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Occluding a speaker’s lip movement while they talk, for example, with a mask, may hinder speech comprehension in adults, but we do not know to what extent it may do so in children. Research has shown that children may rely more on auditory than visual information when young (e.g. Hirst, Cragg & Allen 2018 DOI: http://dx.doi.org/10.1037/xhp0000608 ). For example, young children are less susceptible to McGurk illusions, where visual cues influence auditory speech perception (Hirst et al., 2019 DOI: doi.org/10.1038/s41598-018-30798-8), but susceptibility increases to adult like levels by age 10 years (Hirst et al., 2018, DOI: https://doi.org/10.1038/s41598-018-30798-8). If young children make less use of visual cues to aid speech comprehension, it might be predicted that masks would pose less of a hindrance to comprehension in younger children. With this, Experiment 1 of the current project will investigate whether, and to which extent, basic (surgical) mask wear negatively affects speech comprehension in children of different ages and adults. Importantly, there are several real-world factors to consider when assessing the impact of masks on speech comprehension. First, the real-world typically requires comprehension of speech in noise, for example following conversation in a busy supermarket. Second, many commercially available masks contain appealing designs and patterns, it is unclear whether this may distract away from the content of speech or motivate towards the location of speech sounds. This issue is important to disentangle in light of new information that children’s brains are sensitive to audiovisual distraction much earlier than previously thought (Turoman et al., 2020, DOI: https://doi.org/10.1101/2020.10.20.342758, Turoman et al., 2021, DOI: doi.org/10.1016/j.dcn.2021.100930). Third, new products, such as transparent plastic masks, are appearing on the market, attempting to mitigate potential difficulties with speech comprehension. However, there is currently little to no empirical backing for their usefulness or necessity. As of July 2020, it became a legal requirement in the UK for adults (with the exception of those with medical exemption) to wear face coverings in most public places, due to the COVID-19 pandemic. As such, understanding how children’s perception of adults’ speech could be influenced by mask wearing is both prominent and important, but we must address this via ethologically valid designs. For these reasons, Experiment 2 of the current project will also investigate whether having a design on a mask, as is the case of many commonly available fabric face masks, can influence the effect of mask-wearing on speech comprehension, either by improving or impairing it. Further, Experiment 3 will investigate, in an exploratory fashion, the effect of newly emerging transparent mask technology on speech comprehension. This experiment will also compare the effects of all of the above mask types against each other, in hopes of arriving at a set of age-appropriate guidelines for mask wear.

In this registration, we describe the necessary modifications to the Bayesian sequential hypothesis testing procedure described in the Stage 1 manuscript XLM-2022-2364R2 entitled “The effect of multisensory distraction on working memory: A role for task relevance?”, accepted by the Journal of Experimental Psychology: Learning, Memory, and Cognition (on January 14th, 2023), before additional data collection started on February 24th, 2023 (15h CET). Specifically, to accommodate a later decision on the Stage 1 manuscript than we had hoped, and given limited resource availability (participant credits, staff contracts, and research assistant availability), we had to make two changes to the data collection procedure for Experiment 1, and one change to the subsequent experiments, which we detail below. First, for the initial batch of data in Experiment 1, we recruited and tested 32 participants before the date of acceptance of the Stage 1 report (data collection from November 11 to December 9, 2022, for the aforementioned reasons related to resource availability). To minimize the deviation from the registered report, we did not look into these data or perform any statistical analyses until after acceptance (starting with January 26th, 2023). Further, for subsequent batches of participants per experiment, we will collect data in batches of 10 instead of 5 as previously defined. Thus, after the initial batch 1 of Experiment 1, we will increase the number of participants by steps of 10, rather than by steps of 5, and we plan to do the same in any of the potential subsequent experiments that we may need to run based on the decision tree of the manuscript. To minimize the deviation from our original sampling plan, we will only add batches of 5 participants into our analysis, one participant at a time, thereby making changes only in how many additional data sets are collected per additional batch (+10) but not in how many additional data sets are analyzed per additional batch (+5). We will ensure that the authors only have access to the data of 5 participants at a time, as we would in the original case before the current changes (only a research assistant collecting the data will have access to all 10 datasets). This deviation was decided before the collection of any data other than for batch 1 of Experiment 1, which is evidenced by the timestamp of the current registration. Below are the original and updated methods related to the Bayesian sequential hypothesis testing procedure for Experiment 1, and for potential subsequent experiments (Experiment 2a-d and Experiment 3). In the case of Experiment 1, we first present the original section as in the accepted manuscript, and an updated section as it will be written in the stage 2 manuscript. For potential Experiment 2a-d and Experiment 3, we describe the original intended procedure (not yet in the manuscript) and updated procedure, as they will be written in the stage 2 manuscript (with changes in tense). The stage 2 manuscript will report these deviations transparently.

Why some people have better working memory (WM) performance than others remains poorly understood, but distractor processing, or the ability to exclude irrelevant information amidst competing inputs, could provide an explanation. WM research has established that adults can usually ignore distractors quite successfully (see e.g., Oberauer et al., 2019, pp.8, DOI: https://doi.org/10.5334/joc.58). However, in most WM paradigms, distraction is measured through a concurrent task or stimulus set, presented along with the target task or stimulus set, which later turns out to be irrelevant. This may not be the most representative account of how distraction happens in daily life, or at least not the only account, though different paradigms have seldom been used. In the field of selective attention, by contrast, distraction is studied in various ways. A recent stream of research in this field has shown that the sensory nature of the distractor may determine how well they can be ignored, and that the load involved in the target task may modulate the impact of different types of distractors. For example, a study by Matusz and colleagues (2015, DOI: http://dx.doi.org/10.1016/j.cognition.2014.11.031) has shown that in the presence of many competing visual inputs in the target task (high load), auditory and audiovisual distractors, but not visual distractors, were processed. On the other hand, when there were few competing visual inputs (low load), all distractor types were processed. In the Matusz et al. (2015) study, distractors were introduced peripherally, for brief moments during a target visual task, as interruptions, rather than concurrent stimuli to be processed. Multisensory stimuli are ubiquitous in daily life settings, but it is not clear how these or unisensory distractors affect working memory, and whether memory load has any influence on such effects. For this reason, the present project will investigate, using a similar paradigm to the one of Matusz et al. (2015), whether the sensory nature of distractors (Visual vs. Auditory vs. Audiovisual) affects WM performance, i.e., whether it affects which sensory types of distractors can successfully be ignored, and whether this is modulated by load in working memory as well. Focusing on the type of distractor overlooks the important question of the timing of the distractor. WM is a process composed of Encoding, Maintenance, and Retrieval stages, and it is currently unclear which of these stages is the most vulnerable to distraction. Based on the little (developmental) research on the topic, one may equally deduce that it is Encoding (e.g., Shimi et al., 2015, DOI: https://doi.org/10.3389/fnsys.2015.00153) or Maintenance (e.g., Astle et al., 2012, DOI: http://dx.doi.org/10.1080/17470218.2010.492622). To help reach a consensus in the field of WM, the present project will also investigate whether the stage of WM at which a distractor is presented (Encoding vs. Maintenance) affects WM performance. Thus, the effects of Distractor Type and Distractor Stage on WM performance will be investigated together, using a behavioral paradigm that borrows from WM and selective attention research.

Materials associated with a project where people rated shapes varying in contour (round, angular) and symmetry (asymmetric, D1 group, D8 group) on taste (sweet, sour, bitter) and appraisal (pleasantness, threat). The Data section contains the raw datasets for each of 2 experiments conducted for this project, as well as the full results of a parallel statistical analysis between the experiments, and the results of a correlational analysis with all shapes, not averaged by condition. The Stimuli and code section contains the above mentioned shapes (named by parameters used), the code used to generate them, as well as a sheet of parameters for replicating the shapes used here. The Study flow section contains an outline of each experiment, as presented through the Qualtrics survey platform

Materials associated with a project where people guessed the identity of ancient and unfamiliar letters for /i/ and /u/. The Study Elements section contains stimuli, materials and data. The Public Science section contains activities suitable for use in public museums/galleries or Science Outreach including public lectures or classroom activities. See also: Turoman and Styles (2017) RSOS

Turoman N & Styles SJ. (2016). How well do humans capture the sounds of speech in writing? In Lindborg PM & Styles SJ (Eds.), ICMA Array, vol 2016, Special Issue: Proceedings of Si15, Singapore, August 2015, pp 43–44.Abstract. A large body of research on connections between sensory modalities has shown that deep connections exist between sound and vision, such that people have a tendency to associate certain sounds with certain visual properties, including line-drawn shapes. While recognising the role of written language in audio-visual associations, previous research has largely considered written language a potential source of bias rather than a means of gaining deeper insights into underlying audio-visual associations. We looked to ancient and unfamiliar writing systems spanning recorded human history, to explore whether humans have tried to encode certain characteristics of speech sounds in the letters they created to represent them. Our findings have revealed that modern humans can correctly identify unfamiliar letters at levels higher than would be obtained by chance, and that scripts which encode a particular sound with a particular set of visual characteristics tend to have more correct guesses. This suggests that humans share certain correspondences between sound and sight, which transcend both geographical space and historical time. The present multisensory demonstration aims to provide an interactive experience of the powerful connection between sounds and written letters through a series of activities integrating vision, audition, touch and imagination.