-->PONE-D-25-49173-->-->Implicit processes do not contribute to learning to reach in small mirror reversed environments-->-->PLOS One

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Reviewers' comments:

Reviewer's Responses to Questions

-->Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. -->

Reviewer #1: Partly

Reviewer #2: Yes

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-->2. Has the statistical analysis been performed appropriately and rigorously? -->

Reviewer #1: No

Reviewer #2: Yes

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-->3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.-->

Reviewer #1: Yes

Reviewer #2: Yes

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-->4. Is the manuscript presented in an intelligible fashion and written in standard English?

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Reviewer #1: Yes

Reviewer #2: Yes

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-->5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)-->

Reviewer #1: The manuscript investigates whether implicit processes contribute to learning small mirror reversals compared to small visuomotor rotations. The study addresses a genuine gap in the literature. The finding that successful mirror reversal learners show no implicit aftereffects while rotation learners do appears robust for the specific subset of participants analysed (but see below). The manuscript is overall well written. However, there are fundamental concerns regarding participant exclusion and task comparability that require major revisions to ensure the soundness and validity of the interpretations. Please see below, thank you.

1. Participant exclusion

The most critical issue is the exclusion of 45% of the mirror reversal group (9/20 ppts) as "non-learners", compared to 0% in the VR group. The authors currently relegate this data to supplementary materials, but in reality the difference in attrition rate is too substantial to be treated as a minor limitation. It fundamentally affects the interpretation of the results and the comparability of the tasks. Excluding nearly half of one experimental group while retaining all participants in the control group is at high risk of creating a selection bias. The authors should integrate the non-learner data into the main text rather than treating it as supplementary. This includes performing full-sample analyses that incorporate all 20 recruited participants in the mirror reversal group.

Moreover, the 3 SD learning criterion for inclusion appears arbitrary and thus a sensitivity analysis would be a sensible approach to demonstrate how the results and conclusions change under different inclusion criteria (eg 2 SD, 2.5 SD, 4 SD). The goal here is to determine whether the absence of implicit learning is a robust feature of the task or instaed an artefact of examining only the most successful learners.

2. Tasks comparison

The central premise of the study is a comparison between two "matched" 20° distortions. However, there appears to be a fundamental asymmetry in task complexity that challenges this equivalence. A 20° VR provides a time-invariant error signal regardless of reach trajectory. In contrast, a MR represents a dynamic and state-dependent transformation where the error magnitude and direction vary with hand position. The fact that one task yielded a 100% success rate while the other only 55% points strongly to the hypothesis that these tasks may not be matched in difficulty.

The manuscript should explicitly address this asymmetry: the authors need to consider whether the lack of implicit learning in the mirror reversal condition stems from the nature of the error signal itself, which is a mechanistic explanation distinct from the claim that the task engages a wholly different learning system.

3. Statistical power

Given the high exclusion rate as per above, the final sample size of N=11 for the MR group raises concerns about statistical power. On this note, the reported BF10 of 0.340 offers only moderate support for the null hypothesis, not strong. The authors should conduct more robust statistical tests, eg mixed-effects model on the full sample with learning magnitude as covariate, rather than solely relying on ANOVAs of the filtered subset.

4. RT data

RT is not a pure measure of explicit strategy but could also reflect computational demands, response selection difficulty, motor planning complexity et cetera. The current version of the manuscript implies a direct causal link between elevated reaction times and explicit processing. The authors should revise this language to be more cautious, acknowledging that the data may also reflect the increased cognitive load inherent in calculating the mirror transformation

Reviewer #2: This paper explores the nature of adaptation which occurs in response to a small mirror reversal. While small visuomotor rotation perturbations typically elicit implicit learning, it is unknown whether this is the case for a small mirror reversal. Using a Kinarm, small visuomotor rotations or mirror reversals were imposed during target-directed reaching movements. The results demonstrate that while participants in both groups were able to learn the perturbation to the same extent, the mirror reversal group showed virtually no aftereffects. This suggested that mirror reversal learning was not mediated through implicit processes and may occur through different mechanisms than visuomotor rotation learning.

Overall, I find the manuscript to be well-written and interesting. The introduction is clear and sets up the experiment well. The overall conclusions made by the authors are consistent with the findings. I have some questions regarding the methodology and results and suggest some discussion points to consider further.

Rotation size: In this paper, a 20-degree rotation is referred to as small. I would argue that many researchers would not consider this a small rotation, as many studies use perturbations as small as a few degrees. Is it referred to as small due to previous literature showing a 20-degree rotation typically only elicits implicit adaptation? This is somewhat dependent on whether the participant is told about the rotation, and/or given a strategy to use. Please consider clarifying this further in the introduction and defending the notion of 20-degrees being ‘small’.

Participant instruction: Instructions to the participants during the VR and MR trials have not been reported. Were the participants informed of the perturbation, and if so, what were they instructed to do? Please clarify.

Figure 2: In panel B and C, the cursor rotation appears to be less than 20 degrees. Please modify so that the angular difference between the cursor and target is comparable between the VR trials and MR trials. Additionally, you may consider removing the timeline from each individual panel and only keeping it at the very bottom of the figure below E (like a shared x-axis).

Confirmation of learning: What was the justification behind choosing a difference of at least 3 standard deviations between late baseline and late learning as the cut off for determining learning?

Experimental groups: In typical VR experiments, adaptation data from CW and CCW groups are collapsed and analyzed together. While I understand that rotation in only one direction is directly comparable to MR for each respective target, please elaborate on why these were analyzed as separate groups, especially considering there was no notable differences between these two rotation directions.

AE variability: How was AE variability calculated? In any case, only a singular value over 24 trials was obtained for each participant. Considering that the time series of adaptation behaviour is not stationary (follows a curve), this may not be the best method to capture trial-by-trial changes. This is especially important considering the argument made in the discussion that motor variability can suggest exploration and may suggest a mechanism for learning in the MR task. Seeing as this may be an important measure, consider clearly describing how it was calculated, and alternative methods that may be used to fully describe variability behaviour.

Reaction times: Are the reported SD values the SD of mean RT’s between participants or the mean of within-participant RT SD’s? Please specify whether these reflect within or between subject values. Additionally, there seems to be large differences in SD values across groups. Could this be used as another indicator of different strategies being used? Is this something to analyze further?

Magnitude of AE: mean values for AE magnitude are not reported in the results. Consider including these values when reporting the statistics for learning.

Figure 3A: I appreciate that this figure has been separated for each group (keeping CW and CCW separate) and target. However, considering that there were no significant differences between target position or rotation direction, did you consider collapsing across either/both variables for visualization? Considering the main findings from the learning phase revolve around the differences between VR and MR, you may consider adding a visualization where some of these groups are collapsed. Additionally, the SEM’s for each group look tight, even for the MR group. How does this coincide with the increased AE variability in this group?

Implicit adaptation: It appears the exclusion trials within the learning phase were not analyzed. What were these trials intended to tell us? Additionally, there is only 1 figure showing implicit learning, and it only represents a singular value for each participant. Considering how important implicit adaptation is towards the research question, would there be a way to plot the time course of the exclusion trials over the learning and learning assessment phases?

Non-learners: It is quite interesting that nearly half of the participants could not learn the MR perturbation. Given the large number of participants who did not learn, it may be of interest to move some of these data from the supplementary files to the main results (e.g., Figure 1A and 1B). Further, does the claim that “there were no learning related differences between the MR-L and MR-NL groups” refer to the lack of AE variability between groups, or mean AE? Would a lack of difference in AE variability between the groups suggest that although the non-learners were unable to successfully adapt, they were still engaging in similar exploration strategies compared to the learners? Additionally, it appears that many of the ‘non-learners’ adapted in one target direction. Why might this have been the case? Further speculation/discussion around these issues could enhance these results.

Sensory prediction error (SPE) in the MR task: in the discussion (lines 414-423), it is described that the SPE may be driving implicit adaptation. This raises an interesting question – why is the SPE in the MR task being treated differently? Early work (Mazzoni & Krakauer, 2006) suggested that implicit adaptation to an SPE can override explicit strategy, but perhaps here we are seeing the opposite. Why might this be the case?

Number of trials: it can be concluded from the current MR data that no implicit learning occurred, and nearly half the participants were not able to learn it. Could this have anything to do with the number of trials used? Would implicit adaptation potentially develop if there were more trials or multiple sessions? Additionally, would the non-learners eventually learn the perturbation?

Additional comments:

1. Line 58: bracket missing

2. Line 126: delete ‘were’

3. Line 399: typo: ‘contributed’

4. Typo in supplementary figure 1A: “MR-NL left target” label; “L” not capitalized

5. Ensure citation style stays consistent throughout the paper (Vancouver vs APA)

6. I would suggest adding a README file to your OSF page. Although all the data is accessible, it is not clear what values are given in each excel sheet. Additionally, I would suggest ensuring the code will run without edits from the user (e.g., they will have a different working directory). You may also consider editing the comments in the code to tell the reader which figure is being generated (e.g., “Figure 3”). These changes will help make your data and code more accessible.

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Reviewer #1: No

Reviewer #2: No

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-->PONE-D-25-49173R1-->-->Implicit processes do not contribute to learning to reach in small mirror reversed visuomotor environments-->-->PLOS One

Dear Dr. Heirani Moghaddam,

Thank you for submitting your manuscript to PLOS ONE. Both reviewers are satisfied with the revised version. Yet, they both raised some minor comments that should be addressed before a final decision is made. Please find these suggestions below.

Please submit your revised manuscript by Jun 22 2026 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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-->

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We look forward to receiving your revised manuscript.

Kind regards,

Dimitris Voudouris

Academic Editor

PLOS One

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Reviewer's Responses to Questions

-->Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.-->

Reviewer #1: (No Response)

Reviewer #2: (No Response)

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-->2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. -->

Reviewer #1: Yes

Reviewer #2: Yes

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-->3. Has the statistical analysis been performed appropriately and rigorously? -->

Reviewer #1: Yes

Reviewer #2: Yes

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-->4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.-->

Reviewer #1: Yes

Reviewer #2: Yes

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-->5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.-->

Reviewer #1: Yes

Reviewer #2: Yes

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-->6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)-->

Reviewer #1: I thank the authors for their thorough revision. I am happy to accept, with just one fifnal comment: the Bayes factors for the MR-L and MR-NL groups (BF₁₀ = 0.340 and BF₁₀ = 0.324, respectively) really correspond to anecdotal evidence for the null on standard scales (e.g., Lee & Wagenmakers, 2013), that is, just below the conventional threshold for moderate evidence. The authors may wish to relate the BF values to a standard evidence scale when describing the strength of support for the null

Reviewer #2: I would like to thank the authors for their thorough integration of my previous comments. I only have minor comments remaining.

AE Variability calculation: While I thank the authors for clarifying how they calculated angular variability, I still have some questions regarding this measure. Calculating variability by taking the SD over 24 trials may be a reasonable method for late learning, as participants have reached a plateau. However, during early learning, the SD doesn't necessarily tell us about the variability in reaching movements, since the mean is changing (as they are learning to adapt). This is further exemplified when stating that there was greater variability in early learning compared to late. This could simply be due to the fact that the AE values during early learning are much more spread out as the participant adapts. Is this a limitation in the variability measure? If so, consider identifying this limitation within the manuscript. Alternatively, other measures could be used to determine variability, such as performing a simple curve fit and using the mean residuals based on the fit as a measure of variability.

Figure 3A: It appears that the VR CW group is missing from figure 3A. Please amend this figure or clarify if any groups have been collapsed here in the figure caption.

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Reviewer #1: No

Reviewer #2: No

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Implicit processes do not contribute to learning to reach in small mirror reversed visuomotor environments

PONE-D-25-49173R2

Dear Dr. Heirani Moghaddam,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Dimitris Voudouris

Academic Editor

PLOS One

Additional Editor Comments (optional):

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