanced attention. On one hand, speech-entrainment is a causal mechanism that modulates intelligibility (Riecke, Formisano, Sorger, Baskent, & Gaudrain, 2018;[START_REF] Zoefel | Phase Entrainment of Brain Oscillations Causally Modulates Neural Responses to Intelligible Speech[END_REF]. In turn, intelligibility enhances entrainment [START_REF] Buiatti | Investigating the neural correlates of continuous speech computation with frequency-tagged neuroelectric responses[END_REF][START_REF] Ding | Cortical tracking of hierarchical linguistic structures in connected speech[END_REF]. From this positive correlation between brain-entrainment to speech and speech intelligibility it could be derived that the reduced intelligibility inherent to a foreign language [START_REF] Munro | Processing time, accent, and comprehensibility in the perception of native and foreign-accented speech[END_REF] would be associated with a reduced entrainment. In other words, since brain-entrainment to speech and speech intelligibility interact (Riecke et al., 2018;[START_REF] Zoefel | Phase Entrainment of Brain Oscillations Causally Modulates Neural Responses to Intelligible Speech[END_REF], a decrease in the neural speech tracking would be expected for foreign language perception, at least for the low frequencies corresponding with parsing words from sentences. On the other hand, more cognitive resources should be recruited during foreign language processing to achieve a comprehension level comparable to that of a native language (see for review: [START_REF] Leow | Attention, Awareness, and Foreign Language Behavior[END_REF]). In the specific case of speech perception, increased cognitive resources should be devoted in order to enhance speech tracking/comprehension to similar levels as in a native language. In fact, brain-entrainment to (natural) speech is enhanced by attention [START_REF] Rimmele | The effects of selective attention and speech acoustics on neural speech-tracking in a multi-talker scene[END_REF][START_REF] Zion Golumbic | Mechanisms underlying selective neuronal tracking of attended speech at a "cocktail party[END_REF]. In the case of speech production, it is known that the role of attention in monitoring native and nonnative languages is markedly different [START_REF] Kormos | The Role of Attention in Monitoring Second Language Speech Production[END_REF]. Hence, additional attentional resources should be allocated during foreign language production in order to generate the otherwise more difficult utterances (Rommers, [START_REF] Meyer | Lateralized electrical brain activity reveals covert attention allocation during speaking[END_REF]. Thus, more attentional resources should be deployed during nonative speech perception and production. Altogether, it could be argued that using a foreign language reduces neural coupling to the speech and increases the cognitive load (attention) as compared to a native language [START_REF] Perani | The neural basis of first and second language processing[END_REF]. Based on these assumptions, here we hypothesized that the B2B pattern would be different for linguistic interactions carried out using a native and a foreign language.

We used a two-person-neuroscience approach [START_REF] Hari | Brain basis of human social interaction: from concepts to brain imaging[END_REF][START_REF] Schilbach | Toward a second-person neuroscience[END_REF] with electroencephalographic (EEG) hyperscanning [START_REF] Babiloni | Social neuroscience and hyperscanning techniques: past, present and future[END_REF] to simultaneously record the neural responses of two concomitant participants (a dyad) during a turn-taking verbal interaction in a native and foreign language. This experimental set-up, partially resembles a radio conversation in which

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3 the roles of the speaker and the listener do not overlap while exchanging oral narratives and has been proven to be effective for the study of B2B [START_REF] Pérez | Brain-to-brain entrainment: EEG interbrain synchronization while speaking and listening[END_REF]. In the current study, we employed this set-up to investigate the native-foreign contrast using dyads of native Spanish speakers who also had a good command of English. EEG phase synchronizations between brains were measured using the circular correlation coefficient (CCorr) [START_REF] Jammalamadaka | Topics in circular statistics[END_REF]. A comparison of synchrony estimations between the brains, obtained for theta (3-7 Hz), alpha (8-12 Hz), and beta (13-30 Hz) bands, evaluated differences between the conditions. Those frequency bands contain the range of frequencies that are responsible for the cortical tracking at the timescale of phonemes, syllables, words and phrases [START_REF] Keitel | Perceptually relevant speech tracking in auditory and motor cortex reflects distinct linguistic features[END_REF], and also have a functional role in attention deployment [START_REF] Frey | Not so different after all: The same oscillatory processes support different types of attention[END_REF]. We expected interbrain synchronization differences across dyads associated with the language used. This result would suggest that a language choice for a verbal interaction affects the similarity in the neural patterns of the interlocutors, indicating the need for the inclusion of the linguistic factors in the theoretical accounts of interpersonal communication.

Methods

Participants

We report EEG data from 60 participants (40 females; mean age: 22.5, SD: 2.7 years, range: 18-30). They were recruited from the BCBL participant pool and received monetary compensation for their collaboration. All participants were right-handed as assessed by an adapted version of the Edinburgh Handedness Inventory [START_REF] Oldfield | The assessment and analysis of handedness: the Edinburgh inventory[END_REF], and self-reported adequate hearing, normal or corrected to normal vision, no neurological/psychiatric disorders, and no current drug use. All had completed high school, and most were undergraduates from the University of the Basque Country. None of them had any speech or reading disorder. Individual written informed consent was obtained before the experimental session. The study was conducted in accordance with the Declaration of Helsinki (1964) and approved by the BCBL Ethics Committee.

The linguistic competence in Spanish and English languages was estimated by an interview and a lexical decision test (LexTale) [START_REF] De Bruin | The BEST Dataset of Language Proficiency[END_REF]. In the personal interview, all participants were classified as native Spanish speakers and received a score equal or above 3 (out of 5) in the part conducted in English, indicating at least basic fluency. The percentage of correct responses in the LexTale was markedly higher for Spanish (mean: 93.29, SD: 7.75) than for English (mean: 68.90, SD: 8.41), as expected given the difference in proficiency between the two tested. In addition, their first exposure to English occurred in all cases after the age of three.

Participants performed the study arranged in pairs (i.e. 30 dyads). Each dyad was composed of participants of the same gender [START_REF] Cheng | Synchronous brain activity during cooperative exchange depends on gender of partner: A fNIRS-based hyperscanning study[END_REF], equivalent age (with no more than five years of age difference), and they did not know each other before the experiment. We had three a-priori criteria to exclude participants' data: (i) technical issues during EEG acquisition such as saturation of the amplifiers, high electrode impedance or electrode detachment, (ii) participant discomfort with the experimental set-up, expressed overtly by them or perceived by the experimenter, and (iii) more than 25% of the EEG signal at any trial being irrecoverable due to large artifacts (e.g. laughing, sneezing,

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coughing, yawning or body movements). Data from three additional dyads were excluded due to these criteria. In the case of the analysis involving the audio signal, data from four of the 30 dyads were not included due to technical issues with the audio recordings (i.e., N=26 dyads).

Experimental Task

The dyads of participants were required to alternate between the roles of speaker and listener while interchanging verbal information. Specifically, they were asked to talk and listen about preferences and opinions for six different common topics while following a short plot in the form of five questions that was presented on the screen. Figure 1 depicts an example of this core structure of the experimental task. First, one topic accompanied by a series of five questions was presented on the screen. A cue indicated which of the two participants in dyad had to speak and which had to listen. Thus, depending on the assigned role, participants had to either speak as freely and naturally as possible about the topic (Speaker role), or to listen while paying careful attention to the other's speech (Listener role). In each turn, the speaker had 120 seconds to talk. Information about the remaining time was presented on the screen to facilitate the structuring of the discourse. The countdown clock showed the remaining time at irregular intervals. After each trial, the roles were reversed. Thus, both participants performed the role of speaker and listener for each corresponding topic. In each topic/block, we also recorded a baseline trial of the same length in which both participants had to remain silent. The key manipulation in the experimental design was that half of the topics should be discussed in English (foreign language; English condition) whereas the other topics should be discussed in Spanish (native language; Spanish condition). The language to speak was cued by the language used in the text presented on the screen. Sports, travel and food were used as topics for the English conditions and movies, animals and music, for the Spanish condition. The presentation order of the conditions and topics were random, and so was the order for the roles of listener, speaker and silence in each block. Hence, the experimental task comprised six listening trials, six speaking trials and six silent trials for each participant of the dyad. Half of these trials belonged to the English condition and the other half to the Spanish condition. After completing the experiment, participants were asked to complete a paper and pencil evaluation concerning the information provided by their partner. It consisted of a 30-item recall test created following the specific questions (and language) that were displayed to guide the plot of the conversation for each of the topic, and consequently these were the same for all participants (e.g., "What's his/her favorite sport?")". Each participant scored their partner's responses to assess whether they had paid attention to their speech.

Experimental setting

The experimental procedure started with the experimenters introducing the pair of participants to each other. The experimenters and participants continued engaging in small talk while setting up the EEG cap and electrodes. Detailed instructions and explanations about the experiment (including an example) were provided. Participants were specifically asked to (i) be relaxed and still, avoiding body movements (e.g. gesticulation, nodding); (ii) speak continuously and without much pausing, vocalize clearly and avoid whispering and the use of interjections when cued to speak; and (iii) pay careful attention to the content of the partner's verbal production. They were also informed that a short evaluation about the content of the partner's verbal productions (post-scan questionnaire) would take place at the end of the

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5 experiment and that they would receive a small monetary reward (€5) if responding correctly on at least 24 of the 30 questions.

Participants were seated side by side in a soundproof cabin, with a board placed between them to prevent them from seeing each other. A computer screen facing participants was placed at a distance of approximately one and a half meters, centred, and it was equally visible to the two participants. One microphone was used to record the verbal productions of both participants. The experiment was selfpaced, thus, each participant was provided with a response pad that was used to trigger the start of each trial. Presentation on the screen of all instructions and stimuli was controlled by a custom-written program created and compiled with Experiment Builder© software (SR-Research, Ontario, Canada) that was run on a PC. The program also recorded the audio files and sent the triggers to the PC used for the EEG recordings.

Figure 1. Schematic depiction of the experimental tasks. On each trial, the topic and a list of five questions to discuss, and an indication of whom should speak appeared on the screen. In the example, the topic is Food and the arrow points to the left, so the English language should be used and the left participant should be speaking. In the bottom-right corner, the time remaining in the trial was displayed at irregular intervals. Later on, the roles are reversed.

EEG hyperscanning recordings

Electrophysiological signals of each subject were acquired from a 32-channels BrainAmp Standard amplifier (Brain Products GmbH) with individual Reference and Ground electrodes. The two BrainAmps were connected to a USB 2 Adapter (BUA), and joint signals were monitored/recorded using one custom workspace in BrainVision Recorder. Elastic caps (EasyCap) mounted with 27 scalp Ag/AgCl electrodes were used to record the signal. Electrodes were placed according to the International 10-20 system and included Fp1/Fp2, F3/F4, F7/F8, FC1/FC2, FC5/FC6, C3/C4, T7/T8, CP1/CP2, CP5/CP6, P3/P4, P7/P8, O1/O2, Fz, Cz, and Pz. Ground and online reference electrodes were placed at AFz and FCz, respectively. Additional electrooculography (EOG) electrodes were placed at the external ocular canti (to monitor horizontal eye movements), and three electromyography (EMG) electrodes were placed at the right

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6 cheek, as well as superior and inferior left orbicularis oris muscle (halfway between the centre and the corner of the mouth). Impedance measurements were checked by two individual 32-channels workspaces corresponding to each participant/amplifier. Inter-electrode impedances were set below 5 kΩ at the beginning of the experiment. Data were acquired at a sampling rate of 250 Hz. EEG markers were time-locked to the beginning of each trial.

EEG Preprocessing

The data were analyzed using the EEGLAB toolbox [START_REF] Delorme | EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis[END_REF] v14.1.1 and custom programs, all running in MATLAB (version 2017a, The MathWorks Inc.). The recorded signal was highpass filtered at 2 Hz and separated in the two recordings corresponding to each participant. Then, an adaptive mixture independent component analysis (AMICA) technique [START_REF] Palmer | Modeling and Estimation of Dependent Subspaces with Non-radially Symmetric and Skewed Densities[END_REF] was applied to the data from each participant. AMICA has been shown to maximize mutual information reduction and the dipolarity of scalp projections following decomposition [START_REF] Delorme | Independent EEG sources are dipolar[END_REF]. The number of time points used to estimate the weighting matrix exceeded the minimum recommended amount for satisfactory decomposition in all dyads. Next, an equivalent dipole current source was fit to each IC using the DIPFIT toolbox of EEGLAB [START_REF] Oostenveld | Validating the boundary element method for forward and inverse EEG computations in the presence of a hole in the skull[END_REF]. Then, individual components accounting for blinks and saccades, heartbeat, muscle artifact or line noise were removed from the data. Component rejection was performed manually, guided by the following criteria: (i) the component's topography, (ii) the component's time-series, (iii) the component's power spectrum properties and (iv) properties of the dipole associated with each component: localization out of the head or close to eyes balls that was also associated with low variance (up to 15%). On average, we removed 4 components (range: 3-7, SD: 1.02). Next, an artifact subspace reconstruction (ASR) algorithm (T. [START_REF] Mullen | Real-time modeling and visualization of source dynamics and connectivity using wearable EEG[END_REF]; T. R. [START_REF] Mullen | Real-Time Neuroimaging and Cognitive Monitoring Using Wearable Dry EEG[END_REF] adapted for EEGLAB software (clean_rawdata plugin) was implemented to remove high amplitude artifact from the EEG. ASR transforms a sliding window of EEG data with principal component analysis to identify channels and times of high variance by statistical comparison with clean EEG data containing minimal artifact. The clean data used as calibration data for ASR were automatically found inside each EEG recording. Channels that show variance above a threshold compared to calibration data were eliminated. Corrupted subspaces of multiple channels were reconstructed from neighbouring channels using a mixing matrix that is computed from the covariance matrix of the calibration data. In this study, a sliding window of 500 ms and a variance threshold of 3 SD were used. Those portions of the data that were not possible to reconstruct due to the presence of multiple artifacts were marked to be removed in a posterior step (in seconds: M English : 1, SD English : 1.4; M Spanish : 1.7, SD Spanish : 2; t(58)=1.5, p=.14). Then, bad channels were interpolated. Subsequently, the continuous EEG signal was filter in the frequency band of interest, and 122 seconds epochs were extracted beginning one second prior to the onset of each stimulus. The instantaneous phase was estimated using the Hilbert transform, creating circular variables. Data from the first and last seconds and those time points not possible to reconstruct due to the presence of multiple artifacts were excluded. The CCorr was calculated over every possible combination of dyad's EEG electrodes (total of 729) in each trial by using the Circular Statistics Toolbox [START_REF] Berens | CircStat: A MATLAB Toolbox for Circular Statistics[END_REF]. Next, the calculated CCorr was normalized by Fisher's Z transformation and converted to absolute values. Normalized values obtained in the Silence condition were subtracted from those

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obtained in each corresponding topic [START_REF] Jiang | Neural synchronization during face-to-face communication[END_REF][START_REF] Pérez | Brain-to-brain entrainment: EEG interbrain synchronization while speaking and listening[END_REF]. If the coupling value for the Silence condition was larger than the obtained for the speaking and listening, subtraction was set to zero. This baseline normalization allows to reduce/eliminate non-specific kinds of engagement that may result from physical cohabitation as well as spurious synchronizations that may appear in hyperscanning EEG data [START_REF] Burgess | On the interpretation of synchronization in EEG hyperscanning studies: a cautionary note[END_REF]. Finally, the data were collapsed across topics for the Spanish and English conditions. This resulted in normalized estimations of synchronization in each frequency band, between the 27 channels of the Speaker and the 27 channels of the Listener. The Speaker-Listener situation is twofold for each member of the dyad, yielding independent observations of Speaker and Listener roles for all the participants.

Speech Processing

We computed the amplitude envelope of speech signals using a procedure similar to that described [START_REF] Chandrasekaran | The natural statistics of audiovisual speech[END_REF] and employed in preceding studies [START_REF] Gross | Speech rhythms and multiplexed oscillatory sensory coding in the human brain[END_REF][START_REF] Park | Lip movements entrain the observers' low-frequency brain oscillations to facilitate speech intelligibility[END_REF]. Using the Chimera toolbox [START_REF] Smith | Chimaeric sounds reveal dichotomies in auditory perception[END_REF], nine frequency bands in the range 100-10000 Hz that were equidistant on the cochlear map were constructed. Speech signals were band-pass filtered in these bands, and a Hilbert transform was applied to obtain amplitude envelopes for each of them. A wideband amplitude envelope was obtained by averaging envelopes across bands. The resulting envelopes were downsampled to 250 Hz for further analysis.

Statistical Analysis

A nonparametric bootstrap-based t-test method from EEGLAB's Resampling Statistical Toolkit was used to compare interbrain synchronization and brain to speech synchronization between language conditions. The bootstrap test is a distribution-free test and it does not require any assumptions about the correlation structure of the data. The number of random sampling was set to 10,000. An FDR correction [START_REF] Benjamini | The Control of the False Discovery Rate in Multiple Testing under Dependency[END_REF] for multiple comparisons (q=0.05) was applied to the p values obtained. Statistically significant effects are interpreted as showing differential B2B/speech tracking between native and foreign languages. Note that the experimental within-subjects design and corresponding statistics directly compared conditions and performed stringent corrections for multiple comparisons and spurious synchronizations.

Results

Brain-to-speech synchronization

First, the phase synchronization between the EEG signal and the speech audio envelope was compared between the Spanish and English conditions at the three frequency bands, separately, for the Listener and the Speaker. The heads in the left panel of Figure 2 show the topographical distribution of the tvalues from nonparametric permutation tests. The table on the right shows, for both roles and frequency bands, the electrodes at which the difference was statistically significant (p FDR <.05), by coloring in green a brain-to-speech coupling increased for the Foreign condition (English) and in red the Theta: Differential neural entrainment to the amplitude envelope was found for the Listener, reflected by increased coupling at Fz and FC6 for Spanish and English language, respectively.

Alpha: No statistically significant differences emerged.

Beta: Both the Speaker and the Listener showed increased brain-to-speech coupling at electrodes T8, P7 and FC5 for the Speaker and at P4 for the Listener. Beta band is supposed to reflect the close relationship between language comprehension and motor functions [START_REF] Weiss | Too Many betas do not Spoil the Broth": The Role of Beta Brain Oscillations in Language Processing[END_REF].

In general, these results suggest that neural tracking of a speech signal could variate depending on the language used, with a reduction in tracking in the less proficient language. This novel indication of differential brain-entrainment to speech for native and foreign languages already suggest that B2B patterns would be also differential. This is analysed in the next section.

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Figure 2. Group-level differences in brain entrainment to the speech envelope between the English and Spanish language conditions, for theta, alpha and beta bands, for the Speaker and the Listener's roles. The head plots show the topological distribution of the t-values from nonparametric permutation tests. The different colors represent the scale from -2 to 2. The matrix on the right shows the exact electrodes where the differences bettwen condition are statistically different (p FDR < 0.05) by coloring in green a brain-to-speech coupling increased for the Foreign condition (English) and in red the coupling increased for the Native condition (Spanish). Rows represent the electrodes and columns represent the role-frequency band. Significantly different brain-to-speech synchronization is mainly due to an increase in tracking for the Native condition.

Brain-to-brain synchronization

The baseline-corrected phase synchronization calculated for all Listener/Speaker electrode pair combinations of the EEG signals (i.e. 27 × 27 electrodes) was compared between the Spanish and English conditions for theta, alpha, and beta frequency bands for all the participants (N=60, all df=59). Figure 3 presents dual head plots and a heat map image of the differential patterns of interbrain phase synchronization between language conditions that were statistically significantly different (p FDR <.05).

Both representations depict the same data in complementary ways to facilitate the interpretation of the exact Listener/Speaker electrode pairs at which the differences were observed. The colours green and red are used to specify if the synchronization is larger for the native, Spanish condition (red) or the foreign, English condition (green). In the dual head plot, lines linking the electrodes of the Listener and the Speaker represent the differences. In the heat map, the intersection between the electrode pairs of the Listener (rows) and the Speaker (columns) are coloured to show the electrodes pairs at which there were significant differences between conditions. Supplementary Material 2 contains all exact p-values (uncorrected) and the corresponding t-values associated to these figures.

Theta and Beta: No statistically significant differences between conditions resulted after the FDR correction.

Alpha: Language condition differentially modulated the between-brain coupling at 14 electrodes-pairs, broadly distributed across the scalp of the Listener and the Speaker: 5 show a larger synchronization for the native language context (Spanish), and 9 for the foreign language context (English). Note that electrodes-pairs showing an effect do not include channels identified as bad in more than the half of the participants (namely, Fp1 and F7). The coupling strength between brain signals is increased in both the native language context and the foreign language context. That is, relative to English, we saw increased coupling at Spanish, but also the opposite case.

05). The same results are indicated in the matrix by colouring the intersection between Speaker's electrodes (columns) and Listener's electrodes (rows).

Interbrain coupling increased for the Native condition (Spanish) is indicated in red and increased for the Foreign condition (English) is indicated in green. Significantly different interbrain synchronization is evident between the Native and Foreign language conditions in a broad scalp topography.

Behaviour

Overall performance in the 30-item recall test was markedly high (mean: 96.83%, SD: 5.22, range: 80-100). The high level of recall did not depend on the language in which the conversation about each topic was held since the percentages of correctly recalled items did not significantly vary across language blocks (M English : 97.33, SD English : 5.65; M Spanish : 96.44, SD Spanish : 6.78; t(59)=1.03, p=.31). The additional analysis confirmed that the performance in the different individual topics was similar, with average accuracy levels ranging from 93.33% to 98.67%. This indicate the topics elicited similar interest.

Discussion

Prior studies using the hyperscanning technique have already demonstrated differences in the coupling patterns between brains due to factors like gaze [START_REF] Lachat | Oscillatory Brain Correlates of Live Joint Attention: A Dual-EEG Study[END_REF][START_REF] Leong | Speaker gaze increases information coupling between infant and adult brains[END_REF], cooperation [START_REF] Astolfi | Neuroelectrical hyperscanning measures simultaneous brain activity in humans[END_REF], movement [START_REF] Dumas | Inter-brain synchronization during social interaction[END_REF], or intention [START_REF] Tang | Interpersonal brain synchronization in the right temporo-parietal junction during face-to-face economic exchange[END_REF]. Here we demonstrate that differences in interbrain phase synchronization could be also due to the linguistic context where the exchange of verbal information is set, as illustrated by differences for native and foreign language contexts.

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11 As it could be expected from the studies showing that neural coupling is significantly diminished for an unintelligible language [START_REF] Stephens | Speaker-listener neural coupling underlies successful communication[END_REF], there is a relative increase in interbrain coupling when the speaking and listening takes place in the more intelligible (native) language. However, a relative enhancement of the B2B coupling also takes place in a foreign language context. These results suggest that differences are not exclusively due to a decrease in the quality of the communication when the foreign language is used, given that under this assumption no signs for an enhanced interbrain coupling would have been expected for the foreign language as compared to the native language context. Moreover, considering the behavioral results showing that the item recall test was equivalent across the different language conditions, an explanation purely based on the intelligibility of foreign language speech cannot account for the general pattern of results here presented. Instead, this twofold directionality of the effects indicates that interbrain neural alignment depends on the language context and the demands of speaking and listening in this context.

The finding of dissimilar B2B patterns associated to different linguistic contexts could be interpreted according to the framework of the interactive linguistic alignment (ILA) theory (see [START_REF] Pickering | Toward a mechanistic psychology of dialogue[END_REF]. According to this theory, during verbal communication, production and comprehension processes become aligned at different levels: phonetic, phonological, lexical, syntactic and semantic. In fact, the linguistic operations needed to understand and produce an utterance rely to a great extent on similar networks of the brain [START_REF] Menenti | Shared language: overlap and segregation of the neuronal infrastructure for speaking and listening revealed by functional MRI[END_REF]. Thus, interpersonal linguistic alignment during speaking and listening will be supported by a similar underlying neural configuration (and timing) at each of those linguistic levels mentioned above. Importantly, the neural configuration of each specific linguistic feature will depend on the language system or code used. For illustration purposes, consider the phonological/articulatory alignment for the word 'snake' being produced and perceived in English. Even under the assumption of the existence of subject-invariant semantic representations [START_REF] Mahon | Arguments about the nature of concepts: Symbols, embodiment, and beyond[END_REF], the phonological/articulatory alignment would be different for the corresponding Spanish translation equivalent ('serpiente'). In an extreme positioning of this view, it could be also considered that linguistic features may not be shared across languages at all, and that bilinguals exhibit language-dependent neuroanatomical and semantic representations [START_REF] García-Pentón | The neuroanatomy of bilingualism: how to turn a hazy view into the full picture[END_REF]. In other words, the functional organization (i.e., the neural activation patterns) related to the processing of distinct linguistic features may be different for different language systems (Pérez, Gillon-Dowens, et al., 2015), consequently impacting differently on the neural alignment between interlocutors across languages.

In the current study, differential B2B synchronization or alignment while speaking and listening in native and foreign languages was evident in the alpha frequency band. Increased interbrain coupling results from a direct statistical comparison between conditions and it is interpreted as an indication of a greater similarity between the neurophysiological activity of two different brains. This means that the current results speak for a more similar alpha oscillatory activity in one language vs. the other, but not necessarily for an increase in alpha activity. Alpha oscillations are the prevalent rhythm of the brain, being linked to main cognitive functions such as attention [START_REF] Klimesch | Alpha-band oscillations, attention, and controlled access to stored information[END_REF], working memory [START_REF] Wilsch | Alpha Oscillatory Dynamics Index Temporal Expectation Benefits in Working Memory[END_REF] or decision making [START_REF] Cohen | Oscillatory activity and phase-amplitude coupling in the human medial frontal cortex during decision making[END_REF]. In fact, alpha oscillations seem to play a major role in functional inhibition [START_REF] Jensen | Shaping functional architecture by oscillatory alpha activity: gating by inhibition[END_REF], hindering the

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12 processing capabilities of a given area of the brain. A corollary to that idea is that optimal task performance will correlate with alpha activity in task-irrelevant areas [START_REF] Jensen | Shaping functional architecture by oscillatory alpha activity: gating by inhibition[END_REF]. Interestingly, the topography of the effects denoting increased alignment in alpha is more broadly distributed over the scalp and includes more pairs of electrodes in a foreign language contexts than in the native language, in line with the requirement of an increased auditory selective inhibition due to the challenging conversational situation represented foreign language exchanges of information [START_REF] Strauß | Alpha and theta brain oscillations index dissociable processes in spoken word recognition[END_REF][START_REF] Strauß | Cortical alpha oscillations as a tool for auditory selective inhibition[END_REF]. Besides, alpha is one of the dominant rhythms in motor areas [START_REF] Pineda | The functional significance of mu rhythms: translating "seeing" and "hearing" into "doing[END_REF], and the specific pattern of increased brain-to-brain entrainment in the native language is clustered in fronto-central areas. This could tentatively be taken as evidence supporting a larger similarity between speakers and listeners at the sensory-motor levels of speech production and perception when the interlocutors are expert users of a given language. This observation is supported by the described shared ventral premotor substrate for real-life speech production and perception [START_REF] Glanz Iljina | Real-life speech production and perception have a shared premotor-cortical substrate[END_REF] and the central alpha activity influencing speech tracking in a native language [START_REF] Keitel | Auditory cortical delta-entrainment interacts with oscillatory power in multiple fronto-parietal networks[END_REF]. Overall, the differential B2B alignment found in the alpha (and not theta) band is in line with the evidence supporting the role of alpha in linguistic processing [START_REF] Obleser | Suppressed alpha oscillations predict intelligibility of speech and its acoustic details[END_REF].

We further interpret this differential B2B pattern in the alpha band as a result from the different network configurations operating because of the language-idiosyncratic joint attentional fluctuations. In our view, 'purely attentional' alpha oscillations covary for speech perception and speech production depending on the language context. Joint attention is a ubiquitous element of theories of successful interpersonal communication [START_REF] Schirmer | The Socio-Temporal Brain: Connecting People in Time[END_REF]. Successful communication requires coordinated attention between interlocutors. In the case of the verbal communication, this tight relationship in the attentional fluctuations is established due to interactive prediction processes between the interlocutors [START_REF] Friston | Active inference, communication and hermeneutics[END_REF]. For different languages, there is a change in the probabilistic nature of linguistic behavior, the structure of thought processes, and the perceptual/motor biases (among others), leading interlocutors to prioritize different aspects of events in narrative discourse [START_REF] Beckner | Language Is a Complex Adaptive System: Position Paper[END_REF]. In the context of the current study, and considering that participants were not balanced bilinguals, it seems reasonable to assume fundamental differences between both language settings related to phonemic and prosodic awareness. This way, language proficiency could be automatically imposing particular attentional demands and strategies (i.e., attending smaller chunks of information) when speaking and listening in a foreign language, yielding a direct impact on attentional alignment (Pérez, Carreiras, et al., 2015). In conclusion, we claim that communication in a foreign language would need reshaping the attentional strategies to achieve a mutual understanding resulting in a distinctive fluctuation of joint attention reflected in the alpha band.

Although the focus of our study was on the interbrain synchronization between language contexts, we also noted difference in brain-to speech entrainment to native and foreign languages. Considering that all participants were heavily accented nonnative speakers of English as a foreign language, this could have modulated the brain-to-speech entrainment patterns, adding complexity to the interpretation. However, quite interestingly, no brain-to-speech effects emerged in alpha band, where the main brainto-brain differences were found, suggesting that these two entrainment effects are somewhat

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independent from each other. Although speech intelligibility and brain-entrainment to speech interact reciprocally depending on attention, the effects of brain-to-speech entrainment have been found to be independent of brain-to-brain synchronization. Furthermore, the specific timeline of speech tracking is different for speakers and listeners, highlighting also temporal differences between B2B and brain-tospeech entrainment depending on the conversational role being played [START_REF] Stephens | Speaker-listener neural coupling underlies successful communication[END_REF]. Thus, while B2B and brain-to-speech entrainment relate to seemingly conceptually related elements, establishing a direct link between them is not supported by current evidence, suggesting that one does not emerge as a direct transitive property of the other.

It remains unclear whether factors other than linguistic alignment, joint attention and brainentrainment to speech could yield or interact to lead to the differential interbrain synchronization patterns. One could also attribute the differential entrainment pattern to differences in the emotional processing associated with foreign language communication (Lev-Ari, Ho, & Keysar, 2018) or because using a foreign language reduces mental imagery [START_REF] Hayakawa | Using a foreign language reduces mental imagery[END_REF]. Emotions elicit synchronization in brain activity across individuals [START_REF] Nummenmaa | Emotional speech synchronizes brains across listeners and engages large-scale dynamic brain networks[END_REF] and the degree of empathy correlates with the brain-to-brain coupling [START_REF] Goldstein | Brain-to-brain coupling during handholding is associated with pain reduction[END_REF]. Less emotional engagement in foreign language contexts could be shaping the interbrain synchronization patterns during verbal interactions. Nonetheless, this is admittedly just one of many possible additional factors, and the additional underlying forces (see also [START_REF] Mu | Oxytocin enhances inter-brain synchrony during social coordination in male adults[END_REF] driving the differential B2B pattern to the foreign language remain as open questions for future research.

Brain entrainment to speech is considered as a mechanistic component of speech encoding serving speech segmentation and parsing at different timescales (e.g., words and syllables). In the same way, brain-to-brain entrainment while speaking and listening could be an emergent mechanism enabling to convey information across brains by fostering mutual intelligibility, coordinated (joint) attention and the linguistic alignment needed for successful communication between individuals. Nonetheless, and as a cautionary note, we want to stress that the characterization of B2B as a mechanism that underlies human communication is still premature, given that its specific internal organization as well as its the causal role need to be first identified [START_REF] Craver | Mechanisms in Science[END_REF]. Although previous results indicate that B2B contributes to successful communication [START_REF] Stephens | Speaker-listener neural coupling underlies successful communication[END_REF], this does not necessarily imply that interbrain synchronization is sufficient or even required for successful communication. B2B remains as a measurable reflection of the underlying neural computations that underpin shared cognitive processes [START_REF] Dikker | Brain-to-Brain Synchrony Tracks Real-World Dynamic Group Interactions in the Classroom[END_REF], and future studies on the interactions between B2B and comprehension using techniques that allow for direct stimulation and disruption of the processing in the critical areas [START_REF] Zoefel | Transcranial electric stimulation for the investigation of speech perception and comprehension[END_REF] will clarify if neural alignment is indeed a mechanism underlying the phenomenon of verbal communication.

It is worth noting that any synchronization effects obtained in the current experiment have been solely driven by the linguistic interaction, and not by embodied interactions like lip movements or any kind non-verbal communication. In our view, avoiding visual contact between the interlocutors is beneficial for the purposes of experimental neurolinguistic studies aimed at tracking synchronous neural activity in response to verbal interactions, since visual cues (facial, gestural) not only supplement but sometimes even override the speech signal. Also, interlocutors speak more intelligibly when they cannot see one [START_REF] Bruce | All the better for not seeing you': effects of communicative context on the speech of an individual with acquired communication difficulties[END_REF][START_REF] Pate | Talkers account for listener and channel characteristics to communicate efficiently[END_REF], and this could favor the purposes of studies such as the current one. Moreover, the turn-taking strategy used in our experimental setup resembles 'formal' real life situations, such as interviews and panel discussions, and other scenarios in which the timing of the interactions (and the interaction itself) is constrained by social rules and expectations. Thus, we believe that the paradigm used here could be considered both efficient and ecologically valid for the study of the role of linguistic interactions. Nonetheless, we stress that faceto-face conversations improve the quality of communication, and this could yield different B2B patterns.

Future methodological advances will be of help to explore B2B entrainment in different communicative scenarios.

In sum, it seems clear that the type or nature of the linguistic context impacts on the alignment of neural activity between speakers and listeners, at least for the case tested here with languages in which participants had dissimilar proficiency. These interbrain synchronization effects highlight some mechanisms that occur in linguistic interactions that cannot be otherwise captured by assessing individual brains [START_REF] Hasson | Brain-to-brain coupling: a mechanism for creating and sharing a social world[END_REF]. Findings here open doors to the study of the role of linguistic factors as mediators of social interactions using a multi-person perspective [START_REF] Evans | On projecting grammatical persons into social neurocognition: a view from linguistics[END_REF]. We propose that the study of neurolinguistics more centered on the neural changes resulting from the joint communicative intention will help uncovering the mechanisms and processes involved in interpersonal interactions, improving our understanding of language processing in more ecologically valid settings. As illustrated by the present work, it is only by taking into account the multiple dimensions of factors that influence two-way communication that we will be able to develop comprehensive theoretical accounts of how humans communicate with one another.

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A C C E P T E D

  the Native condition (Spanish). The statistics of these comparisons are included in Supplementary Material 1 (all df=55).

Figure 3 .

 3 Figure 3. Group-level differences in interbrain synchronization patterns between the Foreign and Native language conditions for the alpha band. The dual head plot and the matrix constitute equivalent representations. The coloured lines are connecting those electrodes pairs from the Speaker (red head) and the Listener (blue head) showing statistically significant differences between conditions (p FDR <.05). The same results are indicated in the matrix by colouring the intersection between Speaker's electrodes (columns) and Listener's electrodes (rows).Interbrain coupling increased for the Native condition (Spanish) is indicated in red and increased for the Foreign condition (English) is indicated in green. Significantly different interbrain synchronization is evident between the Native and Foreign language conditions in a broad scalp topography.

Acknowledgment

We thank Rosa M. Fernández, Jo-Anne Blanchet and Gino Ruffo for their support at different stages of the study. We also thank Dr. Blair Armstrong for the revision of the manuscript. The authors acknowledge financial support from the Spanish Ministry of Economy and Competitiveness through the "Severo Ochoa Programme for Centres/Units of Excellence in R&D" (SEV-2015-490) and the PSI2015-65689-P grants.

Code availability

The code that support the findings of this study is available upon request to A.P.

Data availability

The data that support the findings of this study is property of the BCBL institution. For data access request please contact: info@bcbl.eu.

Author Contributions

A.P., G.D., J.A.D. conceived and designed the experiment. M.K. collected and organized the data. A.P. processed the data. A.P., G.D. and J.A.D. analyzed the data and interpreted the results. A.P. drafted the

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Supplementary Material 1. Statistics from the brain-to-speech entrainment. Document containing all electrodes exact p-values (uncorrected) and the corresponding t-values obtained from the comparison between the Spanish and English conditions at the three frequency bands, for the Listener and the Speaker. Supplementary Material 2. Statistics from brain-to-brain entrainment. Document containing all electrodes-pairs' exact p-values (uncorrected) and the corresponding t-values obtained from the comparison between the Foreign and Native language conditions for the alpha band.


Rémi Giraud

Vinh-Thong Ta

Nicolas Papadakis

SUPERPIXEL-BASED COLOR TRANSFER

Keywords:

In this work, we propose a fast superpixel-based color transfer method (SCT) between two images. Superpixels enable to decrease the image dimension and to extract a reduced set of color candidates. We propose to use a fast approximate nearest neighbor matching algorithm in which we enforce the match diversity by limiting the selection of the same superpixels. A fusion framework is designed to transfer the matched colors, and we demonstrate the improvement obtained over exact matching results. Finally, we show that SCT is visually competitive compared to state-of-the-art methods.

INTRODUCTION

Color transfer consists in modifying the color distribution of a target image using one or several reference source images. The produced result must be consistent with the target image structure, and computational time is an important issue to process large images or video sequences. Color transfer. Initiated by [START_REF] Reinhard | Color transfer between images[END_REF], many approaches have been proposed to transfer color statistics in different color spaces [START_REF] Xiao | Color transfer in correlated color space[END_REF][START_REF] Pitié | The linear Monge-Kantorovitch linear colour mapping for example-based colour transfer[END_REF][START_REF] Papadakis | A variational model for histogram transfer of color images[END_REF][START_REF] Nguyen | Illuminant aware gamut-based color transfer[END_REF]. Optimal transportation tools have also been intensively studied to match and transfer the whole color distribution [START_REF] Pitié | Automated colour grading using colour distribution transfer[END_REF][START_REF] Rabin | Removing artefacts from color and contrast modifications[END_REF][START_REF] Frigo | Optimal transportation for example-guided color transfer[END_REF]. Nevertheless, as underlined in [START_REF] Pouli | Progressive color transfer for images of arbitrary dynamic range[END_REF], since color distributions between images may be very different, the exact transfer of the color palette may produce visual outliers. Relaxed optimal transport models, that do no exactly match color distributions, have then been proposed to tackle this issue [START_REF] Ferradans | Regularized discrete optimal transport[END_REF], but they rely on time consuming algorithms. Moreover, when the process is only performed in the color space, incoherent colors may be transfered to neighboring pixels. Artifacts such as JPEG compression blocks, enhanced noise or saturation then become visible [START_REF] Su | Corruptive artifacts suppression for example-based color transfer[END_REF], unless considering object semantic information [START_REF] Frigo | Optimal transportation for example-guided color transfer[END_REF]. In [START_REF] Tai | Local color transfer via probabilistic segmentation by expectationmaximization[END_REF], an EM approach is used to estimate a Gaussian mixture model in color and pixel space, since the pixel location helps to preserve the image geometry. However, a major limitation is the matching of clusters using a greedy approach based on nearest-neighbor criterion, with no control on the selected source colors. In [START_REF] Rabin | Non-convex relaxation of optimal transport for color transfer[END_REF], a relaxed optimal transport model is applied to color transfer using superpixel lower-level representation. Superpixels. These decomposition methods reduce the image dimension by grouping pixels into homogeneous areas [START_REF] Achanta | SLIC superpixels compared to state-ofthe-art superpixel methods[END_REF][START_REF] Van Den Bergh | SEEDS: Superpixels extracted via energy-driven sampling[END_REF][START_REF] Giraud | SCALP: Superpixels with contour adherence using linear path[END_REF]. They have become widely used to reduce the computational burden of various image processing tasks such as multi-class object segmentation [START_REF] Tighe | SuperParsing: Scalable nonparametric image parsing with superpixels[END_REF], object localization [START_REF] Fulkerson | Class segmentation and object localization with superpixel neighborhoods[END_REF] or contour detection [START_REF] Arbelaez | Contour detection and hierarchical image segmentation[END_REF]. Generally, the irregular geometry of the decompositions makes difficult their use into standard processes. However, for color transfer application, superpixels become particularly interesting since they enable to describe consistent color areas, and matches can be found regardless of the superpixel neighboring structure. Superpixel-based approaches such as [START_REF] Rabin | Non-convex relaxation of optimal transport for color transfer[END_REF][START_REF] Liu | Photo stylistic brush: Robust style transfer via superpixel-based bipartite graph[END_REF] allow a better adaptation to color histograms and image content, but still require important computational cost. Except for tracking applications [START_REF] Wang | Superpixel tracking[END_REF], fast superpixel matching methods have been little investigated. For instance, in [START_REF] Gould | PatchMatchGraph: Building a graph of dense patch correspondences for label transfer[END_REF], the PatchMatch (PM) algorithm [START_REF] Barnes | PatchMatch: A randomized correspondence algorithm for structural image editing[END_REF] that finds approximate nearest neighbor (ANN) patches between images is adapted to graphs, and [START_REF] Gould | Superpixel graph label transfer with learned distance metric[END_REF][START_REF] Giraud | SuperPatchMatch: An algorithm for robust correspondences using superpixel patches[END_REF] consider it in the superpixel context. Contributions. In this work, we propose a fast superpixelbased color transfer method (SCT). An example result of SCT is given in Figure 1. To select the color candidates, we use the fast and robust PM algorithm, that we adapt to handle superpixels [START_REF] Giraud | SuperPatchMatch: An algorithm for robust correspondences using superpixel patches[END_REF]. Contrary to [START_REF] Tai | Local color transfer via probabilistic segmentation by expectationmaximization[END_REF], we propose a method to constrain the ANN search process to limit the selection of the same superpixels in the source image. Throughout the paper, we demonstrate the significant improvement obtained with this constraint, that enables to enforce the match diversity and to capture a larger color palette, similarly to [START_REF] Rabin | Non-convex relaxation of optimal transport for color transfer[END_REF]. The selected colors are then transfered by a color fusion approach inspired from the non-local means framework [START_REF] Buades | A non-local algorithm for image denoising[END_REF]. Finally, we show that SCT produces accurate color transfer in low computational time thanks to the superpixel representation.

SUPERPIXEL-BASED COLOR TRANSFER METHOD

ANN Superpixel Matching

PatchMatch algorithm. The PatchMatch (PM) method [START_REF] Barnes | PatchMatch: A randomized correspondence algorithm for structural image editing[END_REF] computes correspondences between pixel patches of two images A and B. It exploits the assumption that if patches are matched between A and B, then their respective adjacent neighbors should also match well. Such propagation, associated with a random selection of patch candidates, enables the algorithm to have a fast convergence towards good ANN. PM is based on three steps. The first one randomly assigns to each patch of A, a corresponding patch in B. An iterative refinement process is then performed following a scan order (top left to bottom right) to refine the correspondences with the propagation and random search steps. For a patch A i ∈ A, the aim is to find the match B (i) ∈ B that minimizes a distance D(A i , B (i) ), for instance the sum of squares differences of color intensities. During propagation, for each patch in A, the two recently processed adjacent patches are considered. Their matches in B are shifted to respect the relative positions in A, and the new candidates are tested for improvement. Finally, the random search selects candidates around the current ANN in B to escape from local minima.

Adaptation to superpixel matching. Several issues appear when considering the PM algorithm to the matching of superpixels [START_REF] Giraud | SuperPatchMatch: An algorithm for robust correspondences using superpixel patches[END_REF]. Since superpixels decompose the image into irregular areas, there is no fixed adjacency relation between the elements. First, a scan order must be defined to process the superpixels. Then, during propagation, the decomposition geometry being also different in the image B, the shift of the neighbor cannot be directly performed. A solution is to select the candidate with the most similar relative orientation computed with the superpixel barycenters. Figure 2

Constraint on Match Diversity

In practice, the ANN search may converge towards exact matching, almost providing the nearest neighbors. The aim of color transfer is to globally capture the source color palette. If the source image contains one or several elements that match well the color set of the target image A, the ANN search may lead to the same match in B. The color transfer would thus provide a result very close to A. Figure 3 illustrates this issue. Since the source image also contains red colors, all superpixels of the target image find a close red match in the source space, leading to no color transfer.

To enforce the match diversity and capture a larger color palette of the source image, we propose to constrain the ANN search and to restrict the number of associations to the same element. To do so, we set a parameter that defines the maximum number of selection of the same superpixel. Such constraint requires the number of source elements |B| to be such that |A| ≤ |B|. In Figure 3, with = 1, the target superpixels now capture the global palette of the source image. First, we make sure that the initialization step respects this constraint when randomly assigning the correspondences. Then, during the following iterative process, a superpixel A i can be assigned to a superpixel B k , only if less than superpixels in A are already assigned to B k . If B k is already matched by elements in A, one superpixel A j assigned to B k must be sent to another superpixel in B to allow A i to match B k . We propose to compute the cost of sending a superpixel A j , currently matched with B k , towards B (i) , the current correspondence of A i , thus making a switch between the matches, and ensuring the respect of the constraint set by . For all superpixels A j matched to B (j) = B k , the switching cost is considered as follows:

C(A i , A j ) = (D(A i , B (j) ) -D(A i , B (i) )) + (D(A j , B (i) ) -D(A j , B (j) )). (1)
If a superpixel A j reduces the global matching distance, i.e., if the cost C < 0, we proceed to the following assignments: argmin

Aj (C(A i , A j )) → B (i) and A i → B (j) = B k .
Comparison to optimal assignment. The proposed ANN algorithm with = 1 approximates the optimal assignment problem, addressed with the Hungarian or Munkres algorithms [START_REF] Munkres | Algorithms for the assignment and transportation problems[END_REF]. Given two sets of elements {A i } i∈{1,...,|A|} and {B j } j∈{1,...,|B|} with |A| ≤ |B|, the aim is to find to each A i , an assignment B (i) that can only be selected once, and to minimize the global distance between the matched elements. In Figure 4, we consider two close images of 1920×800 pixels [START_REF] Korman | Coherency sensitive hashing[END_REF]. We show the target image reconstruction A from the matched superpixels average colors and compare total matching distance and computational time between our approach, optimal resolution [START_REF] Munkres | Algorithms for the assignment and transportation problems[END_REF], and to random superpixel assignments, i.e., the initialization step of our algorithm. Our fast superpixel ANN method provides close results to the optimal resolution while being order of magnitude faster.

Color Fusion Framework

Our matching framework provides an ANN in B to each superpixel of A. The aim is then to transfer the color of the matches to compute the color transfer image A t while preserving the structure of the target A. Since the matched superpixels are very likely to have different shapes, there are no direct pixel associations between elements, and source colors cannot be directly transfered to A at the pixel scale. The average colors of superpixels in B can be transfered to the ones in A but it would give a piece-wise color transfer result.

We propose to consider the average colors from the matched superpixels in a non-local means fusion framework [START_REF] Buades | A non-local algorithm for image denoising[END_REF]. Hence, all matched colors can contribute to the color computation of each pixel in A t . Such approach enables to increase the number of color candidates and leads to new potential ones that adapt well to the target image content. A superpixel A i is described by the set of positions X i and colors C i of the contained pixels p, such that

A i = [X i , C i ] = [(x i /N x , y i /N y ), (r i , g i , b i )/255],
with N x ×N y the size of image A. To compute the new color A t (p) of a pixel p, the weighted fusion of the matched colors is performed based on color and spatial similarity:

A t (p) = j ω(p, A j ) CB (j) j ω(p, A j ) , (2)
Target/Source images Superpixels Average colors

Matched colors Color fusion Color fusion + [29]

Fig. 5: Results of each SCT step. See text for more details.

with CB (j) , the average color of the match of A j in B, and ω(p, A j ) the weight that depends on the distance between the considered pixel p ∈ A i and the superpixel A j ∈ A. This weight is computed similarly to a Mahalanobis distance:

ω(p, A j ) = exp -(p -Āj ) T Q -1 i (p -Āj ) -σ(p) , (3)
where σ(p) sets the exponential dynamic and is set such that

σ(p) = min j (p -Āj ) T Q -1 i (p -Āj )
, and Q i includes spatial and colorimetric covariances of the pixels in A i :

Q i = Q(A i ) = δ 2 s Cov(X i ) 0 0 δ 2 c Cov(C i ) . (4)
The SCT steps are illustrated in Figure 5. We show the decomposition of images into superpixels with average colors, the matched source colors, and results of color fusion and post-processing with a color regrain [START_REF] Pitié | Towards automated colour grading[END_REF].

COLOR TRANSFER RESULTS

Parameter Settings

SCT is implemented with MATLAB using C-MEX code. Superpixel decompositions are computed using [START_REF] Giraud | SCALP: Superpixels with contour adherence using linear path[END_REF] such that each superpixel approximately contains 500 pixels. The superpixel matching is performed on normalized cumulative color histogram features and the number of ANN search iterations is set to 20. The covariance parameters in Eq. ( 4) are set such that δ s =100δ c and δ c =0.1 in order to favor spatial consistency. Finally, unless mentioned, is set to 3 and the results are slightly refined using a color regrain [START_REF] Pitié | Towards automated colour grading[END_REF].

Our method produces results in very low computational time due to the use of superpixels, i.e., less than 1s for images of 480×360 pixels. Decompositions are computed with [START_REF] Giraud | SCALP: Superpixels with contour adherence using linear path[END_REF] in less than 0.4s, matching is performed in approximately 0.1s and color fusion takes 0.25s to provide the color transfer.

Target image Source image [6] [4]

[5] SCT Fig. 7: Visual comparison to [START_REF] Pitié | Automated colour grading using colour distribution transfer[END_REF], [START_REF] Papadakis | A variational model for histogram transfer of color images[END_REF] and [START_REF] Nguyen | Illuminant aware gamut-based color transfer[END_REF]. SCT provides more visually satisfying or equivalent results to the compared methods.

Influence of Match Diversity

Additionally to Figure 3, we illustrate in Figure 6 the influence of the parameter that limits the source superpixel selection. It appears that even fast ANN search may lead to the same best match, as shown with the maps corresponding to the selection of source superpixels. For instance, most target superpixels of the white flower match the only white superpixel in the source image, leading to almost no color transfer. With the proposed method, we select accurate matches while capturing the global color palette of the source image.

Comparison with State-of-the-Art Methods

In this section, we compare the results of SCT to various methods based on optimal transport [START_REF] Pitié | Automated colour grading using colour distribution transfer[END_REF], histogram transfer with a variational model [START_REF] Papadakis | A variational model for histogram transfer of color images[END_REF] and 3D color gamut mapping [START_REF] Nguyen | Illuminant aware gamut-based color transfer[END_REF]. Figure 7 illustrates color transfer examples for all methods. SCT produces more visually satisfying results than the ones of the compared methods. The colors are relevantly transfered to the target image with respect to the initial grain and exposure. For instance, on the first image (top row), [START_REF] Pitié | Automated colour grading using colour distribution transfer[END_REF], [START_REF] Papadakis | A variational model for histogram transfer of color images[END_REF] and [START_REF] Nguyen | Illuminant aware gamut-based color transfer[END_REF] produce color transfers that strongly modify the il-lumination of the target image. All compared methods except SCT fail at transferring the blue color from the desert sky into the sea (middle row), and the orange color of the stones to the grass of the moutain (bottom row). Contrary to the compared methods, we consider a selection of the source colors and our fusion model enables to adapt to the target image, preserving its structure and initial exposure. Finally, while SCT results are computed in less than 1s, while other models such as [START_REF] Papadakis | A variational model for histogram transfer of color images[END_REF] may require prohibitive computational times, up to 120s.

CONCLUSION

In this work, we propose a novel superpixel-based method for color transfer. Our algorithm is based on a fast ANN search and fusion of source colors in a non-local means framework. We introduce a method to constraint the neighbors diversity in the matching process, to get a large color palette of source superpixels. The colors are globally transfered to the target image with respect to the initial grain and exposure, producing visually consistent results. Finally, the use of superpixels within our framework enables to produce color transfer in very limited computational time. Future works will focus on the adaptation to video color transfer using supervoxels.

Fig. 1 :

 1 Fig. 1: Example of color transfer with the proposed SCT method.

Fig. 2 :

 2 Fig. 2: Illustration of propagation step. The superpixel Ai (red) is currently matched to B (i) . Its top-left adjacent neighbors Aj (gray) are considered to provide new candidates. A neighbor Aj is matched to B (j) , which leads to the candidate B k , the neighbor of B (j) with the most similar relative position to the one between Ai and Aj.

  illustrates the selection of a candidate during propagation. Such adaptation of PM provides a fast superpixel ANN matching algorithm that produces an accurate selection of colors to transfer.

Fig. 3 :

 3 Fig. 3: Illustration of matching without ( = ∞) and with ( = 1) constraint on the number of source superpixel selection. Without constraint, all target superpixels match a red one in the source image.

Fig. 4 :

 4 Fig.4: Comparison of optimal assignment using Munkres algorithm[START_REF] Munkres | Algorithms for the assignment and transportation problems[END_REF] and our constrained superpixel ANN matching ( = 1). Target image reconstruction from the matched superpixels average colors (K ≈ 2000) and performances for several superpixel scales.

3 Fig. 6 :

 36 Fig. 6: Examples of color transfer results are shown for different values and compared to the results obtained with no constraint ( = ∞). The maps (bottom row) indicate the number of selection of the source superpixels (black is zero and white is the highest number of selection).


Dr ] P A Gotico

Dr W Quaranta

Prof A Leibl

Prof A Aukauloo
email: ally.aukauloo@u-psud.fr

Dr B Boitrel

Dr R Guillot

Dr M Sircoglou

Dr Z Halime

Keywords: carbon dioxide reduction, hydrogen bonding, iron, porphyrins, urea

Philipp Gotico, Bernard Boitrel, RØgis Guillot, Marie Sircoglou, Annamaria Quaranta, Zakaria Halime,* Winfried Leibl, and Ally Aukauloo* Abstract: Inspired by natures orchestra of chemical subtleties to activate and reduce CO 2 , we have developed a family of iron porphyrin derivatives in to which we have introduced urea groups functioning as multipoint hydrogen-bonding pillars on the periphery of the porphyrinic ring. This structure closely resembles the hydrogen-bond stabilization scheme of the carbon dioxide (CO 2 ) adduct in the carbon monoxide dehydrogenase (CODH). We found that such changes to the second coordination sphere significantly lowered the overpotential for CO 2 reduction in this family of molecular catalysts and importantly increased the CO 2 binding rate while maintaining high turnover frequency (TOF) and selectivity. Entrapped water molecules within the molecular clefts were found to be the source of protons for the CO 2 reduction.

The criticality of global warming effects arising from increasing emission of carbon dioxide (CO 2 ) is challenging scientists to advance research in the development of catalysts that can help capture, activate, and reduce CO 2 . An emphasis is currently being put on the discovery of new cost-efficient molecular catalysts to drive the electrocatalysis of CO 2 reduction and ultimately to use solar energy to drive these energetically uphill chemical transformations. [1][2][3][4][5][6][7][8][9] Still, the route towards industrial upscale applications requires much improvement in the efficiency of these catalysts while maintaining their stability and selectivity. Rational strategies for catalyst design and improvement hinge on what we continually learn from natural systems, as they exhibit exceptional stabilities and performance. Carbon monoxide dehydrogenase (CODH) stands as the typical inspiration for scientists working on the field as it is known to catalyze the reversible reduction of CO 2 to CO. Lessons from the structure and functions of this enzyme point out to some important findings that can be artificially mimicked by catalyst design: 1) a bifunctional activation of CO 2 substrate by two metal centers, 2) an iron-sulfur cluster acting as an electronic relay and buffer to the catalytic unit and 3) precisely positioned amino acid residues to form a hydrogenbond stabilization network with the CO 2 substrate. [10][11][12] Implementing these functionalities in the second coordination sphere [5] such as local proton source, (i.e. phenols, [13][START_REF] Costentin | Proc. Natl. Acad. Sci[END_REF][START_REF] Costentin | Proc. Natl. Acad. Sci[END_REF] carboxylic acids [START_REF] Neri | [END_REF] ), H-bond donors (amines, [17] amides, [18] guanidine [19] ) and reaction intermediate stabilizers (ammonium cations, [20] and imidazolium moieties [21,22] ) have successfully lead to decrease significantly the overpotential while improving the catalytic turnover numbers (TONs) and frequencies (TOFs).

Inspired by the multipoint hydrogen bonding scheme of histidine (H 93 ) and lysine (K 563 ) residues in stabilizing the CO 2 adduct in CODH, we reasoned to introduce urea functions on the periphery of an iron porphyrin, known as one of the most efficient molecular catalysts for the two-electron two-proton reduction of CO 2 to CO. These functions hold two potential NH fragments that can interact with metal bound CO 2 . Reed and co-workers first reported the use of a picket-fence porphyrin with a modified phenyl-urea arm in establishing a hydrogen bond to molecular oxygen and improve the substrate affinity of the complex. [23] Das et al. have shown a crystallographic structure of a neutral urea scaffold that fixes atmospheric CO 2 as carbonate clusters held together by an extended H-bonding stabilization. [24] Neumann and coworkers have recently reported a thiourea tether placed on the second coordination sphere of a rhenium catalyst that improved the electrocatalytic activity in the absence of external proton source. [25] However, the presence of weak acids, such as water, inhibits the activity of the latter system which will be problematic when aligning with the sustainable goal of using water as a free source of electrons and protons. During the course of this study, Chang and Nichols have leveraged this multi-point hydrogen bond donation of urea as an external additive to improve the electrocatalytic activity of nickel cyclam at the same overpotential. [26] We report herein the synthesis of two super-structured iron porphyrins holding in one case four amido groups (FeTPP-Am) and in another four urea functions (FeTPP-Ur) (Scheme 1). Both functions carried a phenyl ring bearing two -CF 3 motifs as electron withdrawing groups to enhance hydrogen bonding aptitude of the NH fragments. These two catalysts were designed starting from a 5,10,15,20-tetrakis(2aminophenyl)porphyrin (TAPP) with an abab configuration (Scheme 1). Unlike studies utilizing hangman, [18,19] and A c c e p t e d m a n u s c r i t p t picket-fence [13,22] structures of porphyrins for CO 2 reduction, this atropoisomer was chosen with the target to provide two sets of hydrogen bonding network in a trans fashion towards a metal bound CO 2 molecule and at the same time to confer two identical chemical faces on each side of the porphyrin molecular platform. Our results showed that the FeTPP-Am catalyst had no marked enhancement on the electrocatalytic activity of CO 2 reduction when compared to the tetraphenylporphyrin (FeTPP) derivative. Interestingly, the urea containing catalyst FeTPP-Ur showed 302 mV positive shift in the catalytic potential for the selective reduction of CO 2 to CO while concomitantly retaining the catalytic performance (TONs and TOFs) of FeTPP functioning at much higher overpotential. Furthermore, water was found to be a sufficient and better proton source in CO 2 -saturated dimethylformamide (DMF) in comparison with more acidic trifluoroethanol (TFE) and phenol (PhOH).

The synthetic route leading to our target catalysts is depicted in the supplementary information (Figure S1). In short, the addition of four equivalents of 3,5-bis(trifluoromethyl)phenyl isocyanate or 3,5-bis(trifluoromethyl)benzoyl chloride to TAPPabab [27,28] leads, respectively to porphyrin ligands bearing four urea (TPP-Ur) or four amido (TPP-Am) groups. Iron insertion in these ligands was performed using ferrous bromide and 2,6-lutidine. X-ray diffraction analyses were obtained for both catalysts FeTPP-Ur and FeTPP-Am. The preservation of the abab configuration was confirmed by the disposition of the tethered Ur and Am arms on the periphery of the porphyrin skeleton (Figure 1 and Supporting Information for a more detailed description of the structures). For both complexes, the distances around the iron (III) center best fit with a high spin configuration with an axial methoxide ligand. Of note, the hydrogen atoms of the amido and the urea groups are oriented towards the iron catalytic center, with Fe•••H distances of 4.840 for the amido groups and from 4.796 to 5.970 for both hydrogen atoms of the urea groups, presaging potential hydrogen bond interactions with CO 2 adduct coordinated to the metal center. An interesting structural feature of the FeTPP-Ur is the presence of entrapped water molecules in the vicinity of the urea functions (Figure S22).

Cyclic voltammograms (CV) of FeTPP-Ur in argondegassed DMF containing 0.1m of tetra-N-butylammonium hexafluorophosphate ([Bu 4 N]PF 6 ) showed three reversible redox waves at 0.226, À0.632, and À1.118 V versus the normal hydrogen electrode (NHE) corresponding, respectively to the formal Fe III/II , Fe II/I , Fe I/0 couples (Figure 1, Table S1). All three waves show an anodic shift when compared to those of the non-functionalized iron porphyrin (FeTPP) under similar experimental conditions. However, the third redox wave is markedly shifted over 300 mV to more positive potential, a shift similar to that of FeTPPF 20 , a FeTPP analogue where all the twenty aryl positions are directly fluorinated (Figure 1, Table S1). This substantial shift cannot be attributed only to the withdrawing inductive effect of the two -CF 3 groups on the aryl ring at the other end of the urea functions. In the case of FeTPP-Am holding the same fluorinated substituted aryl groups, only small anodic shift was noted. Instead, the observation can be attributed to the strong electron delocalization on the urea groups helping to contain the addition of electron on the catalytic unit.

The CVs of reference complexes FeTPP and the fluorinated analogues FeTPPF 8 and FeTPPF 20 in CO 2 -saturated solution show a catalytic current on the third reduction wave corresponding to the catalytic 2-electron reduction of CO 2 to CO (Figure 1). As discussed previously by Costentin and Scheme 1. Molecular drawing of FeTPP-Ur (top left) and FeTPP-Am (top right) and the wireframe and capped sticks representation of their corresponding X-ray structures (FeTPP-Ur: bottom left; FeTPP-Am: bottom right) with a methoxide anion as an axial ligand. Only urea and amide protons are explicitly shown, and solvent molecules are omitted for clarity. The X-ray structure of the FeNi active site (Ccluster) of CO dehydrogenase (CODH) [10] (center) is shown for comparison. SavØant, the counterpart of lowering the overpotential (h = E 0 cat ÀE 0 CO 2 =CO ), through classic incorporation of electron withdrawing groups, leads to a decrease in the TOF of the catalysts (Figure 1 right and Table 1). [5] An escape from this iron law was exemplified with catalysts having a local proton source or favorable second-sphere interactions. [13][START_REF] Costentin | Proc. Natl. Acad. Sci[END_REF][START_REF] Costentin | Proc. Natl. Acad. Sci[END_REF][START_REF] Neri | [END_REF][17][18][19][20]22] In the case of FeTPP-Am, in which hydrogen-bond interaction with amide groups can be expected, only a small positive deviation is observed. This positive deviation is much more pronounced in the case of FeTPP-Ur catalyst which has comparable TOF to that of FeTPP at ca. 300 mV more positive E 0 cat . These comparative studies indicate that the significant enhancement in FeTPP-Ur can be assigned to the multipoint hydrogen bonding induced by the urea groups. In a controlled experiment, the addition of an excess of urea as an external additive during the catalytic reduction of CO 2 by FeTPP did not bring any improvement to neither the catalytic current nor the E 0 cat (Figure S11). This result underlines the important aspect of the 3D pre-organization of the FeTPP-Ur catalyst which places the two urea groups on one side of the porphyrin platform in a position where all four hydrogen atoms of the urea groups can establish hydrogen bonding interactions with a CO 2 substrate on the metal-center from two opposite mesopositions of the porphyrin macrocycle. This result is a clear demonstration on the positioning of the hydrogen bonding patterns for optimizing the electrocatalytic properties of our biomimetic designed catalyst FeTPP-Ur. It is not the sum of the additional NH interactions as compared to FeTPP-Am derivative, but should rather be considered as a close mimic of the lysine and histidine residues of CODH active site. Indeed, based on the structure/function proposal, this pair of amino acids conspires to stabilize a carboxylate intermediate (M-CO 2 ) through multipoint hydrogen bonding. [10] Our choice of introducing urea groups in the second coordination sphere of an iron-porphyrin catalyst was motivated by their ability to bind oxygen atoms of carbonyl groups as well as carbonates. [START_REF] Snellink-Rul | [END_REF][32][33] In some cases, urea groups can even capture atmospheric CO 2 as carbonates/bicarbonate. [24] X-ray structures resolved from single crystals obtained by slow evaporation of H 2 O/acetone saturated solution of TPP-Ur porphyrin, revealed the presence of four acetone molecules bound to the four urea groups through NÀH•••O=C hydrogen bonding interactions (Figure S21), confirming the stabilization of the carbonyls by urea moieties.

To assess the contribution of the urea arms to the binding affinity of CO 2 , we performed the CV of FeTPP-Ur under CO 2 but in the absence of a proton source. In these conditions, where the catalytic 2-electron and 2-proton reduction of CO 2 is not possible, we observe both a loss of reversibility and an anodic shift of the third reduction wave (Figure S18 a). These characteristics are unprecedented for iron-porphyrin catalysts but were reported as indicative of a good CO 2 binding for other macrocyclic catalysts. [34,35] For a thorough comparison, the CO 2 binding rate constant (see Supporting Information for details) of FeTPP-Ur was estimated and found to be an order of magnitude higher than that of reference compounds such as FeTPP or even FeTPP-Am (Table 1).

However, this CO 2 binding magnitude may not be the only parameter to account for the high catalytic performance of FeTPP-Ur. As mentioned above, a stabilization of reactive intermediates such as Fe-CO 2 species through hydrogen bonding interactions with the NH of urea groups may also contribute. To back up this hypothesis, density functional theory (DFT) calculations were performed on model compounds to investigate on the possible geometry of the CO 2 adducts of the triply reduced iron porphyrins. In the case of FeTPP-Am, only two weak hydrogen bonding interactions between the amide arms and the coordinated CO 2 substrate were found with N(H)•••O donor-acceptor distances of 3.021 and 3.352 . In marked contrast, two strong hydrogen bonds were engaged by each urea arms of FeTPP-Ur yielding four short N(H)•••O distances of 2.738, 2.804, 2 2.832 (Figure 2 and Figure S32) comparable to those evidenced in the active site of the CODH (2.637 and 2.884 with Lys and His residue, respectively). This multipoint anchoring of CO 2 is responsible of a free enthalpy of stabilization of 29 kcal mol À1 .

We further interrogated the proton source, a pre-requisite in the reduction of CO 2 . A 5.77 normal kinetic isotope effect (KIE) was measured for the electrocatalytic reduction of CO 2 by FeTPP-Ur with H 2 O/D 2 O as a proton source indicating that proton transfer is involved in the rate determining step (Figure S20). We then extended this study to other sources of proton currently used in this field, that is, trifluoroethanol (TFE) and phenol (PhOH), by comparing the catalytic rates estimated from the foot of the wave (FOW) analysis. h (V) [b] log TOF max [a] The catalytic potential, E 0 cat , is taken as the standard reduction potential for the formal Fe I/0 couple (V vs. NHE). [b] Overpotential values are reported as the difference between the E 0 cat and E 0 CO2=CO = 0.69 V vs. NHE. [29] [c] TOF max values are reported for a CO 2 -saturated DMF solution containing 5.5 m H 2 O based on FOW analysis. [d] CO 2 binding rate constant is estimated based on reported method [START_REF] Savøant | Elements of Molecular and Biomolecular Electrochemistry[END_REF] considering irreversible kinetics upon CO 2 binding in dry DMF (see Supporting Information for details). Although H 2 O is less acidic (pK a = 31.5) than TFE (pK a = 24.0) or PhOH (pK a = 18.8), [36] surprisingly, it has by far the most marked effect on improving the catalytic rate compared to phenol or TFE (Figure S10). [36] Our result is in sharp contrast with a recent study, where the authors observed a severe drop in the catalytic rate upon addition of H 2 O or PhOH for a thiourea-tethered rhenium catalyst. [25] Reasons for this were supported by their DFT calculations suggesting that external protons may disrupt the pre-established hydrogen bond stabilization of the thiourea moiety with the CO 2 adduct. In the case of FeTPP-Ur, water seems to work in synergy with the urea arms to manage the proton supply. Support for this proposal come from the network of water molecules observed in the X-ray structure of FeTPP-Ur (Figure S22) suggesting that such a network may also be in play during the catalytic reduction of CO 2 . A similar water network in the vicinity of the active site of CODH revealed by high resolution X-ray structure was proposed to have a major role in the enzyme reactivity. [10] The geometry of a model structure where a water molecule was inserted in between a urea arm of FeTPP-Ur and CO 2 could be optimized by DFT calculation as a local minimum (Figure 2 right). This configuration is similarly observed for one of the water molecules in the X-ray structure of FeTPP-Ur (O 4 in Figure S22). In contrast with the previously mentioned thiourea-tethered Re catalyst, the CO 2 is in this case maintained in a quasi-unchanged topology while being put in contact with a water molecule held by the second urea arm. The less important effect of PhOH and TFE can be due to 1) their higher acidity which can prevent the formation of preestablished intramolecular hydrogen bonds between urea groups and CO 2 adduct, and/or 2) their steric hindrance which can limit their access to the catalytic center in between the two urea arms.

[c] k CO2 (M À1 s À1 ) [d] FeTPP À1.
Bulk electrolysis experiment was performed on FeTPP-Ur at À1.076 V versus NHE to measure the efficiency at which CO is produced and to evaluate the stability of the catalyst. Gas chromatography analysis of the reaction headspace during bulk electrolysis showed no hydrogen formation and the catalyst FeTPP-Ur operates with the exclusive formation of CO with a Faradaic efficiency as high as 91 % (Figure 3). A stable current density of 0.70 mA cm À2 was achieved during the two-hour electrolysis run (Figure S12 a) which confirms the good stability of the catalyst. Considering a two-electron process, the rate constant (k cat ) was calculated to be 2.76 10 3 s À1 , the TOF to be 455 s À1 , and the TON to be 3.28 10 6 based on the amount of catalyst molecules in the diffusion layer of the working electrode (see Supporting Information for details). As shown in Figure S9, this calculated TOF value fits well in the catalytic Tafel plot of FeTPP-Ur, and further points to the distinct advantages of FeTPP-Ur over other modified iron porphyrins employing the second coordination effect.

In this study, we have described a biomimetic model containing urea functions that provide a multipoint hydrogenbonding scheme to bind and stabilize CO 2 for its reduction to CO at an iron porphyrin catalytic unit. Our results clearly demonstrate a remarkable drop in the overpotential in comparison to single-point hydrogen-bonding models while conserving a high turnover frequency. Such a functionality inspired by the active site of carbon monoxide dehydrogenase, is a significant and versatile tool in the design of synthetic cost-effective catalysts. We also found that within such molecular clefts, water was sufficient as a proton source, indicating a future prospect of using water as a sustainable proton and electron source, when coupled to a water oxidizing component. Like CODH: Urea groups at an iron porphyrin catalyst give multipoint hydrogen-bonding stabilization resembling that found in the CO 2 adduct of carbon monoxide dehydrogenase (CODH). The catalyst gave improved CO 2 reduction to CO. Entrapped water molecules within the molecular clefts were found to be the source of protons for the CO 2 reduction.

A c c e

  p t e d m a n u s c r i t p t Second-Sphere Biomimetic Multipoint Hydrogen-Bonding Patterns to Boost CO 2 Reduction of Iron Porphyrins

Figure 1 .

 1 Figure 1. Cyclic voltammograms of 1 mm FeTPP (black) and its modified analogues (blue = FeTPPF 8 , pink = FeTPPF 20 , green = FeTPP-Am, red = FeTPP-Ur) in DMF containing 0.1 m [Bu 4 N]PF 6 at 25 8C under argon (top left) and under CO 2 with 5.5 m water as proton source (bottom left). Plot of calculated TOF max (from FOW analysis) as a function of catalytic overpotential (right, see Supporting Information for calculation details).

  A c c e p t e d m a n u s c r i t p t

Figure 2 .

 2 Figure 2. Notional model structures of [FeTPP-Ur-CO 2 ] 2À (left) and [FeTPP-Ur-CO 2 ] 2À with a trapped water molecule (right) optimized by DFT calculation at BP86/ Def2-SVP(Fe)-6-31 + G(d,p)(other atoms) level of theory. Hydrogen atoms bound to carbon omitted for clarity. H white, C gray, N blue, O red; Fe orange.

A c c e

  p t e d m a n u s c r i t p t

Figure 3 .

 3 Figure 3. Progress of CO evolution and the corresponding Faradaic efficiency during bulk electrolysis experiments at À1.076 V versus NHE of a CO 2 -saturated DMF solution containing 0.5 mm FeTPP-Ur and 5.5 m H 2 O.

A c c e

  p t e d m a n u s c r i t p t A c c e p t e d m a n u s c r i t p t P. Gotico, B. Boitrel, R. Guillot, M. Sircoglou, A. Quaranta, Z. Halime,* W. Leibl, A. Aukauloo* &&&&-&&&& Second-Sphere Biomimetic Multipoint Hydrogen-Bonding Patterns to Boost CO 2 Reduction of Iron Porphyrins

Table 1 :

 1 Electrochemical properties of the modified iron porphyrins.

	Complex	cat E 0	[a]

Acknowledgements

This work was supported by CEA IRTELIS PhD fellowship program (for P.G.), LabEx CHARMMMAT, and by the French Infrastructure for Integrated Structural Biology (FRISBI) ANR-10-INSB-05-01. Prof. V. Gandon is warmly acknowledged for his advices regarding DFT calculation.

Conflict of interest

The authors declare no conflict of interest.