There are two fundamental processes that the brain engages in: statistical learning and selection. Indeed, past work has shown these processes often come together: People can use a task-irrelevant stimulus to predict a target stimulus even in different modalities (crossmodal statistical learning), thereby enhancing the processing of the target stimulus (selection). Further, people can learn where a distractor will be in order to efficiently suppress it (selecting out), using task irrelevant stimuli in the same modality (within-modality statistical learning).
 
In two experiments Jagini and Sunny found that people did not learn to use a task-irrelevant stimulus from a different modality (cross modal statistical learning) to suppress a distractor (selecting out). They also found that people had little awareness of the relation between the predictor task-irrelevant stimulus and the location of the distractor. The results may reflect limits on what can be achieved unconsciously.

 

Following peer review, the recommender judged that the manuscript met the Stage 2 criteria and awarded a positive recommendation.

 

URL to the preregistered Stage 1 protocol: https://osf.io/qjbmg
 
Level of bias control achieved: Level 6. No part of the data or evidence that was used to answer the research question existed prior to Stage 1 in-principle acceptance.
 
List of eligible PCI RR-friendly journals:
 

 

 

1. Jagini, K. K. & Sunny, M. M. (2023). No reliable effect of task-irrelevant cross-modal statistical regularities on distractor suppression. Stage 2 Registered Report, acceptance of Version 4 by Peer Community in Registered Reports. https://doi.org/10.31234/osf.io/d8wes

Data sharing is perhaps the most fundamental step for increasing the transparency and reproducibility of scientific research. However, the goals of open science must be tempered by ethical considerations, protecting the privacy and safety of research participants. Bridging this gap causes challenges for many fields, such as human neuroimaging. Brain images, as measured with magnetic resonance imaging (MRI), are unique to the participant and therefore contain identifying information by definition. One way to mitigate the risk to participants arising from public data sharing has been "defacing" the MRI scans, i.e., literally removing the part of the image that contains the face and surrounding tissue, while preserving the brain structure. This procedure however also removes information that is not (or at least minimally) identifiable. It also remains unclear whether defacing the images affects image quality and thus the information necessary for addressing many research questions.

 

The current study by Provins et al. (2023) seeks to address this question. Leveraging a publicly available "IXI dataset" comprising hundreds of T1-weighted structural MRI scans, they will assess the effect of defacing on manual and automatic estimates of image quality. Specifically, the researchers will compare image quality ratings by experts for a subset of 185 images. They hypothesise that images in which facial features have been removed are typically assigned higher quality ratings. Moreover, using a full data set of 580 images, which have been obtained across three scanning sites, they will also test the impact defacing MRI scans has on automated quality measures obtained with MRIQC software. The results of this study should have important implications for open science policy and for designing the optimal procedures for sharing structural MRI data in an ethical way. For example, if the authors' hypothesis is confirmed, studies relying on MRI quality measures might be better served by a custodianship model where identifiable data is shared under strict conditions, rather than relying on publishing defaced data. More generally, the outcome of this study may have significant legal implications in many jurisdictions.

 

The Stage 1 manuscript was evaluated at the inital triage stage by the Recommender and PCI:RR team, and another round of in-depth review by two experts. After a detailed response and substantial revisions, the recommender judged the manuscript met the Stage 1 criteria and awarded in-principle acceptance (IPA).

 

URL to the preregistered Stage 1 protocol: https://osf.io/qcket (under temporary private embargo)
 
Level of bias control achieved: Level 2. At least some data/evidence that will be used to answer the research question has been accessed and partially observed by the authors, but the authors certify that they have not yet observed the key variables within the data that will be used to answer the research question AND they have taken additional steps to maximise bias control and rigour.
 
List of eligible PCI RR-friendly journals:
 

 

1. Provins, C., Savary, E., Alemán-Gómez, Y., Richiardi, J., Poldrack, R. A., Hagmann, P. & Esteban, O. (2023). Defacing biases in manual and automated quality assessments of structural MRI with MRIQC, in principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/qcket

Unconscious priming effects have fascinated not just psychologists but also ad-makers and consumers alike. A related phenomenon in perception is illustrated by presenting participants with two-tone images, which are degraded versions of images of objects and scenes. These two-tone images look like and are indeed judged as meaningless dark and light patches. Upon presenting the actual template image, however, the two-tone image is accurately recognized. This perceptual learning is abrupt, robust, and long-lasting (Daoudi et al., 2017). Surprisingly, Chang et al. (2016) showed that such perceptual disambiguation of two-tone images can happen even in the absence of conscious awareness of having seen the template image. 

 

Halchin et al. (2023) in the current study propose to conduct a conceptual replication of Chang et al. (2016) with important modifications to the procedures to address limitations with the earlier work. Specifically, there was no explicit manipulation of levels of conscious awareness of the template images in the original study. Therefore, miscategorization of low-confidence awareness as unaware could have led to an erroneous conclusion about unconscious priors guiding perceptual learning. Such miscategorization errors and how to tackle them are of interest to the broader field of consciousness studies. Furthermore, a conceptual replication of Chang et al. (2016) is also timely given that prior related work suggests that masking impairs not only conscious awareness of visual features but also blocks processing of higher-level information about the images (e.g. object category). 

 

To address the issues identified above, Halchin et al. (2023) propose to experimentally manipulate conscious awareness by masking the template image very quickly (i.e., a short stimulus onset asynchrony; SOA) or by allowing some more time to induce weak and strong conscious awareness, respectively. The SOAs were validated through pilot studies. Furthermore, they include a four-point perceptual awareness scale instead of the original yes/no options to gauge participants’ subjective awareness of the template images. The authors also propose multiple experiments to include different ways of testing participants’ objective ability to identify the masked template images. Last but not least, the proposed design includes a stronger control condition than the original study by using masked images created from related images (e.g. belonging to the same semantic category). Depending on the results obtained in the main experiments, the inclusion of this control allows the authors to conduct a third experiment to investigate whether the results in the first two can be explained by semantic priming. The proposed study is sufficiently powered (as demonstrated through simulations), and Bayesian statistical procedures will be used to test the main hypotheses. In summary, the proposed work offers a significant improvement in terms of experimental procedures over the original study. If the Chang et al. (2016) results are replicated, the stronger design in the current study is likely to lead to a better understanding of the mechanisms underlying unconscious priors guiding perceptual learning. On the other hand, a failure to replicate not just Chang et al. (2016)’s results but also effects across the three experiments in the current study would raise legitimate questions about the reality of unconscious information guiding perceptual learning. 

 

The study plan was refined across two rounds of review, with input from two external reviewers who both agreed that the proposed study is well designed, timely, and scientifically valid. The recommender then reviewed the revised manuscript and judged that the study met the Stage 1 criteria for in-principle acceptance (IPA).

 

URL to the preregistered Stage 1 protocol: https://osf.io/juckg
 
Level of bias control achieved: Level 3. At least some of the data/evidence that will be used to answer the research question already exists AND is accessible in principle to the authors BUT the authors certify that they have not yet accessed any part of that data/evidence.
 
List of eligible PCI-RR-friendly journals:

 

• Advances in Cognitive Psychology
• Collabra: Psychology
• Cortex
• Journal of Cognition
• Peer Community Journal
• PeerJ
• Psychology of Consciousness: Theory, Research and Practice
• Royal Society Open Science
• Studia Psychologica
• Swiss Psychology Open

 

 

1. Daoudi, L. D., Doerig, A., Parkosadze, K., Kunchulia, M. & Herzog, M. H. (2017). The role of one-shot learning in #TheDress. Journal of Vision, 17, 15-15. https://doi.org/10.1167/17.3.15 

 

2. Chang, R., Baria, A. T., Flounders, M. W., & He, B. J. (2016). Unconsciously elicited perceptual prior. Neuroscience of Consciousness, 2016. https://doi.org/10.1093/nc/niw008 

 

3. Halchin, A.-M., Teuful, C. & Bompas, A. (2023). Can one-shot learning be elicited from unconscious information? In principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/juckg

Ensuring universal access to sexual and reproductive health and reproductive rights is a global concern, exemplified by goal 5.6 of the Sustainable Development Goals (UN General Assembly, 2015). Whilst the range of contraceptive options have increased, our understanding of the impacts of use for women are inadequate and represent a key barrier to positive change in policies and practices. In particular, we have few consensuses on the expected impacts of hormonal contraceptive use on women's sexuality and wellbeing.

 

In the current programmatic submission, Botzet et al. (2023) argue that this inconclusive evidence base could be due to the wide heterogeneity in responses, the impacts of this heterogeneity upon attrition, differences in contraceptive methods and dosage effects, confounders, and the potential for reverse causality. Tackling some of these potential factors, Botzet (2023) explore whether hormonal contraceptive use influences sexuality and well-being outcomes, and whether (and to what extent) the effects vary between women. To achieve this they have proposed analysis of longitudinal data from the German Family Panel (PAIRFAM) which includes annual waves of data collection from >6500 women, with separate Stage 2 submissions planned to report findings based on sexuality and well-being. The proposed work will progress our understanding of the impact of hormonal contraceptives by overcoming limitations of more common research approaches in this field, and has the potential to contribute to a more contextualised view of the impact of their impacts in real-world practice.

 

The Stage 1 manuscript was evaluated over three rounds of in-depth review. Based on detailed responses to the reviewers' comments, the recommender judged that the manuscript met the Stage 1 criteria and therefore awarded in-principle acceptance (IPA).

 

 

Level of bias control achieved: Level 3: At least some of the data/evidence that will be used to answer the research question already exists AND is accessible in principle to the authors BUT the authors certify that they have not yet accessed any part of that data/evidence.

 

 

• Collabra: Psychology
• Peer Community Journal
• PeerJ
• Royal Society Open Science
• Studia Psychologica
• Swiss Psychology Open
  
  

 

Botzet, L. J., Rohrer, J. M., Penke, L. & Arslan, R. C. (2023). Hormonal Contraceptive Use and Women's Sexuality and Well-Being: Estimating Treatment Effects and Their Heterogeneity Based on Longitudinal Data. In principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/kj3h2

 

UN General Assembly (2015). Transforming our world : the 2030 Agenda for Sustainable Development, 21 October 2015, A/RES/70/1. Available at: https://www.refworld.org/docid/57b6e3e44.html [accessed 27 September 2023]

Subjective tinnitus is a common disorder in which people experience a persistent sound in the absence of any external source. The underlying causes of tinnitus are debated – although the condition is strongly associated with hearing loss resulting from auditory damage, much remains to be understood about the neural processes that give rise to the phantom perception. Various classes of neurophysiological theories have been proposed, including the “altered gain” model – in which neurons in the auditory pathway increase their responsiveness to compensate for reduced auditory input following hearing loss – and the “noise cancellation” model –  in which disrupted feedback connections from limbic regions are unable to tune out phantom signals. Although these theories account for much observed data, they have not been conclusively supported, and their ability to explain tinnitus is limited by the fact that hearing loss and tinnitus can arise independently and at different times.

 

In the current study, Reisinger et al. (2023) will test an emerging alternative theory based on a Bayesian predictive-coding framework (Sedley et al., 2016) in which the alteration of perceptual priors leads the auditory system to expect a sound that, if functioning normally, it should not expect. Using magnetoencephalography (MEG) in a sample of tinnitus patients (and carefully-matched controls for age, gender, and level of hearing loss), they will ask whether tinnitus is associated with anticipatory brain activation, tuned to the carrier-frequency of an expected auditory stimulus. Specifically, the authors predict that if the predictive-coding framework is correct then individuals with tinnitus should show different regularity-dependent pre-activations of carrier- frequency-specific information compared to the control group, while tone carrier-frequencies should be processed normally in tinnitus patients. They also predict that any such pre-activations should not be related to levels of reported subjective tinnitus distress, as measured with the short version of the Tinnitus Questionnaire (mini-TQ).

 

The Stage 1 manuscript was evaluated over two rounds of in-depth review. Based on detailed responses to the reviewers' comments, the recommender judged that the manuscript met the Stage 1 criteria and therefore awarded in-principle acceptance (IPA).

 

 

Level of bias control achieved: Level 3. At least some data/evidence that will be used to the answer the research question has been previously accessed by the authors (e.g. downloaded or otherwise received), but the authors certify that they have not yet observed ANY part of the data/evidence.

 

 

• Brain and Neuroscience Advances
• Cortex
• F1000Research
• In&Vertebrates
• NeuroImage: Reports
• Peer Community Journal
• PeerJ
• Psychology of Consciousness: Theory, Research and Practice
• Royal Society Open Science

 

 

Reisinger, L., Demarchi, G., Rösch, , S., Trinka, E., Obleser, L., & Weisz, N.  (2023). Registered Report: Are anticipatory predictions enhanced in tinnitus and independent of hearing loss? In principle acceptance of Version 4 by Peer Community in Registered Reports. https://osf.io/6gvpy

 

Sedley, W., Friston, K. J., Gander, P. E., Kumar, S., & Griffiths, T. D. (2016). An integrative tinnitus model based on sensory precision. Trends in Neurosciences, 39, 799-812. https://doi.org/10.1016/j.tins.2016.10.004