‘Pseudoneglect’ is a small, lateralised bias of visuospatial attention towards the left side of space, and is typically observed in healthy adults. Recently, Strauch et al. (2022) reported that bright stimuli presented in the left visual field induced a greater constriction of the pupil (the pupillary light reflex) compared to the same bright stimuli presented in the right visual field. Further, the pupillary restriction bias was positively correlated with a behavioural measure of pseudoneglect (the greyscales task). This is potentially an important development for attention research, because the passive nature of the task, in addition to the ability to track the time course of the bias measures, could provide a new, and highly sensitive, method of studying spatial attention.

 

In this report, Burns and McIntosh (2023) aim to replicate and extend the study of Strauch et al. (2022). The extension centres around investigating whether the pupillary biases are influenced by recording pupillary responses from the right or left eye. In their pilot replication data, Burns & McIntosh identified a larger constriction in response to stimuli on the right side when recording from the right eye. They hypothesise that pupillary biases may be stronger to stimuli presented in the ipsilateral, rather than contralateral, side of space.

 

The Stage 1 manuscript was reviewed over 2 rounds by 2 reviewers, including the authors of the study being replicated. Based on detailed responses to the reviewers’ comments and edits to the Stage 1 report, the recommender judged that the manuscript met the Stage 1 criteria and therefore awarded in-principle acceptance.

 

Level of bias control achieved: Level 6. No part of the data or evidence that will be used to answer the research question yet exists and no part will be generated until after IPA.
 
List of eligible PCI-RR-friendly journals:
 

 

1. Strauch, C., Romein, C., Naber, M., Van der Stigchel, S. & Ten Brink, A. F. (2022). The orienting response drives pseudoneglect—Evidence from an objective pupillometric method. Cortex, 151, 259-271.

 
2. Burns, N. E. & McIntosh, R. D. (2023). Does pupillometry provide a valid measure of spatial attentional bias (pseudoneglect)? In principle acceptance of Version 2 by Peer Community in Registered Reports. https://osf.io/ua9jn

Measurement is a vital activity for all research areas, but we so often fail to provide sufficient clarity, rigor and transparency about it, undermining the validity of our studies' conclusions (Flake & Fried, 2020). This concern is of wide societal interest when applied to the domains of ideology and attitudes where measurements of both implicit and explicit attitudes are assumed to reflect the same underlying concept. The extent to which this can be accepted is undermined by mixed evidence demonstrating a lack of consensus on the extent to which relevant psychological factors similarly predict both implicit and explicit attitudes.

 

In the proposed study, Reid & Inbar (2023) question these assumptions through use of the Project Implicit dataset, exploring the extent to which social dominance orientation (SDO) and right wing authoritarianism (RWA) similarly predict implicit and explicit attitudes. This work is ideally suited for publication through the Registered Reports format because whilst we may expect that relationships between SDO/RWA are similar in effect size across measures of both implicit and explicit attitude (because they tap into the same underlying attitude), there is great scope to acknowledge a more complex set of findings which may not be immediately interpretable or coherent. The proposed work will help us unpack further the assumptions surrounding measurement of attitudes and can help us better understand the extent to which SDO and RWA predict atittudes. 

 

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).

 

URL to the preregistered Stage 1 protocol: https://osf.io/zv4jw
 
Level of bias control achieved: Level 5. All of the data or evidence that will be used to answer the research question already exist, but are currently inaccessible to the authors and thus unobservable prior to IPA (e.g. held by a gatekeeper) 
 
List of eligible PCI-RR-friendly journals:

 

 

 

1. Flake, J. K. & Fried, E. I. (2020). Measurement schmeasurement: Questionable measurement practices and how to avoid them. Advances in Methods and Practices in Psychological Science, 3, 456-465. https://doi.org/10.1177/2515245920952393

 

2. Reid, J. & Inbar, Y. (2023). Implicit Ideologies: Do Right-Wing Authoritarianism and Social Dominance Orientation Predict Implicit Attitudes? In principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/zv4jw

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

In the past two decades, most academic fields have witnessed an open science revolution that has led to significant increases in open access publishing, reproducibility efforts, and scientific transparency in general (e.g., Spellman et al. 2018). One of the key areas in this ongoing change is data sharing. Although some evidence already points at progress in data sharing practices, many new datasets remain unshared (see Tedersoo et al. 2021).
 
In the present registered report, Henderson et al. (2023) empirically explore the factors that either hinder or facilitate data sharing in the UK. By means of semi-structured interviews, the team will chart researchers’ experiences of sharing and non-sharing. Thematic template analysis will be applied to organise the data into a hierarchical map of capabilities, opportunities, and motivations in a theoretical domains framework (COM-B-TDF). The research plan itself meets the highest open science standards and reflects on the authors own positions, from which the current qualitative interview data sharing efforts will be made.
 
The Stage 1 manuscript was reviewed over three rounds by three experts with familiary of the UK cultural context and specializations in open science practices, qualitative research, and data infrastructures. Based on careful revisions and detailed responses to the reviewers’ comments, the recommender judged that the manuscript met the Stage 1 criteria and therefore awarded in-principle acceptance.
 
URL to the preregistered Stage 1 protocol: https://osf.io/2gm5s (under temporary private embargo)
 
Level of bias control achieved: Level 6. No part of the data or evidence that will be used to answer the research question yet exists and no part will be generated until after IPA.  
 
List of eligible PCI RR-friendly journals:

 

 

References
 
1. Henderson, E., Marcu, A., Atkins, L. & Farran, E.K. (2023). Investigating the barriers and enablers to data sharing behaviours: A qualitative Registered Report. In principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/2gm5s

 

2. Spellman, B. A., Gilbert, E. A. & Corker, K. S. (2018). Open Science. Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience, 5, 1-47. https://doi.org/10.1002/9781119170174.epcn519

 

3. Tedersoo, L., Küngas, R., Oras, E., Köster, K., Eenmaa, H., Leijen, Ä., ... & Sepp, T. (2021). Data sharing practices and data availability upon request differ across scientific disciplines. Scientific data, 8, 192. https://doi.org/10.1038/s41597-021-00981-0

Words have served as stimuli in memory experiments for over a century. What makes some words stand out in memory compared to others? One plausible answer is that semantically rich words are more distinctive and therefore exhibit a mirror effect in recognition memory experiments where they are likely to be correctly endorsed and also less likely to be confused with other words (Glanzer & Adams, 1985). Semantic richness can arise due to extensive prior experience with the word in multiple contexts but can also arise due to sensorimotor grounding, i.e., direct perceptual and action-based experience with the concepts represented by the words (e.g. pillow, cuddle). However, previous experiments have revealed inconsistent recognition memory performance patterns for words based on different types of sensorimotor grounding (Dymarska et al., 2023). Most surprisingly, body-related words such as cuddle and fitness exhibited greater false alarm rates. 

In the current study, Dymarska and Connell (2023) propose to test two competing theories that can explain the increased confusability of body-related words: 1) the adaptive account - contextual elaboration-based strategies activate other concepts related to body and survival, increasing confusability; and 2) the attentional account - somatic attentional mechanisms automatically induce similar tactile and interoceptive experiences upon seeing body-related words leading to less distinctive memory traces. The adaptive account leads to different predictions under intentional and incidental memory conditions. Specifically, contextual elaboration strategies are unlikely to be employed when participants do not expect a memory test and therefore in an incidental memory task, body-related words should not lead to inflated false alarm rates (see Hintzman (2011) for a discussion on incidental memory tasks and the importance of how material is processed during memory tasks). However, the attentional account is not dependent on the task instructions or the knowledge about an upcoming memory test. 

Here, Dymarska and Connell (2023) have designed an incidental recognition memory experiment with over 5000 words, disguised as a lexical decision task using carefully matched pseudowords during the encoding phase. The sample size will be determined by using a sequential hypothesis testing plan with Bayes Factors. To test the predictions of the adaptive and attentional accounts, the authors derive a set of lexical and sensorimotor variables (including a body-component) after dimensionality reduction of a comprehensive set of lexical and semantic word features. The analysis will involve running both Bayesian and frequentist hierarchical linear regression to explain four different measures of recognition memory performance based on the key sensorimotor variables and other baseline/confounding variables. While this analysis plan enables a comparison with the earlier results from an expected memory test (Dymarska et al., 2023), the current study is self-contained in that it is possible to distinguish the adaptive and attentional accounts based on the effect of body component scores on hit rate and false alarm rate.

The study plan was refined across two rounds of review, with input from two external reviewers after which the recommender judged that the study satisfied the Stage 1 criteria for in-principle acceptance (IPA).

 

URL to the preregistered Stage 1 protocol: https://osf.io/ck5bg
 
Level of bias control achieved: Level 6. No part of the data or evidence that will be used to answer the research question yet exists and no part will be generated until after IPA.
 
List of eligible PCI RR-friendly journals:
 

 

Dymarska, A. & Connell, L. (2023). Sensorimotor Effects in Surprise Word Memory – a Registered Report. In principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/ck5bg

Dymarska, A., Connell, L. & Banks, B. (2023). More is Not Necessarily Better: How Different Aspects of Sensorimotor Experience Affect Recognition Memory for Words. Journal of Experimental Psychology: Language, Memory, Cognition. Advance online publication. https://dx.doi.org/10.1037/xlm0001265 

Glanzer, M., & Adams, J. K. (1985). The mirror effect in recognition memory. Memory & cognition, 13, 8-20.

Hintzman, D. L. (2011). Research strategy in the study of memory: Fads, fallacies, and the search for the “coordinates of truth”. Perspectives on Psychological Science, 6(3), 253-271.