The importance of integrating research findings is incontrovertible and procedures for coordinate-based meta-analysis (CBMA) such as Activation Likelihood Estimation (ALE) have become a popular approach to combine results of fMRI studies when only peaks of activation are reported. As meta-analytical findings help building cumulative knowledge and guide future research, not only the quality of such analyses but also the way conclusions are drawn is extremely important. Like classical meta-analyses, coordinate-based meta-analyses can be subject to different forms of publication bias which may impact results and invalidate findings. The file drawer problem refers to the problem where studies fail to get published because they do not obtain anticipated results (e.g. due to lack of statistical significance). To enable assessing the stability of meta-analytical results and determine their robustness against the potential presence of the file drawer problem, we present an algorithm to determine the number of noise studies that can be added to an existing ALE fMRI meta-analysis before spatial convergence of reported activation peaks over studies in specific regions is no longer statistically significant. While methods to gain insight into the validity and limitations of results exist for other coordinate-based meta-analysis toolboxes, such as Galbraith plots for Multilevel Kernel Density Analysis (MKDA) and funnel plots and egger tests for seed-based d mapping, this procedure is the first to assess robustness against potential publication bias for the ALE algorithm. The method assists in interpreting meta-analytical results with the appropriate caution by looking how stable results remain in the presence of unreported information that may differ systematically from the information that is included. At the same time, the procedure provides further insight into the number of studies that drive the meta-analytical results. We illustrate the procedure through an example and test the effect of several parameters through extensive simulations. Code to generate noise studies is made freely available which enables users to easily use the algorithm when interpreting their results.

Rather than reflecting the long-term memory construct of a mental number line, it has been proposed that the relation between numbers and space is of a more temporary nature and constructed in working memory during task execution. In three experiments we further explored the viability of this working memory account. Participants performed a speeded dot detection task with dots appearing left or right, while maintaining digits or letters in working memory. Just before presentation of the dot, these digits or letters were used as central cues. These experiments show that the "attentional SNARC-effect" (where SNARC is the spatial-numerical association of response codes) is not observed when only the lastly perceived number cue--and no serially ordered sequence of cues--is maintained in working memory (Experiment 1). It is only when multiple items (numbers in Experiment 2; letters in Experiment 3) are stored in working memory in a serially organized way that the attentional cueing effect is observed as a function of serial working memory position. These observations suggest that the "attentional SNARC-effect" is strongly working memory based. Implications for theories on the mental representation of numbers are discussed.

A wide range of countries decided to go into lockdown to contain the coronavirus disease (COVID-19) pandemic of 2020, a setting separating people and restricting their movements. We investigated how musicians dealt with this sudden restriction in mobility. Responses of 234 people were collected. The majority of respondents (95%) resided in Belgium or the Netherlands. Results indicated a decrease of 79% of live music making in social settings during lockdown compared with before lockdown. In contrast, an increase of 264% was demonstrated for online joint music making. However, results showed that most respondents were largely or even completely unaccustomed with specialized platforms for online joint music making (e.g., JamKazam, Jamulus). Respondents reported to mostly use well-known video-conferencing platforms such as Zoom and Skype when playing together virtually. However, when such video-conferencing platforms were used, they were often not employed for synchronized playing and were generally reported to insufficiently deal with latency issues. Furthermore, respondents depending on music making as their main source of income explored online real-time methods significantly more than those relying on other income sources. Results also demonstrated an increase of 93% in the use of alternative remote joint music-making methods (e.g., recording parts separately and subsequently circulating these digital recordings). All in all, results of this study provide a more in-depth view on joint music making during the first weeks of lockdown induced by the COVID-19 pandemic of 2020, and demonstrate users’ perceptions of performance and usability of online real-time platforms as well as alternative methods for musical interaction.

Although the neuroanatomy of transgender persons is slowly being charted, findings are presently discrepant. Moreover, the major body of work has focused on Western populations. One important factor is the issue of power and low signal-to-noise (SNR) ratio in neuroimaging studies of rare study populations including endocrine or neurological patient groups. The present study focused on the structural neuroanatomy of a Non-Western (Iranian) sample of 40 transgender men (TM), 40 transgender women (TW), 30 cisgender men (CM), and 30 cisgender women (CW), while assessing whether the reliability of findings across structural anatomical measures including gray matter volume (GMV), cortical surface area (CSA), and cortical thickness (CTh) could be increased by using two back-to-back within-session structural MRI scans. Overall, findings in transgender persons were more consistent with sex assigned at birth in GMV and CSA, while no group differences emerged for CTh. Repeated measures analysis also indicated that having a second scan increased SNR in all regions of interest, most notably bilateral frontal poles, pre-and postcentral gyri and putamina. The results suggest that a simple time and cost-effective measure to improve SNR in rare clinical populations with low prevalence rates is a second anatomical scan when structural MRI is of interest.

The importance of integrating research findings is incontrovertible and coordinate based meta-analyses have become a popular approach to combine results of fMRI studies when only peaks of activation are reported. Similar to classical meta-analyses, coordinate based meta-analyses may be subject to different forms of publication bias which impacts results and possibly invalidates findings. We develop a tool that assesses the robustness to potential publication bias on cluster level. We investigate the possible influence of the file-drawer effect, where studies that do not report certain results fail to get published, by determining the number of noise studies that can be added to an existing fMRI meta-analysis before the results are no longer statistically significant. In this paper we illustrate this tool through an example and test the effect of several parameters through extensive simulations. We provide an algorithm for which code is freely available to generate noise studies and enables users to determine the robustness of meta-analytical results.Corresponding author: Freya Acar 4 Main textCorresponding author: Freya Acar 5 developed, which is used most (see Figure 1). Later on, Seed-based d Mapping (Radua and Mataix-Cols, 2012) and multilevel kernel density analysis (MKDA; Wager et al., 2009) arose. As MKDA, ALE uses as input xyz-coordinates of the peaks (foci) reported by the individual studies and determines at which location the convergence of activation is larger than can be expected by chance. Seed-based d mapping also takes peak height into account and offers the possibility of entering entire t-maps into the meta-analysis. An advantage to ALE is that it is accompanied by the BrainMap database Fox and Lancaster, 2002;Fox et al., 2005). The BrainMap database is a collection of over 3000 papers, containing information about e.g. experimental conditions, subjects and allows to extract peak locations in the format adapted to the ALE algorithm.

Prose word count abstract / text: 193 / 4036 RUNNING TITLE: Neuroanatomy in transgender persons

What are the standards for the reporting methods and results of fMRI studies, and how have they evolved over the years? To answer this question we reviewed 160 papers published between 2004 and 2019. Reporting styles for methods and results of fMRI studies can differ greatly between published studies. However, adequate reporting is essential for the comprehension, replication and reuse of the study (for instance in a meta-analysis). To aid authors in reporting the methods and results of their task-based fMRI study the COBIDAS report was published in 2016, which provides researchers with clear guidelines on how to report the design, acquisition, preprocessing, statistical analysis and results (including data sharing) of fMRI studies (Nichols, et al., 2016). In the past reviews have been published that evaluate how fMRI methods are reported based on the 2008 guidelines, but they did not focus on how task based fMRI results are reported. This review updates reporting practices of fMRI methods, and adds an extra focus on how fMRI results are reported. We discuss reporting practices about the design stage, specific participant characteristics, scanner characteristics, data processing methods, data analysis methods and reported results.

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