A Practical Guide for Improving Transparency and Reproducibility in Neuroimaging Research

Early cortical alterations and neuropsychological mechanisms in amyotrophic lateral sclerosis

OBJECTIVE

This study investigates the characteristics of cortical structural and functional alterations in amyotrophic lateral sclerosis (ALS) patients and their modulation of emotional and cognitive functions, as well as to discuss their diagnostic value in early-stage ALS.

METHODS

Fifty-nine ALS patients (28 in ALS 1 and 31 in ALS 2, categorized using King's College Staging) and 31 healthy controls were evaluated using multiparametric MRI, motor and neuropsychological assessments, and serum neurofilament light chain (NfL) levels. Mediation analyses were performed to examine how cortical alterations influence the relationship between emotional and cognitive functions. Support vector machine (SVM) classification models were constructed to assess the diagnostic utility of differential cortical parameters.

RESULTS

ALS 1 patients exhibited increased cortical thickness (CT) and functional activity in the cingulate and frontotemporal regions, correlating with neuropsychological performance and NfL levels. Mediation analysis revealed that perigenual and frontotemporal functional activity significantly modulated the relationship between depressive symptoms and cognitive function. SVM classification showed that the combined altered regions with Amplitude of Low Frequency Fluctuations (ALFF) model achieved slightly better performance (AUC = 0.853, 95 %CI: 0.687-1.000, p < 0.001) compared to CT (AUC = 0.779, 95 %CI: 0.587-0.972, p < 0.001), although both models showed limited efficacy in differentiating between ALS 1 and ALS 2 groups.

CONCLUSIONS

Cortical structural and functional alterations in ALS mediate the impact of depression on cognitive function, offering insights into the neuropsychological mechanisms of the disease and potential biomarkers for early-stage diagnosis.

Left Ventrolateral Prefrontal Cortical Activity During Reward Expectancy and Mania Risk

Importance

Mania/hypomania is the pathognomonic feature of bipolar disorder (BD). As BD is often misdiagnosed as major depressive disorder (MDD), replicable neural markers of mania/hypomania risk are needed for earlier BD diagnosis and pathophysiological treatment development.

Objective

To replicate the previously reported positive association between left ventrolateral prefrontal cortex (vlPFC) activity during reward expectancy (RE) and mania/hypomania risk, to explore the effect of MDD history on this association, and to compare RE-related left vlPFC activity in individuals with and at risk of BD.

Design, Setting, and Participants

This cross-sectional study was conducted from July 2014 to December 2023 at the University of Pittsburgh, Pittsburgh, Pennsylvania. Three samples were formed comprising young adults (aged 18 to 30 years) without BD and with a range of subsyndromal-syndromal affective and anxiety psychopathologies, including a new sample and 2 test samples from our previous research; a sample of individuals aged 18 to 30 years with euthymic BD was also included. All participants were recruited from the community through advertising.

Exposures

Functional magnetic resonance imaging during an RE task.

Main Outcomes and Measures

New sample: whole-brain activity during RE regressed to the Mood Spectrum Self-Report Lifetime Questionnaire (MOODS-SR-L) manic domain score in all participants and in those without history of MDD and RE-related whole-brain activity regressed to the MOODS-SR-L depressive domain score to determine specificity to mania/hypomania risk. Test samples: these associations were examined using parameter estimates of activity extracted from respective masks created from activity in the new sample. A tertile split of MOODS-SR-L manic domain score divided the new sample into 3 mania/hypomania risk groups. Comparison of RE-related activity (extracted parameter estimates) was performed in risk groups and individuals with BD.

Results

Among the 113 individuals in the new sample, 73 were female, and the mean (SD) age was 23.88 (3.32) years. In each of the test samples, there were 52 individuals (39 female; mean [SD] age, 21.94 [2.12] years) and 65 individuals (47 female; mean [SD] age, 21.39 [2.11] years). The euthymic BD group had 37 individuals (30 female; mean [SD] age, 25.12 [3.81] years). In the new sample, 8 clusters of RE-related activity, including left vlPFC activity, showed a positive association with mania/hypomania risk, which remained after excluding individuals with MDD history and was specific to mania/hypomania risk. In the test samples, this association was shown in test sample 1 only (β, 0.21; 95% CI, 0.08-0.35; P = .002; q(false discovery rate [FDR]), 0.006; R2, 0.04). Test sample 2 had a higher proportion with MDD history (49 of 65 [75.3%] compared to 31 of 52 [59.6%] in sample 1). Combining individuals without history of MDD in both test samples replicated the association (β, 0.32; 95% CI, 0.08-0.58; P = .01; q[FDR], 0.023; R2, 0.02). RE-related left vlPFC activity was significantly greater in individuals at highest risk vs lowest (Cohen d, 1.01; 95% CI, 0.29-0.79; P < .001) and medium (Cohen d, 0.59; 95% CI, 0.12-0.63; P = .004) risk, as well as the euthymic BD group (Cohen d, 0.54; 95% CI, 0.07-0.58; P = .01), potentially due to medication effects.

Conclusion and Relevance

Elevated RE-related left vlPFC activity was associated with mania/hypomania risk and attenuated by MDD history. These findings provide a neural target to help develop pathophysiological interventions for individuals with or at risk of mania/hypomania.

Reporting checklists in neuroimaging: promoting transparency, replicability, and reproducibility

Neuroimaging plays a crucial role in understanding brain structure and function, but the lack of transparency, reproducibility, and reliability of findings is a significant obstacle for the field. To address these challenges, there are ongoing efforts to develop reporting checklists for neuroimaging studies to improve the reporting of fundamental aspects of study design and execution. In this review, we first define what we mean by a neuroimaging reporting checklist and then discuss how a reporting checklist can be developed and implemented. We consider the core values that should inform checklist design, including transparency, repeatability, data sharing, diversity, and supporting innovations. We then share experiences with currently available neuroimaging checklists. We review the motivation for creating checklists and whether checklists achieve their intended objectives, before proposing a development cycle for neuroimaging reporting checklists and describing each implementation step. We emphasize the importance of reporting checklists in enhancing the quality of data repositories and consortia, how they can support education and best practices, and how emerging computational methods, like artificial intelligence, can help checklist development and adherence. We also highlight the role that funding agencies and global collaborations can play in supporting the adoption of neuroimaging reporting checklists. We hope this review will encourage better adherence to available checklists and promote the development of new ones, and ultimately increase the quality, transparency, and reproducibility of neuroimaging research.

Multimodal smoking cessation treatment combining repetitive transcranial magnetic stimulation, cognitive behavioral therapy, and nicotine replacement in veterans with posttraumatic stress disorder: A feasibility randomized controlled trial protocol

Tobacco-related deaths remain the leading cause of preventable death in the United States. Veterans suffering from posttraumatic stress disorder (PTSD)-about 11% of those receiving care from the Department of Veterans Affairs (VA)-have triple the risk of developing tobacco use disorder (TUD). The most efficacious strategies being used at the VA for smoking cessation only result in a 23% abstinence rate, and veterans with PTSD only achieve a 4.5% abstinence rate. Therefore, there is a critical need to develop more effective treatments for smoking cessation. Recent studies suggest the insula is integrally involved in the neurocircuitry of TUD. Thus, we propose a feasibility phase II randomized controlled trial (RCT) to study a form of repetitive transcranial magnetic stimulation (rTMS) called intermittent theta burst stimulation (iTBS). iTBS has the advantage of allowing for a patterned form of stimulation delivery that we will administer at 90% of the subject's resting motor threshold (rMT) applied over a region in the right post-central gyrus most functionally connected to the right posterior insula. We hypothesize that by increasing functional connectivity between the right post-central gyrus and the right posterior insula, withdrawal symptoms and short-term smoking cessation outcomes will improve. Fifty eligible veterans with comorbid TUD and PTSD will be randomly assigned to active-iTBS + cognitive behavioral therapy (CBT) + nicotine replacement therapy (NRT) (n = 25) or sham-iTBS + CBT + NRT (n = 25). The primary outcome, feasibility, will be determined by achieving a recruitment of 50 participants and retention rate of 80%. The success of iTBS will be evaluated through self-reported nicotine use, cravings, withdrawal symptoms, and abstinence following quit date (confirmed by bioverification) along with evaluation for target engagement through neuroimaging changes, specifically connectivity differences between the insula and other regions of interest.

Transparency and reproducibility in the Adolescent Brain Cognitive Development (ABCD) study

BACKGROUND

Transparency can build trust in the scientific process, but scientific findings can be undermined by poor and obscure data use and reporting practices. The purpose of this work is to report how data from the Adolescent Brain Cognitive Development (ABCD) Study has been used to date, and to provide practical recommendations on how to improve the transparency and reproducibility of findings.

METHODS

Articles published from 2017 to 2023 that used ABCD Study data were reviewed using more than 30 data extraction items to gather information on data use practices. Total frequencies were reported for each extraction item, along with computation of a Level of Completeness (LOC) score that represented overall endorsement of extraction items. Univariate linear regression models were used to examine the correlation between LOC scores and individual extraction items. Post hoc analysis included examination of whether LOC scores were correlated with the logged 2-year journal impact factor.

RESULTS

There were 549 full-length articles included in the main analysis. Analytic scripts were shared in 30 % of full-length articles. The number of participants excluded due to missing data was reported in 60 % of articles, and information on missing data for individual variables (e.g., household income) was provided in 38 % of articles. A table describing the analytic sample was included in 83 % of articles. A race and/or ethnicity variable was included in 78 % of reviewed articles, while its inclusion was justified in only 41 % of these articles. LOC scores were highly correlated with extraction items related to examination of missing data. A bottom 10 % of LOC score was significantly correlated with a lower logged journal impact factor when compared to the top 10 % of LOC scores (β=-0.77, 95 % -1.02, -0.51; p-value < 0.0001).

CONCLUSION

These findings highlight opportunities for improvement in future papers using ABCD Study data to readily adapt analytic practices for better transparency and reproducibility efforts. A list of recommendations is provided to facilitate adherence in future research.

Structural Brain Differences in the Alzheimer's Disease Continuum: Insights Into the Heterogeneity From a Large Multisite Neuroimaging Consortium

BACKGROUND

Neurodegenerative diseases require collaborative, multisite research to comprehensively grasp their complex and diverse pathological progression; however, there is caution in aggregating global data due to data heterogeneity. In the current study, we investigated brain structure across stages of Alzheimer's disease (AD) and how relationships vary across sources of heterogeneity.

METHODS

Using 6 international datasets (N > 27,000), associations of structural neuroimaging markers were investigated in relation to the AD continuum via meta-analysis. We investigated whether associations varied across elements of magnetic resonance imaging acquisition, study design, and populations.

RESULTS

Modest differences in associations were found depending on how data were acquired; however, patterns were similar. Preliminary results suggested that neuroimaging marker-AD relationships differ across ethnic groups.

CONCLUSIONS

Diversity in data offers unique insights into the neural substrate of AD; however, harmonized processing and transparency of data collection are needed. Global collaborations should embrace the inherent heterogeneity that exists in the data and quantify its contribution to research findings at the meta-analytical stage.

Investigating the neural mechanisms of transcranial direct current stimulation effects on human cognition: current issues and potential solutions

Transcranial direct current stimulation (tDCS) has been studied extensively for its potential to enhance human cognitive functions in healthy individuals and to treat cognitive impairment in various clinical populations. However, little is known about how tDCS modulates the neural networks supporting cognition and the complex interplay with mediating factors that may explain the frequently observed variability of stimulation effects within and between studies. Moreover, research in this field has been characterized by substantial methodological variability, frequent lack of rigorous experimental control and small sample sizes, thereby limiting the generalizability of findings and translational potential of tDCS. The present manuscript aims to delineate how these important issues can be addressed within a neuroimaging context, to reveal the neural underpinnings, predictors and mediators of tDCS-induced behavioral modulation. We will focus on functional magnetic resonance imaging (fMRI), because it allows the investigation of tDCS effects with excellent spatial precision and sufficient temporal resolution across the entire brain. Moreover, high resolution structural imaging data can be acquired for precise localization of stimulation effects, verification of electrode positions on the scalp and realistic current modeling based on individual head and brain anatomy. However, the general principles outlined in this review will also be applicable to other imaging modalities. Following an introduction to the overall state-of-the-art in this field, we will discuss in more detail the underlying causes of variability in previous tDCS studies. Moreover, we will elaborate on design considerations for tDCS-fMRI studies, optimization of tDCS and imaging protocols and how to assure high-level experimental control. Two additional sections address the pressing need for more systematic investigation of tDCS effects across the healthy human lifespan and implications for tDCS studies in age-associated disease, and potential benefits of establishing large-scale, multidisciplinary consortia for more coordinated tDCS research in the future. We hope that this review will contribute to more coordinated, methodologically sound, transparent and reproducible research in this field. Ultimately, our aim is to facilitate a better understanding of the underlying mechanisms by which tDCS modulates human cognitive functions and more effective and individually tailored translational and clinical applications of this technique in the future.

Transparency and Reproducibility in the Adolescent Brain Cognitive Development (ABCD) Study

Background

Transparency can build trust in the scientific process, but scientific findings can be undermined by poor and obscure data use and reporting practices. The purpose of this work is to report how data from the Adolescent Brain Cognitive Development (ABCD) Study has been used to date, and to provide practical recommendations on how to improve the transparency and reproducibility of findings.

Methods

Articles published from 2017 to 2023 that used ABCD Study data were reviewed using more than 30 data extraction items to gather information on data use practices. Total frequencies were reported for each extraction item, along with computation of a Level of Completeness (LOC) score that represented overall endorsement of extraction items. Univariate linear regression models were used to examine the correlation between LOC scores and individual extraction items. Post hoc analysis included examination of whether LOC scores were correlated with the logged 2-year journal impact factor.

Results

There were 549 full-length articles included in the main analysis. Analytic scripts were shared in 30% of full-length articles. The number of participants excluded due to missing data was reported in 60% of articles, and information on missing data for individual variables (e.g., household income) was provided in 38% of articles. A table describing the analytic sample was included in 83% of articles. A race and/or ethnicity variable was included in 78% of reviewed articles, while its inclusion was justified in only 41% of these articles. LOC scores were highly correlated with extraction items related to examination of missing data. A bottom 10% of LOC score was significantly correlated with a lower logged journal impact factor when compared to the top 10% of LOC scores (β=-0.77, 95% -1.02, -0.51; p-value < 0.0001).

Conclusion

These findings highlight opportunities for improvement in future papers using ABCD Study data to readily adapt analytic practices for better transparency and reproducibility efforts. A list of recommendations is provided to facilitate adherence in future research.

Functional neuroimaging as a catalyst for integrated neuroscience

Functional magnetic resonance imaging (fMRI) enables non-invasive access to the awake, behaving human brain. By tracking whole-brain signals across a diverse range of cognitive and behavioural states or mapping differences associated with specific traits or clinical conditions, fMRI has advanced our understanding of brain function and its links to both normal and atypical behaviour. Despite this headway, progress in human cognitive neuroscience that uses fMRI has been relatively isolated from rapid advances in other subdomains of neuroscience, which themselves are also somewhat siloed from one another. In this Perspective, we argue that fMRI is well-placed to integrate the diverse subfields of systems, cognitive, computational and clinical neuroscience. We first summarize the strengths and weaknesses of fMRI as an imaging tool, then highlight examples of studies that have successfully used fMRI in each subdomain of neuroscience. We then provide a roadmap for the future advances that will be needed to realize this integrative vision. In this way, we hope to demonstrate how fMRI can help usher in a new era of interdisciplinary coherence in neuroscience.

Spindle-dependent memory consolidation in healthy adults: A meta-analysis

Accumulating evidence suggests a central role for sleep spindles in the consolidation of new memories. However, no meta-analysis of the association between sleep spindles and memory performance has been conducted so far. Here, we report meta-analytical evidence for spindle-memory associations and investigate how multiple factors, including memory type, spindle type, spindle characteristics, and EEG topography affect this relationship. The literature search yielded 53 studies reporting 1427 effect sizes, resulting in a small to moderate effect for the average association. We further found that spindle-memory associations were significantly stronger for procedural memory than for declarative memory. Neither spindle types nor EEG scalp topography had an impact on the strength of the spindle-memory relation, but we observed a distinct functional role of global and fast sleep spindles, especially for procedural memory. We also found a moderation effect of spindle characteristics, with power showing the largest effect sizes. Collectively, our findings suggest that sleep spindles are involved in learning, thereby representing a general physiological mechanism for memory consolidation.

'One size doesn't fit all': Lessons from interaction analysis on tailoring Open Science practices to qualitative research

The Open Science Movement aims to enhance the soundness, transparency, and accessibility of scientific research, and at the same time increase public trust in science. Currently, Open Science practices are mainly presented as solutions to the 'reproducibility crisis' in hypothetico-deductive quantitative research. Increasing interest has been shown towards exploring how these practices can be adopted by qualitative researchers. In reviewing this emerging body of work, we conclude that the issue of diversity within qualitative research has not been adequately addressed. Furthermore, we find that many of these endeavours start with existing solutions for which they are trying to find matching problems to be solved. We contrast this approach with a natural incorporation of Open Science practices within interaction analysis and its constituent research traditions: conversation analysis, discursive psychology, ethnomethodology, and membership categorisation analysis. Zooming in on the development of conversation analysis starting in the 1960s, we highlight how practices for opening up and sharing data and analytic thinking have been embedded into its methodology. On the basis of this presentation, we propose a series of lessons learned for adopting Open Science practices in qualitative research.

The five pillars of computational reproducibility: bioinformatics and beyond

Computational reproducibility is a simple premise in theory, but is difficult to achieve in practice. Building upon past efforts and proposals to maximize reproducibility and rigor in bioinformatics, we present a framework called the five pillars of reproducible computational research. These include (1) literate programming, (2) code version control and sharing, (3) compute environment control, (4) persistent data sharing and (5) documentation. These practices will ensure that computational research work can be reproduced quickly and easily, long into the future. This guide is designed for bioinformatics data analysts and bioinformaticians in training, but should be relevant to other domains of study.

Multimodal smoking cessation treatment combining transcranial magnetic stimulation, cognitive behavioral therapy, and nicotine replacement therapy in veterans with posttraumatic stress disorder: A feasibility randomized controlled trial protocol

Tobacco-related deaths exceed those resulting from homicides, suicides, motor vehicle accidence, alcohol consumption, illicit substance use, and acquired immunodeficiency syndrome (AIDS), combined. Amongst U.S. veterans, this trend is particularly concerning given that those suffering from posttraumatic stress disorder (PTSD)-about 11% of those receiving care from the Department of Veterans Affairs (VA)-have triple the risk of developing tobacco use disorder (TUD). The most efficacious strategies being used at the VA for smoking cessation only result in a 23% abstinence rate, and veterans with PTSD only achieve a 4.5% abstinence rate. Therefore, there is a critical need to develop more effective treatments for smoking cessation. Recent studies have revealed the insula as integrally involved in the neurocircuitry of TUD, specifically showing that individuals with brain lesions involving this region had drastically improved quit rates. Some of these studies show a probability of quitting up to 5 times greater compared to non-insula lesioned regions). Altered activity of the insula may be involved in the disruption of the salience network's (SN) connectivity to the executive control network (ECN), which compromises that patient's ability to switch between interoceptive states focused on cravings to executive and cognitive control. Thus, we propose a feasibility phase II randomized controlled trial (RCT) to study a patterned form of repetitive transcranial magnetic stimulation (rTMS), intermittent theta burst stimulation (iTBS), at 90% of the subject's resting motor threshold (rMT) applied over a region in the right post-central gyrus most functionally connected to the right posterior insula. We hypothesize that by increasing functional connectivity between the SN with the ECN to enhance executive control and by decreasing connectivity with the default mode network (DMN) to reduce interoceptive focus on withdrawal symptoms, we will improve smoking cessation outcomes. Fifty eligible veterans with comorbid TUD and PTSD will be randomly assigned to two conditions: active-iTBS + cognitive behavioral therapy (CBT) + nicotine replacement therapy (NRT) (n=25) or sham-iTBS + CBT + NRT (n=25). The primary outcome, feasibility, will be determined by achieving a recruitment of 50 participants and retention rate of 80%. The success of iTBS will be evaluated through self-reported nicotine use, cravings, withdrawal symptoms, and abstinence following quit date (confirmed by bioverification) along with evaluation for target engagement through neuroimaging changes, specifically connectivity differences between the insula and other regions of interest.

BrainForge: an online data analysis platform for integrative neuroimaging acquisition, analysis, and sharing

BrainForge is a cloud-enabled, web-based analysis platform for neuroimaging research. This website allows users to archive data from a study and effortlessly process data on a high-performance computing cluster. After analyses are completed, results can be quickly shared with colleagues. BrainForge solves multiple problems for researchers who want to analyze neuroimaging data, including issues related to software, reproducibility, computational resources, and data sharing. BrainForge can currently process structural, functional, diffusion, and arterial spin labeling MRI modalities, including preprocessing and group level analyses. Additional pipelines are currently being added, and the pipelines can accept the BIDS format. Analyses are conducted completely inside of Singularity containers and utilize popular software packages including Nipype, Statistical Parametric Mapping, the Group ICA of fMRI Toolbox, and FreeSurfer. BrainForge also features several interfaces for group analysis, including a fully automated adaptive ICA approach.

The confound of hemodynamic response function variability in human resting-state functional MRI studies

Functional magnetic resonance imaging (fMRI) is an indirect measure of neural activity with the hemodynamic response function (HRF) coupling it with unmeasured neural activity. The HRF, modulated by several non-neural factors, is variable across brain regions, individuals and populations. Yet, a majority of human resting-state fMRI connectivity studies continue to assume a non-variable HRF. In this article, with supportive prior evidence, we argue that HRF variability cannot be ignored as it substantially confounds within-subject connectivity estimates and between-subjects connectivity group differences. We also discuss its clinical relevance with connectivity impairments confounded by HRF aberrations in several disorders. We present limited data on HRF differences between women and men, which resulted in a 15.4% median error in functional connectivity estimates in a group-level comparison. We also discuss the implications of HRF variability for fMRI studies in the spinal cord. There is a need for more dialogue within the community on the HRF confound, and we hope that our article is a catalyst in the process.

Time of day dependent longitudinal changes in resting-state fMRI

Longitudinal studies have become more common in the past years due to their superiority over cross-sectional samples. In light of the ongoing replication crisis, the factors that may introduce variability in resting-state networks have been widely debated. This publication aimed to address the potential sources of variability, namely, time of day, sex, and age, in longitudinal studies within individual resting-state fMRI data. DCM was used to analyze the fMRI time series, extracting EC connectivity measures and parameters that define the BOLD signal. In addition, a two-way ANOVA was used to assess the change in EC and parameters that define the BOLD signal between data collection waves. The results indicate that time of day and gender have significant model evidence for the parameters that define the BOLD signal but not EC. From the ANOVA analysis, findings indicate that there was a significant change in the two nodes of the DMN and their connections with the fronto-parietal network. Overall, these findings suggest that in addition to age and gender, which are commonly accounted for in the fMRI data collection, studies should note the time of day, possibly treating it as a covariate in longitudinal samples.

Open Science Practices in Gambling Research Publications (2016-2019): A Scoping Review

The replication crisis has stimulated researchers around the world to adopt open science research practices intended to reduce publication bias and improve research quality. Open science practices include study pre-registration, open data, open access, and avoiding methods that can lead to publication bias and low replication rates. Although gambling studies uses similar research methods as behavioral research fields that have struggled with replication, we know little about the uptake of open science research practices in gambling-focused research. We conducted a scoping review of 500 recent (1/1/2016-12/1/2019) studies focused on gambling and problem gambling to examine the use of open science and transparent research practices. Our results showed that a small percentage of studies used most practices: whereas 54.6% (95% CI: [50.2, 58.9]) of studies used at least one of nine open science practices, each practice's prevalence was: 1.6% for pre-registration (95% CI: [0.8, 3.1]), 3.2% for open data (95% CI: [2.0, 5.1]), 0% for open notebook, 35.2% for open access (95% CI: [31.1, 39.5]), 7.8% for open materials (95% CI: [5.8, 10.5]), 1.4% for open code (95% CI: [0.7, 2.9]), and 15.0% for preprint posting (95% CI: [12.1, 18.4]). In all, 6.4% (95% CI: [4.6, 8.9]) of the studies included a power analysis and 2.4% (95% CI: [1.4, 4.2]) were replication studies. Exploratory analyses showed that studies that used any open science practice, and open access in particular, had higher citation counts. We suggest several practical ways to enhance the uptake of open science principles and practices both within gambling studies and in science more generally.

Using preregistration as a tool for transparent fNIRS study design

Significance

The expansion of functional near-infrared spectroscopy (fNIRS) methodology and analysis tools gives rise to various design and analytical decisions that researchers have to make. Several recent efforts have developed guidelines for preprocessing, analyzing, and reporting practices. For the planning stage of fNIRS studies, similar guidance is desirable. Study preregistration helps researchers to transparently document study protocols before conducting the study, including materials, methods, and analyses, and thus, others to verify, understand, and reproduce a study. Preregistration can thus serve as a useful tool for transparent, careful, and comprehensive fNIRS study design.

Aim

We aim to create a guide on the design and analysis steps involved in fNIRS studies and to provide a preregistration template specified for fNIRS studies.

Approach

The presented preregistration guide has a strong focus on fNIRS specific requirements, and the associated template provides examples based on continuous-wave (CW) fNIRS studies conducted in humans. These can, however, be extended to other types of fNIRS studies.

Results

On a step-by-step basis, we walk the fNIRS user through key methodological and analysis-related aspects central to a comprehensive fNIRS study design. These include items specific to the design of CW, task-based fNIRS studies, but also sections that are of general importance, including an in-depth elaboration on sample size planning.

Conclusions

Our guide introduces these open science tools to the fNIRS community, providing researchers with an overview of key design aspects and specification recommendations for comprehensive study planning. As such it can be used as a template to preregister fNIRS studies or merely as a tool for transparent fNIRS study design.

Functional magnetic resonance imaging of headache: Issues, best-practices, and new directions, a narrative review

OBJECTIVE

To ensure readers are informed consumers of functional magnetic resonance imaging (fMRI) research in headache, to outline ongoing challenges in this area of research, and to describe potential considerations when asked to collaborate on fMRI research in headache, as well as to suggest future directions for improvement in the field.

BACKGROUND

Functional MRI has played a key role in understanding headache pathophysiology, and mapping networks involved with headache-related brain activity have the potential to identify intervention targets. Some investigators have also begun to explore its use for diagnosis.

METHODS/RESULTS

The manuscript is a narrative review of the current best practices in fMRI in headache research, including guidelines on transparency and reproducibility. It also contains an outline of the fundamentals of MRI theory, task-related study design, resting-state functional connectivity, relevant statistics and power analysis, image preprocessing, and other considerations essential to the field.

CONCLUSION

Best practices to increase reproducibility include methods transparency, eliminating error, using a priori hypotheses and power calculations, using standardized instruments and diagnostic criteria, and developing large-scale, publicly available datasets.

Multisite test-retest reliability and compatibility of brain metrics derived from FreeSurfer versions 7.1, 6.0, and 5.3

Automatic neuroimaging processing tools provide convenient and systematic methods for extracting features from brain magnetic resonance imaging scans. One tool, FreeSurfer, provides an easy-to-use pipeline to extract cortical and subcortical morphometric measures. There have been over 25 stable releases of FreeSurfer, with different versions used across published works. The reliability and compatibility of regional morphometric metrics derived from the most recent version releases have yet to be empirically assessed. Here, we used test-retest data from three public data sets to determine within-version reliability and between-version compatibility across 42 regional outputs from FreeSurfer versions 7.1, 6.0, and 5.3. Cortical thickness from v7.1 was less compatible with that of older versions, particularly along the cingulate gyrus, where the lowest version compatibility was observed (intraclass correlation coefficient 0.37-0.61). Surface area of the temporal pole, frontal pole, and medial orbitofrontal cortex, also showed low to moderate version compatibility. We confirm low compatibility between v6.0 and v5.3 of pallidum and putamen volumes, while those from v7.1 were compatible with v6.0. Replication in an independent sample showed largely similar results for measures of surface area and subcortical volumes, but had lower overall regional thickness reliability and compatibility. Batch effect correction may adjust for some inter-version effects when most sites are run with one version, but results vary when more sites are run with different versions. Age associations in a quality controlled independent sample (N = 106) revealed version differences in results of downstream statistical analysis. We provide a reference to highlight the regional metrics that may yield recent version-related inconsistencies in published findings. An interactive viewer is provided at http://data.brainescience.org/Freesurfer_Reliability/.

Notes on fiber length measurements: A case study in the underbelly of open source neuroscience

Being on the bleeding edge of research requires the use of new and regularly updated software. The result is the occasional and inevitable occurrence of bugs. In the following work we present a case study where a feature request introduced a bug in a neuroimaging software package, which had consequences for the quality of results in a published article. We discuss the process of diagnosis, rectification and analysis replication.

Open and reproducible neuroimaging: From study inception to publication

Empirical observations of how labs conduct research indicate that the adoption rate of open practices for transparent, reproducible, and collaborative science remains in its infancy. This is at odds with the overwhelming evidence for the necessity of these practices and their benefits for individual researchers, scientific progress, and society in general. To date, information required for implementing open science practices throughout the different steps of a research project is scattered among many different sources. Even experienced researchers in the topic find it hard to navigate the ecosystem of tools and to make sustainable choices. Here, we provide an integrated overview of community-developed resources that can support collaborative, open, reproducible, replicable, robust and generalizable neuroimaging throughout the entire research cycle from inception to publication and across different neuroimaging modalities. We review tools and practices supporting study inception and planning, data acquisition, research data management, data processing and analysis, and research dissemination. An online version of this resource can be found at https://oreoni.github.io. We believe it will prove helpful for researchers and institutions to make a successful and sustainable move towards open and reproducible science and to eventually take an active role in its future development.

Good scientific practice in EEG and MEG research: Progress and perspectives

Good scientific practice (GSP) refers to both explicit and implicit rules, recommendations, and guidelines that help scientists to produce work that is of the highest quality at any given time, and to efficiently share that work with the community for further scrutiny or utilization. For experimental research using magneto- and electroencephalography (MEEG), GSP includes specific standards and guidelines for technical competence, which are periodically updated and adapted to new findings. However, GSP also needs to be regularly revisited in a broader light. At the LiveMEEG 2020 conference, a reflection on GSP was fostered that included explicitly documented guidelines and technical advances, but also emphasized intangible GSP: a general awareness of personal, organizational, and societal realities and how they can influence MEEG research. This article provides an extensive report on most of the LiveMEEG contributions and new literature, with the additional aim to synthesize ongoing cultural changes in GSP. It first covers GSP with respect to cognitive biases and logical fallacies, pre-registration as a tool to avoid those and other early pitfalls, and a number of resources to enable collaborative and reproducible research as a general approach to minimize misconceptions. Second, it covers GSP with respect to data acquisition, analysis, reporting, and sharing, including new tools and frameworks to support collaborative work. Finally, GSP is considered in light of ethical implications of MEEG research and the resulting responsibility that scientists have to engage with societal challenges. Considering among other things the benefits of peer review and open access at all stages, the need to coordinate larger international projects, the complexity of MEEG subject matter, and today's prioritization of fairness, privacy, and the environment, we find that current GSP tends to favor collective and cooperative work, for both scientific and for societal reasons.

Reproducing FSL's fMRI data analysis via Nipype: Relevance, challenges, and solutions

The "replication crisis" in neuroscientific research has led to calls for improving reproducibility. In traditional neuroscience analyses, irreproducibility may occur as a result of issues across various stages of the methodological process. For example, different operating systems, different software packages, and even different versions of the same package can lead to variable results. Nipype, an open-source Python project, integrates different neuroimaging software packages uniformly to improve the reproducibility of neuroimaging analyses. Nipype has the advantage over traditional software packages (e.g., FSL, ANFI, SPM, etc.) by (1) providing comprehensive software development frameworks and usage information, (2) improving computational efficiency, (3) facilitating reproducibility through sufficient details, and (4) easing the steep learning curve. Despite the rich tutorials it has provided, the Nipype community lacks a standard three-level GLM tutorial for FSL. Using the classical Flanker task dataset, we first precisely reproduce a three-level GLM analysis with FSL via Nipype. Next, we point out some undocumented discrepancies between Nipype and FSL functions that led to substantial differences in results. Finally, we provide revised Nipype code in re-executable notebooks that assure result invariability between FSL and Nipype. Our analyses, notebooks, and operating software specifications (e.g., docker build files) are available on the Open Science Framework platform.

State or trait: the neurobiology of anorexia nervosa - contributions of a functional magnetic resonance imaging study

BACKGROUND

The understanding of the cerebral neurobiology of anorexia nervosa (AN) with respect to state- versus trait-related abnormalities is limited. There is evidence of restitution of structural brain alterations with clinical remission. However, with regard to functional brain abnormalities, this issue has not yet been clarified.

METHODS

We compared women with AN (n = 31), well-recovered female participants (REC) (n = 18) and non-patients (NP) (n = 27) cross-sectionally. Functional magnetic resonance imaging was performed to compare neural responses to food versus non-food images. Additionally, affective ratings were assessed.

RESULTS

Functional responses and affective ratings did not differ between REC and NP, even when applying lenient thresholds for the comparison of neural responses. Comparing REC and AN, the latter showed lower valence and higher arousal ratings for food stimuli, and neural responses differed with lenient thresholds in an occipital region.

CONCLUSIONS

The data are in line with some previous findings and suggest restitution of cerebral function with clinical recovery. Furthermore, affective ratings did not differ from NP. These results need to be verified in intra-individual longitudinal studies.

Decision neuroscience and neuroeconomics: Recent progress and ongoing challenges

In the past decade, decision neuroscience and neuroeconomics have developed many new insights in the study of decision making. This review provides an overarching update on how the field has advanced in this time period. Although our initial review a decade ago outlined several theoretical, conceptual, methodological, empirical, and practical challenges, there has only been limited progress in resolving these challenges. We summarize significant trends in decision neuroscience through the lens of the challenges outlined for the field and review examples where the field has had significant, direct, and applicable impacts across economics and psychology. First, we review progress on topics including reward learning, explore-exploit decisions, risk and ambiguity, intertemporal choice, and valuation. Next, we assess the impacts of emotion, social rewards, and social context on decision making. Then, we follow up with how individual differences impact choices and new exciting developments in the prediction and neuroforecasting of future decisions. Finally, we consider how trends in decision-neuroscience research reflect progress toward resolving past challenges, discuss new and exciting applications of recent research, and identify new challenges for the field. This article is categorized under: Psychology > Reasoning and Decision Making Psychology > Emotion and Motivation.

(Un)common space in infant neuroimaging studies: A systematic review of infant templates

In neuroimaging, spatial normalization is an important step that maps an individual's brain onto a template brain permitting downstream statistical analyses. Yet, in infant neuroimaging, there remain several technical challenges that have prevented the establishment of a standardized template for spatial normalization. Thus, many different approaches are used in the literature. To quantify the popularity and variability of these approaches in infant neuroimaging studies, we performed a systematic review of infant magnetic resonance imaging (MRI) studies from 2000 to 2020. Here, we present results from 834 studies meeting inclusion criteria. Studies were classified into (a) processing data in single subject space, (b) using an off the shelf, or "off the shelf," template, (c) creating a study specific template, or (d) using a hybrid of these methods. We found that across the studies in the systematic review, single subject space was the most used (no common space). This was the most used common space for diffusion-weighted imaging and structural MRI studies while functional MRI studies preferred off the shelf atlases. We found a pattern such that more recently published studies are more commonly using off the shelf atlases. When considering special populations, preterm studies most used single subject space while, when no special populations were being analyzed, an off the shelf template was most common. The most used off the shelf templates were the UNC Infant Atlases (24%). Using a systematic review of infant neuroimaging studies, we highlight a lack of an established "standard" template brain in these studies.

Surface-Based Amplitude of Low-Frequency Fluctuation Alterations in Patients With Tinnitus Before and After Sound Therapy: A Resting-State Functional Magnetic Resonance Imaging Study

This study aimed to investigate abnormal tinnitus activity by evaluating brain surface-based amplitude of low-frequency fluctuation (ALFF) changes detected by resting-state functional magnetic resonance imaging (RS-fMRI) in patients with idiopathic tinnitus before and after 24 weeks of sound therapy. We hypothesized that sound therapy could gradually return cortical local brain function to a relatively normal range. In this prospective observational study, we recruited thirty-three tinnitus patients who had undergone 24 weeks of sound therapy and 26 matched healthy controls (HCs). For the two groups of subjects, we analyzed the spontaneous neural activity of tinnitus patients by cortical ALFF and detected its correlation with clinical indicators of tinnitus. Patients’ Tinnitus Handicap Inventory (THI) scores were assessed to determine the severity of their tinnitus before and after treatment. Two-way mixed model analysis of variance and Pearson’s correlation analysis were used in the statistical analysis. Student–Newman–Keuls tests were used in the post hoc analysis. Interaction effects between the two groups and between the two scans revealing local neural activity as assessed by ALFF were observed in the bilateral dorsal stream visual cortex (DSVC), bilateral posterior cingulate cortex (PCC), bilateral anterior cingulate and medial prefrontal cortex (ACC and MPC), left temporo-parieto-occipital junction (TPOJ), left orbital and polar frontal cortex (OPFC), left paracentral lobular and mid cingulate cortex (PCL and MCC), right insular and frontal opercular cortex (IFOC), and left early visual cortex (EVC). Importantly, local functional activity in the left TPOJ and right PCC in the patient group was significantly lower than that in the HCs at baseline and was increased to relatively normal levels after treatment. The 24-week sound therapy tinnitus group demonstrated significantly higher ALFF in the left TPOJ and right PCC than in the tinnitus baseline group. Also, compared with the HC baseline group and the 24-week HC group, the 24-week sound therapy tinnitus group demonstrated slightly lower or higher ALFF in the left TPOJ and right PCC, and there were no differences between the 24-week sound therapy tinnitus and HC groups. Decreased THI scores and ALFF changes in the abovementioned brain regions were not correlated. Taken together, surface-based RS-fMRI can provide more subtle local functional activity to explain the mechanism of tinnitus treatment, and long-term sound therapy had a normalizing effect on tinnitus patients.

Large, open datasets for human connectomics research: Considerations for reproducible and responsible data use

Large, open datasets have emerged as important resources in the field of human connectomics. In this review, the evolution of data sharing involving magnetic resonance imaging is described. A summary of the challenges and progress in conducting reproducible data analyses is provided, including description of recent progress made in the development of community guidelines and recommendations, software and data management tools, and initiatives to enhance training and education. Finally, this review concludes with a discussion of ethical conduct relevant to analyses of large, open datasets and a researcher's responsibility to prevent further stigmatization of historically marginalized racial and ethnic groups. Moving forward, future work should include an enhanced emphasis on the social determinants of health, which may further contextualize findings among diverse population-based samples. Leveraging the progress to date and guided by interdisciplinary collaborations, the future of connectomics promises to be an impressive era of innovative research, yielding a more inclusive understanding of brain structure and function.

Crowdsourcing Global Perspectives in Ecology Using Social Media

Transparent, open, and reproducible research is still far from routine, and the full potential of open science has not yet been realized. Crowdsourcing–defined as the usage of a flexible open call to a heterogeneous group of individuals to recruit volunteers for a task –is an emerging scientific model that encourages larger and more outwardly transparent collaborations. While crowdsourcing, particularly through citizen- or community-based science, has been increasing over the last decade in ecological research, it remains infrequently used as a means of generating scientific knowledge in comparison to more traditional approaches. We explored a new implementation of crowdsourcing by using an open call on social media to assess its utility to address fundamental ecological questions. We specifically focused on pervasive challenges in predicting, mitigating, and understanding the consequences of disturbances. In this paper, we briefly review open science concepts and their benefits, and then focus on the new methods we used to generate a scientific publication. We share our approach, lessons learned, and potential pathways forward for expanding open science. Our model is based on the beliefs that social media can be a powerful tool for idea generation and that open collaborative writing processes can enhance scientific outcomes. We structured the project in five phases: (1) draft idea generation, (2) leadership team recruitment and project development, (3) open collaborator recruitment via social media, (4) iterative paper development, and (5) final editing, authorship assignment, and submission by the leadership team. We observed benefits including: facilitating connections between unusual networks of scientists, providing opportunities for early career and underrepresented groups of scientists, and rapid knowledge exchange that generated multidisciplinary ideas. We also identified areas for improvement, highlighting biases in the individuals that self-selected participation and acknowledging remaining barriers to contributing new or incompletely formed ideas into a public document. While shifting scientific paradigms to completely open science is a long-term process, our hope in publishing this work is to encourage others to build upon and improve our efforts in new and creative ways.

Age of First Exposure to Contact and Collision Sports and Later in Life Brain Health: A Narrative Review

A controversial theory proposes that playing tackle football before the age of 12 causes later in life brain health problems. This theory arose from a small study of 42 retired National Football League (NFL) players, which reported that those who started playing tackle football at a younger age performed worse on selected neuropsychological tests and a word reading test. The authors concluded that these differences were likely due to greater exposure to repetitive neurotrauma during a developmentally sensitive maturational period in their lives. Several subsequent studies of current high school and collegiate contact/collision sports athletes, and former high school, collegiate, and professional tackle football players have not replicated these findings. This narrative review aims to (i) discuss the fundamental concepts, issues, and controversies surrounding existing research on age of first exposure (AFE) to contact/collision sport, and (ii) provide a balanced interpretation, including risk of bias assessment findings, of this body of evidence. Among 21 studies, 11 studies examined former athletes, 8 studies examined current athletes, and 2 studies examined both former and current athletes. Although the literature on whether younger AFE to tackle football is associated with later in life cognitive, neurobehavioral, or mental health problems in former NFL players is mixed, the largest study of retired NFL players (N = 3,506) suggested there was not a significant association between earlier AFE to organized tackle football and worse subjectively experienced cognitive functioning, depression, or anxiety. Furthermore, no published studies of current athletes show a significant association between playing tackle football (or other contact/collision sports) before the age of 12 and cognitive, neurobehavioral, or mental health problems. It is important to note that all studies were judged to be at high overall risk of bias, indicating that more methodologically rigorous research is needed to understand whether there is an association between AFE to contact/collision sports and later in life brain health. The accumulated research to date suggests that earlier AFE to contact/collision sports is not associated with worse cognitive functioning or mental health in (i) current high school athletes, (ii) current collegiate athletes, or (iii) middle-aged men who played high school football. The literature on former NFL players is mixed and does not, at present, clearly support the theory that exposure to tackle football before age 12 is associated with later in life cognitive impairment or mental health problems.

When Is Simultaneous Recording Necessary? A Guide for Researchers Considering Combined EEG-fMRI

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) provide non-invasive measures of brain activity at varying spatial and temporal scales, offering different views on brain function for both clinical and experimental applications. Simultaneous recording of these measures attempts to maximize the respective strengths of each method, while compensating for their weaknesses. However, combined recording is not necessary to address all research questions of interest, and experiments may have greater statistical power to detect effects by maximizing the signal-to-noise ratio in separate recording sessions. While several existing papers discuss the reasons for or against combined recording, this article aims to synthesize these arguments into a flow chart of questions that researchers can consider when deciding whether to record EEG and fMRI separately or simultaneously. Given the potential advantages of simultaneous EEG-fMRI, the aim is to provide an initial overview of the most important concepts and to direct readers to relevant literature that will aid them in this decision.

The Effects of Amyloid and Tau on Functional Network Connectivity in Older Populations

Background: Neuroimaging studies suggest that aged brains show altered connectivity within and across functional networks. Similar changes in functional network integrity are also linked to the accumulation of pathological proteins in the brain, such as amyloid-beta plaques and neurofibrillary tau tangles seen in Alzheimer's disease. However, less is known about the specific impacts of amyloid and tau on functional network connectivity in cognitively normal older adults who harbor these proteins. Methods: We briefly summarize recent neuroimaging studies of aging and then thoroughly review positron emission tomography and functional magnetic resonance imaging studies measuring the relationship between amyloid-tau pathology and functional connectivity in cognitively normal older individuals. Results: The literature overall suggests that amyloid-positive older individuals show minor cognitive dysfunction and aberrant default mode network connectivity compared with amyloid-negative individuals. Tau, however, is more closely associated with network hypoconnectivity and poorer cognition. Those with substantial amyloid and tau experience even greater cognitive decline compared with those with primarily amyloid or tau, suggesting a potential interaction. Multimodal neuroimaging studies suggest that older adults with pathological protein deposits show amyloid-related hyperconnectivity and tau-related hypoconnectivity in multiple functional networks, including the default mode and frontoparietal networks. Discussion: We propose an updated model considering the effects of amyloid and tau on functional connectivity in older individuals. Large, longitudinal neuroimaging studies with multiple levels of analysis are required to obtain a deeper understanding of the dynamic relationship between pathological protein accumulation and functional connectivity changes, as amyloid- and tau-induced connectivity alterations may have critical and time-varying effects on neurodegeneration and cognitive decline. Impact statement Amyloid and tau accumulation have been linked with altered functional connectivity in cognitively normal older adults. This review synthesized recent functional imaging literatures in a discussion of how amyloid and tau can interactively affect functional connectivity in nonlinear ways, which can explain previous conflicting findings. Changes in connectivity strength may depend on the accumulation of both amyloid and tau, and their integrative effects seem to have critical consequences on cognition. Elucidating the effects of these pathological proteins on brain functioning is paramount to understand the etiology of Alzheimer's disease and the aging process overall.

Strategies to Understand the Weight-Reduced State: Genetics and Brain Imaging

Most individuals with obesity or overweight have difficulty maintaining weight loss. The weight-reduced state induces changes in many physiological processes that appear to drive weight regain. Here, we review the use of cell biology, genetics, and imaging techniques that are being used to begin understanding why weight regain is the normal response to dieting. As with obesity itself, weight regain has both genetic and environmental drivers. Genetic drivers for "thinness" and "obesity" largely overlap, but there is evidence for specific genetic loci that are different for each of these weight states. There is only limited information regarding the genetics of weight regain. Currently, most genetic loci related to weight point to the central nervous system as the organ responsible for determining the weight set point. Neuroimaging tools have proved useful in studying the contribution of the central nervous system to the weight-reduced state in humans. Neuroimaging technologies fall into three broad categories: functional, connectivity, and structural neuroimaging. Connectivity and structural imaging techniques offer unique opportunities for testing mechanistic hypotheses about changes in brain function or tissue structure in the weight-reduced state.

Cortical thickness in Parkinson's disease: a coordinate-based meta-analysis

Parkinson's disease (PD) is a common age-related neurodegenerative disease that affects the structural architecture of the cerebral cortex. Cortical thickness (CTh) via surface-based morphometry (SBM) analysis is a popular measure to assess brain structural alterations in the gray matter in PD. However, the results of CTh analysis in PD lack consistency and have not been systematically reviewed. We conducted a comprehensive coordinate-based meta-analysis (CBMA) of 38 CTh studies (57 comparison datasets) in 1,843 patients with PD using the latest seed-based d mapping software. Compared with 1,172 healthy controls, no significantly consistent CTh alterations were found in patients with PD, suggesting CTh as an unreliable neuroimaging marker for PD. The lack of consistent CTh alterations in PD could be ascribed to the heterogeneity in clinical populations, variations in imaging methods, and underpowered small sample sizes. These results highlight the need to control for potential confounding factors to produce robust and reproducible CTh results in PD.

Resting-State fMRI to Identify the Brain Correlates of Treatment Response to Medications in Children and Adolescents With Attention-Deficit/Hyperactivity Disorder: Lessons From the CUNMET Study

Neuroimaging research seeks to identify biomarkers to improve the diagnosis, prognosis, and treatment of attention-deficit/hyperactivity disorder (ADHD), although clinical translation of findings remains distant. Resting-state functional magnetic resonance imaging (R-fMRI) is increasingly being used to characterize functional connectivity in the brain. Despite mixed results to date and multiple methodological challenges, dominant hypotheses implicate hyperconnectivity across brain networks in patients with ADHD, which could be the target of pharmacological treatments. We describe the experience and results of the Clínica Universidad de Navarra (Spain) Metilfenidato (CUNMET) pilot study. CUNMET tested the feasibility of identifying R-fMRI markers of clinical response in children with ADHD undergoing naturalistical pharmacological treatments. We analyzed cross-sectional data from 56 patients with ADHD (18 treated with methylphenidate, 18 treated with lisdexamfetamine, and 20 treatment-naive patients). Standard preprocessing and statistical analyses with attention to control for head motion and correction for multiple comparisons were performed. The only results that survived correction were noted in contrasts of children who responded clinically to lisdexamfetamine after long-term treatment vs. treatment-naive patients. In these children, we observed stronger negative correlations (anticorrelations) across nodes in six brain networks, which is consistent with higher across-network functional segregation in patients treated with lisdexamfetamine, i.e., less inter-network interference than in treatment-naive patients. We also note the lessons learned, which could help those pursuing clinically relevant multidisciplinary research in ADHD en route to eventual personalized medicine. To advance reproducible open science, our report is accompanied with links providing access to our data and analytic scripts.

Transparency in clinical trials: Adding value to paediatric dental research

BACKGROUND

Even though considered as studies with high methodological power, many RCTs in paediatric dentistry do not have essential quality items in their design, development, and report, making results' reliability questionable, replication challenging to conduct, wasting time, money, and efforts, and even exposing the participants to research for no benefit.

AIM

We addressed the main topics related to transparency in clinical research, with an emphasis in paediatric dentistry.

DESIGN

We searched for all controlled clinical trials published from January 2019 up to July 2020 in the three paediatric dentistry journals with high journal Impact Factor, indexed on Medline. These papers were assessed for transparency according to Open Science practices and regarding reporting accuracy using some items required by CONSORT.

RESULTS

53.6% of the studies declared registration, 75% had sample size calculation, 98.2% reported randomisation, and from those, 65.4% explained the randomisation method. Besides that, no study shared their data, and 6.8% were published in open access format.

CONCLUSIONS

Unfortunately, a large proportion of RCTs in paediatric dental research show a lack of transparency and reproducibility.

Fully synthetic neuroimaging data for replication and exploration

Scientific transparency, data exploration, and education are advanced through data sharing. However, risk for disclosure of personal information and institutional data sharing regulations can impede human subject/patient data sharing and thus limit open science initiatives. Sharing fully synthetic data is an alternative when it is not possible to share real or observed data. Here we describe a data sharing approach that borrows principles and methods from multiple imputation to replace observed values with synthetic values, thereby creating a fully synthetic neuroimaging dataset that accurately represents the covariance structure of the observed dataset. Predictor tables composed of demographic, site, behavioral and total intracranial volume (ICV) variables from 264 pediatric cases were used to create synthetic predictor tables, which were then used to synthesize gray matter images derived from T1-weighted data. The synthetic predictor tables demonstrated pooled variance and statistical estimates that closely approximated the observed data, as reflected in measures of efficiency and statistical bias. Similarly, the synthetic gray matter data accurately represented the variance and voxel-level associations with predictor variables (age, sex, verbal IQ, and ICV). The magnitude and spatial distribution of gray matter effects in the observed imaging data were replicated in the pooled results from the synthetic datasets. This approach for generating fully synthetic neuroimaging data has widespread potential for data sharing, including replication, new discovery, and education. Fully synthetic neuroimaging datasets can enable data-sharing because it accurately represents patterns of variance in the original data, while diminishing the risk of privacy disclosures that can accompany neuroimaging data sharing.

A tale of too many tasks: task fragmentation in motor learning and a call for model task paradigms

Motor learning encompasses a broad set of phenomena that requires a diverse set of experimental paradigms. However, excessive variation in tasks across studies creates fragmentation that can adversely affect the collective advancement of knowledge. Here, we show that motor learning studies tend toward extreme fragmentation in the choice of tasks, with almost no overlap between task paradigms across studies. We argue that this extreme level of task fragmentation poses serious theoretical and methodological barriers to advancing the field. To address these barriers, we propose the need for developing common 'model' task paradigms which could be widely used across labs. Combined with the open sharing of methods and data, we suggest that these model task paradigms could be an important step in increasing the robustness of the motor learning literature and facilitate the cumulative process of science.

Data Triangulation in Consumer Neuroscience: Integrating Functional Neuroimaging With Meta-Analyses, Psychometrics, and Behavioral Data

This article reviews a wide range of functional magnetic resonance imaging (fMRI) studies conducted in the field of consumer neuroscience to (1) highlight common interpretative approaches of neuroimaging data (i.e., forward inference and reverse inference), (2) discuss potential interpretative issues associated with these approaches, and (3) provide a framework that employs a multi-method approach aimed to possibly raise the explanatory power and, thus, the validity of functional neuroimaging research in consumer neuroscience. Based on this framework, we argue that the validity of fMRI studies can be improved by the triangulation of (1) careful design of neuroimaging studies and analyses of data, (2) meta-analyses, and (3) the integration of psychometric and behavioral data with neuroimaging data. Guidelines on when and how to employ triangulation methods on neuroimaging data are included. Moreover, we also included discussions on practices and research directions that validate fMRI studies in consumer neuroscience beyond data triangulation.

Improving practices and inferences in developmental cognitive neuroscience

The past decade has seen growing concern about research practices in cognitive neuroscience, and psychology more broadly, that shake our confidence in many inferences in these fields. We consider how these issues affect developmental cognitive neuroscience, with the goal of progressing our field to support strong and defensible inferences from our neurobiological data. This manuscript focuses on the importance of distinguishing between confirmatory versus exploratory data analysis approaches in developmental cognitive neuroscience. Regarding confirmatory research, we discuss problems with analytic flexibility, appropriately instantiating hypotheses, and controlling the error rate given how we threshold data and correct for multiple comparisons. To counterbalance these concerns with confirmatory analyses, we present two complementary strategies. First, we discuss the advantages of working within an exploratory analysis framework, including estimating and reporting effect sizes, using parcellations, and conducting specification curve analyses. Second, we summarize defensible approaches for null hypothesis significance testing in confirmatory analyses, focusing on transparent and reproducible practices in our field. Specific recommendations are given, and templates, scripts, or other resources are hyperlinked, whenever possible.

An assessment of the autism neuroimaging literature for the prospects of re-executability

Background: The degree of reproducibility of the neuroimaging literature in psychiatric application areas has been called into question and the issues that relate to this reproducibility are extremely complex. Some of these complexities have to do with the underlying biology of the disorders that we study and others arise due to the technology we apply to the analysis of the data we collect. Ultimately, the observations we make get communicated to the rest of the community through publications in the scientific literature. Methods: We sought to perform a 're-executability survey' to evaluate the recent neuroimaging literature with an eye toward seeing if the technical aspects of our publication practices are helping or hindering the overall quest for a more reproducible understanding of brain development and aging. The topic areas examined include availability of the data, the precision of the imaging method description and the reporting of the statistical analytic approach, and the availability of the complete results. We applied the survey to 50 publications in the autism neuroimaging literature that were published between September 16, 2017 to October 1, 2018. Results: The results of the survey indicate that for the literature examined, data that is not already part of a public repository is rarely available, software tools are usually named but versions and operating system are not, it is expected that reasonably skilled analysts could approximately perform the analyses described, and the complete results of the studies are rarely available.  Conclusions: We have identified that there is ample room for improvement in research publication practices. We hope exposing these issues in the retrospective literature can provide guidance and motivation for improving this aspect of our reporting practices in the future.

An assessment of the autism neuroimaging literature for the prospects of re-executability

Background: The degree of reproducibility of the neuroimaging literature in psychiatric application areas has been called into question and the issues that relate to this reproducibility are extremely complex. Some of these complexities have to do with the underlying biology of the disorders that we study and others arise due to the technology we apply to the analysis of the data we collect. Ultimately, the observations we make get communicated to the rest of the community through publications in the scientific literature. Methods: We sought to perform a 're-executability survey' to evaluate the recent neuroimaging literature with an eye toward seeing if our publication practices are helping or hindering the overall quest for a more reproducible understanding of brain development and aging. The topic areas examined include availability of the data, the precision of the imaging method description and the reporting of the statistical analytic approach, and the availability of the complete results. We applied the survey to 50 publications in the autism neuroimaging literature that were published between September 16, 2017 to October 1, 2018. Results: The results of the survey indicate that for the literature examined, data that is not already part of a public repository is rarely available, software tools are usually named but versions and operating system are not, it is expected that reasonably skilled analysts could approximately perform the analyses described, and the complete results of the studies are rarely available.  Conclusions: We have identified that there is ample room for improvement in research publication practices. We hope exposing these issues in the retrospective literature can provide guidance and motivation for improving this aspect of our reporting practices in the future.

A Neglected Topic in Neuroscience: Replicability of fMRI Results With Specific Reference to ANOREXIA NERVOSA

Functional magnetic resonance imaging (fMRI) studies report impaired functional correlates of cognition and emotion in mental disorders. The validity of preexisting studies needs to be confirmed through replication studies, which there is a lack of. So far, most replication studies have been conducted on non-patients (NP) and primarily investigated cognitive and motor tasks. To fill this gap, we conducted the first fMRI replication study to investigate brain function using disease-related food stimuli in patients with anorexia nervosa (AN). Using fMRI, we investigated 31 AN patients and 27 NP for increased amygdala and reduced midcingulate activation when viewing food and non-food stimuli, as reported by the original study (11AN, 11NP; Joos et al., 2011). Similar to the previous study, we observed in the within group comparisons (food>non-food) a frontoinsular activation for both groups. Although in AN the recorded activation clustered more prominently and extended into the cingulate cortex. In the between-group comparisons, the increased amygdala and reduced midcingulate activation could not be replicated. Instead, AN showed a higher activation of the cingulate cortices, the pre-/postcentral gyrus and the inferior parietal lobe. Unlike in the initial study, no significant differences between NP>AN could be observed. The inconsistency of results and the non-replication of the study could have several reasons, such as high inter-individual variance of functional correlates of emotion processing, as well as intra-individual variances and the smaller group size of the initial study. These results underline the importance of replication for assessing the reliability and validity of results from fMRI research.

Altered local connectivity in chronic pain: A voxel-wise meta-analysis of resting-state functional magnetic resonance imaging studies

BACKGROUND

A number of studies have used regional homogeneity (ReHo) to depict local functional connectivity in chronic pain (CP). However, the findings from these studies were mixed and inconsistent.

METHODS

A computerized literature search will be performed in PubMed, Web of Science, Embase, China National Knowledge Infrastructure (CNKI), WanFang, and SinoMed databases until June 15, 2019 and updated on March 20, 2020. This protocol will follow the Preferred Reporting Items for Systematic review and Meta-Analysis Protocols (PRISMA-P). The Seed-based d Mapping with Permutation of Subject Images (SDM-PSI) software will be used for this voxel-wise meta-analysis.

RESULTS

This meta-analysis will identify the most consistent ReHo alterations in CP.

CONCLUSIONS

To our knowledge, this will be the first voxel-wise meta-analysis that integrates ReHo findings in CP. This meta-analysis will offer the quantitative evidence of ReHo alterations that characterize brain local functional connectivity of CP.

PROSPERO REGISTRATION NUMBER

CRD42019148523.

Assessing the impact of introductory programming workshops on the computational reproducibility of biomedical workflows

INTRODUCTION

As biomedical research becomes more data-intensive, computational reproducibility is a growing area of importance. Unfortunately, many biomedical researchers have not received formal computational training and often struggle to produce results that can be reproduced using the same data, code, and methods. Programming workshops can be a tool to teach new computational methods, but it is not always clear whether researchers are able to use their new skills to make their work more computationally reproducible.

METHODS

This mixed methods study consisted of in-depth interviews with 14 biomedical researchers before and after participation in an introductory programming workshop. During the interviews, participants described their research workflows and responded to a quantitative checklist measuring reproducible behaviors. The interview data was analyzed using a thematic analysis approach, and the pre and post workshop checklist scores were compared to assess the impact of the workshop on the computational reproducibility of the researchers' workflows.

RESULTS

Pre and post scores on a checklist of reproducible behaviors did not change in a statistically significant manner. The qualitative interviews revealed that several participants had made small changes to their workflows including switching to open source programming languages for their data cleaning, analysis, and visualization. Overall many of the participants indicated higher levels of programming literacy, and an interest in further training. Factors that enabled change included supportive environments and an immediate research need, while barriers included collaborators that were resistant to new tools, and a lack of time.

CONCLUSION

While none of the workshop participants completely changed their workflows, many of them did incorporate new practices, tools, or methods that helped make their work more reproducible and transparent to other researchers. This indicates that programming workshops now offered by libraries and other organizations contribute to computational reproducibility training for researchers.