A marathon, not a sprint - neuroimaging, Open Science and ethics

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.

Open Data governance at the Canadian Open Neuroscience Platform (CONP): From the Walled Garden to the Arboretum

Scientific research communities pursue dual imperatives in implementing strategies to share their data. These communities attempt to maximize the accessibility of biomedical data for downstream research use, in furtherance of open science objectives. Simultaneously, such communities safeguard the interests of research participants through data stewardship measures and the integration of suitable risk disclosures to the informed consent process. The Canadian Open Neuroscience Platform (CONP) convened an Ethics and Governance Committee composed of experts in bioethics, neuroethics, and law to develop holistic policy tools, organizational approaches, and technological supports to align the open governance of data with ethical and legal norms. The CONP has adopted novel platform governance methods that favor full data openness, legitimated through the use of robust deidentification processes and informed consent practices. The experience of the CONP is articulated as a potential template for other open science efforts to further build upon. This experience highlights informed consent guidance, deidentification practices, ethicolegal metadata, platform-level norms, and commercialization and publication policies as the principal pillars of a practicable approach to the governance of open data. The governance approach adopted by the CONP stands as a viable model for the broader neuroscience and open science communities to adopt for sharing data in full open access.

Ethical Imperatives for Working With Diverse Populations in Digital Research

Digital research methodologies are driving a revolution in health technology but do not yet fully engage diverse and historically underrepresented populations. In this paper, we explore the ethical imperative for such engagement alongside accompanying challenges related to recruitment, appreciation of risk, and confidentiality, among others. We critically analyze existing research ethics frameworks and find that their reliance on individualistic and autonomy-focused models of research ethics does not offer adequate protection in the context of the diversity imperative. To meet the requirements of justice and inclusivity in digital research, methods will benefit from a reorientation toward more participatory practices.

Open Data in the Era of the GDPR: Lessons from the Human Cell Atlas

The Human Cell Atlas (HCA) is striving to build an open community that is inclusive of all researchers adhering to its principles and as open as possible with respect to data access and use. However, open data sharing can pose certain challenges. For instance, being a global initiative, the HCA must contend with a patchwork of local and regional privacy rules. A notable example is the implementation of the European Union General Data Protection Regulation (GDPR), which caused some concern in the biomedical and genomic data-sharing community. We examine how the HCA's large, international group of researchers is investing tremendous efforts into ensuring appropriate sharing of data. We describe the HCA's objectives and governance, how it defines open data sharing, and ethico-legal challenges encountered early in its development; in particular, we describe the challenges prompted by the GDPR. Finally, we broaden the discussion to address tools and strategies that can be used to address ethical data governance.

Fostering openness in open science: An ethical discussion of risks and benefits

Transformation of science by embracing the concepts of open science presents a very attractive strategy to enhance the reliability of science. Open science policies embody the concepts of open data and open access that encompass sharing of resources, dissemination of ideas, and synergizing the collaborative forums of research. Despite the opportunities in openness, however, there are grave ethical concerns too, and they present a dual-use dilemma. Access to sensitive information is seen as a security risk, and it also possesses other concerns such as confidentiality, privacy, and affordability. There are arguments that open science can be harmful to marginalized groups. Through this study, we aim to discuss the opportunities of open science, as well as the ethical and security aspects, which require further deliberation before full-fledged acceptance in the science community.

Open Science in Africa: What policymakers should consider

As Open Science (OS) is being promoted as the best avenue to share and drive scientific discoveries at much lower costs and in transparent and credible ways, it is imperative that African governments and institutions take advantage of the momentum and build research infrastructures that are responsive to this movement. This paper aims to provide useful insight into the importance and implementation of OS policy frameworks. The paper uses a systematic review approach to review existing literature and analyse global OS policy development documents. The approach includes a review of existing OS policy frameworks that can guide similar work by African governments and institutions. This critical review also makes recommendations on key issues that Africa should consider in the process of OS policy development. These approaches can be widely used as further foundations for future developments in OS practices on the continent.

How Machine Learning is Powering Neuroimaging to Improve Brain Health

This report presents an overview of how machine learning is rapidly advancing clinical translational imaging in ways that will aid in the early detection, prediction, and treatment of diseases that threaten brain health. Towards this goal, we aresharing the information presented at a symposium, "Neuroimaging Indicators of Brain Structure and Function - Closing the Gap Between Research and Clinical Application", co-hosted by the McCance Center for Brain Health at Mass General Hospital and the MIT HST Neuroimaging Training Program on February 12, 2021. The symposium focused on the potential for machine learning approaches, applied to increasingly large-scale neuroimaging datasets, to transform healthcare delivery and change the trajectory of brain health by addressing brain care earlier in the lifespan. While not exhaustive, this overview uniquely addresses many of the technical challenges from image formation, to analysis and visualization, to synthesis and incorporation into the clinical workflow. Some of the ethical challenges inherent to this work are also explored, as are some of the regulatory requirements for implementation. We seek to educate, motivate, and inspire graduate students, postdoctoral fellows, and early career investigators to contribute to a future where neuroimaging meaningfully contributes to the maintenance of brain health.