The Effect of Simulating Climbing Movements on Rock Memory and Exploratory Movement in Rock Climbing

Abstract

Simulating climbing movements on a given route is important for fluent rock climbing. We investigated the effect of simulated action during rock climbing route finding on memory and exploratory movement. Participants were 12 climbers and 12 non-climbers who completed three experimental tasks: (a) a questionnaire, the Vividness of Movement Imagery Questionnaire-2 (VMIQ-2) for measuring vividness of motor imagery, (b) a memory task requiring recognition of rock climbing holds on the route, and (c) a traversing task requiring participants to climb a given route and count the number of exploratory movements made during climbing. During route finding in the memory/traversing task, we experimentally manipulated the simulative body action with motor imagery. Results showed that the simulative action affected exploratory movement during climbing, but it did not affect memorization of the holds. In the traversing task, climbers showed more exploratory movement when the simulative action was present during route finding, while the non-climbers showed an opposite trend. Moreover, for non-climbers, the effect of the simulative action was modulated by the vividness of kinesthetic imagery. We concluded that simulative body action during route finding facilitated motor imagery and spatial information processing for subsequent climbing involving exploratory movement.

Keywords

rock climbing exploratory action chunking motor imagery gestures

Introduction

Free climbing is a type of rock climbing that requires climbing without artificial tools. In free climbing, before an actual climbing, a climber first observes a climbing route and makes a plan of action to avoid falling. This pre-climbing observation process is called “route finding” (Boschker et al., 2002; Cordier et al., 1994). Route finding simulates how to move with given climbing holds, which are grips and stances for supporting one’s own body weight. During route finding, a climber simulates a series of movements based on their own motor competency (Pezzulo et al., 2010; Sugi & Ishihara, 2019) and anticipated limb movements. Because climbing holds along a climbing route have various shapes and alignments, the climber must properly simulate how to grasp or stand on an individual hold and then move the whole body with the holds. Most experienced climbers intuitively recognize the importance of route finding for fluent climbing, with no pauses and no awkward movements. In accordance with this view, Sanchez et al. (2012) found that when climbers climbed a given route without preliminary route finding, the climbing time and number of stops increased, compared to when they engaged in route finding before climbing. Thus, route finding and simulating body actions on a given route can affect later climbing performance.

In addition to the practical benefit of route finding, this process contains various psychological processes, such as eye-movements (Seifert et al., 2017), visual information processing (Sugi & Ishihara, 2019), cognitive resources (Green & Helton, 2011), memory (Boschker et al., 2002), and decision making (Whitaker et al., 2019). These studies highlighted the differences in route finding and climbing between novices (including non-climbers) and expert climbers. Specifically, a climber watches and memorizes a given route, using their cognitive resources for creating a motor plan of reasonable movement based on his/her motor competency. The simulative body actions during route finding seem to occur automatically, especially before the first attempt. Although most climbers engage in this simulative action during route finding and some studies have pointed out the effects that body action has for spatial memory (Morimoto, 2016), motor imagery (Guillot et al., 2013), and cognitive processing (Goldin-Meadow et al., 2001), the role of simulated body movement during route finding has not been fully explored in rock climbing research.

Sugi and Ishihara (2019) investigated the effect of simulative action during route finding on the climber’s memory of the route’s features (i.e., recognition of given holds). In their study, participants engaged in route finding for two types of routes – a possible route (5+ in French grading) or an impossible route (motorically impossible) with or without simulative actions during route finding. The routes consisted of twelve holds on a climbing wall (3.8 m high, 2.6 m wide). After their route finding, participants completed a distraction task (subtracting numbers for 20 seconds) and were then asked to recognize the given holds. Their hold recognition was higher for the possible route than for the impossible route, regardless of the presence of simulative actions (Sugi & Ishihara, 2019). This study suggested that recalling a given route was more affected by the feasibility of the route than the presence of simulative actions during route finding. Although Sugi and Ishihara (2019) measured the participants’ recognition of holds, the effect of simulative action during route finding on the performance of actual climbing remains unclear.

For appropriate route finding, climbers should develop accurate motor imagery that reinforces an actual physical performance (Landers, 1983). Recent studies suggested that motor imagery with physical movement (dynamic motor imagery or dMI) better facilitated actual motor performance than static motor imagery, because of the added temporal and spatial congruency of motor imagery with physical movement and actual performance (Guillot et al., 2013). Route finding with simulative body actions shares features of dMI such that the same facilitation should be observed from simulated actions in climbing as have been observed in dMI research for other motor movements.

Route finding also requires processing spatial information and recalling route content information for later climbing. This process depends on the individual’s cognitive resources (Green & Helton, 2011). In terms of the relationship between physical movement and cognitive load, simulative actions as gestures can reduce cognitive load and assist exploring spatio-motoric information, because body expression supports recall of this information and activating spatio-motoric representations (Kita et al., 2017; Pyers et al., 2021). Thus, the simulative action during route finding should facilitate information processing and change climbers’ exploratory movements during climbing.

In the present study, we focused on body action during route finding to understand the relationship between specific route finding methods and climbing performance. To investigate the relationship between the simulative action during route finding and the movement during climbing, we focused on exploratory movement. Exploratory movement in climbing is defined as changing the hand position on a hold until a climber moves to the next hold (Pijpers et al., 2005). Exploratory movement is an apt performance reflection of route finding. For example, when climbers climb a given route without route finding, they must touch the hold and search the surface of it to locate the most suitable hand position during climbing, because they have no preliminary information about the route and hold (Sanchez et al., 2012). On the other hand, an appropriate simulation during route finding should lead to fewer exploratory movements, due to congruency between simulation and actual climbing. In addition to this, we also measured the vividness of motor imagery as a baseline to explore the influence of the ability of motor imagery.

In the current study, participants were asked to perform both a memory task and a traversing task. To prevent any confounding influences on the usual climbing procedure (from route finding to climbing) due to our measurements of memory performance and exploratory movement, the memory task and the traversing task were independently performed in the experiment. In the memory task, we measured memory performance by assessing whether the recollection of a given route was accurate to see whether our previous findings (Sugi & Ishihara, 2019) can be replicated under a condition in which the route was aligned horizontally (i.e., traversing). In the traversing task, we measured the number of touches (i.e., exploratory movements) to investigate whether the simulative action during the route finding phase affected the performance of the later climbing movements.

We hypothesized that the memory performance of a given route would be mediated by the participants’ motor competencies. That is, we expected a possible climbing route for each participant to be better memorized than a motorically impossible climbing route, due to the motor chunks of possible action sequences. If simulative action during route finding facilitates spatial/kinesthetic memorization, memory scores should be improved when the simulative action is performed. For the traversing task, we predicted less exploratory movement after the participants engaged in a simulative action, because the simulative action during route finding should help create motor imagery and facilitate spatial information processing that requires better preparation for subsequent climbing. If this prediction was correct, regardless of the participant’s motor imagery ability, the simulative action should decrease exploratory movements.

Method

Participants

Twelve non-climbers (4 females; two left-handed; M age = 23.83, SD = 2.97 years) and thirteen climbers (excluding one participant due to machine trouble; two females; one left-handed; M age = 22.83, SD = 0.99 years; M climbing experience = 17.8, SD = 10.9 months) voluntarily participated in this experiment. They were recruited from Tokyo Metropolitan University and the mountaineering club at the university. Participants were naive to purpose of the study, and they reported having normal or corrected-to-normal vision. The experiment was approved by the local university ethics committee; all participants provided informed consent.

Apparatus

The climbing wall was 1.8 m high and 3.6 m wide, and it was tilted at 88° backward to a concrete wall¹ (see Figure 1). The wall included 242 holds of different sizes, orientations, and colors. The experimental area was surrounded by a black curtain and a concrete wall. The participants were videotaped during the traversing task, with video data recorded by two cameras (Panasonic, HC-V230M; GoPro, Hero6). The analysis for the video data was conducted with free software (Kinovea Ver.0.8.26, https://www.kinovea.org/), which allows easy analysis for counting the number of participant touches on the wall from the frame by frame video.

Tasks and Procedures

This experiment consisted of three tasks: completing a questionnaire, taking a memory test, and completing a traversing task. The order of these three tasks was counterbalanced across the participants. After finishing the three tasks, the participants responded to another questionnaire regarding their climbing experience and the experimental task (Table 1).

Table 1.

Items of the Post-Task Questionnaire Regarding the Experimental Task.

Memory Task	Traversing Task
I could imagine a movement during route finding	I could imagine a movement during route finding
I felt it would be easier to imagine a movement when there was a simulative action during route finding	I felt it would be easier to imagine a movement when there was a simulative action during route finding
There was a route which was impossible to imagine a movement	I could climb a given route with a movement as I imagined
	I could grasp a hold with the most suitable way for a movement

Ratings were on a scale from 1 (not at all) to 11 (completely agree).

Questionnaire

For this task, participants were asked to complete the Vividness of Movement Imagery Questionnaire-2 (VMIQ-2; Roberts et al., 2008), which was translated into Japanese by the first author.² This questionnaire asks respondents about the vividness of three types of mental representations: Internal Visual Imagery (first-person perspective; IVI), External Visual Imagery (third-person perspective; EVI), and Kinesthetic Imagery (KI). The participants then rated the vividness of their own mental imagery (with regard to IVI, EVI, and KI) for twelve movements (e.g., walking, picking up a coin) by assigning rating numbers from 1 (“Perfectly clear and as vivid as normal vision or feel of movementˮ) to 5 (“No image at all, you only “knowˮ that you are thinking of the skillˮ). The vividness of each type of motor imagery was determined by summing the scores (12–60). Low VMIQ-2 scores indicate greater vividness of one’s motor imagery. The participants answered this questionnaire sitting on a chair with their eyes closed.

Memory

For this task, participants were asked to watch a given route and recall it later. To test whether the climbability of the route affected its memorization (Sugi & Ishihara, 2019), we gave participants two types of routes: a possible and an impossible route. For the possible route, twelve holds were set as suitable and reasonable for climbing (with a climbing difficulty of 3+ according to French grading). For the impossible route, twelve holds were set unreasonably, making them impossible for climbing. We set three routes for each route type and randomized the order of their presentation.

Before the memory task, participants were instructed to watch the given route assuming they would climb it after the route finding. The participants stood 1.5 m away from the wall and conducted the memory task in two experimental conditions – one in which they acted and one in which they did not act. In the act condition, the participants were asked to move their limbs according to the action that they imagined during route finding. In the non-act condition, they were asked to just stand and watch the given route without making any physical movements. The experimenter indicated the routes with a laser pointer from the start hold to the goal hold: Each hold was pointed to for around two seconds, and the pointer was then moved onto the next hold for approximately one second. The presentation of the route was repeated twice for each route. The total time for route finding was about 70 seconds for each route.

After route finding, the participants completed a distraction task. The participants were asked to turn their back against the wall and subtract 3 from 99 for 20 seconds. This distraction task was intended to preclude the participants from using short-term memory to recall the given holds, seeking, instead, their reliance on memory “motor chunks,” which are units that connect a series of actions and a given object (Pezzulo et al., 2010). This distraction task thus allowed us to see the characteristics of memory chunk performance (vs. short-term memory) for a feasible action sequence. After finishing the distraction task, participants turned to the wall and pointed to the hold that they memorized with the laser pointer. Memory performance was defined by the rate of correct answers. The mean correct rate in each condition and each participant was transformed by arcsin for analysis.

Traversing

In the traversing task, participants were asked to traverse two given routes (from the left side to the right side of the wall, and vice versa). The difficulty of the routes was easy enough (3+ in French grading) that non-climbers could perform it successfully. The routes included seven holds, and the holds required participants to explore their way by some grasping to keep their balance during moving.

The participants observed the given route under both an “act” and a “non-act” condition, as well as in the memory task. To compare the number of touches on a hold within the same climbing movement, the participants were instructed which hold they should grip with their left or right hand. This specifying instruction made participants focus on the exploratory action in the same way as they would during climbing. The holds used in each route were also indicated with red tape so that participants would not forget which hold was to be gripped during traversing. The reason for designating the holds with red tape was to rule out an extra touching of a hold derived from mistaken sequences due to memory issues. In the act condition, participants were asked to move their own body according to their imagery of climbing the wall during route finding. In the non-act condition, the participants were asked to just watch the climbing wall without any of their own body movements during route finding. The total time for route finding was around 35 seconds on each route in both conditions. Before each attempt, the participants engaged in a distraction task like the one performed in the memory task. The distraction task here was to prevent participants from observing any climbing holds and simulating any movements in their mind. After completing the route finding and the distraction task, the participants were asked to traverse the route six times. We instructed that the traversing should be done as fluently as possible, and, if the participants fell during traversing, they were to still try to avoid falling again with the same posture. The procedure was maintained until the participant completed the sixth trial. The participants received no instructions or feedback concerning how they were to grasp each hold during the task.

We analyzed the video data obtained from traversing movements and counted the number of touching incidents on each hold. Each analysis of counting on the video data was conducted twice by the first and second authors (i.e., counted four times for one video data). The counting number for each hold in each trial was averaged for each author’s counts. If the numbers counted were different by more than four between the first and the second counts by the same author, the counting was redone, and the average number of counts would then be based on the total number of times counting was necessary. Then, the summation of the number of touches in each condition was calculated by averaging the means of the total number of the countings by each author in each trial. The intraclass correlation coefficient (ICC) was 0.82.

Statistical Analysis

For VMIQ-2 scores, we calculated the descriptive values of the score for each type of imagery (IVI, EVI, and KI) and each participant using R (Ver. 3.6.1, R Core Team, 2019). We entered each VMIQ-2 score into a (generalized) linear mixed model to investigate the effect of the vividness of motor imagery on the memory scores and exploratory movement scores of the traversing task.

For the memory task, we applied a linear mixed model to test the relationship between the memory score and independent variables. We entered the participant’s Group (climbers/non-climbers), Action (act/non-act), Route (possible/impossible), and each VMIQ-2 score as fixed effects. As a random effect, we had intercepts for participants. We started to apply a full model with all effects, then evaluated the model using the lme4 (Bates et al., 2015) and the MuMin packages (Barto, 2020). We applied a model including parameters related to the independent variables and also used lme4 package for fitting and analyzing the mixed model. We then selected the model based on information criterion, AIC with Mumin package. Spearman’s correlation coefficients were calculated to assess the correlation between each VMIQ-2 score and the memory score in each condition.

For the traversing task, Spearman’s correlation coefficients between the number of touches and the trial were calculated to check a convergence of climbing movements in each condition. Then, we computed the number of exploratory movements by subtracting the number of touches in the minimum trial from those in the first trial. This number would reflect the additional touching to explore the hold’s surface for moving to the next hold. We then performed a generalized linear mixed model (GLMM) with a log-link function and gamma distribution as a link function on the exploratory movement as a dependent variable. We excluded a participant who showed the largest number of touches in the first trial because this indicated that the number of touches was not converged among trials (excluded 2.08% data). As a fixed effect, we entered Group, Action, the VMIQ-2 score. We also entered the intercepts by the participants as a random effect. Spearman’s correlation coefficients were calculated between each VMIQ-2 score and the number of exploratory movements as in the memory task. All effects were tested at a significance level (α) of 0.05 and reported with 95% confidence intervals (CI).

Results

Questionnaire Task

Table 2 shows the descriptive values of VMIQ-2 scores (Table 2). We found a significantly positive correlation between some of the types of imagery (Table 3).

Table 2.

Descriptive Value of Each Motor Imagery in the Questionnaire Task.

Experience	IVI	EVI	KI
Climber	24.83 (10.50)	28.25 (9.30)	20.00 (6.82)
Non-climber	23.25 (6.92)	25.83 (7.95)	21.75 (6.02)

IVI: Internal visual imagery; EVI: External visual imagery; KI: Kinesthetic imagery [Mean (SD)]

Table 3.

Correlations Between Imagery Scores by Participants’ Experience.

Experience	IVI-EVI	IVI-KI	EVI-KI
Climber	0.41	0.80*	0.48
Non-climber	0.57*	0.60*	0.31

IVI: Internal visual imagery; EVI: External visual imagery; KI: Kinesthetic imagery.

∗p < 0.05.

Memory Task

Figure 2 shows the score of the memory task in each condition. Mixed linear models yielded a significant main effect of Route [χ² (1) = 7.65, p < 0.01; β = 0.060, t (70) = 2.76, p < 0.01, 95% CI [0.018, 0.10]]. Both groups (climbers/non-climbers) showed a higher score in the possible routes (M = 7.26, SD = 1.72 in the climbers; M = 5.74, SD = 2.64 in the non-climbers) than those in the impossible routes (M = 6.35, SD = 1.90 in the climbers; M = 5.35, SD = 2.36 in the non-climbers). We also found a main effect of the score of IVI and KI [χ² (1) = 8.25, p < 0.01; β = −0.093, t (22) = −2.87, p < 0.01, 95% CI [−0.016, −0.030]; χ² (1) = 5.26, p < 0.05; β = −0.078, t (22) = −2.29, p < 0.05, 95% CI [−0.014, −0.012], respectively].³ The participants who showed higher scores of IVI and KI (i.e., lower vividness) also showed lower memory score, while the scores of EVI did not show a significant relationship with the memory score [χ² (1) = 2.36, p = 0.12; β = −0.055, t (22) = 1.68, p = 0.097, 95% CI [−0.13, 0.015]] (Figure 3). A main effect of Action did not reach significance [χ² (1) = 2.83, p = 0.093; β = 0.037, t (70) = −1.54, p = 0.14, 95% CI [−0.0060, 0.079]]. Spearman’s correlation rank test showed a significant negative relationship between the score of IVI and the memory test score in the non-climbers (ps < 0.05). The other two VMIQ-2 scores (EVI/KI) did not show a significant relationship with the memory score. To investigate whether a climbing skill level related to the memory score, we also calculated Spearman’s correlation coefficients between climbing skill level and the memory score for the climbers (Figure 4). There were no significant correlations in either condition (ps > 0.05).

The result of the questionnaire regarding the memory task is shown in Table 4. The non-climbers reported that they felt it difficult to engage in mental imagery [t (10) = −3.59, p < 0.01]. Both groups showed significantly higher ratings than the midpoint for the items regarding the simulative action [t (11) = 3.5, p < 0.01 for the climbers; t (11) = 2.54, p < 0.05 for the non-climbers] and the climbability of a given route [t (11) = 17.63, p < 0.01 for the climbers; t (11) = 3.52, p < 0.01 for the non-climbers].

Table 4.

Group Differences in the Questionnaire in the Memory Task.

Item	Mean (SD)		Difference to Midpoint
Item	Climber	Non-Climber	Climber	Non-Climber	Group Difference
I could imagine a movement during route finding	5.08 (1.98)	3.26 (2.32)	n.s.	*	†
I felt it would be easier to imagine a movement when there was a simulative action during route finding	6.83 (2.57)	6.26 (2.38)	*	*	n.s.
There was a route which was impossible to imagine a movement	9.33 (1.20)	7.35 (3.20)	*	*	†

†: p < 0.10, ∗: p < 0.05.

Traversing Task

Figure 5 shows a plot of the number of touches in each trial. The number of touches in both groups significantly decreased along with the trial in each condition (ps < 0.05). This trend indicated that the participants’ movement converged with a certain action and exploratory movements were decreasing along with the trial.

The generalized linear mixed model yielded a significant main effect of Action on exploratory movement [χ2 (1) = 15.43, p < 0.01; β = 0.82, t = −3.93, p < 0.01, 95% CI [0.37, 0.72]] and a significant interaction between the Experience and Action [χ2 (1) = 20.73, p < 0.01; β = 2.99, t = 4.55, p < 0.01, 95% CI [1.87, 4.80]] and Action and KI [χ2 (1) = 7.35, p < 0.01; β = 1.37, t = 2.71, p < 0.01, 95% CI [1.09, 1.73]].⁴ Among climbers, the exploratory movement was significantly higher in the act condition than in the non-act condition [χ2 (1) = 11.79, p < 0.01; β = 0.52, t = −3.44, p < 0.01, 95% CI [0.36, 0.75]]. In the non-climbers, on the other hand, the exploratory movement was significantly lower in the act condition than in the non-act condition [χ2 (1) = 11.23, p < 0.01; β = 1.54, t = 3.16, p < 0.01, 95% CI [1.18, 2.02]] (Figure 6). Moreover, among non-climbers, we observed a significant interaction between the KI score and the Action condition [χ2 (1) = 12.08, p < 0.01; β = 1.58, t = 3.48, p < 0.01, 95% CI [1.22, 2.04]]. Among non-climbers, the exploratory movement increased as KI scores were higher (reflecting lower KI vividness) in the non-act condition, while this trend disappeared in the act condition (Figure 7). Among climbers, on the other hand, the KI score was not significantly related to exploratory movement [p = 0.37]. The IVI and EVI scores were not related to exploratory movement for either climbers or non-climbers. Spearman’s correlation rank test showed that there was no significant relationship between each VMIQ-2 score and the number of exploratory movements (ps > 0.05). As in the memory task, we calculated Spearman’s correlation coefficients between climbing skill level and the number of exploratory movements (Figure 8). A generally negative trend was observed, but it did not reach significance.

The result of the questionnaire regarding the traversing task is shown in Table 5. Both groups showed significantly higher ratings than the midpoint for the items regarding the easiness of imagery due to the simulative action [t (11) = 7.97, p < 0.01 for the climbers; t (11) = 3.20, p < 0.01 for the non-climbers]. Although both groups also reported the patterning movements along with the trial [t (11) = 7.97; t (11) = 3.20, ps < 0.01, respectively], non-climbers reported significantly lower easiness ratings for items related to climbing movement (congruity with imagined action/the way of grasping hold) than climbers [t (21) = 2.43, p < 0.05; t (21) = 2.28, p < 0.05].

Table 5.

Group Difference in the Questionnaire in the Traversing Task.

Item	Mean (SD)		Difference to Mid-Point		Group Difference
Item	Climber	Non-Climber	Climber	Non-Climber	Group Difference
I could imagine a movement during route finding	6.92 (1.47)	5.91 (2.98)	*	n.s.	n.s.
I felt it would be easier to imagine a movement when there was a simulative action during route finding	7.92 (1.79)	6.96 (2.93)	*	*
I could climb a given route with a movement as I imagined	5.75 (1.87)	3.57 (2.31)	†	*	*
I could grasp a hold with the most suitable way for a movement	8.17 (1.43)	5.61 (3.27)	*	n.s.	*
A movement was patterned as climb repeatedly	8.75 (1.92)	8.3 (1.92)	*	*	n.s.

†: p < 0.10, ∗: p < 0.05.

Discussion

In the present study, we investigated the effect of simulative movement during route finding on climbers’ and non-climbers’ memorization of a given route and on their exploratory movement in climbing. We found that simulative action affected exploratory movement during climbing, but did not affect the memory of a given climbing route. Moreover, the vividness of participants’ motor imagery, especially, their kinesthetic imagery modulated the effect of simulative action for non-climbers.

Memory Task

In the memory task, both climbers and non-climbers memorized routes on the basis of a route’s climbability. This is in line with previous findings (Pezzulo et al., 2010; Sugi & Ishihara, 2019) that making chunks (i.e., a certain unit of holds for an action sequence) based on the observer’s motor competency is critical for memorizing a climbing route. Interestingly, the non-climbers who had no climbing scheme in their motor repertory (as shown in Table 4) showed better memory performance in the possible route condition than in the impossible route, just as climbers did. An action possibility of basic action (e.g., reaching, stepping) can be judged accurately based on the actor’s action capability (e.g., Fajen et al., 2008) unless they are in an unstable situation (Hajnal et al., 2016). The non-climbers might judge their possibility of imagined motor climbing movement in a way that is similar to their daily actions (e.g., walking, grasping). That is, a climbing action can be interpreted as an extension of daily actions. Most climbing movements consist of actions to move your own body and to keep your posture on a wall by grasping or standing on a hold. In terms of keeping your own body in balance, for example, going up stairs with a supporting handrail seems quite similar to climbing actions. In our experiment, moreover, the direction of the route was horizontal rather than vertical, and did not include climbing-specific actions (e.g., dyno, heel hook). This circumstance might lead to the activation of a certain locomotive action even for the non-climbers, due to the similarity of this task to daily actions. If the non-climbers just memorized a given route spatially (e.g., position) or morphologically (e.g., color, shape), there should have been no difference between their performance on possible and impossible routes.

We observed no effect of simulative action for memorizing a route in either climbing or non-climbing groups. Despite their subjective reports (Table 4) of easiness of imagery due to simulative action, these results indicate that simulative action did not directly facilitate memorizing a given climbing route. In contrast to these results, some prior memory researchers (Morimoto, 2016; Naka & Naoi, 1995) reported an effect of visuo-motor encoding in spatial memorization. Actual body movement, encoding spatial information, giving a motor command and/or receiving perceptual feedback has separately and additively helped participants maintain spatial information (Morimoto, 2016). A possible explanation for the lack of a simulative action effect on memory in our results is the difference of a focal point between the encoding phase and the recognition phase in our study. In the encoding phase, participants might have focused on their movements in relation to the holds needed for later climbing, but in the recognition phase, participants simply designated the hold with the laser pointer (hardly activating any climbing related representations).

Considering the focal point of route finding, the simulative action effect may be reflected by memory of kinetic action; that is, participants might memorize their own body action, not just given holds. This is partially supported by our findings that simulative action affected exploratory movement in climbing because exploratory movement required participants to retain the information from imagined motor repertoires during route finding. A recognition task that asked participants to recall required movements for climbing a given route might be an efficient index for detecting the effect of simulative action. Indeed, Boschker et al. (2002) reported that expert climbers more often mentioned climbing opportunities in a given route after route finding than did inexperienced climbers. Their study supported the idea that, for later climbing, climbers more often recall motor information than positional hold information.

We also found that the participants who showed a higher vividness for the first-person perspective and for kinesthetic motor imagery scored higher score for memorization of a given route. The vividness of motor imagery reflects the reality of an image, and this imagery shares a common representation of motor execution (e.g., Jeannerod, 2001). Thus, the vividness of internal and kinesthetic motor imagery can reflect the content of motor execution. First-person perspective and kinesthetic imagery are categorized into internal imagery, and internal imagery relates to the feeling of executing an action itself (Jeannerod, 1994). A third-person perspective, on the other hand, is a visual representation of a third person and can be favored to visually represent a general outline of an action (Hardy & Callow, 1999). Our finding that internal imagery (IVI/KI) related to the memory score suggests that participants predominantly developed their first-person perspective and kinesthetic imagery during route finding. These internal imageries may also relate to forming motor chunks based on motor competency.

Traversing Task

In the traversing task, designed to investigate the effect of simulative action during route finding on exploratory movement during climbing, we found that simulative action during route finding was associated with increased exploratory movement among climbers but decreased exploratory movement among non-climbers. In terms of dynamic Motor Imagery (dMI) and/or gestures, we assumed that simulative action during route finding would facilitate motor imagery and/or spatial information processing (Guillot et al., 2013; Kita et al., 2017) and lead to a greater repertoire of possible movements in the mind for later motor execution. Motor imagery with physical movement (dMI) compensates for a lack of proprioceptive feedback in static imagery by making an actual “practice” movement, and this can lead to enhanced motor performance because of the congruity of imagery and motor performance (Holmes & Collins, 2001). This added perceptual feedback might facilitate the motor imagery and increase the number of choices of possible climbing movements for later climbing. Our results of opposite trends between our two groups, possibly reflected a difference in climbing strategies of climbers and non-climbers.

For climbers, the most suitable way to grasp a given hold contributes fluent climbing. In this experiment, moreover, because of the inclination of the wall (i.e., slab wall), participants could explore the holds without arm fatigue, minimizing the demand for less touching. Accordingly, it seemed reasonable for the climbers to try all possible ways that they imagined during route finding, even if they temporally found a way of grasping good enough to move. Thus, climbers touched a hold more often due to the simulative action because they could develop more imagery of climbing movements and could climb according to these imagined repertoires (Table 5). As a result, the climbers explored the surface of the hold more with simulative action than without it.

For non-climbers, due to a lack of knowledge about the suitable way of grasping for climbing, the fastest way to climb a given route was reasonable as fluent climbing. Thus, non-climbers might have stopped the exploration once they found a way of grasping that was good enough to move to the next hold. The simulative action facilitated the motor imagery for the non-climbers and an appropriate movement was likely included in these imageries, while the motor imagery without the simulative action might have led to poor imagery and no appropriate movement was likely included in their choices. This led to more exploration to find a way of grasping that was good enough to move during climbing. As a result, non-climbers, as opposed to climbers, showed less exploratory movement in the act condition and more exploratory movement in the non-act condition as opposed to the climbers.

Considering such an opposite trend in the act condition (though not statistically significant), in which the non-climbers with low KI (higher kinetic vividness) showed more exploratory searching, another interpretation would be possible. That is, when participants had poor imagery (high KI or in the non-act condition), they would make more searches because they knew no appropriate way to search for a given hold during climbing. On the other hand, non-climbers with rich imagery (low KI or in the act condition) would struggle to choose an appropriate grip because of too many possible choices. This would lead the least exploratory movements occurring from moderate imagery ability. Non-climbers were affected by the vividness of kinesthetic imagery in the non-act condition. Perhaps the non-climbers who showed lower KI vividness could not imagine a specific climbing movement without the benefit of simulative action. With insufficient climbing experience and difficulty visualizing a climber’s perspective, non-climbers might predominantly develop KI instead of visual imagery. However, it seemed difficult for non-climbers with lower KI to imagine a possible climbing movement through KI, making simulative action important as a compensatory mechanism (Chu & Kita, 2011).

Among climbers, exploratory movement was not affected by the vividness of any types of motor imagery. This suggests that the climbers could make motor plans regardless of their imagery ability in our easy experimental climbing route. This assumption is partially supported by our finding of no significant correlation between climbing skill level and number of exploratory movements.

Our finding of an association between simulative action and exploratory movement may have been related to gestures. Gestures can decrease the cognitive load of a given motor task because gestures facilitate retaining information about body position and movement by expressing mental content (Goldin-Meadow et al., 2001). Moreover, increasing spatial information by using gestures (i.e., perceptual-motor activation) can facilitate a participant’s mental representation of climbing and perhaps help them to find a climbing path (Alibali et al., 2011; So et al., 2014).

In our experiment, participants were required to imagine a series of movements for the later climb by first observing a given route. This task included spatial (route finding) and kinesthetic (traversing) factors, and these factors were required for motor planning and retaining route information for later climbing. Although the climbing route did not physically demand high intensity to climb, it did require a certain cognitive load for fluent climbing. Thus, by using gestures, the participants could more easily make a motor plan through simulative action.

Limitations and Directions for Further Research

In the memory task, our results replicated the previous study (Sugi & Ishihara, 2019) that a climbing route is memorized based on climbability, and that simulative movements during route finding did not affect the memory score. We also found no relationship between the climbing skill level and the memory score. Some studies (e.g., Pezzulo et al., 2010) reported differences between expert and novice climbers in a difficult route, suggesting that the memory of motor action is mediated by one’s motor competency. Since we did not experimentally manipulate the route difficulty in the present study, further study manipulating action/climbing difficulty is needed to generalize the effect of motor competency on the memory of a sequential action.

In the traversing task, we found that the simulative action affected the number of touching incidents, and this was modulated by climbing experience and by the vividness of motor imagery. In our experiment, the conditions for route finding were manipulated (act/non-act condition) to elucidate the general tendency concerning the effect of simulative action. This provides the first step in investigating a climber’s behavior in route finding. Our study, however, measured neither individual climbing strategies nor imagery contents in each condition. Such factors influence on the simulative action should also be investigated. Additionally, the route difficulty seems to serve as an important factor for the exploratory movement. By considering the overall negative trend between climbing skill level and the number of exploratory movements as shown in Figure 8, investigations closely test the relationship between the climbability and needed exploratory movements.

With respect to the practical contribution to climbing, investigation of the effect of simulative action in a climbing situation would be important. Particularly, the dMI and gestures could play an important role in determining the effect of simulative action in route finding. However, we cannot directly distinguish them in our experiment so far because we manipulated only the presence or absence of simulative action without changing any physical intensities of climbing. The dMI is typically observed in a movement that includes both temporal and spatial factors (Guillot et al., 2013). The traversing task used in the present study required the participants to make an appropriate choice in a given situation but the task itself did not necessarily require a temporal matching of the whole body movement using a ballistic stretch because the slab wall (leant backwards) was relatively easy to traverse. Therefore the climbing task content (e.g., configuration of holds) and difficulty (e.g., inclination of the wall) should be experimentally manipulated so as to further elucidate how gestures affect climbing.

Conclusion

Simulative actions and exploratory movements are often observed in rock climbing. These two climbing related behaviors are empirically recognized as important for a better performance, but there is little scientific evidence regarding the relationship between these behaviors. Our findings shed light on the relationship between the simulative action (i.e., route finding in the preparatory phase) and exploratory movement (i.e., climbing per se). Practically, both climbers and coaches need to understand the possible interaction between optimal route finding and fluent climbing for a better performance (Sanchez et al., 2012), especially in the case of climbing on difficult routes. The present study showed that memorizing a climbing route was mediated by the route’s climbability, while the participant’s simulative action during route finding was influenced by the participant’s exploratory movements at the later climb. The effect of the simulative action can be further modulated by the vividness of the participant’s motor imagery, especially their kinesthetic imagery and also by their climbing experience. Our findings therefore imply an interaction of cognitive function and physical performance in climbing that is apt to be a key factor for understanding characteristics of climbers and novice practitioners.

Footnotes

Notes

Acknowledgments

The authors wish to thank Miki Fukuda for the administrative coordination of the experimental environment. The authors are grateful to Kuniyasu Imanaka and laboratory colleagues for their helpful comments on this work. The authors are also grateful to the reviewers and the editor for valuable comments and suggestions.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the basic research budget of Tokyo Metropolitan University to M.I.

ORCID iDs

Takahiro Sugi

Masami Ishihara

Author Biographies

Takahiro Sugi, M.A. in Psychology, is a Doctoral Course student of the Graduate School of Humanities [Psychology] at Tokyo Metropolitan University. He is interested in action possibility in climbing and perceptual-motor control.

Anda-Maria Niţu, B.A. in Psychology, is currently a Master's Course student of Health Psychology at King's College London. Her main research area is perceived barriers/attitudes to exercise and sport in patients with single ventricle physiology.

Masami Ishihara, D.Sc., is a professor of experimental psychology at Tokyo Metropolitan University. His research interests cover the area of human perception, cognition, and action.

The Results of Three Types of Imagery in the Same Formula for the Memory Score.

Internal Visual Imagery (IVI)				External Visual Imagery (EVI)				Kinesthetic Imagery (KI)
Predictors	Estimates	CI	p	Predictors	Estimates	CI	p	Predictors	Estimates	CI	p
(Intercept)	0.75	0.68 – 0.82	<0.001	(Intercept)	0.75	0.68 – 0.83	<0.001	(Intercept)	0.75	0.68 – 0.83	<0.001
standardized_IVI	−0.093	−0.16 – −0.03	0.004	standardized_EVI	−0.055	−0.13 – 0.015	0.125	standardized_KI	−0.078	−0.14 – −0.01	0.022
Action [non]	0.037	−0.01 – 0.079	0.093	Action [non]	0.037	−0.01 – 0.079	0.093	Action [non]	0.037	−0.01 – 0.079	0.093
route_type [possible]	0.060	0.018 – 0.10	0.006	route_type [possible]	0.060	0.018 – 0.10	0.006	route_type [possible]	0.060	0.018 – 0.10	0.006
Random effects				Random effects				Random effects
σ²	0.01			σ²	0.01			σ²	0.01
τ_{00 ID}	0.02			τ_{00 ID}	0.03			τ_{00 ID}	0.02
ICC	0.66			ICC	0.71			ICC	0.68
N_ID	24			N_ID	24			N_ID	24
Observations	96			Observations	96			Observations	96
Marginal R²/Conditional R²	0.228/0.734			Marginal R²/Conditional R²	0.099/0.737			Marginal R²/Conditional R²	0.169/0.736

The Results of Three Types of Imagery in the Same Formula for the Exploratory Movement Score.

Internal Visual Imagery (IVI)				External Visual Imagery (EVI)				Kinesthetic Imagery (KI)
Predictors	Estimates	CI	p	Predictors	Estimates	CI	p	Predictors	Estimates	CI	p
(Intercept)	11.98	7.24 – 19.84	<0.001	(Intercept)	12.02	7.21 – 20.02	<0.001	(Intercept)	11.96	7.15 – 19.99	<0.001
exp [non_climber]	0.60	0.29 – 1.24	0.167	exp [non_climber]	0.60	0.29 – 1.25	0.174	exp [non_climber]	0.59	0.28 – 1.23	0.160
standardized_IVI	0.76	0.53 – 1.10	0.144	standardized_EVI	1.02	0.71 – 1.46	0.917	standardized_KI	0.82	0.57 – 1.19	0.300
Action [non]	0.51	0.36 – 0.73	<0.001	Action [non]	0.52	0.36 – 0.74	<0.001	Action [non]	0.52	0.37 – 0.72	<0.001
exp [non_climber] *Action [non]	2.99	1.82 – 4.91	<0.001	exp [non_climber] *Action [non]	2.96	1.76 – 4.98	<0.001	exp [non_climber] *Action [non]	2.99	1.87 – 4.80	<0.001
standardized_IVI *Action [non]	1.25	0.98 – 1.59	0.073	standardized_EVI *Action [non]	0.98	0.76 – 1.26	0.869	standardized_KI *Action [non]	1.37	1.09 – 1.73	0.007
Random effects				Random effects				Random effects
σ²	0.25			σ²	0.26			σ²	0.23
τ_{00 ID}	0.31			τ_{00 ID}	0.32			τ_{00 ID}	0.32
ICC	0.55			ICC	0.55			ICC	0.58
N_ID	24			N_ID	24			N_ID	24
Observations	47			Observations	47			Observations	47
Marginal R²/Conditional R²	0.180/0.634			Marginal R²/Conditional R²	0.121/0.600			Marginal R²/Conditional R²	0.165/0.650

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