Saccades to both vision and touch are modified following adaptation but cross-modal transfers are asymmetrical.

Ali Batikh, Valérie Gaveau, Muriel Panouillères, Éric Koun, Romeo Salemme, Alessandro Farnè, Denis Pélisson

► To cite this version:

Ali Batikh, Valérie Gaveau, Muriel Panouillères, Éric Koun, Romeo Salemme, et al.. Saccades to both vision and touch are modified following adaptation but cross-modal transfers are asymmetrical.. Journal of Neurophysiology, In press, 10.1152/jn.00154.2024 . hal-04689294

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3 Saccades to both vision and touch are modified following
4 adaptation but cross-modal transfers are asymmetrical.

5 Ali Batikh¹ https://orcid.org/0000-0002-0306-8903, Valérie Gaveau¹

6 https://orcid.org/0000-0002-2255-5766, Muriel T.N. Panouillères¹ https://orcid.org/0000-0003-0264-2093, Éric Koun¹ https://orcid.org/0000-0003-3624-3701, Roméo Salemme¹

7 https://orcid.org/0000-0003-2255-5766, Alessandro Farnè¹, Roméo Salemme¹

8 https://orcid.org/0000-0003-1075-540X, Alessandro Farnè¹, https://orcid.org/0000-0001-5769-3491, Denis Pélisson¹

9 https://orcid.org/0000-0002-9114-7758

10 ¹IMPACT Team of Lyon Neuroscience Research Center INSERM U1028 CNRS UMR5292 University Claude Bernard Lyon 1, France.

11 § These authors contributed equally to this work.

12 Correspondence: Ali Batikh (ali.batikh.97@gmail.com).

13
14
15
16

17 ABSTRACT

18 Adaptation of reactive saccades (RS), made toward the sudden appearance of stimuli in our
19 environment, is a plastic mechanism thought to occur at the motor level of saccade generation. As
20 saccadic oculomotor commands integrate multisensory information in the parietal cortex and superior
21 colliculus, adaptation of RS should occur not only towards visual but also tactile targets. In addition,
22 saccadic adaptation in one modality (vision or touch) should transfer cross-modally. To test these
23 predictions, we used the double-step target paradigm to adapt rightward saccades made at two
24 different eccentricities toward the participants' index and middle fingers, identified either visually
25 (Experiment1) or tactually (Experiment2). In each experiment, the rate of adaptation induced for the
26 adapted modality and the rate of adaptation transfer to the non-adapted modality were compared to
27 that measured in a control (no adaptation) session. Results revealed that touch-triggered RS can be
28 adapted as well as visually triggered ones. Moreover, the transfer pattern was asymmetric: visual
29 saccadic adaptation transferred fully to tactile saccades, whereas tactile saccadic adaptation, despite full
30 generalization to non-adapted fingers, transferred only partially to visual saccades. These findings
31 disclose that in the case of tactile saccades, adaptation can be elicited in the absence of post-saccadic
32 visual feedback. In addition, the asymmetric adaptation transfer across sensory modalities suggests that
33 the adaptation locus for tactile saccades may occur in part upstream of the final motor pathway
34 common to all saccades. These findings bring new insights both on the functional loci(us) and on the
35 error signals of RS adaptation.

36 NEW & NOTEWORTHY

37 The present study revealed that, as predicted from a large literature, adaptation of visual reactive
38 saccades transfers to tactile saccades of the same as well as neighboring amplitudes. Furthermore, in a
modified double-step target paradigm, tactile saccades exposed to repeated errors adapt with similar rate and spatial generalization as visual saccades, but this adaptation only slightly transfers to visual saccades. These findings bring new information on saccadic adaptation processes.

**Keywords:** Saccadic adaptation; Touch; Vision; Cross-modal transfer.

43

## INTRODUCTION

We perform over 100,000 saccades per day to bring the image of objects of interest onto the fovea, the highest acuity part of our retina. Saccadic eye movements triggered by the sudden appearance of an object are classified as reactive (or reflexive) (RS), whereas those produced based on our internal goals are defined as voluntary saccades (VS). The latter relies on the activation of a wider neural network in comparison with the former (1).

Not only visual but also auditory (i.e., the sound of car brakes nearby) as well as somatosensory stimuli (i.e., a bee landing on our hand), can trigger saccadic eye movements. Compared to visual saccades, auditory saccades are less accurate, their latency decreases with increasing amplitude and they display a lower peak velocity (2). Similarly to auditory saccades, tactile (or somatosensory) saccades are less precise, less accurate, and display longer latency and lower velocity peak than visual saccades of the same amplitude (3–5). Consequently, due to their lower speed and longer duration, saccades toward a non-visual target show a curved trajectory more often than visual saccades, reminiscent of feedback- or feedforward-based on-line correction (6).

Importantly, the categorization into reactive or voluntary also applies to tactile saccades. Amlôt and Walker (7) studied the latency of pro-saccades (RS directed toward a target) and anti-saccades (VS to the opposite direction of a target) in response to visual or tactile targets and found that, in both modalities, the latency of pro-saccades is shorter than the latency of anti-saccades. Also, an equivalent of the visual grasp reflex (the failure of the oculomotor system to inhibit an erroneous pro-saccade toward the visual target in anti-saccades trials) was observed for tactile anti-saccades, with a very similar erroneous pro-saccades rate in the tactile (11.04%) and visual modality (13.13%). Whether voluntary or reflexive, the increased latency of somatosensory saccades relative to visual saccades can be attributed in large part to the additional processing step of coordinate transformation, as evidenced by Neggers and Bekkering (8). In their study of goal-directed eye and hand movements toward visual and tactile targets delivered on the participants' knee, these authors found that across subjects correlations between saccadic and hand reaction time (RT) were higher for somatosensory than visual targets. They argued that the information elicited by tactile stimulation of the knee, initially encoded in a leg-reference frame, had to be translated into an adequate reference frame for both the eye and arm motor responses, leading to correlated RT. In contrast, the information elicited by the visual target, initially encoded in an adequate reference frame for the saccadic system, thus needs to be translated into another reference frame only for the arm movement, yielding a weaker correlation between eye and hand RTs.

The additional cost of coordinate transformation on somatosensory saccades is further evidenced by the so-called crossed versus uncrossed hand paradigm (9). The reaction time of saccades toward a tactile target on the hand is longer when hands are crossed over the midsagittal plane than in the uncrossed hands condition. This cost is thought to be related to a conflict between the somatotopic (anatomical) representation of the stimulated hand locus and its external (spatial) representation. In
addition, in the crossed condition some tactile saccades follow a curved trajectory: these 'turnaround' saccades start in the direction dictated by the anatomical coding of the target and then are corrected in flight toward the actual, spatial location of the target. This phenomenon can be used to timestamp the underlying coordinate transformation between the anatomical and spatial representations of tactile targets. Indeed, firstly, the latency of the turnaround point relative to the tactile stimulation (332 ± 30 ms) was similar to the reaction time of straight saccades in the crossed hands posture (319 ± 25 ms); and secondly, the reaction time of turnaround saccades was similar to that of (straight) saccades executed when the arms are uncrossed (6).

The superior colliculus (SC) plays an important role in the convergence of somatosensory and visual signals. Groh and Sparks (10) found that among 86 neurons exhibiting saccade-related activity in the monkey SC, all but one additionally responded both to tactile and visual input. Interestingly, just like visuo-saccadic neurons, these multisensory saccadic neurons have a saccadic movement field, meaning their motor discharge is tuned to the amplitude and direction of the impending saccade and not to its endpoint relative to the body. Therefore, at the SC level, the somatosensory signals have already been transformed into saccadic signals encoded in an eye-centered coordinate reference frame. To test whether this transformation takes place within the SC, the researchers also recorded the target-related activity of 34 SC somatosensory neurons while monkeys performed saccades toward visual or tactile stimulations delivered to their hands. They found that the discharge of 74% of those cells varies with initial eye position and is therefore not solely encoded in a somatotopic reference frame, suggesting that somatosensory signals reaching the SC have already been remapped, at least in part, in upstream structures (11).

One critical feature of the oculomotor system is its plasticity. Saccades are the fastest movements that we can produce. Due to their high speed, and besides the exceptions already mentioned above, saccades usually cannot be modified in flight, but nonetheless, their precision is maintained throughout life. Sensorimotor adaptation mechanisms correct for saccade errors caused by fatigue, aging, or neurological diseases. Errors eliciting such so-called saccadic adaptation occur when the saccade landing position repeatedly overshoots (hyper-metria) or undershoots the target position (hypo-metria), leading respectively to an adaptive decrease or increase of saccade amplitude. In the laboratory, saccadic adaptation is most often elicited by the double-step target paradigm introduced by McLaughlin (12). This method consists of stepping a visual target (1st step) to elicit the saccadic response and, when the eyes are in-flight, stepping it again either backward or forward relative to the on-going saccade (2nd step) to elicit a post-saccadic error. Although the intrasaccadic step is usually not consciously perceived by subjects, the resulting post-saccadic error elicits, shortly after the primary saccade, a corrective saccade bringing the eye back to the stepped target. When repeated across identical double-step trials, the post-saccadic error is interpreted by the brain as a saccade programming error and leads adaptation mechanisms to reduce (for backward steps) or increase (for forward steps) the primary saccade amplitude, reaching a steady state level after some 10th to 100th of trials in humans (for review see, (13–15)).

Saccadic adaptation has been initially thought to result from motoric changes unfolding at the level of the cerebellum and brainstem (for review see (14, 15)). However, further studies disclosed that this mechanism additionally affects visual perception and relies also on higher cerebral areas. Studies combining fMRI with the double-step target paradigm have identified several cerebral or/and cerebellar areas whose activation can be related to the different subprocesses of saccadic adaptation: the
detection and the processing of the motor error, the learning process itself, the modifications in corrective saccades metrics (16-20).

Behavioral studies have also mitigated the pure motoric hypothesis of adaptation, but mainly for VS. First, studies comparing the effect of RS adaptation onto non-adapted VS (RS-to-VS transfer) to the effect of VS adaptation onto non-adapted RS (VS-to-RS transfer) found an asymmetric pattern of transfer of adaptation with a stronger transfer from VS to RS than the other way around, suggesting the existence of partially segregated adaptation sites for these two types of saccades (21, 22). Second, RS and VS also show different patterns of adaptation transfer to hand-pointing movements and anti-saccades. Indeed, adaptation of VS, but not of RS, transfers to hand pointing movements performed under gaze fixation condition (23), suggesting that only the former type of adaptation involves a sensory level. In addition, the adaptation of RS along a single horizontal direction transfers toward anti-saccades performed in the same (adapted) direction but not to those directed away (un-adapted direction) whereas in the case of VS, unidirectional adaptation transfers to both adapted and un-adapted directions. As in anti-saccades tasks the sensory and the motor vectors are dissociated, these results suggest that RS adaptation takes place at a motor level, whereas VS adaptation recruits both motor and sensory loci (24). Altogether, these studies strongly suggest that backward adaptation of RS acts at an oculomotor level. In contrast, as forward adaptation (of both VS and RS) has been much less investigated, its corresponding neural substrates are still debated. Forward adaptation is generally harder to induce than backward adaptation and the underlying mechanisms were suggested to differ between these two types of adaptation (25, 26). For these reasons, we focused the present study on RS backward adaptation mechanisms.

This hypothesis that RS backward adaptation takes place at a motor level implies that backward adaptation of visually triggered RS should transfer toward RS triggered by stimuli in other sensory modalities. In agreement with this prediction, Frens and van Opstal (27) showed that adaptation of visually guided RS transferred to 'auditory saccades' of the same vector (see also (28)). However, no empirical evidence from tactile saccades is available to support the notion of a motor locus of adaptation for RS. Indeed, neither the possibility to induce adaptation of touch-triggered saccades, nor the cross-modal transfer of adaptation to and from tactile saccades, have ever been investigated so far.

Thus, the present study seeks to further characterize the mechanisms involved in RS adaptation by addressing these two questions. To this twofold aim, we performed two experiments where backward saccadic adaptation was induced by the double-step target paradigm. In Experiment 1, we adapted RS toward visual targets (LEDs placed on the fingers of the participants' right hand) and tested the effect of such adaptation on RS toward both visual and tactile targets (electrocutaneous stimulations of the participant's fingers). In Experiment 2, we exposed participants to adaptation of RS toward tactile stimuli thanks to a tactile double-step paradigm and tested the effect of such potential adaptation again on RS toward both visual and tactile targets. We predicted in both experiments, first a significant decrease of adapted RS amplitude due to the adaptation exposure and second, a significant generalization of this adaptation to non-adapted RS toward nearby targets as well as a significant transfer to RS in the non-adapted modality.
# EXPERIMENT 1: TRANSFER OF VISUAL SACCADES ADAPTATION TO TACTILE SACCADES.

## MATERIALS AND METHODS

### 1. Participants

Sample size was calculated via the open access software G*Power 3.1.9.7 (effect size = 0.4, alfa = 0.05, Power = 0.8 and correlation among repeated measures = 0.6). There was no previous study investigating the transfer of adaptation from visual to tactile saccades, therefore we relied on the high visual to auditory transfer of adaptation reported in the literature (28) to select an effect size = 0.4. Twenty-one naïve volunteers (all right-handed, 8 males and 13 females, mean age 27.5 ± 4.2 ranging between 22 and 37 years old) participated in the first experiment. Fifteen participants were involved in a session where adaptation was elicited (ADAPT session), and fifteen participants were involved in another session where control saccades were performed (CTRL session) (nine of them had participated in the ADAPT session).

Participants' vision was normal or corrected-to-normal. Exclusion criteria were simultaneous participation in other experiments involving sensorimotor adaptation, a history of neurological or psychiatric disorders, cognitive disorders preventing the comprehension of the instructions, consumption of psychotropic drugs or alcohol, and severe sleep deprivation during the last 24 hours. Participants were asked not to wear makeup or to remove it before the experiment (to prevent any problem with the eye tracker).

Both experiments of this study were done in two separate phases. The initial sample sizes for Experiment 1 and 2 were 10 and 16 respectively. Around eight months later and following the reviewers suggestions on the first submitted version of the manuscript, sample sizes were increased to 15 participants in the first experiment and 30 participants in the second one.

### 2. Ethical Statement

Both Experiment 1 and Experiment 2 of the present study conformed with the Code of Ethics of the World Medical Association (Declaration of Helsinki 1964) and were approved by the ethics committee of INSERM U1028 (IRB00003888; decision n° 21-762 dated 19/01/2021). An informed consent was received from every participant prior to each experiment.

### 3. Experimental setup

Participants were sitting in total darkness with their head stabilized using a chinrest. They faced a vertical panel situated 30 cm from their eyes which maintained their right hand in a vertical position by a strap surrounding their wrist and rings surrounding the second phalanx of their fingers. In this position, the pinky, ring, middle, index, and thumb fingers were respectively at 5, 10, 15, 20, and 25 degrees of visual angle in the horizontal axis relative to the participant's midline (see Figure 1A). Six red light-emitting diodes (LED, diameter 2 mm) were positioned on the panel: one LED used as a fixation point (FP) was located at the participant's gaze level and 5 degrees to the left of the participant's midline; the five other LEDs were embedded in the rings maintaining the fingers. LEDs located on the index, middle, and ring fingers were horizontally aligned with the FP, the pinky and thumb LEDs were located below this line. The LEDs were attached on the front face of 5 wooden rings fixed on a vertical wooden board, allowing to maintain each finger aligned with its corresponding LED. In addition, rings and board were painted black and, before inserting their fingers in the rings, participants wore a black fabric glove.
Finally, the LEDs' intensity was kept low enough to prevent any lightning of the black gloves or rings.
Therefore, the participants could never see the location of their fingers or hand during the experiment.
For tactile stimulation, two electro-dermal electrodes with opposite polarities (Neuroline 7000, Ambu, Denmark) were placed on each finger underneath each LED, at the level of the distal (anode) and middle (cathode) phalanxes. The supra-threshold (100% detection accuracy) electrocutaneous stimulus felt like tingling, resulting from a squared wave pulse delivered by constant-current stimulators (Iso-Flex, A.M.P.I., Israel). A horizontal ruler was positioned on the top of the vertical panel (50 mm above the middle finger position), allowing to measure, at the beginning and end of each session, the participants' perceptual estimate of the middle finger position of their unseen hand (see below: section4/Procedures). Eye movements were recorded with an infrared eye tracker (EyeLink 1000, SR Research, Canada) at a frequency of 1000 Hz with an accuracy of 0.1°. Eye velocity was calculated online using a two-point central difference algorithm (29) and the time of saccade onset, used to trigger intra-saccadic target step or target extinction during rightward saccades, was based on a velocity threshold of 30°/s.

Each experimental session started with a calibration of the eye tracker, with participants being asked to fixate a central LED as well as four other LEDs placed on the panel (up, down, to the right, and the left of the central LED). A drift correction was performed after each experimental block and, whenever the eye drifted more than two degrees from the central LED, a calibration of the eye tracker was repeated.

## 4. Procedures

As experiments were conducted in a completely dark room, we took into consideration the fact that our conscious perception of hand position drifts toward our body midline (so-called proprioceptive drift) (30). We thus measured this drift before and after ADAPT and CTRL sessions, by asking participants to indicate which number on the visible ruler best matched the position of their occluded middle finger (measured 9 times, randomly sliding the ruler each time to avoid response strategies (31)).

ADAPT and CTRL sessions each involved five steps: a PRE proprioceptive location assessment, a saccade PRE-exposure phase, a saccade Exposure phase, a saccade POST-exposure phase, and a POST proprioceptive location assessment. We detail the time course of the saccade trials below (see Figure 1B).

During PRE-exposure the baseline performance of visual saccades and tactile saccades was evaluated: participants performed one block of 75 rightward saccades directed toward visual targets (visual block) and one block of 75 rightward saccades directed toward tactile targets (tactile block). All trials were initiated with the participants staring at the FP for a random duration (2000 to 3000 ms). Then, the FP was turned off and one of the five (visual or tactile) peripheral stimuli was presented randomly. Participants were instructed to saccade toward the location of the target as rapidly and as precisely as possible. During the saccadic response, the (visual or tactile) stimuli were terminated, but participants nonetheless had to maintain fixation on the now-absent target until the reappearance of the FP. At the end of the trial, the Fixation LED was turned on again, indicating the participant to get prepared for the next trial. Participants were asked to blink on their way back to the fixation point to reduce the amount of blinking that can occur during the saccades.

In the Exposure phase, participants performed 120 visual saccades randomly directed toward the index or the middle finger. As in PRE-exposure, each trial started with a fixation period which ended with the simultaneous appearance of the visual stimulus and the disappearance of the FP. In the ADAPT session, saccade onset detection triggered a 5 deg leftward intra-saccadic displacement of the target
248 (from the index to the middle finger or from the middle to the ring finger), this backward shift being
249 aimed at inducing an adaptive shortening of saccade amplitude (12). During the CTRL session, aimed at
250 measuring any potential change of saccade metrics unrelated to adaptation mechanisms, the target
251 remained at its initial location (index or middle finger) for the duration of the trial.

252 The POST-exposure was identical to the PRE-exposure phase. Comparisons of saccade gain
253 between these 2 phases allowed evaluating the after-effect of visual saccades adaptation and the
254 transfer of adaptation to tactile saccades.

255 The order of the two saccade blocks (visual and tactile) performed in each PRE- and POST-
256 exposure phase was counterbalanced between participants: half of them performed the visual block
257 followed by the tactile block in the PRE-exposure, then the tactile followed by the visual block in the
258 POST-exposure (Vis-Tact/Tact-Vis) and the other half vice versa (Tact-Vis/Vis-Tact).

259 The nine participants who performed both experimental sessions (ADAPT and CTRL) were tested
260 with at least one week washout delay in-between to avoid any cross-over effects related to the
261 retention of adaptation (32).

262 5. Analysis

263 Horizontal and vertical eye positions were analyzed offline using software developed in MATLAB by our
264 team. Saccades onset and offset were identified based on a velocity threshold of 15°/s. Saccade
265 amplitude was measured as the difference between eye positions 50 ms before the saccade onset and
266 50 ms after the saccade offset. The following dependent variables were then extracted for each saccade:
267 1) gain: ratio between the saccade amplitude and the target initial eccentricity (difference between the
268 target position and saccade starting position), this parameter was used to investigate the effect of the
269 double-step adaptation exposure on saccade size as it presents the advantage, over saccade amplitude,
270 of being expressed relative to the target distance, thus allowing to measure the mean accuracy of
271 saccades toward targets of different eccentricities pooled together (see (14), (13)); 2) latency: time
272 between the appearance of the initial target (T1) and the saccade onset; 3) duration: time between
273 saccade onset and saccade offset; 4) peak velocity: maximum eye velocity reached during the saccade.
274 Trials where saccades were made toward the pinky were discarded from further analyses; indeed, this
275 closest target from fixation (10°) was the most difficult for our participants to localize through tactile
276 saccades, resulting in the highest saccade amplitude variability among all fingers; in addition, restricting
277 our analyses to the ring and thumb allowed us to perform our generalization tests to the two
278 symmetrical locations around the index and middle fingers used for adaptation. Trials where the
279 saccadic gain fell outside the range defined by the mean gain +/- 2 x standard deviations (calculated and
280 applied for each participant across each session, phase, modality and target location separately), trials
281 where the saccade latency was lower than 80 ms or higher than 700 ms, and trials where a blink
282 occurred during the primary saccade were excluded from the analysis (exclusion of 9.57% of the trials in
283 total).

284 Two additional parameters were then calculated. First, in the exposure phase, the slope of the
285 linear relationship between saccadic gain and trial number was calculated for visual saccades toward the
286 middle and the index fingers, separately. Second, we calculated, for each finger and separately in the
287 adapted and the non-adapted modality, the following ratio of saccadic gain change between the pre-
288 and post-exposure phases: Gain change ratio = (Gain PRE – Gain POST) / Gain PRE. Therefore a positive
289 gain change ratio indicates a decrease in saccadic gain in the POST-exposure phases compared to the
290 PRE-exposure (compatible with backward adaptation) while a negative gain change ratio indicates an
291 increase in saccadic gain (for example, a gain change ratio of +0.3 corresponds to a 30% decrease of gain
292 in post-exposure relative to pre-exposure).

293 6. Statistical analyses

294 Statistical analyses were done using IBM SPSS statistics 29.0.0.0. First, to check if the double-step
295 exposure successfully elicited adaptation of visual RS, the slope of the linear relationship between
296 saccadic gain and trial number was submitted to a repeated measures ANOVA with the factor 'Target
297 position' (middle finger vs index finger) as within-subjects factor and the factor 'Session' (ADAPT vs
298 CTRL) as between-subjects factor. In addition, the gain change ratio of RS in the visual (adapted)
299 modality, used as a measure of adaptation after-effect, was also submitted to the same repeated
300 measures ANOVA Target position (middle and index fingers) x Session (ADAPT vs CTRL). Second, to
301 investigate whether adaptation of visual RS generalized to targets near the adapted locations, the gain
302 change ratio of visual saccades toward non-adapted fingers was submitted to a repeated measures
303 ANOVA with 'Target position' (ring and thumb fingers) as within-subjects factor and 'Session' (ADAPT vs
304 CTRL) as between-subjects factor. A similar ANOVA was performed on the gain change ratio of tactile
305 saccades toward all 4 fingers to investigate the transfer of adaptation to the other modality, except this
306 time the within-subjects factor 'Target position' had 4 levels (ring, middle, index and thumb fingers). We
307 included in this analysis of transfer only participants who showed a significant level of adaptation (14
308 subjects out of 15), i.e. showing a significant decrease of visual RS gain (independent-samples t-test
309 comparisons between PRE and POST phases) at least for the index or the middle finger.

310 Third, we submitted the proprioceptive assessments to a repeated measures ANOVA with the
311 factor 'Phase' (PRE vs POST) as within-subjects factor and 'Session' as between-subjects factor.

312 We also analyzed separately the latency, duration, and peak velocity, for both visual and tactile
313 saccades in the 14 significantly adapted participants using a 3-way repeated measures ANOVA with
314 'Phase' (PRE vs POST), 'Modality' (Visual vs Tactile) and 'Target position' (index vs middle finger) as
315 within-subjects factors and 'Session' (ADAPT vs CTRL) as between-subjects factor (see supplemental
316 material for the results of this analysis).

317 RESULTS

318 1. The adaptation of visual RS

319 As stated in the Methods, the existence of visual RS adaptation was addressed by two analyses of visual
320 RS performed toward the index and the middle fingers, first, on the slope of the gain change during the
321 exposure phase, then on the ratio of gain change between PRE and POST phases. Examples of gain
322 values for individual saccades performed toward the index and the middle fingers in the PRE- and POST-
323 exposure phases (visual and tactile saccades) as well as during the Exposure phase (visual saccades) are
324 plotted in Figure 2.

325 a. Gain slope during Exposure phase

326 The gain change during the Exposure phase of the ADAPT session can be seen in supplemental figure 1
327 for all significantly adapted participants (see Methods). The mean slopes of the gain change during the
328 exposure block are illustrated in Figure 3A. The repeated measures ANOVA revealed a main effect of the
329 factor Session (F(1, 28) = 20.061, p < 0.001) (mean slope ± s.d.: ADAPT = - 0.000549 ± 0.000528, CTRL =
330 0.000164 ± 0.000319). No other significant effect or interactions were found (all F ≤ 3.212, all p ≥ 0.084).
331 These results suggest that the double-step paradigm was successful in reducing the size of visual
332 saccades similarly for both adapted locations and that this decrease was significantly larger than in the
333 CTRL (no step) paradigm.

334 b. Gain change ratio between PRE and POST phases

335 As illustrated in Figure 3B, the mean gain change ratio for visual RS performed toward the index and the
336 middle fingers was larger in the ADAPT session than in the CTRL session. Indeed, the 2-way ANOVA
337 revealed a significant main effect of the factor Session (F(1, 28) = 139.45, p-value < 0.001) (mean gain
338 change ratio ± standard deviation: ADAPT = 0.1238 ± 0.04, CTRL = -0.0207 ± 0.025) as well as a
339 significant Session × Target position interaction (F(1, 28) = 5.05, p = 0.033). There was no significant
340 main effect of the factor Target position (F(1, 28) = 0.569, p-value = 0.457). Post hoc pairwise Bonferroni
341 comparisons showed a significant difference between the ADAPT and CTRL session for both middle
342 fingers (p-value < 0.001) and index finger (p value < 0.001); it also revealed a significant difference
343 between the index and the middle fingers (mean difference index - middle = -0.018 ± 0.008, p value =
344 0.043) in the ADAPT session but not in the CTRL (mean difference index - middle = 0.009 ± 0.008, p value
345 = 0.300). These results indicate that visual RS gain after-effects were significantly larger in the ADAPT
346 session than in the CTRL session, showing that exposure to the double-step paradigm successfully
347 induced adaptation of visual saccades.

348 We next verified whether the order of visual and tactile blocks, despite their counterbalancing
349 (see Procedures section), could affect the above results. To this aim, we submitted the gain change ratio
350 to the same ANOVA but with the additional between-subjects factor ‘Block order’ (Tact-Vis/Vis-Tact vs
351 Vis-Tact/Tact-Vis). This analysis showed that there was neither a main effect of Block order nor any
352 interaction with the other factors (Session and Target position, all F ≤ 2.730, all p values ≥ 0.111). In
353 sum, these results strengthen our conclusion that exposure to the double step paradigm successfully
354 induced adaptation of visual saccades.

355 2. Transfer analysis

356 This analysis includes only the 14 participants who were significantly adapted in the ADAPT session for
357 at least one of the two ‘adapted’ fingers (middle and/or index finger) (see Methods).

358 As shown in Figure 4A, visual RS adaptation generalized to nearby locations. Indeed, the
359 repeated measure ANOVA performed on the gain change ratio of non-adapted visual RS showed a
360 significant main effect of the Session factor (F(1, 26) = 51.778, p-value < 0.001) (mean gain change ratio
361 ± standard deviation: ADAPT = 0.114 ± 0.050, CTRL = -0.013 ± 0.043) with no other significant main
362 effect or interaction (all F ≤ 1.664, all p values ≥ 0.208). This result indicates a significantly larger gain
363 decrease for visual non-adapted saccades in the ADAPT in comparison to CTRL session, irrespective of
364 the target location.

365 We tested a possible effect of the order of visual blocks in the experimental protocol, by
366 submitting the gain change ratio to the above ANOVA with the additional ‘Block order’ factor (Tact-
367 Vis/Vis-Tact vs Vis-Tact/Tact-Vis). Results showed neither significant main effect of Block order, nor
368 significant interaction with the other factors of the ANOVA (all F ≤ 1.821, all p values ≥ 0.190).

369 As shown in Figure 4B, the visual RS adaptation transferred to tactile RS. Indeed, the repeated
370 measures ANOVA performed on the gain change ratio of non-adapted tactile RS showed a significant
371 main effect of the Session factor (F(1, 26) = 15.766, p-value < 0.001) (mean gain change ratio ± standard
deviation: ADAPT = 0.167 ± 0.108, CTRL = -0.017 ± 0.136) with no other significant main effect or
372 interaction (all F ≤ 1.447, all p values ≥ 0.243). This result indicates a significantly larger gain decrease for
373
374 tactile non-adapted saccade in the ADAPT in comparison to CTRL session, irrespective of the target location.

375 As for the previous analysis, we tested a possible effect of the order of visual and tactile blocks, by submitting the gain change ratio to the above ANOVA with the additional 'Block order' factor (Tact-Vis/Vis-Tact vs Vis-Tact/Tact-Vis). Results showed neither significant main effect of Block order, nor significant interaction with the other factors of the ANOVA (all F ≤ 1.681, all p values ≥ 0.192).

379 In summary, these results indicate that the gain of visual RS to non-adapted targets (ring and thumb fingers) as well as the gain of all non-adapted tactile RS decreased significantly more in the ADAPT session than in the CTRL session, therefore showing that visual RS adaptation generalized to nearby locations and transferred to tactile RS.

384 3. Proprioceptive drift

385 As shown in Figures 5, participants underestimated their unseen middle finger location. This proprioceptive drift was larger in the POST phase in comparison to the PRE phase (Figure 5B) but importantly, this pattern of change did not differ between the CTRL and the ADAPT sessions (Figure 5A).
386
387 Indeed, the repeated measure ANOVA disclosed a significant main effect of the factor Phase (F(1, 28) = 24.78, p < 0.001) (mean estimations (in degree) ± s.d.: PRE = 11.96 ± 3.06, POST = 8.7 ± 3.33), but no significant main effect of Session, and no significant Session × Phase interaction (all F ≤ 0.237, all p ≥ 0.630). Therefore, the proprioceptive drift of the hand increased to a comparable extent during the ADAPT and CTRL exposures. Thus, changes in proprioceptive drift differ from, and hence are not likely responsible for, the changes in tactile RS gain reported above.
388
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393

394
395 EXPERIMENT 2: INVESTIGATING THE ADAPTATION OF TACTILE SACCADES AND ITS TRANSFER TO VISUAL SACCADES.

396 Results from Experiment 1 indicate that the adaptation of visual RS transfers fully to non-adapted saccades in the same modality. Most notably, they additionally reveal that visual RS adaptation also transfers to tactile RS, irrespective of whether they were directed toward adapted or non-adapted finger locations. Importantly, this transfer across modalities is independent of the proprioceptive drift, as the latter was equally present in the CTRL condition where neither adaptation nor transfer were observed.

401 In keeping with the previously reported visual-to-auditory adaptation transfer (27), this visual-to-tactile adaptation transfer is consistent with the hypothesis that RS adaptation modifies the saccade motor command, thus acting downstream, at a level of the final common pathway where multisensory information about the target has already been transformed into a motor, oculocentric, reference frame. 402
403
404 To further support this hypothesis, we designed Experiment 2 to determine, first, whether saccades to tactile targets can be adapted and, second, whether saccadic adaptation transfer is bidirectional, i.e., 405 also from tactile to visual saccades. To this twofold aim, we adapted the double-step paradigm to electrocutaneous stimulation of the fingers during the tactile saccade execution, to repeatedly expose 406
tactilely triggered saccades to a backward aiming error. Then, similarly to Experiment 1, we assessed the 407
effectiveness of this tactile saccade adaptation and measured its effect on both visual and tactile 408
saccades performed toward different target eccentricities. 410
411
412

# MATERIALS AND METHODS

413

## 1. Participants

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Sample size was estimated via G\*Power 3.1.9.7 (effect size = 0.25, alpha = 0.05, Power = 0.8, correlation among repeated measures = 0.6). As in Experiment 1, previous studies investigating tactile saccades adaptation were lacking, therefore we based our choice of a moderate effect (effect size = 0.25) on the well-established low precision (high standard deviation of the gain) of tactile saccades (4). Thirty volunteers (3 left-handed, 22 females and 8 males, mean age = 26.8 ± 4.7, ranging between 19 and 37 years old) participated in Experiment 2 (all but one, the experimenter, were naïve to the objectives of this study). Inclusion and exclusion criteria were the same as in Experiment 1. All participants performed an ADAPT and a CTRL session separated by at least 7 days, in a counterbalanced order (15 participants started with the CTRL session, and the other 15 started with the ADAPT session).

423

## 2. Experimental setup

424

425

426

The experimental setup was the same as for Experiment 1. Eye movements were recorded at a 1000 Hz frequency using the remote configuration of the EyeLink® 1000 plus infrared Eye Tracker (SR Research, Canada).

427

## 3. Procedures

428

429

430

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434

435

The design was the same as in Experiment 1, except that all subjects performed both ADAPT and CTRL sessions (within-subject design). Each session consisted of the same 5 steps as in Experiment 1: a PRE proprioceptive location assessment, a saccade PRE-exposure phase, a saccade exposure phase, a saccade POST-exposure phase, and a POST proprioceptive location assessment. The testing order of tactile and visual saccades blocks in the PRE-exposure and POST-exposure phases were counter-balanced between participants: half of them performed visual saccades before tactile saccades in the PRE-exposure then tactile saccades before the visual ones in the POST-exposure (Vis-Tact/Tact-Vis), the other half were assigned the reverse order (Tact-Vis/Vis-Tact).

436

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438

The PRE- and POST- exposure blocks differed from those of Experiment 1 only by the duration of the visual and tactile targets, here 100 ms, to make the tactile stimulations more comfortable for participants, and by a slightly reduced intensity of the LED to provide a more comfortable contrast.

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447

For the exposure phase in the ADAPT session, a tactile target double-step paradigm was implemented, as follows. Participants first fixated on the FP for a random duration similar to Experiment 1, then a tactile stimulation was applied for 100 ms to their index or middle finger. Participants had to look as rapidly and as precisely as possible toward their stimulated finger and as soon as their saccadic eye movement was detected, a second tactile stimulation of 100 ms was delivered on the middle finger or the ring finger, respectively (inducing in every trial a 5° tactile backward step). Participants were asked to fixate on the last felt position of the tactile stimulation until the FP reappeared. In the CTRL session, the sequence of events was identical except that the second tactile stimulation was applied to the same, initially stimulated, finger (no target step).

448

## 4. Analyses

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450

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As in Experiment 1 saccades performed toward the pinky finger were discarded from the analysis. The same exclusion criteria were used as in Experiment 1, which resulted in the exclusion of 12.9% of trials. As in Experiment 1, we calculated the following parameters for all visual and tactile saccades: latency, amplitude, gain, duration, and peak velocity; then, the slope of the relationship between tactile saccade
gain and trial number of the exposure phase was computed separately for the ADAPT and CTRL sessions and for the middle and the index fingers. We finally computed the gain change ratio.

## 5. Statistical analyses

A data quality check showed that some participants systematically performed very hypometric tactile saccades in the PRE-exposure phase of both the ADAPT and CTRL sessions. Thus, using K-Means clustering methods, we checked if we could detect significantly different sub-groups in our sample of 30 participants based on their mean tactile saccades gain in the PRE-exposure phase. The number of sub-groups was determined using the elbow method (3 sub-groups) then fed to the K-Means clustering revealing that all three subgroups differ statistically from each other's according to their mean tactile RS gain: group 1 (5 subjects, mean gain = 0.374, range 0.342 to 0.471), group 2 (11 participants, mean gain = 0.676, range 0.623 to 0.752) and group 3 (14 participants, mean gain = 0.9915, range 0.847 to 1.205). As this study focused on the adaptive amplitude reduction of saccades, we decided to exclude group 1, resulting in a final sample size of 25 participants. This decision was based on the fact that the strong hypo-metricity of tactile saccades in group 1 would have led 1) to a biased and underestimated adaptation capacity (amplitude reduction adaptation is limited when baseline saccade gain is already low), and 2) even if those participants would nonetheless be adapted, to a biased and underestimated transfer of such adaptation to the visual modality because the adapted tactile saccades vectors would differ too much from the non-adapted visual saccades vectors.

Using the same method we checked if we could identify participants with very hypometric saccades in Experiment 1. We were able to identify 2 best fitted subgroups of participants according to their mean tactile RS gain, however, none of them qualified to have very hypometric saccades (mean gain ± standard deviation: Group 1 (7 participants) = 0.589 ± 0.116, Group 2 (8 participants) = 0.9392 ± 0.093) which might be related to the smaller sample size in Experiment 1 compared to Experiment 2.

We then followed the same analysis strategy as in Experiment 1. First, the slope of the linear relationship between saccadic gain and trial number during exposure was submitted to a two-way repeated measures ANOVA with the within-subjects factors 'Session' (ADAPT vs CTRL) and Target position (middle vs index fingers). Then, the gain change ratio of tactile (adapted modality) RS, used as a measure of adaptation after-effect, was submitted to the same repeated measures Target position (index and the middle fingers) x Session (ADAPT vs CTRL) ANOVA. Second, we investigated a possible generalization and/or transfer of adaptation. To this aim, we submitted the gain change ratio of non-adapted tactile and visual RS to two separate 2-way repeated measures ANOVA with 'Target position' and 'Session' (ADAPT vs CTRL) as within-subjects factors. The 'Target position' factor had 2 levels in the first ANOVA (ring vs thumb fingers) and 4 in the second ANOVA (ring, middle, index and thumb fingers). We included in this last analysis only participants who showed a significant level of adaptation (13 subjects out of 25), i.e. showing a significant decrease of tactile RS gain (independent-samples t-test comparisons between PRE and POST phases) at least for the index or the middle finger. Third, we submitted the proprioceptive assessments to a two-way repeated measures ANOVA with the within-subjects factors 'Session' (ADAPT vs CTRL) and 'Phase' (PRE vs POST).

As in Experiment 1, we also analyzed separately the latency, duration, and peak velocity, for both visual and tactile saccades in adapted participants only (see supplemental material for the results of this analysis).
494

# RESULTS

495

## 1. The adaptation of tactile RS

496 As in Experiment 1, we present below examples of gain values for individual saccades performed toward the index and the middle fingers in the PRE- and POST-exposure phases (tactile and visual saccades), as well as during the Exposure phase (tactile saccades), plotted in Figure 6.

499 a. Gain Slope during exposure phase
500 The gain change during the Exposure phase of the ADAPT session can be seen in supplemental figure 2 for all significantly adapted participants (see Methods). The mean slopes of gain change during the exposure phase are illustrated in Figure 7A. The repeated measures ANOVA revealed a significant main effect of the factor Session (F(1, 24) = 4.971, p = 0.035) (ADAPT = -0.000942 ± 0.001145, CTRL = -0.000154 ± 0.001196). No other significant main effect or interaction was found (all F ≤ 0.772, all p ≥ 0.388). These results suggest that the target double step paradigm was successful in reducing the size of tactile saccades similarly for both adapted locations and that this decrease was significantly larger than in the CTRL (no-step) paradigm.

508 b. Gain change ratio between PRE and POST phases
509 The results of this analysis, illustrated in Figure 7B, revealed that the gain change ratios of tactile RS performed toward the two trained targets (index and middle fingers) were larger in the ADAPT session than in the CTRL session. Indeed, the two-way repeated measures ANOVA showed a significant main effect of the factor Session (F(1,24) = 10.614, p-value = 0.003) (mean gain change ratio ± standard deviation: ADAPT = 0.0877 ± 0.1594, CTRL = -0.0272 ± 0.2102). No further main effects or interactions were found (all F ≤ 1.758, all p values ≥ 0.197). Thus, the significantly larger after-effect in the ADAPT session than in the CTRL session suggests that the double step paradigm exposure successfully induced adaptation of tactile saccades.

517 We then tested the effects of block order and of session order by adding to the previous repeated measures ANOVA the following two between-subjects factors: 'Block order' (Tact-Vis-Vis-Tact vs Vis-Tact-Tact-Vis) and 'First session' (ADAPT vs CTRL). This analysis showed neither main effect of these two additional factors, nor significant interactions between them or with the other factors (Session and Target) (all F ≤ 3.163, all p values ≥ 0.09). These results show that the blocks order did not affect our previous conclusion.

523 2. Transfer analysis.
524 As in Experiment 1, this analysis includes only the 13 participants who were significantly adapted in the ADAPT session for at least one of the two 'adapted' fingers (middle and/or index finger) (see Methods).
525 The 2-way repeated measures ANOVA performed on the gain change ratio of tactile non-adapted RS showed significant main effect of the factor Session (F(1, 12) = 8.198, p-value = 0.014) as well as a significant Session × Target location interaction (F(1, 12) = 6.127, p-value = 0.029). Post hoc pairwise Bonferroni comparisons performed to assess this interaction showed significant differences between sessions for both the ring (p-value = 0.014) and thumb (p-value = 0.031) fingers (mean ± standard deviation for ring finger: ADAPT = 0.222 ± 0.202, CTRL = 0.016 ± 0.221, Thumb finger: ADAPT = 0.186 ± 0.087, CTRL = 0.106 ± 0.116). It revealed neither significant difference between Target locations in the ADAPT session (p-value = 0.473) nor in the CTRL session (p-value = 0.086). There was no significant main effect for the factor Target location (F(1, 12) = 0.436, p-value = 0.521). These results
535 (plotted in Figure 8A) suggest that the adaptation of tactile RS generalized to tactile RS toward nearby
536 non-adapted locations.

537 We then tested the potential effects of block order and session order by an ANOVA with two
538 additional between-subjects factor ‘Block order’ (Tact-Vis-Vis-Tact vs Vis-Tact-Tact-Vis) and ‘First
539 session’ (ADAPT vs CTRL). This analysis showed neither significant main effect of Block order and First
540 session, nor significant interaction between these two factors or with the other within-subjects factors
541 (all F ≤ 3.018, all p-values ≥ 0.116).”

542 The 2-way repeated measures ANOVA performed on the gain change ratio for visual non-
543 adapted RS showed a significant main effect of the factor Session (F(1, 12) = 13.462, p-value = 0.003)
544 (mean ± standard deviation: ADAPT = 0.034 ± 0.062, CTRL = -0.008 ± 0.048). No other main effects or
545 interaction were found in this ANOVA (all F ≤ 2.444, all p-values ≥ 0.113). These results (plotted in Figure
546 8B) suggest that the adaptation of tactile RS transferred to visual RS performed toward all tested
547 locations.

548 We also tested the potential effects of block order and session order by a similar ANOVA with
549 two additional between-subjects factor ‘Block order’ (Tact-Vis-Vis-Tact vs Vis-Tact-Tact-Vis) and ‘First
550 session’ (ADAPT vs CTRL). This analysis showed neither significant main effect of Block order and First
551 session, nor significant interaction between these two factors or with the other within-subjects factors
552 (all F ≤ 1.606, all p-values ≥ 0.237).

553 In summary, the current analysis indicates that the gain of tactile RS to non-adapted targets
554 (ring and thumb fingers) as well as the gain of all non-adapted visual RS decrease specifically in the
555 ADAPT session, therefore showing that tactile RS adaptation generalized to nearby locations and
556 transferred to visual RS.

### 3. Proprioceptive drift

558 As shown in Figure 9, participants underestimated the location of their unseen middle finger location.
559 This proprioceptive drift increases with time from PRE to POST phase (Figure 9B), but importantly, it did
560 so similarly in both the ADAPT and the CTRL sessions (Figure 9A). Indeed, the repeated measure ANOVA
561 indicates a significant main effect of the factor Phase (F(1, 24) = 18.59, p < 0.001) (mean estimations (in
562 degree) ± s.d.: PRE = 9.49 ± 3.1, POST = 7.9 ± 3.9), but no significant main effect of the factor Session,
563 and no significant Session × Phase interaction (all F ≤ 1.453, all p ≥ 0.240). Therefore, the decrease of
564 saccadic gain observed for tactile RS in the ADAPT session (see previous sections) appears unrelated to
565 the proprioceptive drift.

## DISCUSSION

566 In this study, we sought to determine whether RS adaptation operates at the motor level, i.e., modifying
567 the saccadic command. To test this hypothesis we adapted, separately, reactive visual or tactile
568 saccades and we investigated the transfer of adaptation to the non-adapted modality, the reasoning
569 being that if motor, then saccadic adaptation should also transfer to saccades triggered by other sensory
570 modalities. We found in Experiment 1 that adaptation of reactive visual saccades strongly transferred to
571 tactile saccades and we reported for the first time in Experiment 2, experimental support for the
572 existence of adaptation of tactile saccades, although this adaptation transferred to visual saccades only
573 slightly. In the following sections, we discuss the results obtained in this study in respect to the existing
574 literature on saccadic adaptation.
Within the visual modality, saccadic adaptation has been shown to transfer to non-adapted saccades according to a spatial gradient known as the adaptation field (13, 27). This means that adaptation of a given saccade fully transfers to all saccades with the same vector, i.e., direction and amplitude, irrespective of their initial/final position and that, conversely, the rate of transfer progressively decreases as the amplitude and/or the direction of the tested saccades deviates from the adapted vector. When the deviation of direction between the two saccade vectors reaches 90° no transfer of adaptation is observed at all, but with a deviation of 45° a transfer of about 50% occurs, reflecting a large adaptation field. The visual adaptation field is also quite extended along the saccade amplitude dimension and is asymmetric (33), with a higher rate of adaptation transfer to saccades larger than the adapted saccade compared to smaller-sized saccades.
Here, while we replicate the adaptation field finding (Experiment 1) for the visual modality, we reveal for the first time (Experiment 2) the existence of adaptation for tactile saccades (discussed below). In addition, we further disclose that tactile saccades adaptation also displays an adaptation field. Indeed, after the adaptation of tactile saccades toward the middle and the index finger a generalization of adaptation has been shown to non-adapted tactile saccades toward the ring and the thumb fingers. Moreover, the high amount of adaptation spatial generalization seen for both sensory modalities in the present experiments fits with the existence of wide adaptation fields and can further be attributed to the simultaneous training of two slightly different saccade vectors (to the middle and the index finger). Importantly, this spatial generalization further argues that the decrease in tactile saccades gain during the exposure phase of the adaptation session in Experiment 2 is not related to a strategy followed by participants to saccade directly toward the second tactile stimulation but rather to a plastic gain reduction resulting from backward adaptation mechanisms. This interpretation is also compatible with the significant after-effect on the saccade gain observed in the POST-exposure phase in comparison to the PRE-exposure phase.

The transfer of visual saccades adaptation to saccades in a different modality has been reported so far for auditory saccades only, as indicated in the introduction (27, 28). With Experiment 1, we were able to show that an adaptation transfer exists also from visual to tactile saccades. These cross-modal, visual-to-auditory, and visual-to-tactile, transfers of adaptation argue for a motor functional locus of RS backward adaptation common for saccades in all modalities and possibly situated at the cerebello-brainstem level. Furthermore, this hypothesis would also predict a significant cross-modal transfer of adaptation in the reverse direction, i.e., from tactile saccades to visual saccades. Indeed, Experiment 2 provided evidence for the existence of such transfer, which however, turned out to be much smaller than the visual-to-tactile transfer of adaptation. Note that the mere presence of some transfer provides another piece of evidence for our interpretation that adaptive processes largely dominated potential strategies in the decrease of tactile saccade gain observed during exposure. This strong asymmetry of adaptation transfers between visual-to-tactile versus tactile-to-visual suggests multiple adaptation functional loci for tactile saccades, with at least one located upstream from the adaptation locus of visual saccades and from of the oculomotor commands common to all saccade's modalities.

Vision is known to be the dominant sensory modality that we rely on to localize in our environment the targets of our motor responses, including saccades (4, 8). When auditory and visual or tactile and visual targets are presented simultaneously at relatively close locations, the perception of auditory and tactile targets is biased toward the visual ones if the latter provides clear information about its location, a phenomenon known as the ventriloquist effect (34). Furthermore, the dominance of vision and its important role in shaping the perception from other senses can be seen in the deficits in
auditory localization in children with visual impairment compared to normal-sighted children (35). The separation of functional adaptation loci that we suggest based on the asymmetrical cross-modal transfer can be also thought as a higher weight given by the adaptation processes to visual information in comparison to other sensory modalities, leading to a generalization of saccadic adaptation induced by a visual error to saccades performed toward tactile or auditory targets but only partially in the other way around. According to this hypothesis, the adaptation of auditory saccades, if possible, should also transfer asymmetrically to visual saccades. Further studies will test this prediction and should first determine whether auditory saccades can be adapted at all.

The second main finding of our study is that RS toward tactile targets can be adapted, even though its prevalence appears reduced as compared to visual RS adaptation (several individual participants failed to demonstrate a significant after-effect). To our knowledge, this is the first demonstration that the gain of non-visual saccades can be reduced with a modified version of the double step target paradigm. Tactile saccades (like other non-visual saccades) differ from visual saccades by their longer latency, their reduced speed and, critically in the context of saccade adaptation, their gain is much more variable and lower on average. Also, the modified double step paradigm used here to adapt tactile saccades may differ from the double step paradigm originally designed to adapt visual saccades by the way that the change of stimulated finger during the ongoing saccade is interpreted by participants' central nervous system. In particular, since this double tactile stimulation was consciously detected by all except one participant (as confirmed by report at debriefing), as opposed to the intra-saccadic target step of the visual saccade adaptation procedure, which is frequently masked by saccadic suppression, one may wonder whether it can truly yield an adequate error signal for adaptation mechanisms. These peculiarities lead us to consider whether the decrease in tactile saccades gain seen in the adaptation exposure of Experiment 2 is related to genuine adaptation mechanisms and to discuss potential alternative explanations. The first alternative cause is strategy, that our participants could have used during exposure as they consciously detected the change in location of tactile stimulation during their saccades. However, the gain of tactile saccades 1) progressively decreased (see supplemental figures) during the adaptation exposure phase and 2) remained low in the post-exposure phase (after-effect) despite the fact that the tactile target no longer 'jumped'. These observations differ i) from the sudden drop of saccade gain which can be expected at the beginning of the exposure phase if participants only used a conscious strategy, and ii) from the immediate recovery of saccade gain which can be expected at the beginning of the post-exposure phase when target no longer jumps, and the potentially associated strategy, are discontinued. As explained in the method sections the order of the visual and tactile saccades block was counterbalanced between participants. Therefore, in experiment 2 half of our participants performed the visual POST-exposure block directly after the exposure phase and only then, the tactile POST-exposure block, making highly unlikely the possibility that they maintained a strategy across a complete block of visual saccades. In addition, if such strategy was used by the remaining participants who performed the tactile POST-exposure block immediately after exposure, we should have seen an effect of 'block order' when tested as a between subjects factor in the ANOVA of gain change ratio, which was not the case. In previous saccadic adaptation studies, including when the intra-saccadic visual target step is consciously detected (36-38), both the slow gain change during exposure and the post-exposure after-effect are considered as hallmarks of true (or implicit) adaptation. Furthermore, a recent study by Heins and Lappe (38) showed that saccadic adaptation takes place even when the error was attributed to external sources i.e. to error in machine decoding. In their experiment, participants were presented with a fixation point around which multiple objects were placed in a
circular array. They were instructed to choose a certain object while fixating and then to communicate this object to the computer by performing a saccade toward it once the fixation point disappeared. At the end of the saccade, a feedback about the decoded chosen target was presented to the participants. Participants were warned that some bias could be erroneously added to the saccade endpoint information used to decode which target they chose, and that in such case they have to take into account these mistakes to keep trying enabling the machine to correctly decode the chosen targets. The results of this experiment show that changes in saccades trajectory occurred progressively during exposure and were preserved in post exposure indicating a genuine adaptive learning even though participants applied some strategies in order to reach a better machine decoding performance. In addition, another study performed by the same team (37) showed that backward saccadic adaptation occurs when participants were aware of the intrasaccadic step irrespective of whether they were told to follow the target step at the end of the primary saccade, or to ignore this second step and maintain fixation on the first target location. Also, in the tactile modality, it is well-established that healthy people make frequent errors in determining the identity of touched fingers (39, 40). Therefore, in Experiment 2 even if participants can clearly feel that 2 fingers were touched, it cannot be taken for granted that they know which ones, nor which exactly was the last one, therefore making the use of a strategy less likely. Despite all these considerations, and according to a reviewer's suggestion, the hypothesis that changes in tactile saccade gain in Experiment 2 are due to strategic responses of participants to the double-finger stimulation during exposure cannot be ruled out in full. For this, further experiments will be necessary, for example by testing whether these changes of tactile saccade gain do transfer to other spatial locations/body parts.

The second alternative is fatigue, which would also account for the decrease of the amplitude of the tactile saccades in Experiment 1. Yet, our control sessions of both Experiments 1 and 2 argue against this possibility. Indeed, we have seen no significant changes in tactile or visual saccades gain either during the exposure phase or between the PRE- and the POST-exposure phases of the control sessions. Thus, the gain changes observed during the exposure of adaptation sessions were specific, ruling out any explanation based on fatigue.

A third alternative explanation of the tactile saccades gain decrease seen in the adaptation sessions of this study is the proprioceptive drift. In the dark, the perception of our hands placed in an eccentric position tends to drift toward our midline progressively over time, as shown by Wann and Ibrahim (30) and we still don't know why it occurs. In this study we showed that our participants' perception of their right hand's middle finger did drift toward their midline, with a higher drift rate reached in the POST- vs PRE- proprioceptive assessment blocks. Importantly however, this drift did not differ between the adaptation and the control sessions, which provided evidence that the proprioceptive drift was not responsible for the decrease in tactile saccades gain seen both in Experiment 1 and in Experiment 2.

Thus, altogether and in addition to the partial tactile-to-visual transfer demonstrated, these observations led us to propose that saccades toward tactile targets can both be modified via transfer of visual saccade adaptation (Experiment 1) and can themselves be directly adapted (Experiment 2).

An interesting issue raised by the present findings concerns the nature of error signals driving saccadic adaptation. Four main candidates have been considered in the literature: corrective saccades, post-saccadic retinal error, prediction error and postdiction error. Although corrective saccades and post-saccadic retinal error are the simplest motor or sensory signals the brain can use to monitor the accuracy of primary saccades, experimental evidence soon argued in favor of the prediction error (18,
41-43). This prediction error hypothesis (44, 45) states that the error signal is the result of a comparison between the predicted error (target location relative to the saccade landing position predicted from the efference copy) and the actual error (post-saccadic target retinal image relative to the fovea). In their recent modeling study, Masselink and Lappe (46) proposed the postdictive error hypothesis, according to which error signals diving saccadic adaptation mechanisms result from a comparison between the motor command of the saccade and the post-saccadic visual error postdicted back to pre-saccadic space based on the efferent copy. Note that in all these four different accounts, saccadic adaptation always relies on visual information of post-saccadic target location either directly (post-saccadic retinal error hypothesis) or indirectly through the generation of a corrective saccade, or through the computation of the prediction error or of the postdiction error. In sharp contrast, the present Experiment 2 suggests that saccades toward tactile targets, thus executed in absence of any visual feedback, could still be adapted. Therefore, our study highlights that the saccadic error feedback involved in saccadic adaptation is not necessarily visual but can be extracted from tactile information about the target location on the body. Further studies are required to determine how this non-visual information is transformed from its native anatomical frame of reference into an eye-centered frame of reference suitable for the saccadic adaptation mechanisms.

In conclusion, we showed that the adaptation of visual RS transfers strongly to tactile RS, in favor of a motor functional locus of RS adaptation. We also revealed for the first-time evidence for a possible induction of backward adaptation of tactile RS via a tactile double step target paradigm and that this adaptation transfers very partially to visual RS, suggesting that an adaptation locus specific of tactile RS is upstream the locus of visual RS adaptation.

## DATA AVAILABILITY

Source data for this study are openly available at
https://osf.io/ehjd2/?view_only=8fe4eda5446847be84ee6dc0968cd057

## SUPPLEMENTAL MATERIAL

Supplementary analysis can be found at
https://osf.io/ehjd2/?view_only=8fe4eda5446847be84ee6dc0968cd057

## ACKNOWLEDGMENTS

We are grateful to Sonia Alouche, Jean-Louis Borach, and Frederic Volland from IMPACT team at Lyon Neuroscience Research Center for their administrative and technical help during this study. We are also grateful to the constructive remarks and suggestions provided by all the reviewers.

## GRANTS

This study was supported by the ANR grant DEC-SPACE (ANR-21-CE28-0001) to A.F. and has been performed within the framework of the LABEX CORTEX (ANR-11-LABX-0042).

## DISCLOSURES

The authors declare that they have no competing interests.
744 AUTHOR CONTRIBUTIONS

745 Conception and design of the study: A.B., V.G., M.T.N.P., A.F., and D.P; Setup preparation and Software:
746 A.B., V.G., E.K., and R.S.; Data collection: A.B. and V.G.; Data analysis: A.B.; Data interpretation: A.B., A.F.
747 and D.P; Original draft: A.B.; Critical revisions: A.F. and D.P; All the authors approved the final
748 manuscript for submission.

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856

FIGURE LEGENDS

857 Figure 1: Experiment 1 setup and procedure. (A) A vertical board was placed in the frontal plane at 30 cm from the participants' eyes. The right hand was immobilized in a supine position on the board through rings located on the 5 fingers. The rings, separated from each other by five degrees, contained a red LED that served as visual target, and a pair of electrodes placed on each finger allowed to generate an electrocutaneous stimulation which served as tactile target. Another red LED serving as fixation point was placed on the board five degrees to the left of the participant's midline. At the top of the board, a ruler was made visible to participants during the proprioceptive location assessment. At any other time, the environment was completely dark and invisible (except a single lit LED in visual saccade trials), as the whole set-up was painted black, the participants' hand was covered by a black tissue glove and when lit, the LEDs' intensity was low. (B) Participants gazed at the FP which disappeared simultaneously with the presentation of a peripheral stimulus on one of their fingers in the visual or tactile modality, according to counterbalanced blocks of trials; once the saccade onset detected, the stimulus either stepped backward in the exposure phase of the ADAPT session (I), remained stationary until the end of the trial in the exposure phase of the CTRL session (II), or turned off in the PRE- and POST-exposure phases (III).
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871 Figure 2: Experiment 1 individual data (participant 15, ADAPTATION session): the gain of tactile (blue) and visual (orange) saccades toward the middle and the index fingers in the PRE- and the POST-exposure phases (black lines represent the mean gain value) as well as the variation of gain across trials in the Exposure phase (slope value and statistical significance of the linear regression are presented in the central panel).
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876 Figure 3: Experiment 1 adaptation results (all participants). Panel A: mean saccadic gain change in the exposure phase (slope of the linear regression between saccadic gain and trial number) in the ADAPTATION and CONTROL sessions. Panel B: mean saccadic gain change ratio between the PRE- and the POST-exposure phases in the ADAPTATION and CONTROL sessions. In both graphs, only visual saccades toward the index and the middle fingers were considered. Error bars represent standard deviations. ***: t-tests (p < .001).
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882 Figure 4: Experiment 1 generalization and transfer results (only adapted participants). Mean saccadic gain change ratio in the ADAPTATION and the CONTROL sessions, plotted as a function of the target location separately for visual (Panel A) and tactile (Panel B) saccades, as well as the grand mean (MEAN)
883
884
885 of gain change ratio across all locations plotted in each panel. Only non-adapted locations are plotted in
886 this figure. Error bars represent standard deviations. *** : t-test (p < .001).

887 Figure 5: Experiment 1 proprioceptive drift results (all participants). Mean estimated position of the
888 middle finger location in the PRE- and POST- proprioceptive location assessment phases of the
889 ADAPTATION and CONTROL sessions are plotted separately (Panel A) and as a grand mean pooled over
890 both sessions (Panel B). The dotted line represents the actual middle finger location. Error bars
891 represent the standard deviation. ns : t-test (p > .05), *** : t-test (p < .001).

892 Figure 6: Experiment 2 individual data (participant 16, ADAPTATION session): the gain of tactile (blue)
893 and visual (orange) saccades toward the middle and the index fingers in the PRE- and the POST-exposure
894 phases (black lines represent the mean gain value) as well as the variation of gain across trials in the
895 Exposure phase (slope value and statistical significance of the linear regression are presented in the
896 central panel).

897 Figure 7: Experiment 2 adaptation results (all participants). Panel A: mean saccadic gain change in the
898 exposure phase (slope of the linear regression between saccadic gain and trial number) in the
899 ADAPTATION and CONTROL sessions. Panel B: mean saccadic gain change ratio between the PRE- and
900 the POST-exposure phases in the ADAPTATION and CONTROL sessions. In both graphs only tactile
901 saccades toward the index and the middle fingers were considered. Error bars represent standard
deviations. * : t-test (p < .05), ** : t-test (p < .01). 902

903 Figure 8: Experiment 2 generalization and transfer results (only adapted participants). Mean saccadic
904 gain change ratio in the ADAPTATION and the CONTROL sessions, plotted as a function of the target
905 location separately for tactile (Panel A) and visual (Panel B) saccades, as well as the grand mean (MEAN)
906 of gain change ratio across all locations for visual saccades. Only non-adapted locations are plotted in
907 this figure. Error bars represent standard deviations. t-tests : * (p < .05), ** (p < .01).

908 Figure 9: Experiment 2 proprioceptive drift results (all participants). Mean estimated position of the
909 middle finger location in the PRE- and POST- proprioceptive location assessment phases of the
910 ADAPTATION and CONTROL sessions are plotted separately (Panel A) and as a grand mean pooled over both
911 sessions (Panel B). The dotted line represents the actual middle finger location. Error bars represent
912 the standard deviation. ns : t-test (p > .05), *** : t-test (p < .001).
A

<figure><img src="image_1.png" /></figure>

B

<figure><img src="image_2.png" /></figure>

<figure><img src="image_3.png" /></figure>

I. Exposure\ADAPTATION

<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /></figure>

III. PRE- and POST-exposure

II. Exposure\CONTROL

<figure><img src="image_6.png" /></figure>
Saccadic gain (Participant 15, Experiment 1)

<figure><img src="image_7.png" /></figure>

slope = -0.0009
p-value < 0.001
Visual saccades (N=15)

<figure><img src="image_8.png" /></figure>

<figure><img src="image_9.png" /></figure>
Gain change ratio (N=14 adapted participants)

A. Visual saccades

<figure><img src="image_10.png" /></figure>

B. Tactile saccades

<figure><img src="image_11.png" /></figure>
Proprioceptive drift

A. Middle finger estimated position across sessions and phases (N=15)

<figure><img src="image_12.png" /></figure>

B. Middle finger estimated position across phases (N=21)

<figure><img src="image_13.png" /></figure>
Saccadic gain (Participant 16, Experiment 2)

<figure><img src="image_14.png" /></figure>

slope = -0.0013
p-value < 0.001
Tactile saccades (N=25)

A. Gain change in
the Exposure phase

<figure><img src="image_15.png" /></figure>

B. Pre- vs Post- exposure
gain change

<figure><img src="image_16.png" /></figure>
Gain change ratio (N=13 adapted participants)

<figure><img src="image_17.png" /></figure>

<figure><img src="image_18.png" /></figure>
Proprioceptive drift (N=25)

A. Middle finger estimated position across sessions and phases

<figure><img src="image_19.png" /></figure>

B. Middle finger estimated position across phases

<figure><img src="image_20.png" /></figure>
# Saccades to both vision and touch are modified following adaptation but cross-modal transfers are asymmetrical.

## METHODS

<figure><img src="image_21.png" /></figure>

## OUTCOME

<figure><img src="image_22.png" /></figure>

$$ \text{Gain change ratio} = \frac{(\text{Gain PRE} - \text{Gain POST})}{\text{Gain PRE}} $$

## CONCLUSION

* Visual saccade adaptation transfers to tactile saccades.

* Tactile saccades show adaptive changes using the double-step target paradigm.

* Tactile saccade adaptation: 1. generalizes to nearby non-adapted locations, 2. transfers partly to visual saccades.