Cognitive models ascribe a pivotal role to cognitive biases in the development and maintenance of mental disorders. For instance, attentional biases that prioritize the processing of threat-related stimuli have been suggested to be causally involved in the development and maintenance of anxiety disorders, including generalized anxiety disorder (GAD), which is marked by pathological worry. Therefore, these biases have garnered significant interest as potential diagnostic indicator and as targets for modification.

 

The idea that attention bias modification (ABM) can serve as a therapeutic intervention for GAD and other disorders was fueled by a seminal study by Hazen et al. (2009). In this study, 23 individuals experiencing high levels of worry underwent a computerized attentional retraining of threat stimuli (ARTS) or placebo control training during five training sessions. Relative to control, attention retraining was found to reduce preferential attention to threat, as well as depression and anxiety symptoms. However, as Pond et al. (2024) highlight in their review of the literature, the evidence endorsing the efficacy of ABM in alleviating anxiety disorders is still inconclusive. Moreover, some researchers contend that early positive findings might have been inflated due to demand effects.

 

Based on these considerations, Pond et al. (2024) propose a direct replication of Hazen et al. (2009) by subjecting a high-worry sample to five sessions of ARTS or placebo control. Departing from the frequentist analyses used in the original study, the authors will employ Bayesian analyses that allow more nuanced interpretation of the results, allowing consideration of evidence in support of the null hypothesis. The sampling plan will adhere to a Bayesian stopping rule, whereby the maximal sample size will be set at n=200. Furthermore, the authors extend the original study by addressing potential demand effects. For this purpose, they include a measure of phenomenological control (i.e., the ability to generate experiences align with the expectancies of a given situation) and evaluate its potential moderating impact on the attention bias training.

 

The Stage 1 manuscript was evaluated by three expert reviewers in two rounds of in-depth review. Following responses from the authors, the recommender determined that Stage 1 criteria were met and awarded in-principle acceptance (IPA).

 

URL to the preregistered Stage 1 protocol: https://osf.io/5f7u9
 
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. Hazen, R. A., Vasey, M. W., & Schmidt, N. B. (2009). Attentional retraining: A randomized clinical trial for pathological worry. Journal of Psychiatric Research, 43, 627-633. https://doi.org/10.1016/j.jpsychires.2008.07.004 

 

2. Pond, N., Meeten, F., Clarke, P., Notebaert, L., & Scott, R. B. (2024). The efficacy of attentional bias modification for anxiety: A registered replication. In principle acceptance of Version 5 by Peer Community in Registered Reports. https://osf.io/5f7u9

 

For nearly a century, rhythmic patterns in electrical brain activity have been of major interest in neuroscience and electrophysiology, but much remains to be discovered about their causal contribution to cognition and behaviour. Low-frequency oscillations in the alpha band (~8-13 Hz) have been suggested to facilitate the organisation and delivery of visual information to higher-level systems, including those involved in perception and decision-making. If so, visual perception should also operate in cycles that are synchronous with – and determined by – the phase of ongoing low-frequency oscillatory activity.

 

In this #EEGManyLabs study, Ruzzoli et al. (2023) propose a large-scale, multi-lab investigation (9 labs; N=315 human participants) of the relationship between the phase of alpha oscillations and visual perception. The authors focus in particular on replicating a formative study by Mathewson et al. (2009) which reported that during high-amplitude alpha fluctuations, stimulus visibility depended on the time the stimulus was presented relative to the phase of the pre-stimulus alpha activity. In addition, the amplitude of visual evoked potentials recorded with EEG was larger when the target was presented at peaks in pre-stimulus alpha. To explain their findings, Mathewson proposed an influential pulsed inhibition hypothesis in which low alpha power boosts both cortical excitability and stimulus processing (and hence perception), while high alpha power makes stimulus processing dependent on the phase during the alpha cycle at which the stimulus is presented.

 

In the first of (up to) two studies, the authors will seek to directly replicate the key finding of Mathewson et al: that when alpha power is high, the oscillatory phase determines perceptual performance and event-related electrophysiological correlates in a masked visual detection task. Specifically, (a) alpha oscillations are predicted to modulate the probability of perceiving a target stimulus within a single oscillatory cycle, with detection rate associated with separated (and potentially opposite) phase angles, and (b) alpha phase at the onset of the stimulus should drive electrophysiological correlates of stimulus processing (including the amplitude and/or latency of the N1 ERP component).

 

Provided the results of this first study do not conclusively disconfirm these hypotheses, the authors will then conduct a follow-up study in which the temporal predictability of the target onset (in relation to a fixation stimulus) is reduced to test the more severe hypothesis that the observed correlations between alpha phase and perception are linked directly to ongoing oscillations, independent of temporal expectations.

 

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).

 

URL to the preregistered Stage 1 protocol: https://osf.io/scqj8​ (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. 

 

 
References

 

1. Ruzzoli, M., Cuello, M. T., Molinaro, N., Benwell, C. S. Y., Berkowitz, D., Brignani, D., Falciati, L., Harris, A. M., Keitel, C., Kopčanová, M., Madan, C. R., Mathewson, K., Mishra, S., Morucci, P., Myers, N., Nannetti, F., Nara, S., Pérez-Navarro, J., Ro, T., Schaworonkow, N., Snyder, J. S., Soto-Faraco, S., Srinivasan, N., Trübutschek, D., Zazio, A., Mushtaq, F., Pavlov, Y. G., & Veniero, D. (2023). In principle acceptance of Version 2 by Peer Community in Registered Reports. https://osf.io/scqj8​

 

2. Mathewson, K. E., Gratton, G., Fabiani, M., Beck, D. M., & Ro, T. (2009). To see or not to see: prestimulus α phase predicts visual awareness. Journal of Neuroscience, 29, 2725-2732. https://doi.org/10.1523/JNEUROSCI.3963-08.2009

Previous research has demonstrated that experimental participants – both adults and infants – can track syllable co-occurrences in an artificial speech stream. This statistical learning (SL) is thought to support word segmentation and to be a core component of language acquisition. There is also some evidence that SL, as measured through artificial language tasks, is related to individual differences in language learning. What is not well understood is the underpinnings of individual differences in SL. In the current study, van der Wulp et al. (2023) will investigate the relationship between auditory SL and musical – specifically rhythmic – abilities. This work takes advantage of recent methodological innovations which allow online assessment of SL via electroencephalography (EEG) measures of neural entrainment. Up to N=105 participants will be recruited (using a well specified optional stopping procedure) and will be exposed to an artificial language using this EEG method to measure their response to the language through the exposure phase. In addition, post-tests will assess participants’ learning of the artificial language using behavioural tasks, as well as their abilities in a battery of tasks measuring rhythmic, musical, and cognitive abilities, and their vocabulary size. Core analyses will investigate whether the neural signature of statistical learning is found at a group level (i.e. replicating previous work) and whether at the individual level this is related to rhythm perception. Bayes factors will be used to assess the extent of evidence for these hypothesized relationships over the null. Exploratory analyses will explore other relationships, including with working memory and vocabulary size. 

 

The topic of individual differences in language learning and is important, but work in this area is often underpowered, and the correlational nature of the research makes it vulnerable to HARKing. In this context, the current RR looks set to make an important contribution. The Stage 1 manuscript was evaluated over two rounds of in-depth review by the recommender and two expert reviewers, and one additional round of review by the recommender, before issuing 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:
 

• Advances in Cognitive Psychology
• Brain and Neuroscience Advances
• Collabra: Psychology
• Cortex
• Experimental Psychology
  
• Imaging Neuroscience
• In&Vertebrates
• Journal of Cognition
• NeuroImage: Reports
• Peer Community Journal
• PeerJ
• Royal Society Open Science
• Studia Psychologica

 

References
 
1. van der Wulp, I. M., Struiksma, M. E., Batterink, L. J., & Wijnen, F. N. K. (2023). Investigating individual differences in linguistic statistical learning and their relation to rhythmic and cognitive abilities: A speech segmentation experiment with online neural tracking. In principle acceptance of Version 4 by Peer Community in Registered Reports. https://osf.io/2y6sx

 

Self-control has shown to be a trait related to beneficial outcomes, including health, academic achievement and relationship quality. It is mostly understood as the ability to surpress immediate urges in order to achieve long-term goals, such as not watching another episode and therefore reaching a healthy amount of sleep. An emerging perspective on self-control shows that there is broader variety in applied strategies, such as removing oneself from a tempting situation, or reminding oneself of one's long-term goal, or reinterpreting the temptation.

 

Katzir et al. (2021) developed a novel instrument, the Self-Control Strategy Scale, that measured the tendency to engage in eight such strategies. In the current study, Roth et al. (2023) propose to translate the scale into German and assess its psychometric properties. Further, they will determine which strategies are related to particular outcomes that may be beneficial; for example, amount of physical activity engaged in, how healthy the diet is, exam performance and life satisfaction.

 

The Stage 1 manuscript was evaluated over two rounds of in-depth review by the recommender and at least two expert reviewers, before issuing in-principle acceptance.

 

URL to the preregistered Stage 1 protocol: https://osf.io/s7qwk
 
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. Katzir, M., Baldwin, M., Werner, K. M., & Hofmann, W. (2021). Moving beyond inhibition: Capturing a broader scope of the self-control construct with the Self-Control Strategy Scale (SCSS). Journal of Personality Assessment, 103, 762-776. https://doi.org/10.1080/00223891.2021.1883627

 

2. Roth, L. H. O., Jankowski, J., Clay, G., Meindl, D., Vogt, L.-M., Wagner, V., Nordmann, A., Stenzel, L., Freiman, O., Mlynski, C., & Job, V. (2023). Self-Control beyond inhibition. German Translation and Quality Assessment of the Self-Control Strategy Scale (SCSS). In principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/s7qwk

The Spatial-Numerical Association of Response Codes (SNARC) effect refers to the fact that smaller numbers receive faster responses with the left hand, and larger numbers with the right hand (Dehaene et al., 1993). This robust finding implies that numbers are associated with space, being represented on a mental number line that progresses from left to right. The SNARC effect is held to depend on relative number magnitude, with the mental number line dynamically adjusting to the numerical range used in a given context. This characterisation is based on significant effects of relative number magnitude, with no significant influence of absolute number magnitude. However, a failure to reject the null hypothesis, within the standard frequentist statistical framework, is not firm evidence for the absence of an effect. In this Stage 1 Registered Report, Roth and colleagues (2023) propose two experiments adapted from Dahaene’s (1993) original methods, with a Bayesian statistical approach to confirm—or rule out—a small effect (d = 0.15) of absolute number magnitude in modulating the classic SNARC effect.

 

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

 

URL to the preregistered Stage 1 protocol: https://osf.io/ae2c8
 
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

 

Dehaene, S., Bossini, S., & Giraux, P. (1993). The mental representation of parity and number magnitude. Journal of Experimental Psychology: General, 122(3), 371–396. https://doi.org/10.1037/0096-3445.122.3.371

 

Roth, L., Caffier, J., Reips, U.-D., Nuerk, H.-C., & Cipora, K. (2023). One and only SNARC? A Registered Report on the SNARC Effect’s Range Dependency. In principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/ae2c8