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Irrelevant auditory and tactile signals interact with the visual target onset and modulate saccade latencies, not visual signals

Saccadic eye movements bring events of interest to the center of the retina, enabling detailed visual analysis. This study explored whether irrelevant auditory (experiments A, B & F), visual (C & D) or tactile signals (E & F) delivered around the onset of a visual target modulates saccade latency. Participants were instructed to execute a quick saccade toward a target stepping left or right from a fixation position. We observed an interaction between auditory beeps or tactile vibrations and the oculomotor reaction that included two components: a warning effect resulting in faster saccades when the signal and the target were presented simultaneously; and a modulation effect with shorter – or longer – latencies when auditory and tactile signals were delivered before – or after – the target onset. Combining both modalities only increased the modulation effect to a limited extent, pointing to a saturation of the multisensory interaction with the motor control. Interestingly, irrelevant visual stimuli (black background or isoluminant noise stripes in peripheral vision, flashed for 10 ms) increased saccade latency whether they were presented just before or after target onset. The lack of latency reduction with visual signals suggests that the modulation observed in the auditory and tactile experiments was not related to priming effects but rather to low-level audio- and tactile-visual integration. The increase in saccade latency observed with irrelevant visual stimuli is discussed in relation to saccadic inhibition. Our results demonstrate that signals conveying no information regarding where and when a visual target would appear modulate saccadic reactivity, much like in multisensory temporal binding, but only when these signals come from a different modality.


Introduction
Our environment continuously provides information through physical signals that are 2 transduced and processed by various sensory systems. Although the study of human perception has 3 long focused on isolated senses, in the last decades the interaction between different sensory 4 systems has started to gain interest. Many scientists now believe that the nature of purely visual 5 contexts studied in the laboratory is quite different from the multisensory scenarios found in more 6 ecological settings; and that vision per se is often influenced at early stages by other modalities such 7 as audition. 8 Let us consider a daily life illustration: as we wander in a fun fair the sudden explosion of a 9 balloon on the right side of our visual field will automatically attract our gaze. This orientation 10 behavior facilitates further sensory processing needed for a fast reaction to a potential danger. The 11 resulting brief acoustic signal and salient visual change generated by the explosion are transmitted in 12 the air and then transduced by our auditory and visual systems at different speeds. Although these 13 signals reach the brain areas responsible for their integration at different moments (Keetels & 14 Vroomen, 2012; Pöppel, Schill, & von Steinbüchel, 1990), we will most likely perceive them as 15 simultaneous. Moreover, depending on the distance to the blowing balloon, the auditory signal 16 might reach the observer either before or after the visual signal. The mechanisms involved in the 17 subjective timing of natural events must then show some degree of flexibility to connect each 18 unimodal component and combine them into a single multisensory event. Furthermore, the 19 observed advantage of the visual modality over other senses for spatial processing does not hold for 20 the temporal domain: the auditory system is more sensitive and reliable than the visual system to 21 process the timing of events (Vidal, 2017). When presenting a flash just before or after a short beep, 22 the visual stimulus is perceived closer in time to the auditory stimulus than it actually is (Slutsky & 23 Recanzone, 2001). Consistently, the perception of a flash shifts either forward or backward in time 24 when paired with a lagging or leading sound click, respectively (Fendrich & Corballis, 2001). This 25 phenomenon -termed temporal ventriloquism -has been used to produce famous illusions (Shams,26 Kamitani, & Shimojo, 2000; Freeman & Driver, 2008), to modulate low-level features of the visual 27 system (Scheier, Nijhawan, & Shimojo, 1999; Morein-Zamir, Soto-Faraco, & Kingstone, 2003; 28   or to modulate visually-guided motor control (Maij,Brenner,& Smeets,29 2009). 30 Going back to our initial example, the literature tells us that the blowing sound affects the 31 moment when we visually perceive the visual counterpart of the balloon explosion, the latter being 32 shifted in time toward the auditory signal. Consequently, one might wonder whether this could 33 3 influence the triggering of the saccade bringing the retinal image of the visual event on the fovea. For 1 instance, if the balloon is far enough, the blowing sound will hit our senses and be processed after 2 the visual signal and delay the moment we perceive the explosion. Would this also delay the 3 execution of eye movements toward the location of the explosion as well? In other words, does 4 multisensory temporal binding influence the latency of actions we execute in response to 5 multisensory events? This is the question addressed in the present set of experiments. 6 To investigate the influence of multisensory temporal binding on motor reaction times to 7 multimodal events, we will use saccadic eye movements, as they proved to allow the measurement 8 of small differences in processing time (Carpenter, 1988). In addition, our decision of using saccades 9 to investigate multisensory binding, lies in the fact these eye movements are partly controlled by the 10 superior colliculus (SC), a well-known brain structure also involved in multisensory processing. In 11 mammals the SC in which sensory and motor maps are connected, transforms sensory inputs into 12 motor commands (D. L. Sparks, 1988; David L. Sparks & Nelson, 1987;Wurtz & Goldberg, 1972). The 13 mechanism underlying gaze fixation has been proposed to involve fixation cells in the rostral SC, 14 which inhibit the generation of saccades through the excitation of omnipause neurons in the 15 brainstem (Munoz & Wurtz, 1993). Importantly, SC was also the first structure where audiovisual 16 integration in time and space was observed (Meredith, Nemitz, & Stein, 1987; Stein, Meredith, & 17 Wallace, 1993; : neurons in the superficial SC layers respond to 18 visual stimuli and neurons in the intermediate and deep SC layers also respond to auditory stimuli, 19 such that auditory and visual sensory maps are connected at a very early processing stage. 20 Audiovisual interactions in monkey SC modulate saccade-related activity, though less than what 21 expected from earlier recordings (Maarten A Frens & Van Opstal, 1998). This physiological 22 organization has functional consequences that might be quantified in behavioral studies. 23 Only a handful of studies have investigated the influence of signals from non-visual sensory 24 modalities on the execution of saccades. Ross & Ross (1981) used continuous warning signals -onset 25 or offset of either sounds or visual symbols at fixation -around the time of target onset. Saccade 26 latencies were shorter for auditory signals presented 300 ms, 100 ms or 0 ms before target onset, 27 indistinctly for sound onset or offset, when compared to latencies in conditions without warning 28 signals. However, the nature of these effects proved to be different from what was observed with 29 visual signals as saccades were delayed when visual stimuli were displayed after target onset. 30 Moreover, onset and offset of visual signals differentially affected the execution of saccades. 31 However, the study used a group design and lacked data points precisely where strongest 32 multisensory interactions are expected to happen, that is, for stimulus onset asynchronies (SOA) 33 within [−100 ms; +100 ms]). Another study reported a facilitation modulated with SOA ranging 34 between −50 ms and +100 ms for spatially congruent sounds, which disappears with incongruent 35 4 sounds (M. A. Frens, Van Opstal, & Van der Willigen, 1995). However, the limited number of 1 participants (N=3) constrained statistical conclusions and weakened the impact of the study. Similar 2 multisensory latency variations have been reported for SOAs ranging from −30 ms to +120 ms, again 3 modulated by the spatial congruency between the sound and the visual target (H Colonius & Arndt, 4 2001). These multisensory influences have an effect on saccades that could share similar mechanisms 5 and combine with the gap/overlap effect (Saslow, 1967). Saccade latencies decrease when the 6 fixation disappears before target onset (gap) and increase when it remains after target onset 7 (overlap). 8 Another line of research focused on the effects of spatial congruency across modalities. 9 Saccades toward a visual target had shorter or longer latencies when an auditory distractor was 10 spatially aligned or misaligned, respectively (Corneil & Munoz, 1996). These effects depend on the 11 physical distance between the visual target and the sound source (H Colonius & Arndt, 2001; M. A. 12 Frens et al., 1995). For combined congruent audiovisual targets, the latency decrease was well 13 predicted by independent race models, suggesting that multisensory integration in the target 14 selection is not optimal (Corneil & Munoz, 1996). Finally, inhibiting saccades toward an auditory 15 distractor when the fixation point is already turned off proved more difficult than when the fixation 16 remains visible at the target onset (Munoz & Corneil, 1995), revealing an interaction between 17 disengaging fixation and the target selection in the SC. Importantly, tactile stimulations as well 18 influence saccades, both in the spatial and temporal dimensions (Hans Colonius & Diederich, 2004): 19 latencies are reduced when a touch is delivered before target onset, the facilitation being maximal 20 when the touch and visual target are spatially congruent (Amlôt, Walker, Driver, & Spence, 2003). 21 Reactive saccades (i.e. stimulus-driven) have been observed using purely somatosensory stimuli 22 (Amlôt & Walker, 2006), which points to early interactions of the visual and tactile modalities in the 23 generation of saccades. The best locus candidate being again the deep layers of SC (Findlay & Walker,24 1999; Amlôt & Walker, 2011). 25 The current project brings new insights into the multisensory interactions occurring when 26 programming and executing eye-movements. We investigated whether an irrelevant stimulus 27 delivered around the appearance of a visual target, which expectedly alters the perceived timing of 28 the target onset, might influence saccade latencies. Specifically, we used auditory (experiments A 29 and B), visual (experiments C and D), tactile (experiment E) and combined tactile and auditory stimuli 30 (experiment F) to probe the effects of multisensory temporal integration on the possible mechanisms 31 underlying the selection and execution of saccades. Our results indicate reliable SOA dependent 32 multisensory effects on saccadic reaction time when using sounds or touches. Visual stimuli, on the 33 other hand, appear to produce a different behavioral pattern, indicating that temporal integration 34 requires signals from different modalities. 35 1 The goal of the first experiment was to test whether a short beep presented in temporal 2 proximity with the onset of the visual target alters the execution of saccades. We measured the 3 latencies of saccades toward visual targets appearing either rightward or leftward of a fixation, while 4 delivering a beep with a stimulus onset asynchrony (SOA) ranging from −240 ms (beep first) to 5 +240 ms (beep after). Saccadic eye-movements were chosen for they provide reliable and short 6 reaction times, allowing one to quantify subtle differences in decision processing delays. A baseline 7 condition without beep was also tested. 8

9
Participants 10 8 volunteers (5 women and 3 men) participated in this experiment, all naïve to the purpose of 11 the experiment except two of the authors. Participants were aged between 22 and 43 years old 12 (average 32.3), all right handed. They gave a written consent after being informed of the 13 experimental methods used and their right to interrupt the experiment at any time. The whole 14 project was approved by the local ethics committee and complies with the regulations described in 15 the Declaration of Helsinki. 16 17 Subjects sat in front of a screen with head movements restricted by a chin and head rest. 18 Stimuli were generated on a Mac computer running Mac OS 10.6.8 operating system. Routines were 19 written in Matlab 7.10.0 using the PsychToolbox 3.0.9 (Brainard, 1997;Pelli, 1997). The right eye 20 position was recorded using an SR Research EyeLink 1000 video eye tracker (sampling at 1000Hz) 21 mounted on the same structure as the chin rest. Visual stimuli were displayed on a Sony Trinitron 22 CRT monitor running at a resolution of 1024×768 and refreshed at 100Hz (frames of 10 ms). The chin 23 rest was adjusted so that the eyes in primary position were aligned with the center of the screen, at a 24 distance of 57 cm. The fixation point was a small white disk (0.12° in diameter) displayed at the 25 center of the screen. The saccade target was a white disk (0.36° in diameter) that could appear either 26 to the left or to the right of the fixation at an eccentricity of 8°. Background was set to 50% grey level 27 (25.8 cd/m 2 luminance after gamma correction). Beeps were 20 ms 880 Hz tones attenuated by a 28 raised-cosine waveform (50% after 10 ms) delivered binaurally through closed headphones 29 (Beyerdynamics DT770). The computer audio driver was set so that the audiovisual jitter remained 30 below 1 ms. The accuracy of the timing of visual and auditory stimuli was controlled using a dual- 31 channel oscilloscope connected to both the auditory output and a photosensitive cell placed directly 1 on the screen. Subjects were asked to fixate it and to avoid blinking during the stimulus presentation. After 6 a random delay ranging from 750 ms to 1250 ms, the fixation was turned off and the saccade target 7 appeared either leftward or rightward, at an eccentricity of 8°. In most trials of experiment A a beep 8 was delivered around the time of target onset. Trial conditions were defined as the combination of beep baseline where no beep was played) and 2 target directions (left and right). Subjects were 12 instructed to perform a saccade as quickly and accurately as possible toward the visual target, 13 regardless of the non-informative beeps.  with the baseline conditions, no signal was delivered. The participant had to shift gaze toward the target 22 as fast as possible. The saccade latency is defined as the delay between the target appearance and the 23 eye-movement onset; the saccade duration is the time needed to land on the target. 24 7

Apparatus and Stimuli
The first five subjects completed 8 sessions of 300 trials totalizing 2100 trials (105 per 1 SOA × direction). For the remaining three subjects, the experiment was reduced to 4 sessions of 240 2 trials totalizing 960 trials (48 trials per SOA × direction). The order of the conditions was randomized 3 within blocks of 40 trials. Between each session subjects had a few minutes break where they could 4 stand out of the setup to rest. The calibration procedure (using 13 positions on the monitor) was 5 performed at the beginning of each session. After each block of 50 trials, subjects could rest for a few 6 seconds without moving their heads, then a potential drift in eye movement calibration was checked 7 (using a single location) and corrected if needed, before resuming. 8 Data processing 9 We used the Eyelink online saccade detector to identify saccades onset and offset, using 30°/s 10 velocity and 8000°/s 2 acceleration thresholds (Stampe, 1993). Invalid trials in which either no saccade 11 was detected, eyes blinked, saccades started too late (latency>400 ms) or fell too short 12 (amplitude<3°) -were discarded. An adaptive low-pass filter was then applied to the set of latencies 13 in order to remove most of anticipatory saccades. For each condition, the cutoff criterion of the 14 latency distribution was determined using an iterative process. The cutoff started at 80 ms and 15 increased by steps of 1 ms until fewer than 1% of the remaining saccades in the distribution were not 16 directed toward the target. Because anticipatory saccades have 50% chances to go in the wrong 17 direction, limiting these saccades below 1% mechanically limited anticipatory saccades going in the 18 right direction below 1% as well (see the discussion below for more details on this issue). In this 19 experiment, the cutoff was set at the lowest value (80 ms), with the proportions of saccades in the 20 wrong direction averaging 0.10% across participants (maximum 0.29%). This filter was designed to 21 adapt to individual peculiarities and find the optimal tradeoff between a maximum of visually-driven 22 saccades in the distributions while removing a maximum of saccades programmed before processing 23 the visual signal related to target onset. At this stage, only two saccades going in the wrong direction 24 were detected across all subjects. Finally, saccades falling short (gain<0.45) and going in the wrong 25 direction were excluded. A total of 12327 saccades out of the 13080 recorded trials were analyzed 26 (94.2%). For each subject and each SOA condition, the median value and the median absolute 27 deviation (MAD) of the saccade latency distribution were computed. In order to reduce inter- 28 individual dispersion for the statistical analyses, and to allow for comparisons between experiments, 29 we have normalized the median latency and the MAD taking the No signal condition (i.e. No beep in 30 experiment A) as a baseline, using the following equations: where ' is either the median latency or the MAD of a given condition, and ( is the standard 1 deviation of ' across all conditions. A two-way repeated measure ANOVA (design: 9 SOA × 2 target 2 direction) was performed on the n scores . The No beep condition, that always had a null n score by 3 construction, was excluded from the design. There was neither a main effect of Target direction 4 (F(1,7)=2.17, p=0.18) nor a SOA x Target direction interaction (F(8,56)=0.77, p=0.63). Consequently, 5 left and right saccades were pooled together in a single distribution and the median of this collapsed 6 distribution was further analyzed using a one-way repeated measure ANOVA with SOA as factor. 7 Planned comparisons consisted of paired student t-tests between SOA conditions, and a single 8 sample t-test to test the difference with the No beep baseline, as detailed below. To ensure that 9 n scores did not deviate from normality and that they met the homoscedasticity assumption required 10 for parametric statistics, we conducted a Shapiro-Wilk's test and a Levene's test before performing 11 these planned comparisons. Except otherwise stated, throughout this article all sets of measures had 12 distributions that did not significantly differ from normality, and the compared sets had 13 homogeneous variances. The alpha value for significance was set to 0.00555 after Bonferroni 14 correction for multiple comparisons on a single data set (here 9 comparisons). S1 Table reports the   15 results of all these tests along with the corresponding effect size (Cohen's d). 16

17
The effects of auditory beeps on the saccade onset as a function of SOA are summarized in Fig   18   2. The general pattern of individual median latencies -plotted in grey -show great similarities across 19 subjects, with some inter-individual differences in the amplitude of the effects. To reduce this 20 disparity we computed, for each SOA condition, the n scores taking the No beep condition as a baseline, 21 which revealed a great homogeneity in participants' behaviors. SOA had a significant main effect on 22 the n scores (F(8,56)=55.50, p<0.0001, η p 2 =0.89). In order to evaluate the extent of the warning effect 23 when a beep is delivered near target onset, we performed single sample t-tests with the n scores 24 observed in the SOA=0 ms condition and with the average n scores across the range of SOAs. This 25 analysis revealed that saccade latency decreased significantly by about 11.0 ms when the target and 26 the beep were presented simultaneously (p<0.0002) and by 7.6 ms on average (p<0.00001), 27 compared to the No beep condition. 28 To further investigate possible modulations of saccade latency we then performed paired t- 29 tests on the n scores comparing the SOA=0 ms reference with each of the other SOA condition. Saccade 30 latencies tended to be shorter for earlier beeps (i.e. beep onset precedes target onset) compared to 31 synchronous beeps (p=0.024 and p=0.038 for SOA=−120 and −60 ms respectively) and increased 32 significantly for later beeps (i.e. beep onset follows target onset) (p<0.0001 for all positive SOA). This 33 9 modulation produced saccades that tended to have even longer latencies than the No beep baseline 1 for SOA=+60 ms and +120 ms (paired t-tests, p=0.011 and p=0.008), before returning to the 2 asymptotic level of the baseline at SOA=+240 ms. Within the studied range of SOA, beeps modulated 3 the saccadic reaction time by about 22 ms, corresponding to 16% of the median latency observed 4 with synchronous auditory and visual stimuli. 5 Finally, we performed the same analyses on the median absolute deviation (right panel) to 6 determine the effect of the beeps on the temporal precision of saccades. Interestingly, delivering a 7 synchronous beep significantly reduced latency dispersion (p<0.003), which was significantly larger 8 than with a synchronous beep for SOA=−120 ms (p<0.004), 60 ms (p<0.002) and 120 ms (p<0.0004). possibly involved in a gap paradigm (Fischer & Weber, 1993). Moreover, early beeps tended to 8 reduce the saccade latencies compared to the synchronous beep condition, while late beeps 9 significantly delayed the saccades for all positive SOAs, producing saccades with even longer 10 latencies than when no beep was delivered. For beeps occurring 240 ms after target onset, saccade 11 latencies decreased back to the baseline asymptote. 12 It is noteworthy that subjects sometimes initiated their saccades before having correctly 13 processed where the target appeared, mostly in conditions where the beep was presented before 14 target onset. This could possibly reduce the latencies for negative SOAs and produce the overall 15 pattern we observed. However, we believe that this was not the case. Saccades triggered before 16 proper target detection have 50% chance of going in the right direction. To remove these 17 anticipatory saccades, we used a similar reasoning as what has been proposed to isolate true express 18 saccades (Fischer & Weber, 1993). Individual histograms showing, for each condition, the number of 19 initial saccades going in the opposite direction -plotted either before or after applying the adaptive 20 low-pass filter on latencies described in the Materials and Methods -are provided in Fig S4 of the 21 supporting information. Only 12 saccades going in the wrong direction remained, a negligible fraction 22 of the distribution (considering the 12327 that were analyzed). Therefore, we are confident that the 23 vast majority of saccades programmed before target detection (but going in the right direction) were 24 also removed by our low-pass filter. Moreover, unlike for means, the analysis of medians is rather 25 robust to extreme values. We can therefore conclude that anticipatory saccades did not significantly 26 contribute to the observed latency modulations. 27 In this experiment, we presented a sound in the majority of trials and participants might have 28 developed an expectation such that in each trial they waited for a sound before triggering the 29 saccade. This strategic behavior would obviously lead to increased latencies in trials in which the 30 sound was played after the visual target or not played at all. One could therefore argue that the 31 effect we observed might be simply induced by the experimental design. In order rule out this 32 possibility, we conducted a control experiment in which the experimental conditions were blocked to 33 better control the participant's expectation.
34 Experiment B -Blocked control 1 This experiment used the same method as experiment A except that conditions now were 2 blocked and only 3 SOAs (−60, 0 and +60 ms) and the No beep condition were used. In other words 3 each SOA condition and the No beep condition were presented in separate blocks. If the warning 4 effect found in experiment A was due to delayed saccades in the No beep condition rather than 5 shorter latencies with synchronous beeps, this advantage should be reduced or cancelled when 6 blocking the experimental conditions. Similarly, if the modulation effect found in experiment A was 7 due to waiting for the late arrival of beeps, one would expect to find a limited difference between

15
A total of 2727 out of 2880 recorded trials were analyzed (94.7%). After applying our low-pass 16 filter to remove anticipatory saccades, only 3 saccades going in the wrong direction remained. Given   6 Grouping the various trial types in blocks should promote forming expectations about when 7 exactly the beep would appear with respect to target onset. We did not observe a reduction of the 8 advantage found in experiment A when delivering a synchronous beep, nor limited difference 9 13 between the SOA=0 ms and the other positive SOA conditions. The absence of differences in the 1 blocked versus interleaved experiments provides a clear indication that the modulation observed in 2 experiment A is not a design artifact related to a strategic waiting for the auditory signal. Overall, 3 these results support the view that the effects on saccade latency result from multisensory 4 interaction influencing the temporal processing of the target. Auditory and visual maps encoding 5 saccadic goals in space have been found in the deep layers of superior colliculus (D. L. Sparks, 1988; 6 David L. Sparks & Nelson, 1987). These maps are spatially kept in register permitting efficient 7 audiovisual integration (Jay & Sparks, 1984). The evidence for integration in the temporal dimension 8 reported here could take place in the superior colliculus as well. Indeed, auditory events delivered 9 near the timing of target onset would produce a stronger multisensory activity in the motor maps 10 coding for the target in SC (M. A. Frens et al., 1995). 11 Interestingly, multisensory interactions influenced the temporal processing of the target, even 12 though the beeps did not provide any information regarding the direction or timing of the target. In 13 an earlier study, we found that the temporal integration of a beep and a flash can modulate the 14 perceived appearance of the flash, so that it is perceived later or, to some extent, earlier in time, 15 depending on whether it is preceded or followed by a beep (Vidal, 2017). Such asymmetrical 16 modulation was also reported for multisensory integration after adaptation to an audiovisual 17 temporal lag ( triggering, suggesting that the same multisensory mechanisms might be involved. Importantly, two 20 interaction modes depending on the audiovisual offset are possible (Vidal, 2017): for offsets below 21 40 ms, a single fused bimodal event is perceived while for larger offsets and up to 200 ms, two 22 separate events are perceived but they are reported as being closer in time than they physically are. 23 Supposing that the same perceptual law applies to the target onset, we propose that for short SOAs 24 the beep and the target were perceived as being simultaneous while for longer SOAs the perceived 25 target is only shifted in time toward the beep. Consequently, participants might have detected the 26 visual target faster or slower depending on whether the auditory signal preceded or followed the 27 target, thus modulating saccade latency. It should however be pointed out that the extent of 28 latencies modulations reported here (about 12 ms) is much smaller than what has been found in 29 purely perceptual tasks (about 120 ms, Vidal, 2017), a result that will be further discussed in the 30 general discussion. To probe whether the modulation effects we found in the two previous experiments is specific 2 to audiovisual integration and to disentangle it from possible alertness effects, we conducted 3 another experiment in which the auditory signal (beep) was replaced by a visual signal. The visual 4 signal was a full-screen luminosity decrease from the usual grey background (25.8 cd/m 2 ) to a totally 5 black background (0 cd/m 2 ) lasting one frame (10 ms) before returning to the original grey value. We showed that neither synchronous flashes (p=0.52) nor flashes in general (p=0.34) affected saccade 27 latencies, compared to the No flash condition. Moreover, student t-tests comparing the SOA=0 ms 28 reference with each of the other SOA condition showed that flashes increased saccade latency both 29 when they were presented just before (p=0.020 for SOA=−30 ms) and after target onset (p<0.003 30 and p<0.0004 for SOA=+30 and +60 ms, respectively). This reactivity impairment is confirmed by the 31 reduced accuracy observed in the saccade landing positions: saccadic gains were significantly lower 32 when flashes were delivered 30 ms before or 120 ms after target onset (p<0.004, see supporting 33 15 information S5 Fig left). In order to compare the results from experiment C with the ones from  . Statistics were unpaired t-tests performed on the n score differences between experiments for each of the 9 SOA conditions. Three stars indicate highly significant differences after Bonferroni correction (p<0.00555), single stars and two stars significant differences without correction (p<0.05 and p<0.01 respectively). Red arrows indicate the overall range of variations. 1 In this experiment, the data show that when a visual signal -a background flash -was 2 presented 30 to 60 ms after target onset, saccades were strongly impaired with longer latencies and 3 lower spatial accuracies. When the background flash was presented 30 ms before target onset, 4 saccades were also impaired albeit to a limited extent. However, when the visual signal and the 5 target onset were simultaneous we observed similar saccade latencies both when the target was 6 presented alone and when it was combined with a simultaneous flash. However, when the visual 7 signal occurred between 60 to 120 ms before target onset, saccade latency tended to decrease. 8 These findings could be regarded as related to the effects induced by visual warning signals -onset, 9 offset or change of symbol 'o' within the fixation cross -on saccades (L. E. Ross & Ross, 1980; S. M. 10 Ross & Ross, 1981). The authors reported a warning effect when the visual signal was delivered 11 100 ms to 600 ms before target onset, with shorter latencies than without a visual signal. Conversely, 12 when the visual signal was delivered 50 to 150 ms after target onset, saccade execution was impaired 13 and latencies were longer. Furthermore, they found differential effects between onset and offset 14 signals on saccade latencies, which points to underlying mechanisms similar to the ones involved in 15 the gap and overlap effects (Saslow, 1967). Indeed, in the Ross and Ross (1980;1981) paradigm, 16 visual signals inside the fixation cross that appeared before (or disappeared after) target onset could 17 have impaired (or facilitated) the release of fixation by modulating the activity of the rostral pole of avoid such interactions between visual signal, fixation and target, we used a full-background flash 20 conveying no spatial information. Despite this important methodological difference we also found 21 longer saccade latencies when the flash was presented 30 ms before and 30 or 60 ms after target 22 onset. However, we found a limited warning effect when the flash appeared more than 60 ms before 23 target onset; and no changed in latencies when the flash coincided with the target onset. Curiously, 24 White et al. (2005) found a strong warning effect using a large pink noise visual distractor presented 25 before target onset. In their study, the visual signal remained on until the end of the trial, which 26 might explain why they did not observe the same detrimental interference we did. Indeed, the rapid 27 transient feature of our visual signal probably comes with a stronger propensity to divert attention. 28 Moreover, in their study only the fixation-to-target SOA was manipulated, inducing a gap or overlap 29 situation, while the distractor always appeared at the offset of fixation. Therefore, the effect of the 30 visual signal timing relative to the target onset -our SOA -could only be determined indirectly by 31 subtracting the gap/overlap effect obtained in baseline conditions, reducing the validity of this result. 32 Because the transient visual signal we used did not provide a fixation signal that could 33 compete with the target, the changes in saccade latencies we observe here cannot result from a 34 difficulty to release fixation, as in it is thought to be the case in an overlap paradigm. Instead, in our 1 experiment the reduced saccade performance could relate to masking effects produced by saccadic 2 inhibition. On the one hand, it is well established that when a visual distractor is presented limited. As discussed earlier, this difference could relate to the transient nature of our signal, but also 17 to different choices in the design, which allowed us to assess directly the effect of the signal offset on 18 latencies. Lastly, the reduced gain of saccade amplitudes observed when the flash was presented 19 about 100 ms after the target onset is yet another signature of SI (Guillaume, 2012). Interestingly, we 20 found no saccadic impairment when both flash and target onset occurred simultaneously, which 21 could be interpreted as the absence of RDE when using large distractors (White et al., 2005). 22 However, in such situation, the drastic change in luminance contrast when the background screen 23 turns black increases the saliency of the target, which might reduce its processing time: the RDE 24 could be compensated by an opposite effect due to the increased visibility of the target. 25 Overall, we found a limited visual warning effect: adding background flashes before the target 26 onset did not lead to shorter saccadic latencies, except for the 120 ms SOA. We could not find 27 evidence for visual-visual temporal integration either: irrelevant background flashes did not attract 28 the target onset in time to modulate saccade latencies in the same way as beeps did. As we 29 proposed, the latency modulation observed with auditory signals could result from audiovisual 30 integration, taking place most probably in the deep layers of the superior colliculus. We now suggest 31 that mechanisms other than multisensory integration are involved when using this visual signal, 32 namely saccadic inhibition and the RDE. At this stage, three hypotheses could explain this difference: 33 (i) the modulation resulting from cue combination is specific to audiovisual integration; (ii) sensory The change in background luminance used in experiment C was particularly salient. Notably, 12 the whole background luminance was significantly altered for 10 ms over a large portion of the visual 13 field, which included the attended regions of the visual field where the visual target was presented. 14 This salient signal could have generated a strong saccadic inhibition resulting in the significant 15 masking effects observed in experiment C, behind which visual-visual integration evidence would be 16 concealed. To rule out this explanation, we created a new visual signal where the overall changes in 17 saliency were much reduced. The background flash was replaced by a pair of horizontal isoluminant 18 strips flashed for 10 ms in peripheral vision (see Fig 1).  SOA=−60 and −30 ms, respectively), a tendency that became mostly significant with flashes 5 presented after the target (p<0.0026 for SOA=+30 and +120 ms, and p=0.018 for SOA=+60 ms). This 6 impairment is partly confirmed by the reduced accuracy observed in the landing positions when 7 flashes were delivered after target onset: saccadic gains tended to be lower (p=0.012 for 8 SOA=+120 ms, see supporting information S5 Fig right). Curiously, a single sample t-test on the n scores 9 of the SOA=0 ms condition showed that adding synchronous flashes tended to reduce saccade 10 latencies by 9.9 ms (p=0.020), although across the whole range of SOAs, flashes did not affect 11 latencies (p=0.51). 12 In order to compare the results of experiment D with the results of experiment C, we 13 computed for both experiments the individual median latency differences between each SOA 14 condition and its respective No flash baseline. We then performed unpaired Student t-tests to 15 compare these latency differences between experiments and found a quite similar pattern of 16 behavior, except that with strips flashes saccades were significantly faster when SOA=0 ms 17 (p<0.0055), and the limited warning effect found for SOA=−120 and −60 ms with background flashes 18 tended to disappear (p=0.041 and p=0.057, respectively). and C (grey plot): median latency differences (top) and n score differences (bottom) aligned on the No flash condition (dashed lines). Statistics were unpaired t-tests performed on the n score differences between experiments for each of the 9 SOA conditions. Three stars indicate highly significant differences after Bonferroni correction (p<0.00555) while single stars significant differences without correction (p<0.05).

Discussion
Red arrows indicate the overall range of variations.

1
In this experiment, we used a new visual signal -isoluminant strips flashed for 10 ms in 2 peripheral vision -designed to induce a much lower transient change in saliency than the full- 3 background luminance decrease used in experiment C. During the debriefing, subjects reported that 4 these flashes were indeed barely visible. We expected that this type of visual signal would limit the 5 remote distractor effect (RDE), and thus reveal a potential modulation -even limited -of saccade 6 latency similar to the one observed with the auditory signal. The effects on saccade latency were to 7 some extent reduced with strips flashes compared to background flashes, which supports our 8 hypothesis regarding the limited RDE. The limited warning effect that we observed when the 9 background flashes were presented 120 ms and 60 ms before the target onset was eliminated with 10 the strips flashes. However, there was still no evidence for visual-visual temporal interactions: 11 irrelevant flashes did not combine with the target onset to modulate saccade latencies. The strips 12 flashes also led to a reduced accuracy in saccade landing positions when the flash occurred after 13 target onset. Interestingly, when the target and signal onset were synchronous, saccade latencies 14 were shorter. As previously discussed, the target visibility could be increased by the simultaneous 15 flash, producing an effect opposite to the RDE. One might speculate that, although with the low- 16 saliency signal, this effect could have been reduced, this was not the case and since the masking 17 effect mediated by the saccadic inhibition was reduced, the combined effect resulted in saccade 18 latencies 10 ms shorter than without visual signal. 19 To summarize, contrary to what we observed with auditory signals, visual targets were not 20 temporally integrated to visual signals, and consequently did not modulate saccade latencies. This 21 multisensory effect is therefore either exclusive to audiovisual interactions, or requires a sensory 22 signal coming from another, non-visual, modality. To address this question, experiments E and F 1 investigated whether we could evidence multisensory interaction with tactile and audio-tactile 2 signals.
3 4 We found that visual signals -whether salient or not -presented around target onset do not 5 produce the same temporal interaction resulting in saccade latencies modulation as auditory signals 6 do. In a new experiment, we replaced the auditory event (beep) with a brief tactile stimulation 7 (100Hz vibration for 10 ms) to investigate whether a similar multisensory integration effect could be 8 observed.

Experiment E -Touches & Saccades
Participants were asked to place their hands on the table at a comfortable distance. One 9 hand was placed on top of the other, and the tactile stimulation was delivered at the center of the 10 dorsal surface of the top hand by a solenoid tactor (Dancer Design). The tactor was held in place by 11 an adhesive ring and was controlled with Matlab. In order to avoid any possible biases induced by the 12 hand receiving the tactile stimulation, the left and right hand positions were alternated after each 13 block of 60 trials, hence stimulating alternately each hand. Closed headphones were used to prevent 14 the participant from hearing the noise produced by the tactile vibrations. Except for the tactile 15 stimulation and hand alternation, the experimental protocol was the same as for experiment A. 8 16 volunteers (5 women and 3 men) participated in this experiment, only one from the same initial pool. 17 They were between 22 and 42 years old (average 29.6) and all but one were right handed. 18

19
A total of 7520 out of 7680 recorded trials were analyzed (97.9%). Only 24 saccades going in showed that saccade latencies were not reduced in the SOA=0 ms condition with synchronous tactile 5 stimulations (p=0.11), although across the SOA range tactile stimulation tended to reduce latencies 6 by 5.8 ms on average (p=0.044), compared to the No touch baseline. Further paired t-tests 7 comparing the SOA=0 ms with each other SOA condition, showed that latencies decreased when 8 touch was delivered before target onset (p<0.001 for SOA=−60 ms and below; and p=0.048 for 9 SOA=−30 ms) and increased when delivered after target onset (p=0.0082 and p<0.0002 for SOA=+30 10 and +60 ms respectively). 11 In order to compare with the results of experiment A, we computed the individual median 12 latency differences between each of the SOA condition and the No beep (experiment A) or No touch 13 (experiment E) baselines. We then performed unpaired Student t-tests to compare these latency 14 differences between experiments and found a very similar pattern of behavior, albeit shifted in time 15 by roughly 30 ms. The tactile modulation found in the synchronous condition would correspond to 16 the auditory modulation in the SOA=+30 ms condition. As a consequence, the warning effect with the 17 tactile stimulation is to be found in the SOA=-30 ms, which explains why the SOA=0 ms condition was 18 not different than the No touch baseline. not (strips flashes) supports the idea that these interactions more likely happen between but not 6 within modalities, much as what has been reported in a different context (Hillis et al., 2002). Indeed, account for the fact that saccades had shorter latencies when beeps but not tactile stimuli were 1 simultaneous with the onset of the visual target. Experiment F will explore this issue in more details.
2 3 In this last experiment, we directly compared the modulation of saccade latencies produced by 4 auditory, tactile and audio-tactile signals. Contrasting the data from experiments A (auditory stimuli) 5 and E (tactile vibrations) suggests that touch led to a smaller modulation of saccade latencies than 6 auditory stimuli. Experiment F aimed at further investigating this issue using an interleaved-modality 7 within-subject design. This experiment also evaluated whether multimodal irrelevant stimuli 8 presented around the time of the visual target onset modulate saccade latencies more strongly 9 compared to unimodal irrelevant signals. As reported above, the multisensory modulation of saccade 10 latency resulting from tactile vibrations and auditory beeps are shifted in time relative to one 11 another. This temporal shift explains why delivering beeps simultaneously with the visual target 12 significantly decreased saccade latency but not touches. This difference might depend on the fact 13 that sound are transduced faster than tactile stimuli delivered to the hand. Consequently, we 14 conducted a preliminary experiment with a single participant 1 to assess the temporal offset between 15 the auditory and tactile stimuli that is required to perceive the two events simultaneously, the audio- 16 tactile Point of Subjective Simultaneity (PSS). The PSS was estimated using a temporal order 17 judgment task ("Touch was first/second?"). This experiment showed that a brief touch had to be 18 delivered 28ms before the beep to be perceived as occurring simultaneously with the beep. 19 Based on the results obtained in this preliminary experiment, in experiment F, we used for all 20 participants a fixed 30 ms delay between tactile and auditory stimuli (i.e. touch delivered 30 ms 21 before beeps). This delay was also used in a tactile only condition: the tactile vibration that in  7). The other comparisons between sensory modalities did not reach 21 significance (p=0.11 for tactile vs. audio and p=0.27 for audio vs. audio-tactile). 22 Experiment F replicated the findings we observed in experiment A, B and E. Notably, auditory 23 and tactile signals decreased and increased saccade latencies depending on whether they were 24 presented before or after the visual target, respectively. Moreover, the fact that simultaneous beeps 25 and tactile stimuli decreased saccade latencies suggests that this modulation was combined with a 26 warning effect caused by the mere presentation of another sensory event. It is noteworthy that the 27 injected delay introduced between auditory and tactile signals cancelled the temporal shift between 28 modalities, as illustrated by the horizontal alignment of the latency modulation curves. However, 29 these curves show different vertical scaling. In order to compare the strength of the modulation 30 between unimodal and multimodal signals, we computed individual linear regressions of n scores for 31 each modality condition, within the range [−60 ms, +60 ms] where latency modulations were 32 maximal (bottom-right plot of Fig 7). Average slopes (mean ± SEM in s -1 ) were respectively 33 11.54 ± 1.32, 18.78 ± 1.84 and 21.63 ± 1.10 for tactile, auditory and audio-tactile stimulations. Paired 34 26 Student t-tests revealed that slopes for tactile were lower than for auditory (p<0.04) and audio-1 tactile (p<0.01), but they were not significantly lower for auditory than for audio-tactile (p=0.22). Finally, the saccade latency spread quantified by the median absolute deviation followed a 3 very similar pattern for all sensory signals, with a tendency to increase with SOA (SOA=+120 ms 4 against SOA=0 ms: p=0.013 for auditory and p=0.04 for audio-tactile). These results are consistent 5 with what was observed in experiment A for auditory stimuli and in experiment E for tactile stimuli. 6 We also tested whether for the audio-tactile signal, the auditory and tactile components were 7 combined following the Bayesian optimal law predicted by the maximum likelihood estimator (MLE, 8 27 see . We computed for each participant the MLE prediction on the standard 1 deviation of the saccade latencies for the audio-tactile combination using the following formula: 3 where σ * 0 and σ + 0 are respectively the auditory and tactile standard deviations of the latency 4 distributions for the SOA=0 ms condition. We then compared this prediction σ ) *+ 0 with the 5 standard deviation measured in the audio-tactile condition σ *+ 0 using a paired student t-test (see 6 supporting information S6 Fig). The MLE prediction was significantly lower than the observed one 7 (p<0.001), indicating that the variability reduction expected in a Bayesian framework by combining 8 two modalities is far from achieved. In fact, the audio-tactile bimodal variability was not even 9 significantly lower than the ones for unimodal conditions (p=0.93 for auditory and p=0.49 for tactile).

11
Whether we add an irrelevant beep, touch or a combination of both, saccade reaction times 12 are altered in similar ways. Compared to the No signal condition, latencies are generally shorter, and 13 increase rather linearly for irrelevant stimuli presented in the range of [−120 ms; +120 ms] after the 14 target onset. The within participant design of this experiment allowed us to confirm that auditory 15 signals do produce a significantly stronger modulation effect than tactile signals, as we suggested 16 when comparing experiments A and E. However, combining both modalities did not systematically 17 increase the slopes of saccade latency modulations as a function of the SOA: audio-tactile signals 18 produced a stronger modulation of saccade latencies than unimodal tactile signals, but only 19 marginally when compared to the effects of unimodal auditory signals. This suggests that the saccade 20 latencies reached a lower limit with auditory modulation with a saturation that did not allow further 21 processing improvement with an additional modality, e.g. tactile. Finally, in many spatial perceptual 22 problems the multisensory cue-combination is found to be optimal according to MLE Bayesian 23 framework, for example when using both haptic and visual modalities to estimate size ( 27 the combined interference of irrelevant auditory and tactile signals with latency clearly did not follow 28 Bayes law, which points to potentially distinct underlying integration mechanisms than for 29 perception. Because saccades involve specific brain structures -the superior colliculus -one cannot 30 exclude that the integration of the different sensory maps could follow different rules than in other 31 goal-directed motor actions.

32
General Discussion 1 A multisensory effect between modalities but not within 2 In this project, we addressed a key issue of the multisensory domain: is there a supramodal 3 system in the brain that would gather perceptual evidence indistinctly from any sensory inputs 4 available in order to guide motor behavior? Our experiments showed that irrelevant auditory signals 5 (beeps) presented around target onset influenced oculomotor reactions, with a temporal modulation 6 that depends on the SOA between the target and the irrelevant signal. Notably, saccade latencies 7 decreased or increased when the visual target onset was preceded or followed by a task-irrelevant 8 auditory stimulus (experiments A and B). A similar modulation was observed also when auditory 9 stimuli were replaced by or combined with tactile vibrations delivered to participants' hand 10 (experiments E and F). These results suggest that the visual target onset was temporally bound to the 11 task-irrelevant auditory and/or tactile signals. Consequently, participants might have perceived the 12 onset of the visual target sooner or later, depending on whether auditory and tactile signals 13 preceded or followed the target, which, ultimately, modulated saccade latencies. 14 However, we did not observe the same latency modulation when using transient visual signals 15 (experiments C and D). In fact, we found that the visual signals often increased saccade latencies 16 even when they occurred before target onset. This effect can be attributed to saccadic inhibition and 17 the related remote distractor effect rather than sensory integration processes. In line with our 18 predictions, saccadic inhibition appears to be stronger for the salient signal (black background, 19 experiment C) than for the weaker signal (isoluminant strips, experiment D). Curiously, when the 20 flash and the target onset occurred simultaneously, the target visibility increased which 21 compensated for the saccadic inhibition latency impairment. In sum, our findings show that the 22 modulation of oculomotor response is not specific to audiovisual interactions, as touch can also 23 influence saccade reaction times. However, we did not find such modulation with visual signals, 24 which indicates that external signals only contribute between and not within modalities, much as 25 what has been reported in a different context (Hillis et al., 2002). 26 A potential illusory overlap/gap effect 27 It is puzzling that the extent latency modulation reported here when using audiovisual 28 stimulations (about 12 ms in experiment A and B) was far weaker than what has been reported when 29 simply estimating the perceived time shift induced by multisensory integration of audiovisual events 30 (about 120 ms, Vidal, 2017). We propose that this difference might be due to a perceptual illusion 31 that limited the effects on the saccadic latencies. During debriefing, some of the participants 32 29 reported a peculiar temporal sequencing of the target onset and the fixation offset: although both 1 events were always perfectly synchronous, when the beep occurred after the target onset, it seemed 2 as if, for a brief instant, there was neither fixation nor target on the screen, as if a temporal gap had 3 been introduced between the two events. This phenomenon points toward the possibility that the 4 only the perceived target onset was affected by some temporal multisensory integration mechanism 5 (Fendrich & Corballis, 2001;Slutsky & Recanzone, 2001;Vidal, 2017). The multisensory temporal 6 integration could have shifted the target onset so that it is perceived later than the physical event for 7 beeps after (positive SOA), producing an illusory gap. Conversely, the relative target onset would be 8 perceived sooner for beeps first (negative SOA), producing an illusory overlap (illustrated in Fig 8). In 9 both situations, the expected modulation by the audiovisual integration would be reduced by the 10 illusory gap/overlap, as the latter goes in opposite direction than the multisensory effect. Indeed, 11 early studies investigated the effects of an overlap/gap paradigm where the fixation offset and target 12 onset where manipulated separately so that a gap (neither on the screen) or an overlap (both on the 13 screen) was introduced (Reuter-Lorenz, Hughes, Saslow, 1967). Saccade latencies 14 are greatly reduced with a gap and increased with an overlap. Importantly this effects are also 15 present for saccades toward acoustic targets, which suggests that the facilitation of premotor 16 processes in the superior colliculus could be responsible for the gap effect rather than the processing 17 of the target itself (Fendrich, Hughes, & Reuter-Lorenz, 1991; Rolfs & Vitu, 2007). We speculate that 18 an illusory gap/overlap due to beeps shifting the perceived onset time of the target -could have 19 minimized the effect of beeps on saccades. This interesting issue is currently under investigation. Conclusion and openings 1 We found that both auditory and tactile events falling within a large binding window of visual 2 events reliably affect saccadic latencies. This modulation is stronger when auditory and tactile signals 3 are combined. On the contrary, an external visual signal mostly impairs saccadic reactivity. This 4 demonstrate that combining multiple sources of information does not systematically lead to 5 improved performance, as often reported in the multisensory literature. Mechanisms specific to each 6 motor behavior might have different ways of processing and combining those sources of information. 7 For saccades, auditory and tactile information do interact to improve the reactivity to a visual target 8 onset, but not visual information. To illustrate the functional significance of this phenomenon, let us 9 consider an ecological example: while walking on grassy slopes, careless bees flying around us or 10 grasshoppers jumping as we approach can produce both auditory and tactile signals. These signals 11 combine with the visual signal to improve the localization about where to aim the saccade and 12 quickly foveate the moving insect. Here we showed that even when the sound and/or touch are non- 13 informative about where the target is located and when the event occurs, saccades are still triggered 14 faster. One might wonder whether this ability could have an evolutionary grounding. Reacting to 15 something moving in the visual field and making noise would be more crucial for survival than if 16 moving silently, or is it just a matter of general alertness? 17 Supporting information 18 S1 Table. Student's t-tests and related tests for all experiments but F. The statistical analyses to 19 compare the mean median latency n score of each condition with the SOA=0 ms reference condition 20 followed 3 steps: a normality test (Shapiro-Wilk), a variance test (Levene) and a paired Student's t-test. 21 This  deviation computed when SOA=0 ms for each modality with the associated MLE optimal prediction. 6 Comparisons were done using paired t-tests. 7