Implicit Visuomotor Adaptation Remains Limited after Several Days of Training

Synthesis

SYNTHESIS

The reviewers highlighted the high quality and difficulty of the experiments and recognized the importance the work in understanding the role of implicit adaptation in motor learning. The reviewers noted the particular significance of the reduction in implicit learning for the mirror reversal task. Both reviewers also noted, however, significant issues related to the conclusions that are being drawn from the results. Both reviewers had major comments about the current exposition, though there is some difference in perspective about the degree to which adaptation may contribute to de novo motor learning. Both reviewers were concerned by the large variability across subjects, particularly given the small sample size, and felt that this variation in behavior was not discussed in sufficient detail. The reviewers provide detailed suggestions regarding these and other important issues, which you should find useful in revising your manuscript.

Reviewer 1

ADVANCES THE FIELD

The data collected is difficult to collect because it requires 5 consecutive days of experiments in each subject. In addition, the experiments seem performed well and data quality seems high.

STATISTICS

A power analysis is required (as detailed in comments to authors) and some error bars are missing in the plots.

SOFTWARE

We downloaded and tried to run Figures_8_9.m but received an error “Unrecognized function or variable ‘plot_format’.”

COMMENTS

The manuscript explores how practice over several consecutive days impacts implicit adaptation in two different tasks: a visuomotor rotation task and a mirror task. In the rotation task, implicit adaptation plateaus after the first day of training and afterwards remains constant. In the mirror task, implicit adaptation drifts towards 0 throughout the entire practice. The central claim of the paper is that in neither task does 5 days of training lead to a marked increase in the amount of implicit adaptation. For visuomotor rotation, the failure of the implicit adaptation to increase is interpreted to mean that implicit adaptation is limited in its ability to reach full adaptation. In the mirror reversal task, the authors interpret their result to mean that implicit adaptation has no ability to successfully adapt to mirror reversal. Taken together, the results lead the authors to question the utility of implicit adaptation for the broader spectrum of motor skill learning.

The manuscript targets a key area of exploration in the study of motor control. The authors are correct that extrapolating findings about implicit adaptation from visuomotor rotation to other motor tasks, such as the mirror task, can provide valuable insights into the mechanisms of implicit adaptation in general motor learning. However, we have reservations about the work as it currently stands. These can be broadly categorized into issues with the experimental design, the statistics, the interpretation of the existing literature and the interpretation of the results. We detail the major and minor points below.

Major issues

Existing literature:

In discussing the evidence that adaptation only plays a minor role in visuomotor rotations (lines 38-39) the authors only provide support for a weaker claim: that explicit re-aiming does play a role. Indeed, the Mazzoni and Krakauer (2006) paper they cite shows implicit adaptation can override explicit strategies. The authors should also relate to recent evidence showing that long-term retention (in the form of savings) can actually proceed without formation or recalling of explicit strategies (Yin et al. 2020). We feel (as discussed below) that the authors need to clarify the point they feel is made by the experiments and then reassess how their experiments will extend the existing literature. Two additional papers should also be discussed:

Telgen J Neurosci 2014 (https://www.jneurosci.org/content/34/41/13768)

Yang bioRxiv 2020 (https://www.biorxiv.org/content/10.1101/2020.01.15.906545v1.full)

Experimental design:

The authors set out their question in the introduction: can implicit adaptation can lead to long term motor learning in the absence of explicit re-aiming. The experimental design does not seem to answer this question. There is simply no condition with an absence of explicit re-aiming. When this question has been asked (see Yin 2020 referenced above), it has been answered in the affirmative. Again, the authors should clarify which question their data addresses and make a strong link between the question and the experimental design.

Indeed, the experimental design seems to encourage explicit re-aiming. For example, it has been shown previously that reporting can affect different aspects of adaptation: it promotes full asymptote (see preprint by Langsdorf et al. 2020), it has been associated with more explicit re-aiming and less implicit adaptation (see Leow et al. 2018 and preprint by Maresch et al. 2020). Moreover, large rotations (Bond et al. 2015) that are introduced abruptly (Werner et al. 2015) also cause more explicit re-aiming. This suggests that possibility that the authors consider collecting data in conditions which are known to contribute to stronger implicit learning. At the least, this should be discussed as a limitation of this study.

Along similar lines, the authors argue (line 44) that because implicit adaptation is only partial, it cannot lead to long-term motor learning. This seems like a strange claim. Can it be justified?

The claim that the authors can make on the basis of this design is that not all explicit learning eventually becomes implicit. This seems like a straw man argument. Even if it is taken seriously, it may be that more than 5 days are necessary to make some tasks fully implicit. The Stratton (1896) and Kohler (1941) studies which led the authors to choose 5 days actually used five full days of continuous exposure. This is much more exposure than used in the current study. We imagine that extending the experiments to more than 5 days or trying to have subjects practice for entire days will not be practical, but this limitation does need to be discussed.

Statistics:

It would be helpful to present a power analysis that would show that this sample size is large enough to show an effect of at least 2 - 3 degrees. If not, the authors should consider collecting additional data to achieve 90% power for an effect size of 2-3 degrees. In this case, many would argue that the additional subjects should be analyzed separately in order to preserve the purity of the statistical approach. The power of the original study for a small effect size should be reported.

Figures 6 & 10: Error bars on the bar for the mean and individual subject error bars would be helpful. Also, a scatterplot of implicit adaptation vs aftereffect with error bars in both directions would give a better indication of how these measures relate to each other.

Lines 328 - 329: if arguing for similarity, an equivalence test should be conducted (Lakens Advances in Methods and Practices in Psychological Science 2018 has a nice tutorial).

Figure 10: this figure is mean to show that aftereffects are in the direction opposite to the appropriate direction, suggesting an inability of subjects to change the way their implicit system corrects. This argument would be made more powerful if the results were broken down by quadrants, to show that for each the corrections were in the “standard” and not the “reversed” direction.

Discussion:

The discussion, and the paper generally, feels to us that it glosses over the inter-subject differences. Individual subject variability was quite pronounced: some subjects show almost 45{degree sign} of implicit adaptation and others close to 0{degree sign} in the rotation task. The sample size is very small and the data is very noisy (as shown by the large between-subject variance). In line 233, the SEM of re-aiming and implicit adaptation is around 16{degree sign}, meaning implicit adaptation could be as big as explicit re-aiming in some cases. In the mirror task, some subjects show implicit adaptation appropriate for the mirror task and others do not. This is especially important since task details could affect the proportions of subjects showing more implicit adaptation in the two tasks. The discussion should fully address both intersubject variability and the possibility that subtle details of task design may be influencing the results.

The discussion should address the authors expectation (lines 331-334) that implicit adaptation should become more appropriate for the mirror reversal task after more days of training. What are the two alternative theories of how implicit adaptation might work with regards to the mirror task and how do they lead to different expected results. Once this is discussed, the actual results can be understood in the correct context.

Much of the discussion (lines 443-512) is devoted to the topic of proceduralization and theories of motor learning. This seems off topic both in terms of the central question in the manuscript and the design of the experiments. It also seems largely speculative. We recommend reducing this part of the discussion to no more than 20 lines (slightly less than a page).

There is no clearly set out discussion of the studies limitations. This should be added. It should discuss, at the least, the intersubject variability, the relatively small number of subjects, the relatively limited amount of training in the tasks, and the interpretational difficulties associated with measures of explicit and implicit adaptation.

Minor comments

Line 44: asymptotic adaptation remained partial instead of insufficient?

The authors’ continuous implicit measure is solely derived from explicit reports. They also use aftereffects as a measure of the final implicit adaptation. This can be problematic since these measures have been found to differ profoundly in many situations (Taylor et al. 2014, Bond et al. 2015, Leow et al. 2015, Bromberg et al. 2019). The authors themselves find a mismatch between these two measures. It has been suggested that implicit adaptation as derived from reporting may not measure the same as the aftereffect (see preprint by Maresch et al. 2020). This mismatch between measures should be addressed in the discussion of possible limitations of the study.

Many analyses are not described in the methods (individual subject differences, regression comparing adaptation at the end of each day to beginning of next day, comparison between implicit and aftereffect on day 5). These should be included in the methods section.

Was online or endpoint feedback used during rotation trials? The description is somewhat confusing: line 125: a small circular cursor (0.15 cm 125 radius) provided online feedback and then line 136: endpoint feedback was displayed for 500 ms.

Is there a reason that 12 targets were used in Experiment 1? How many targets in Experiment 2 (I think 4, but it’s not explicitly stated)?

Reaction time calculation line 186-187: Reaction times were calculated as the interval from target appearance to aim-report, except where noted. The authors call the “re-aiming reaction time”. While this seems appropriate, I’m still wondering in how far this really reflects an actual reaction time. A short discussion about what this type of reaction time means and how it differs with other reaction time calculations would be desirable.

Line 233: How is the SEM calculated? Did the authors account for within subject variability?

Line 235-237: the authors are correct that a direct comparison of explicit and implicit is inappropriate. However, the authors can measure the percentage of total re-aiming that is accounted for by explicit adaptation and test how this changes over time. This would answer the question the authors are getting at here.

Figure 4 & 11: Calling subject 4C representative seems problematic. Subjects seems to have a uniform distribution of implicit adaptation between 0 and 20{degree sign}, with two outliers having implicit adaptation near 40{degree sign}. Thus, subject 4C is not necessarily more representative than subject 4B. Perhaps in this and all similar plots, it makes more sense to present the median subject, rather than claiming that anyone is representative?

Line 300: saying that “implicit adaptation was constrained” overstates the case. It was only constrained in some subjects.

Figure 11: some subjects’ implicit adaptation seems appropriate for the mirror reversal; this should be mentioned in the text.

The figure order is switched between the rotation and mirror experiments. This is confusing. To maintain the proper order, the figures for the mirror experiment should be first figure 13, then figure 11, then figure 12, then figure 10.

Typos:

Line 115: made

Line 229: measured

Line 422: underlying

Line 443: admit instead of submit?

Reviewer 2

ADVANCES THE FIELD

The idea of testing for implicit adaptation in the context of a mirror-reversal is interesting. The finding that it is gradually suppressed over 5 days may spark further research. There are also interesting analyses regarding inter-individual differences in implicit adaptation.

STATISTICS

Small sample sizes (n=12) but the authors use caution when interpreting, especially correlations.

COMMENTS

Here the authors report two experiments in which participants (n=12 in each) are exposed to either a 45 deg visuomotor rotation or a mirror-reversal perturbation over 5 consecutive days. They find that for the rotation, implicit adaptation saturates at ∼15 deg and remains stable for each participant across days, but is highly variable across participants. During mirror-reversal implicit adaptation is gradually suppressed over the 5 days.

The work is properly conducted, generally clear and provides novel insight regarding implicit adaptation in the context of visuomotor rotation and mirror-reversal. My main issue is that the work is framed around a debatable working hypothesis that I feel takes away from the novelty of the findings. I have other (minor) comments to ameliorate the paper.

I have a problem with the framing of the paper. It’s unclear why the author assume (or test the hypothesis) that implicit adaptation processes would potentially be making a large contribution to motor skill learning the novo. In my opinion (and to much of the field), there is a pretty clear line between adaptation (a recalibration process of a previously learned movement) and motor skill learning (acquiring an entirely new motor control policy); they are distinct processes that serve different functions (see this recent review for instance: Spampinato and Celnik 2020, Neuroscientist). Even the authors apparently get this (line 47 : “It is difficult to see how asymptotically constrained implicit adaptation could produce long-term motor learning in the absence of explicit re-aiming.”; see also line 426). I do not understand why the authors make a conundrum off of this. Overall this leads the authors to conclude that implicit adaptation cannot account for motor learning de novo, which is quite expected and not very compelling (eg. last sentence of abstract: “implicit adaptation processes, as studied in sensorimotor adaptation paradigms, may only make subtle recalibrations of an existing skill and cannot contribute to motor skill learning de novo” ; or sig statement: “These findings question the utility of implicit adaptation processes to motor skill learning more broadly”). I think this framing reduces the novelty/excitement of the findings. This is perhaps best exemplified on line 511: “we hold that classic implicit adaptation is not the driving force behind motor learning, but that another system is largely responsible.” Sure! Was there actually any current model or theory that entertained this possibility?? If we were to generalize, would the authors also hypothesize that visuomotor adaptation have anything to do with other types of de novo motor skills, like sequence learning? I suggest the authors either bolster their case for why we would expect that implicit adaptation would fully account for de novo motor skill learning (emphasizing more on current literature - and less on 19th century Stratton) or change their premise and focus on the actual results (saturation over 5 days, or decrease in the mirror-reversal). I prefer option 2.

The very large inter-individual differences in implicit adaptation are really intriguing (and almost worrisome for all who rely on this task to learn something robust about the brain!). It would be nice if the authors discussed this more in depth, what this means in terms of the relative interplay between implicit and explicit processes, how it is (un)related to the measured aftereffects, and the broader implications. At current, the discussion is relatively heavy on the explicit process (which was not the main question of the paper) and relatively light on these interesting findings.

I do not understand where the data for each day are in figures 8A and 9A (line 325).

Why isn’t there a figure like figure 3 for the mirror experiment? Also please order the different analyses and figures the same way for both exps. (the aftereffects figure is not at the same place in both).

Minor comments:

Line 35: “dissociated"

Line 115: “made” a reaching movement

Some aspects of the methods are not clear:

Line 118-123: Please present the time allowed for the tapping.

Line 164-170: the target locations are not obvious for the mirror.

The intuition behind the 2 experiments is not obvious by just reading the methods. The first paragraphs of the results for each exp (line 223 and 309) are helpful and could be presented earlier.

Author Response

1

We would like to thank the reviewers for their thoughtful and detailed comments on the manuscript. We

apologize in advance for some lengthy replies to a few of the comments. The reviewers raised really

interesting questions, which required a great deal of unpacking. We hope that we have clarified a number

of the issues raised in the reviews and have made substantial changes to the manuscript.

Below we address each comment in turn. Reviewer comments are in blue and our response is in black.

Simple changes to the text are italicized and included below. For more extensive changes to the text, we

included page and line numbers that point to the red-lined document.

Synthesis Statement for Author (Required):

SYNTHESIS

The reviewers highlighted the high quality and difficulty of the experiments and recognized the

importance the work in understanding the role of implicit adaptation in motor learning. The reviewers

noted the particular significance of the reduction in implicit learning for the mirror reversal task. Both

reviewers also noted, however, significant issues related to the conclusions that are being drawn from the

results. Both reviewers had major comments about the current exposition, though there is some difference

in perspective about the degree to which adaptation may contribute to de novo motor learning. Both

reviewers were concerned by the large variability across subjects, particularly given the small sample

size, and felt that this variation in behavior was not discussed in sufficient detail. The reviewers provide

detailed suggestions regarding these and other important issues, which you should find useful in revising

your manuscript.

Reviewer 1

ADVANCES THE FIELD

The data collected is difficult to collect because it requires 5 consecutive days of experiments in each

subject. In addition, the experiments seem performed well and data quality seems high.

STATISTICS

A power analysis is required (as detailed in comments to authors) and some error bars are missing in the

plots.

We have included a post-hoc power analysis in the revised manuscript (page 7, lines 115-119) and a

description of our methods is detailed below (on page 5 of this response letter).

SOFTWARE

We downloaded and tried to run Figures_8_9.m but received an error “Unrecognized function or variable

‘plot_format’.”

Apologies for this oversight. It was an in-house function used to format the plots. We have double

checked our code to ensure that there are no more missing contingencies.

COMMENTS

The manuscript explores how practice over several consecutive days impacts implicit adaptation in two

different tasks: a visuomotor rotation task and a mirror task. In the rotation task, implicit adaptation

plateaus after the first day of training and afterwards remains constant. In the mirror task, implicit

adaptation drifts towards 0 throughout the entire practice. The central claim of the paper is that in neither

task does 5 days of training lead to a marked increase in the amount of implicit adaptation. For

visuomotor rotation, the failure of the implicit adaptation to increase is interpreted to mean that implicit

adaptation is limited in its ability to reach full adaptation. In the mirror reversal task, the authors interpret

their result to mean that implicit adaptation has no ability to successfully adapt to mirror reversal. Taken

together, the results lead the authors to question the utility of implicit adaptation for the broader spectrum

of motor skill learning.2

The manuscript targets a key area of exploration in the study of motor control. The authors are correct

that extrapolating findings about implicit adaptation from visuomotor rotation to other motor tasks, such

as the mirror task, can provide valuable insights into the mechanisms of implicit adaptation in general

motor learning. However, we have reservations about the work as it currently stands. These can be

broadly categorized into issues with the experimental design, the statistics, the interpretation of the

existing literature and the interpretation of the results. We detail the major and minor points below.

Major issues

Existing literature:

In discussing the evidence that adaptation only plays a minor role in visuomotor rotations (lines 38-39)

the authors only provide support for a weaker claim: that explicit re-aiming does play a role. Indeed, the

Mazzoni and Krakauer (2006) paper they cite shows implicit adaptation can override explicit strategies.

The authors should also relate to recent evidence showing that long-term retention (in the form of

savings) can actually proceed without formation or recalling of explicit strategies (Yin et al. 2020). We

feel (as discussed below) that the authors need to clarify the point they feel is made by the experiments

and then reassess how their experiments will extend the existing literature. Two additional papers should

also be discussed:

Telgen J Neurosci 2014 (https://www.jneurosci.org/content/34/41/13768)

Yang bioRxiv 2020 (https://www.biorxiv.org/content/10.1101/2020.01.15.906545v1.full)

Based on the reviewer’s comment here and a fresh read of the manuscript, we now see that our narrative

flow (in the introduction) appears to emphasize the existence of explicit re-aiming strategies rather than

discussing how implicit adaptation appears to be limited. We missed an opportunity to discuss several

studies that make the stronger claim that implicit adaptation is limited (note, we don’t think implicit

adaptation plays an insignificant role, rather it can be very useful for small perturbations).

First, when explicit and implicit learning are dissociated using the verbal report procedure, we have

observed that the implicit adaptation asymptotes to a value far less than complete learning and, in fact, the

implicit adaptation function is largely insensitive to rotation magnitude (in this study we tested rotations

of only 15 degrees or larger; Bond and Taylor 2015). Second, when explicit re-aiming strategies are

rendered irrelevant using the visual-error-clamp procedure, a similar pattern emerges: Implicit adaptation

asymptotes too early and appears insensitive to rotation magnitude (tested between 7-95 degrees;

Morehead, Taylor, et al. 2017). We should note that there have been a few modifications to simplicity of

this conclusion, with a few recent reports showing that implicit adaptation is proportional for rotations

under approximately 8 degrees and there may be an effect of reward (Kim, Morehead et al., 2018; Kim et

al., 2019; Leow et al., 2018; Hutter and Taylor 2018). Finally, a recent study by Avraham, Morehead, et

al., 2021 suggests that the contribution of implicit adaptation appears to even decrease with extended

training, similar to the result we observed here.

We have now expanded our discussion of these studies in the introduction (page 3, lines 44-52) to provide

more support for the notion that implicit adaptation may be limited:

"In parallel to the recognition that strategies play an important role in adaptation tasks, we see rapidly

emerging evidence that the implicit process is highly stereotyped regardless of the particular task

demands. The implicit process asymptotes to a value far less than complete learning and is largely

insensitive to perturbation magnitude (Bond and Taylor, 2015; Morehead et al., 2017). Morehead and

colleagues (2017), revealed a stereotyped implicit learning curve when the incentive to strategize was

completely removed. Surprisingly, asymptotic implicit learning remained insufficient to account for the

perturbation after many hours of practice. (Morehead and Smith, 2017, Morehead et al., 2017; Kim et al.,3

2018). Finally, recent evident suggests that the contribution of the implicit process decreases with

extended training (Avraham, et al., 2020).”

The reviewer also noted a few studies that they would like us to address. We feel that the title of Mazzoni

and Krakauer (2006) can be a bit misleading. In that study, while the explicit re-aiming strategy is

initially effective, implicit adaptation gradually begins to accumulate causing performance to deteriorate.

Despite their title, it doesn’t necessarily mean that implicit adaptation completely overrides the strategy,

but instead is simply added on top of the aiming strategy. We’ve run an extended version of that study (4

times as many trials) and found that as implicit adaptation causes more and more deterioration in

performance, participants will begin to explicitly re-aim their movements to offset implicit adaptation

(Taylor and Ivry 2011).

The savings-in-relearning study by Yin and colleagues (2020) is difficult to interpret as savings in the relearning block could be the result of an explicit strategy. Yes, they used conditions to prevent or

discourage strategy use in the first rotation block, using either an error clamp or gradual perturbations, but

the washout and re-learning blocks involved abrupt rotations. Thus, the participants could have formed a

strategy in the re-learning block or even had meta-learning/structural learning of a strategy during the

washout (Bond and Taylor 2017). Or, specific to the error clamp condition, the participants could have

observed the pattern of errors during the clamp block and used that information to quickly form a strategy

in the re-learning block (McGregor & Gribble 2015, 2017, Wanda, Li, Thoroughman 2013). Furthermore,

specific to the gradual condition, gradual conditions do not always imply that participants didn’t use a

strategy. We have observed explicit re-aiming in the later stages of a gradual condition, presumably

because the rate of gradual increase was too high for implicit adaptation to keep up or implicit reached

asymptote (Butcher, Ivry et al., 2018). We should also note that Morehead et al (2015) and Haith et al

(2015) did not observe what would be considered implicit savings, and Avraham et al., 2021 suggests that

implicit is actually reduced in the re-learning block, and even performed a post-hoc analysis on the

dataset from Yin and Wei 2020 and found that those data show attenuation of implicit adaptation too. We

should note that these findings have been challenged by Albert et al., 2021, so clearly more work is

required to flesh out all of these possibilities.

Finally, the study by Yang et al. 2020 may suggest that under a more de novo learning situation - one

that requires continuous feedback control, the feedback controller may become tuned to a mirror reversal

(revealed by their control systems approach). While feedback control was examined in Telgen et al.

2014, Kasuga et al. 2015, Grisenko and Kalaska 2009, and Hadjiosif et al., 2021, these tasks were center out reaching tasks and may have emphasized feedforward over feedback control, and may not necessarily

be a de novo learning situation per se. We now discuss these studies in detail in our discussion.

We have made substantial changes to the introduction, pages 2-6, and discussion, pages 29-35, to address

these issues (since the changes are substantial, we did not include the text in this response letter).

Experimental design:

The authors set out their question in the introduction: can implicit adaptation lead to long term motor

learning in the absence of explicit re-aiming. The experimental design does not seem to answer this

question. There is simply no condition with an absence of explicit re-aiming. When this question has been

asked (see Yin 2020 referenced above), it has been answered in the affirmative. Again, the authors should

clarify which question their data addresses and make a strong link between the question and the

experimental design.4

Apologies for the lack of clarity on our part, our goal was not to determine if implicit adaptation would

lead to long-term learning in the absence of explicit re-aiming. Instead, we wanted to know if implicit

adaptation would begin to replace explicit re-aiming.

We have included the sentence (page 4, lines 68-70): “If the implicit process, as measured in this task,

will eventually contribute substantially to overall compensation, we expect to see a steady increase in the

proportion of learning accounted for by the implicit process over time.

Indeed, the experimental design seems to encourage explicit re-aiming. For example, it has been shown

previously that reporting can affect different aspects of adaptation: it promotes full asymptote (see

preprint by Langsdorf et al. 2020), it has been associated with more explicit re-aiming and less implicit

adaptation (see Leow et al. 2018 and preprint by Maresch et al. 2020). Moreover, large rotations (Bond et

al. 2015) that are introduced abruptly (Werner et al. 2015) also cause more explicit re-aiming. This

suggests that possibility that the authors consider collecting data in conditions which are known to

contribute to stronger implicit learning. At the least, this should be discussed as a limitation of this study.

We agree with the reviewer that our experiment design encourages participants to explicitly re-aim - we

require them to report their aim on each trial. When participants are instructed to indicate their aim on

each trial (regardless of the reporting method: verbal reports, adjusting a report using a keyboard, mouse,

touch screen, etc.) the rate of performance improvements seems to be faster compared to groups that are

not required to report (more standard rotation tasks). However, when the aftereffects of report groups are

compared to non-reporting groups, there is very little difference (Taylor et al 2014; Bond and Taylor

2017). Interestingly, Maresch and Donchin (2020) found similar sized aftereffects across their groups,

which were also far less than the size of the rotation (∼35 degrees on average for a 60-degree rotation),

although they found more radical differences between groups when assaying explicit/implicit during

training. To our knowledge, any study that instructed participants to stop re-aiming during washout has

not revealed aftereffects that have fully compensated for the rotation. The visual error-clamp procedure

reinforces these results, as re-aiming is likely not at play and yet implicit adaptation does not fully

compensate for the rotation (Morehead et al., 2017; Kim et al., 2019).

Again, however, our goal was to determine if implicit adaptation would eventually counteract a

reasonably large rotation - one that typically causes participants to explicitly re-aim - given sufficient

training. It should be noted that we don’t know how to define or operationalize “more” or “less” explicit

re-aiming. Yes, participant’s explicit re-aiming angle can be larger or smaller but that doesn’t necessarily

mean that it is more or less explicit. A recent paper has shown that two different explicit re-aiming

strategies for the same sized rotation, one likely relied on mental rotation of a planned movement vector

while the other reflected retrieval of a cached motor plan (McDougle and Taylor 2019). The former

requires longer preparation time to implement, but here too it is difficult to say if this is more or less

explicit. Going forward, we will need figure out how to operationalize these terms as more or less explicit

knowledge, deliberation time, etc.

Along similar lines, the authors argue (line 44) that because implicit adaptation is only partial, it cannot

lead to long-term motor learning. This seems like a strange claim. Can it be justified? The claim that the

authors can make on the basis of this design is that not all explicit learning eventually becomes implicit.

This seems like a straw man argument. Even if it is taken seriously, it may be that more than 5 days are

necessary to make some tasks fully implicit. The Stratton (1896) and Kohler (1941) studies which led the

authors to choose 5 days actually used five full days of continuous exposure. This is much more exposure

than used in the current study. We imagine that extending the experiments to more than 5 days or trying

to have subjects practice for entire days will not be practical, but this limitation does need to be discussed.5

We entirely agree with the reviewer’s assessment here. It may very well be the case that much more

exposure is required to develop a fully implicit mapping. While one hour a day for five days may not be

sufficient to have an implicit mapping that fully accounts for the rotation, we were expecting to see a

significant positive slope of implicit adaptation across the days. That is, we expected to see implicit

adaptation gradually rise while explicit re-aiming gradually decrease. On average, we don’t see an

increase and even a slight decrease in implicit with more exposure, which has recently been reported by

Avraham and colleagues (2021). So, yes, full implicit adaptation may be a straw man, but a gradual

increase in implicit adaptation was what we were expecting at a minimum.

We have modified the text to reflect this more modest prediction on page 4, lines 67-72:

"In Experiment One, we investigate adaptative learning to a visual perturbation over five days of

training. If the implicit process, as measured in this task, will eventually contribute substantially to

overall compensation, we expect to see a steady increase in the proportion of learning accounted for by

the implicit process over time. We find that the implicit process, on average, does not change over the

training period. However, we also find substantial between-subject differences that raise questions about

the validity of the measure.”

Statistics:

It would be helpful to present a power analysis that would show that this sample size is large enough to

show an effect of at least 2 - 3 degrees. If not, the authors should consider collecting additional data to

achieve 90% power for an effect size of 2-3 degrees. In this case, many would argue that the additional

subjects should be analyzed separately in order to preserve the purity of the statistical approach. The

power of the original study for a small effect size should be reported.

We are unsure for what data the reviewer would like to see a power analysis for 2-3 degrees of change.

We have taken the comment to refer to the t-tests applied to the difference between the first and last days

of implicit adaptation (please correct us here if we misinterpreted the comment). But assuming this was

the case, we were hesitant to run a power analysis, in part, because of the straw man comment above. If

we were expecting adaptation to be full (∼45 degrees) after five days and we knew that implicit

adaptation asymptotes ∼20-25 degrees from previous work, then our power would be unreasonably high

(∼2 subjects). If we took the more modest prediction, that implicit would simply increase between days,

then we don’t know what effect size to estimate as no study has examined implicit adaptation across days

(using methods that attempt to dissociate or isolate implicit adaptation). 2-3 degrees, as the reviewer

suggests, sounds reasonable but is ultimately arbitrary. As such, we opted to recruit a sample size that is

in the range of many studies of visuomotor rotations (10-15 subjects).

However, assuming a 3-degree change in mean and a SD of 3-degrees results in a suggested sample of 10

participants to achieve 90% power. A post-hoc power analysis results in a power level of just over 85% to

observe the reduction of implicit adaptation found in Experiment 2.

We have now added this to the methods (page 7, lines 115-119) with the caveat is that we didn’t know a

priori what effect size to estimate.

"We did not have an a priori effect size estimate with which to calculate a power analysis. However,

assuming a 3-degree change in mean and a SD of 3-degrees results in a suggested sample of 10

participants to achieve 90% power. A post-hoc power analysis conducted on the reduction of implicit

adaptation found in Experiment 2 results in a power level of just over 85% to observe the reported

effect.”6

Figures 6 & 10: Error bars on the bar for the mean and individual subject error bars would be helpful.

Also, a scatterplot of implicit adaptation vs aftereffect with error bars in both directions would give a

better indication of how these measures relate to each other.

Figures 6 and 10 (now 6 and 12) were changed as suggested. Similar to Maresch and Donchin, we too

observe a disconnect between implicit adaptation measured via subtraction during training and with

aftereffects. However, we should note that neither measure shows full implicit adaptation (∼45 degrees)

after 5 days of training.

Figure 6. (A) Average aftereffect for each subject averaged across the 32 trials of no-feedback washout

(with subjects instructed to aim and move directly to the target). Error bars represent one standard error

of the mean. (B) The time course of washout for the average across subjects, and individual trial values

for the three example subjects defined in Figure 3. Shaded area represents between-subjects standard

error. (C) Correlation between each individuals’ adaptation as measured via subtraction (hand angle

minus explicit re-aiming over the last 32 trials of training) vs washout (average hand angle in 32 washout

trials). Error bars represent one standard error of the mean along each dimension. The marker color and

shape represent an individual subject across all figures in this manuscript.7

Figure 12. (A) Average corrected aftereffects for each subject across the 32 trials of no-feedback,

washout (with subjects instructed to aim and move directly to the target). Each subject is jittered left to

right in order of least to most explicit re-aiming at the end of Day 5. (B) The time course of washout for

the average across subjects and individual trial values for three representative subjects [#5 (Lowest), #8

(Median), #12 (Highest), re-aiming on last day). The shaded area represents the standard error of the

mean for all subjects.

Lines 328 - 329: if arguing for similarity, an equivalence test should be conducted (Lakens Advances in

Methods and Practices in Psychological Science 2018 has a nice tutorial).

The reviewer asks us to determine the threshold for an effect that is “trivially small”. The equivalence test

requires positive and negative bounds against which we could test the result but given the exploratory

nature of this data and analysis there is no particular reason to pick {plus minus}1{degree sign} over {plus minus}5{degree sign} or {plus minus}10{degree sign}. Although we do

not believe this arbitrary determination will provide additional information beyond the simple t-test, we

conducted the suggested equivalence test against a bound of {plus minus}6{degree sign} (conservatively proposing that anything

more than a 1/4 reduction of implicit recalibration is nontrivial). The result was consistent with our

previous suggestion that implicit recalibration was suppressed in the mirror-reversal task (t=3.2, p<.01).

Figure 10: this figure is meant to show that aftereffects are in the direction opposite to the appropriate

direction, suggesting an inability of subjects to change the way their implicit system corrects. This

argument would be made more powerful if the results were broken down by quadrants, to show that for

each the corrections were in the “standard” and not the “reversed” direction.8

We have added additional panels to figure 10 (now 12) to show the difference in aftereffects for different

quadrants in the mirror task. See above.

Discussion:

The discussion, and the paper generally, feels to us that it glosses over the inter-subject differences.

Individual subject variability was quite pronounced: some subjects show almost 45{degree sign} of

implicit adaptation and others close to 0{degree sign} in the rotation task. The sample size is very small

and the data is very noisy (as shown by the large between-subject variance). In line 233, the SEM of reaiming and implicit adaptation is around 16{degree sign}, meaning implicit adaptation could be as big as

explicit re-aiming in some cases. In the mirror task, some subjects show implicit adaptation appropriate

for the mirror task and others do not. This is especially important since task details could affect the

proportions of subjects showing more implicit adaptation in the two tasks. The discussion should fully

address both intersubject variability and the possibility that subtle details of task design may be

influencing the results.

We agree that the sample size is quite small and that individuals show substantial differences in the

relative contribution of implicit and explicit re-aiming. This is why we carefully included many examples

of different subjects in figures, so that the reader could view the full gambit of learning styles. However,

we do not think that additional subjects would significantly alter the results - as you would simply see

more examples of the various ‘types’ of subjects. Additional subjects would not change the fact that there

is great variability between subjects.

We conducted a meta-analysis across 5 studies, with over 50 subjects, using the aim-report procedure

(identical to Taylor, Krakauer, and Ivry 2014). It shows the same variance as seen in these experiments.

While there are a few subjects that appear to show full implicit learning, the vast majority appear similar

or less to the mean observed in the present study. We opted not to include this meta-analysis in the paper

given the differences in study design, such as number of trials and verbal reports, as well as difficult in

visualizing learning time courses for all 50 subjects. Nonetheless, we thought the reviewer may find the

data interesting.

Figure: A) Final hand angle (purple), verbally reported aiming angle (explicit, blue) and subtraction

(implicit, red). B) The time series was fit with a two-state model fitting, showing the variety of explicit

and implicit learning time courses. Rotation was present between trials 57-376 (vertical dashed lines). In

washout, participants were instructed to stop aiming and cursor feedback was removed.9

Results (page 23, lines 371-376):

"Analysis of within- and between-subject variance: As with the visuomotor rotation, there was significant

variance in how subjects responded to the visuomotor mirror reversal (approximately -15{degree sign} to 15{degree sign}, Figure

11). Subjects were successful through a combination of implicit adaptation and explicit re-aiming, lost all

implicit adaptation by the end of training, or reversed the direction of implicit adaptation. Reversed,

visualized as negative, implicit adaptation is appropriate for the mirror reversal task.”

Discussion (page 30, lines 468-476):

The implicit process in the mirror reversal task initially was counterproductive to performance before

becoming suppressed with increased training. These findings may have been expected given the recent

evidence that the implicit process falls well short of full learning in visuomotor adaptation tasks

(Morehead and Smith, 2017; Morehead, Taylor, Parvin, and Ivry, 2017; Kim et al., 2018; Kim, Parvin,

and Ivry, 2019) and in the wrong direction in the mirror reversal task (Gritsenko and Kalaska 2009;

Lilicrap et al 2013; Telgen 2014; Kasuga 2015; Hadjiosif et al., 2021). Nonetheless, we thought that this

limitation of implicit process may be overcome with more training, an idea that failed to be supported by

our five-day experiments.

The discussion should address the authors expectation (lines 331-334) that implicit adaptation should

become more appropriate for the mirror reversal task after more days of training. What are the two

alternative theories of how implicit adaptation might work with regards to the mirror task and how do

they lead to different expected results. Once this is discussed, the actual results can be understood in the

correct context.

We now discuss on pages 32-33 (lines, 516-550) how implicit adaptation may become more appropriate

either by changing the error derivative or reparameterization of the transformation matrix:

"Implicit recalibration in the mirror reversal task

The mirror reversal results present an exciting future opportunity to determine the error signal

that initiates suppression of the implicit process in the mirror reversal task. Large variability in

individual behavior provides a foothold to understanding suppression of implicit processes. Here we

consider a few possible explanations that could be a target for future research.

The mirror reversal, unlike a rotation task, has an error-signal with a constantly switching sign.

Previous work has shown that inconsistency in error signals reduces overall learning (Castro et al.,

2014) and the implicit process in particular (Hutter and Taylor, 2018), which is consistent with the motor

system storing a history of errors (Herzfeld et al., 2014). Here, we would expect participants that

experienced more error switching, through their unique history of missing the target, to suppress implicit

adaptation more quickly and fully (Albert et al., 2020).

Second, the difference between rotations and mirror-reversals could be thought of as a

reparameterization, as previously considered in rotations, compared with learning a completely new

structure, suggested for the mirror reversal (Braun, Aertsen, and Wolpert, 2009). The reparameterization

of the transformation matrix, as seen in adaptation to a rotation, might be the fundamental function of the

implicit process. Indeed, the implicit process may be exceptional at matrix reparameterization. In

contrast, learning a mirror reversal requires learning the full structure of the task, including the

relationship between parameters in the transformation matrix. It appears that the implicit process tries to

reparametrize the transformation matrix as if it were a rotation even if doing so is inappropriate for the

task. Only after days of training does the implicit process appear to stop reparametrizing inappropriately.

It could be that once a new structure is specified, the structure of the mirror reversal, the implicit process

becomes appropriate for this new structure. The speed of learning this structure would dictate how

quickly implicit processes began reparametrizing appropriately.10

A slightly lower-level of description of this problem, one rooted in control engineering, was put

forth in a recent study by Hadjiosif and colleagues (2021), which compared adaptation under a

visuomotor rotation and a mirror reversal as a way to distinguish between updating forward model

updating and updating a control policy. They too find that the implicit process in a mirror reversal was

directed in the wrong direction to counter a mirror reversal, which is inconsistent with the updating a

forward model. Instead, implicit learning of a mirror reversal may require direct updating of a control

policy. Learning a new control policy would again have the outcome of changing the structure of the

transformation matrix.

These explanations are highly speculative, and additional research is necessary to pin down the

reason for implicit processes being counterproductive in a mirror reversal task, and the subsequent

suppression of implicit recalibration.”

Much of the discussion (lines 443-512) is devoted to the topic of proceduralization and theories of motor

learning. This seems off topic both in terms of the central question in the manuscript and the design of the

experiments. It also seems largely speculative. We recommend reducing this part of the discussion to no

more than 20 lines (slightly less than a page).

We have significantly reduced the proportion of the discussion that is dedicated to the topic of

proceduralization. We do believe it is relevant and should be discussed in light of our results, especially

given recent resurging interest in this topic. It has now been reduced to ∼35 lines of text.

There is no clearly set out discussion of the studies limitations. This should be added. It should discuss, at

the least, the intersubject variability, the relatively small number of subjects, the relatively limited amount

of training in the tasks, and the interpretational difficulties associated with measures of explicit and

implicit adaptation.

We have addressed this concern in various places throughout the manuscript, particularly in the

discussion on pages 29-35. We made sure to highlight potential reasons for the high degree of between subject variability we observed and differences in reporting measure versus aftereffects.

Minor comments

Line 44: asymptotic adaptation remained partial instead of insufficient?

The authors’ continuous implicit measure is solely derived from explicit reports. They also use aftereffects

as a measure of the final implicit adaptation. This can be problematic since these measures have been

found to differ profoundly in many situations (Taylor et al. 2014, Bond et al. 2015, Leow et al. 2015,

Bromberg et al. 2019). The authors themselves find a mismatch between these two measures. It has been

suggested that implicit adaptation as derived from reporting may not measure the same as the aftereffect

(see preprint by Maresch et al. 2020). This mismatch between measures should be addressed in the

discussion of possible limitations of the study.

Following up on our response above, we agree that it would be good to discuss this issue in the

manuscript. An entire section entitled “Limitation of the Implicit Process and Measurement Reliability"

has been added to the discussion, in particular (page 31, lines 493-509):

"An additional possibility for the limited degree of implicit recalibration observed here, as well as the

variability between participants, may be the result of explicit strategy use. While several studies

suggested a considerable degree of independence between implicit and explicit processes (Mazzoni and

Krakauer 2006; Taylor and Ivry 2011; Taylor et al., 2014), this has recently been challenged.

Participants who reported their explicit aiming direction throughout training, showed less implicit11

recalibration than participants who were only probed at the end of training (Maresch and Donchin

2020). By asking participants to report their aiming location on each trial, learning may be shifted more

toward explicit strategies. It should be noted that in the original study of the aim report method, there

was very little difference in the size of aftereffects between groups that reported on each trial versus never

reported (Taylor et al., 2014). This was, in part, our reasoning for not including a no-report control

group in conjunction with the difficulty of recruiting participants for a five-day study where the primary

dependent measure (i.e., aftereffects) occurs only once at the end of the study. What’s more, like Maresch

and Donchin (2020), we too find no correlation between the degree of implicit adaptation measured via a

subtraction measure during training and the size of the aftereffect. Nonetheless, implicit adaptation

appeared limited in both measures. Clearly, more work is needed to flesh out this psychological

equivalent of the measurement problem.”

Many analyses are not described in the methods (individual subject differences, regression comparing

adaptation at the end of each day to beginning of next day, comparison between implicit and aftereffect

on day 5). These should be included in the methods section. Was online or endpoint feedback used during

rotation trials? The description is somewhat confusing: line 125: a small circular cursor (0.15 cm 125

radius) provided online feedback and then line 136: endpoint feedback was displayed for 500 ms.

Apologies for the lack of clarity here. There was both online and endpoint feedback provided as follows:

Online feedback was provided throughout the reach, but once the hand past 7 cm (the target distance), the

cursor was frozen at the position for 500 ms (endpoint).

Page 9, lines 159-164:

"During each trial, once the right hand moved out past 7 cm, endpoint feedback was displayed for 500

ms in a position contiguous with the last point of on-line feedback. If the position of the cursor completely

overlapped with the target (< 1 deg. of angular deviation), the subject heard a pleasant “ding”.

Otherwise, an unpleasant “buzz” sounded. The feedback “Too Slow” was given if the reach time from

start to 7 cm exceeded 600 ms (<1% of trials, these trials were excluded from further analysis).”

Is there a reason that 12 targets were used in Experiment 1? How many targets in Experiment 2 (I think 4,

but it’s not explicitly stated)?

We used 16 targets in experiment one to cover the full learning space. Since experiment 1 used a 45

degree rotation, we wanted to replicate the same size perturbation in the mirror reversal task of

experiment 2. Target location in the mirror task defines the size of the perturbation. For example, a target

at 0 degrees (in a standard Cartesian) results in a 180 degree perturbation in the mirror task. Likewise, a

target at 67.5 degrees results in a 45 degree perturbation (hand goes to 67.5 and cursor is reflected across

the y-axis and goes toward 112.5 degrees). Given this constraint, we could only have 4 targets to provide

a consistent 45 degree perturbation.

Page 10-11, lines 193-197:

"In order to allow comparison between the two experiments, the four targets in Experiment Two (Mirror Task) were located 22.5{degree sign} from the midline so that the solution to the perturbed reach was a 45{degree sign} angle.

The 12 targets in Experiment One were evenly spaced 22.5{degree sign} apart on the aiming ring (Figure 2). Both

experiments were programmed such that each of the targets appeared before any was again repeated.”

Reaction time calculation line 186-187: Reaction times were calculated as the interval from target

appearance to aim-report, except where noted. The authors call the “re-aiming reaction time”. While this

seems appropriate, I’m still wondering in how far this really reflects an actual reaction time. A short12

discussion about what this type of reaction time means and how it differs with other reaction time

calculations would be desirable.

In full disclosure, we didn’t design the study with reaction times in mind and participants were not under

any time pressure, so our reaction time measures should be viewed with caution. We don’t feel

comfortable speculating as to the number of processes that could be subsumed under this measurement

(fixating the target, selecting an aim location, tapping the touchscreen, planning the movement with the

right hand, etc.).

Page 8, lines146-148:

"Subjects were instructed to proceed through the experiment as quickly as possible, however, there was

no time limit for tapping the aim location or beginning the reaching movement.”

Line 233: How is the SEM calculated? Did the authors account for within subject variability?

Our SEM calculation is only between subject variability. We found the square of the difference between

each data point (subject) and the sample mean, finding the sum of those values. Then, that sum was

divided by the sample size minus one (variance). Taking the square root of this variance results in the SD.

Finally, we divide the SD by the square root of the sample size (12) to give us SEM.

Line 235-237: the authors are correct that a direct comparison of explicit and implicit is inappropriate.

However, the authors can measure the percentage of total re-aiming that is accounted for by explicit

adaptation and test how this changes over time. This would answer the question the authors are getting at

here.

Our intent here was simply to report the explicit and implicit values, but we didn’t want a reader to think

that we should do any comparisons between explicit and implicit since implicit is defined as hand angle

minus implicit.

Figure 4 & 11: Calling subject 4C representative seems problematic. Subjects seems to have a uniform

distribution of implicit adaptation between 0 and 20{degree sign}, with two outliers having implicit

adaptation near 40{degree sign}. Thus, subject 4C is not necessarily more representative than subject 4B.

Perhaps in this and all similar plots, it makes more sense to present the median subject, rather than

claiming that anyone is representative?

Apologies for the confusion here. Our use of the word “representative” in the figure caption “A subject

(#6) representative of the average taken from the middle of the distribution,” was a poor choice in

wording. We were purposely avoiding the “representative” subject. Instead, we were trying to illustrate

the diversity in adaptation curves across the group. We rank ordered the subjects in terms of implicit

adaptation (Fig. 4A), then showed the subject with the least (Fig. 4B), median (Fig. 4C), and most

implicit adaptation (Fig 4D). Our use of representative here was meant to simply mean that the subject in

the middle is the median subject and represents the implicit value observed in the average. We have

removed the word representative entirely.

Line 300: saying that “implicit adaptation was constrained” overstates the case. It was only constrained in

some subjects.

The wording has been adjusted as follows on page 19, lines 331-334:

"On average, we found the implicit process to be constrained, which is consistent with the findings from

studies examining the capacity of single-session implicit learning. However, we saw great variability13

between subjects, including evidence from two subjects that implicit recalibration could eventually

replace explicit re-aiming.”

Figure 11: some subjects’ implicit adaptation seems appropriate for the mirror reversal; this should be

mentioned in the text.

The following is included in the text on page 23, lines 371-376:

"As with the visuomotor rotation, there was significant variance in how subjects responded to the

visuomotor mirror reversal (approximately -15{degree sign} to 15{degree sign}, Figure 11). Subjects were successful through a

combination of implicit adaptation and explicit re-aiming, lost all implicit adaptation by the end of

training, or reversed the direction of implicit adaptation. Reversed, visualized as negative, implicit

adaptation is appropriate for the mirror reversal task.”

The figure order is switched between the rotation and mirror experiments. This is confusing. To maintain

the proper order, the figures for the mirror experiment should be first figure 13, then figure 11, then figure

12, then figure 10.

Thank you for pointing this out. We have rearranged the figures as suggested.

Typos:

Line 115: made

Line 229: measured

Line 422: underlying

Line 443: admit instead of submit?

The typos have been fixed.

Reviewer 2

ADVANCES THE FIELD

The idea of testing for implicit adaptation in the context of a mirror-reversal is interesting. The finding

that it is gradually suppressed over 5 days may spark further research. There are also interesting analyses

regarding inter-individual differences in implicit adaptation.

STATISTICS

Small sample sizes (n=12) but the authors use caution when interpreting, especially correlations.

We agree that a sample size of 12 subjects is on the smaller side. As discussed above (on page 5 of this

response letter), an a priori power analysis was too optimistic (∼2 subjects). As such, we opted to recruit a

sample size that is typical of visuomotor adaptation tasks (10-15 subjects). While we observed quite a

range of variation between subjects, an individual’s behavior was much more consistent across days, and

we tried to be very transparent about the diversity of behaviors between subjects. In the end, we don’t

think that recruiting more participants would radically change the results. As the reviewer noted, we made

sure to be extra cautious in interpreting the results.

COMMENTS

Here the authors report two experiments in which participants (n=12 in each) are exposed to either a 45

deg visuomotor rotation or a mirror-reversal perturbation over 5 consecutive days. They find that for the14

rotation, implicit adaptation saturates at ∼15 deg and remains stable for each participant across days, but

is highly variable across participants. During mirror-reversal implicit adaptation is gradually suppressed

over the 5 days.

The work is properly conducted, generally clear and provides novel insight regarding implicit adaptation

in the context of visuomotor rotation and mirror-reversal. My main issue is that the work is framed around

a debatable working hypothesis that I feel takes away from the novelty of the findings. I have other

(minor) comments to ameliorate the paper.

I have a problem with the framing of the paper. It’s unclear why the author assume (or test the hypothesis)

that implicit adaptation processes would potentially be making a large contribution to motor skill learning

the novo. In my opinion (and to much of the field), there is a pretty clear line between adaptation (a

recalibration process of a previously learned movement) and motor skill learning (acquiring an entirely

new motor control policy); they are distinct processes that serve different functions (see this recent review

for instance: Spampinato and Celnik 2020, Neuroscientist). Even the authors apparently get this (line 47 :

"It is difficult to see how asymptotically constrained implicit adaptation could produce long-term motor

learning in the absence of explicit re-aiming.”; see also line 426). I do not understand why the authors

make a conundrum off of this. Overall this leads the authors to conclude that implicit adaptation cannot

account for motor learning de novo, which is quite expected and not very compelling (eg. last sentence of

abstract: “implicit adaptation processes, as studied in sensorimotor adaptation paradigms, may only make

subtle recalibrations of an existing skill and cannot contribute to motor skill learning de novo” ; or sig

statement: “These findings question the utility of implicit adaptation processes to motor skill learning

more broadly”). I think this framing reduces the novelty/excitement of the findings. This is perhaps best

exemplified on line 511: “we hold that classic implicit adaptation is not the driving force behind motor

learning, but that another system is largely responsible.” Sure! Was there actually any current model or

theory that entertained this possibility?? If we were to generalize, would the authors also hypothesize that

visuomotor adaptation have anything to do with other types of de novo motor skills, like sequence

learning? I suggest the authors either bolster their case for why we would expect that implicit adaptation

would fully account for de novo motor skill learning (emphasizing more on current literature - and less on

19th century Stratton) or change their premise and focus on the actual results (saturation over 5 days, or

decrease in the mirror-reversal). I prefer option 2.

We feel that this is a very tricky issue to address. We (obviously) agree with the reviewer that implicit

adaptation appears to be very different from de novo motor skill learning and this view has gained

attraction in recent years (as pointed out in reviews by Spampinato and Celnik 2020 and Krakauer et al.,

2019). However, in many of the foundational papers that motivated the internal model adaptation

framework, it has been suggested that adaptation of an internal model formed a critical aspect of motor

skill learning. And sensorimotor adaptation tasks have been viewed as studying internal model adaptation

(what we believe would be viewed as implicit adaptation). Furthermore, it is very often the case that a

study is motivated by describing skill learning and then there’s a switch to studying a sensorimotor

adaptation task (the senior author here is likely guilty of this very “bait-and-switch”).

Just a quick look through some “foundational” papers for the internal model framework:

Jordan and Rumelhart (1992) setup their paper saying “Consider a skill-learning task such as that faced by

a basketball player learning to shoot a basket” and then proceed to build-up the internal model

framework. Cognitive Science.

Mussa-Ivaldi (1999): “The acquisition of complex skills is facilitated by internal models of limb

dynamics”. Current Opinion Neurobiology.15

Wolpert, Ghahramni, and Flanagan (2001): “Skilled motor behaviour requires both inverse and forward

internal models. Motor learning can be viewed as the acquisition of forward and inverse internal models

appropriate for different tasks and environments.” Trends in Cognitive Science.

Shmuelof et al., (2011) takes a more nuanced view, but includes adaptation as a mechanism of skill

learning: “We propose that motor skills are acquired through the combination of fast adaptive processes

and slower reinforcement processes.” Neuron. We note that this group has carved off adaptation as a

process unrelated to skill learning now and, in fact, recently published in The Journal of Neuroscience

entitled “Did we get sensorimotor adaptation wrong? Implicit adaptation as direct policy updating rather

than forward-model-based learning” clearly challenging aspects of the internal model framework.

However, we cannot be absolutely sure if the authors held the view that studying adaptation tasks was a

model for motor skill learning at the time of writing these papers. Furthermore, given the conviction of

the reviewer that no one really held this view and our agreement that implicit adaptation cannot form the

basis of skills, we have reframed the paper to take a view that is at least consistent with adaptation

forming part of a motor skill execution - this may be a more reasonable, consensus view. Nevertheless,

our findings are still problematic for this view, as implicit adaptation can work in opposition to task

performance and appears to be limited on average.

We have reframed the manuscript with this view throughout.

Abstract

These findings are consistent with a handful of recent studies suggesting that implicit adaptation

processes, as studied in sensorimotor adaptation paradigms, only make subtle recalibrations of an existing

skill and cannot contribute to motor skill learning de novo. However, individuals solve the task in a

highly heterogeneous fashion, with some compensating using implicit adaptation and others relying on

explicit re-aiming. This heterogeneity calls into question the usefulness of using group-level data when

analyzing explicit re-aiming and implicit adaptation in visuomotor adaptation tasks.

We agree with the reviewer, looking at only the averages can be highly misleading and doesn’t reflect the

diversity of the study population. This is why we presented data from individual subjects that spanned the

"distribution” in addition to the mean. We have now included a meta-analysis from a number of data sets

from our lab examining the dissociation between explicit and implicit learning in visuomotor rotation task

(page 8, above). Again, we observe a similar level of heterogeneity at the individual level.

We should note that we don’t think that individuals are volitionally choosing to solve the task differently

but given their own personal limitations in implicit adaptation may need to have a larger proportion of the

rotation compensated for through an explicit re-aiming strategy.

We have underscored this problem of averaging in our discussion (page 35, lines 593-594): “This

variation questions the validity of averaging over subjects to make claims about implicit processes"

Significance Statement

In this set of studies, we find that implicit adaptation cannot fully account for learning in adaptation tasks,

such as the visuomotor rotation and mirror reversal tasks, even following several days of training. In fact,

implicit adaptation can be counterproductive to learning. These findings question the utility of implicit

adaptation processes to motor skill learning more broadly. However, we find significant between subject

differences that call into question traditional interpretation of these group-level results.

The very large inter-individual differences in implicit adaptation are really intriguing (and almost

worrisome for all who rely on this task to learn something robust about the brain!). It would be nice if the16

authors discussed this more in depth, what this means in terms of the relative interplay between implicit

and explicit processes, how it is (un)related to the measured aftereffects, and the broader implications. At

current, the discussion is relatively heavy on the explicit process (which was not the main question of the

paper) and relatively light on these interesting findings.

We hope that our inclusion of the meta-analysis (page 8, above) and resulting discussion of the individual

differences has helped bring attention to this issue.

The following is included in the discussion on page 30, lines 479-486:

"Enormous variability, spanning the entire range from zero to full adaptation through implicit processes,

was seen across individuals. This suggests that the traditional method of averaging over participants is

simplifying, and perhaps obscuring, experimental results (Gallistel 2004). It remains an open question as

to why there is such a degree of inter-subject variability; however, this degree of variability has been

observed in several studies where for even small rotations, on the order of 3-10{degree sign}, they found implicit

recalibration ranging from nearly zero to almost 50{degree sign} (Stark-Inbar et al., 2017; Morehead et al 2107; Kim

et al., 2018; Kim et al., 2019).”

I do not understand where the data for each day are in figures 8A and 9A (line 325).

The x-axis was confusingly labeled by bin number. It has been adjusted to indicate days.

Why isn’t there a figure like figure 3 for the mirror experiment? Also please order the different analyses

and figures the same way for both exps. (the aftereffects figure is not at the same place in both).

Rotating all the targets to a common axis in the mirror reversal task isn’t as straightforward as it is in a

visuomotor rotation task. The mirror reversal task is effectively like a dual adaptation task where different

targets have different rotation directions applied (CCW in quadrant 1, CW in quadrant 2, CCW in

quadrant 3, and CW in quadrant 4). This is why we opted to both include the state-space model

predictions and keep the data separated for the quadrants with common directions as if it were a rotation

task. Of course, we can do extra folds of the quadrants and flipping signs to get onto a common axis, but

we felt that this becomes much less transparent. Below is an example of the data all rotated and flipped to

a common axis, but we would prefer not to include this in the manuscript unless the reviewer has a strong

preference for it.17

The ordering of figures has been changed to be more symmetrical with experiment 1.

Minor comments:

Line 35: “dissociated"

Line 115: “made” a reaching movement

Typos fixed.

Some aspects of the methods are not clear:

Line 118-123: Please present the time allowed for the tapping.

In full disclosure, we didn’t design the study with reaction times in mind and participants were not under

any time pressure, so our reaction time measures should be viewed with caution.

Page 8, lines 144-148:

"Once an aim was recorded, the target turned from orange to green, the aiming ring disappeared, and

the subject was able to begin their reach with the right hand (see Figure 2). Subjects were instructed to

proceed through the experiment as quickly as possible, however, there was no time limit for tapping the

aim location or beginning the reaching movement.”

Line 164-170: the target locations are not obvious for the mirror.

An additional panel was added to the methods figure (Figure 2) in order to more clearly illustrate the

target locations.

The intuition behind the 2 experiments is not obvious by just reading the methods. The first paragraphs of

the results for each exp (line 223 and 309) are helpful and could be presented earlier.

We added this summary at the beginning of the Methods section on page 13, lines 249-251:18

"In two experiments, twenty-four subjects participated in a visuomotor rotation task for one hour each

day for five consecutive days. Subjects attempted to compensate for a visual perturbation of 45{degree sign} while

reaching to targets that appeared on a circle centered on the start-position.