The authors have done an excellent job at addressing my comments to the previous version. I appreciate in particular that they are now willing to test a substantially larger number of participants and that the ms now addresses the question of the low sensitivity in awareness tests. I only have relatively minor comments to the present version:

On page 7 the authors write “We hypothesise that if the participants are aware of the the relationship between auditory and visual distractor location regularities, we expect that the score received by each location linearly decreases from its distance from the actual HpValD location”. The sentence sounds a bit mysterious because the reader still has no clue as to how locations will be scored. This is not explained until page 15.

The new power calculations basically assume that the expected effect size is roughly the same in reaction times and in the awareness test (i.e., d = 0.45). But the former are measured over hundreds of trials and the latter are measured in just six questions. Implicitly, this means that the authors expect each question of the awareness test to be much more sensitive and informative than each trial of the visual search task, which is an arguable assumption, in my opinion. I am not asking the authors to make any change in the ms regarding this. I am just trying to highlight a recurrent problem in this area of research. There is a great paper about this problem by Sascha Meyen in JEP:General. https://www.tml.cs.uni-tuebingen.de/team/luxburg/publications/MeyenEtal2021.pdf

The author has answered my questions adequately. I have no further comments. 

The registered report “Do task-irrelevant cross-modal statistical regularities induce distractor suppression in visual search? ” is well written and has a valid research question. The logic and rationale of the proposed hypotheses are clear. Also, the methodology is sound, clear and replicable. The authors have also considered additional outcome-neutral conditions for manipulation checks. Some concerns are listed below.

On p.5, at the end of the first paragraph, the authors claimed that there seems to be enough evidence to support that our brain learns and utilize statistical regularities of both task-relevant and task-irrelevant sensory stimuli for optimizing behaviour. Given the authors only mainly introduced the influence of statistical regularities of the salient distractors in the previous part, they should make it more clear the evidence about task-relevant and task-irrelevant stimuli, respectively. 

The authors have included Chen et al.’s crossmodal contextual cueing studies which are quite relevant. However, I suggest the authors consult more crossmodal selective attention literature. For example, Spence C’s lab has done a lot of studies on this topic. 

For the data analysis, the significance level alpha is set to 0.02. Why not use an alpha level of .05 that is commonly used to better balance the issues of Type I and Type II errors?

Overall, this is an interesting research proposal and I would like to see the outcome in the near future. 

The main goal of the two experiments proposed in this RR is to explore whether distractor inhibition in the additional singleton task can be modulated by contextual auditory information. Specifically, the singleton distractor will be present more frequently in two particular locations, each of then cued by a distinctive sound. The question is whether participants will learn to use this sound to suppress attention to the location whether the singleton distractor is most likely to appear in that trial. Although this type of contextual modulations have been explored in other visual statistical learning paradigms, this is the first time that such an effect is tested in the additional singleton task. I think it can be quite interesting for researchers working in this area. I have relatively minor comments about the general procedure, design and context that I think should be easy to tackle in a revised version.

The authors (and editor) won’t be surprised to find out that I am a bit concerned about the awareness test included at the end of the experiment and the type of conclusions that can be drawn from them. The awareness tests included in this paradigm are almost always doomed to suggest that learning was unconscious. Participants’ learning is assessed through hundreds of visual search trials using a continuous measure (reaction times), but their awareness is assessed briefly in 2-4 yes/no questions. Logically this procedure is much more sensitive to detect a significant effect in reaction times than to detect an equivalent effect in awareness, introducing a strong bias to conclude that learning was unconscious. To be completely honest, this is not the authors’ fault: this kind of awareness tests is common in the area, but it happens to be highly misleading, and a well powered and carefully designed RR should avoid these shortcomings by all means. I am definitely not asking the authors to cite these papers, but to better appreciate these problems they might find useful to read our papers addressing this question in contextual cueing (Vadillo et al., 2016, PBR), location probability learning (Vadillo et al., 2020, JEP:Gen) and the additional singleton task (Vicente-Conesa et al., 2021, https://psyarxiv.com/yekvu/). In the particular case of location probability learning and the additional singleton task it is quite difficult to improve the sensitivity of the awareness test, because they are essentially a one-shot test, i.e., one cannot include more and more testing trials to improve the sensitivity of the awareness test, as can be done for instance in the contextual cueing task. But at least, one can try to complement the traditional yes/no dichotomous responses by continuous and potentially more sensitive measures. For instance, in the location probability learning task we have found that asking participants to rate the percentage of times the target has appeared in each quadrant is a more sensitive test than simply asking them to select a quadrant (e.g., Giménez-Fernández et al., 2020, JEPHPP). It is still a quite suboptimal measure, but slightly more sensitive. The authors can also consider replacing their yes/no or discrete choice responses by confidence ratings or any other response that provides a more nuanced and graded measure of awareness.

In any case, even if the authors decide to stick to this procedure (which I strongly advise against) I would still ask the authors to describe in much more detail what analyses they are planning to run on their awareness data. For the first and third questions (which are not very informative; this particular type of subjective rating is known to conflate “unawareness” with a conservative bias; see Flemming and Lau, 2014, https://www.frontiersin.org/articles/10.3389/fnhum.2014.00443/full), the authors plan to estimate the proportion of “yes” responses. But for the second and fourth question I don’t think they provide sufficient information to understand how they are planning to process and analyze these responses. They say that they will calculate the “distance between the locations indicated by the participant and the actual locations”. But how are they planning to do this? Recall that there are actually two high-probability locations and participants are selecting two locations. Let’s imagine that the actual locations are, say 1 and 5, and the participant chooses 2 and 3, for instance. How is this reduced to a single distance score? In addition, the authors say that they will analyze these scores by comparing them against zero. But I can’t understand the logic of this analysis. Shouldn’t the authors compare the observed score against the score that would be ideally observed if responses were completely random? I think that the authors need to provide much more detail here.

Power. The sample size was calculated to provide reasonable power to detect a d = 0.6 effect. But why is this effect size a good reference? I am sure that distractor suppression in the additional singleton task is usually much larger than this, but do we have any evidence to expect that the contextual (auditory) modulation of the effect, if true, will be larger than this? In relation to my previous note, the study also plans to determine whether learning was unconscious. Knowing that responses to the awareness test are likely to be quite noisy (see my previous paragraphs) would N = 39 be enough to test this hypothesis with sufficient power? I honestly doubt it. Our meta-analysis of awareness in the contextual cueing task yielded an average effect of dz = .31, and there are good reasons to suspect that the typical awareness test in the contextual cuing task is much more sensitive than the traditional test in the additional singleton task (e.g., it usually includes around 24 trials instead of one-shot responses). For the probabilistic cuing task we found an average awareness effect of h = .35, which requires at least 64 participants to reach just 80% power.

Minor comments

“task-irrelevant” -> the auditory stimuli are characterized in the ms as “task-irrelevant”. But given that they actually convey useful information (i.e., where the distractor is going to appear) I wonder if the name is actually fair. Wouldn’t it be better to refer to these stimuli as “contextual” stimuli instead?

At several points, the ms gives the impression that the studies explore how participants “anticipate” the distractors, i.e., how they are “perceptually suppressed by pro-active modulations” (p. 6). If the goal is to study anticipatory behavior, shouldn’t the auditory signals be presented before the search display instead of simultaneously?

p. 7 “HpValD” and “HpInVald”. The meaning of these acronyms only becomes clear in the following pages. Wouldn’t it be easier to understand the Hypotheses section if the previous paragraphs introduced the designed briefly, including the condition names?

p. 7 I found it a bit weird that the authors present Hypothesis 1:2 as an additional hypothesis. It is simply the negation of Hypothesis 1:1, isn’t it? Same comment in the Study Design Table.

p. 7 “… the former condition associated with the search trials… should produce fater RTs” Faster compared to what? Same problem in the following sentence.

p. 13. Note that the singleton distractors appear much more frequently in two locations than in any of the other locations. This is unavoidable, of course, but it is important to remember that it renders some of the statistical comparisons meaningless. For instance, there is no reason to compare either HpValD or HpInvalD with the low probability distractor location. Any significant difference could be due to either to the fact that the sound is unpredictive in the latter condition or to the fact that the distractor has appeared in a location where it seldom appears. It will be quite difficult to interpret this result. So, I wonder if it makes sense to include all four conditions in a single ANOVA (p. 17)

p. 19. In the awareness test, will participants understand what “colored non-target locations” are?

Signed,

Miguel Vadillo