An open-access accelerated adult equivalent of the ABCD Study neuroimaging dataset (a-ABCD) – ScienceDirect

Abstract:  As public access to longitudinal developmental datasets like the Adolescent Brain Cognitive Development StudySM (ABCD Study®) increases, so too does the need for resources to benchmark time-dependent effects. Scan-to-scan changes observed with repeated imaging may reflect development but may also reflect practice effects, day-to-day variability in psychological states, and/or measurement noise. Resources that allow disentangling these time-dependent effects will be useful in quantifying actual developmental change. We present an accelerated adult equivalent of the ABCD Study dataset (a-ABCD) using an identical imaging protocol to acquire magnetic resonance imaging (MRI) structural, diffusion-weighted, resting-state and task-based data from eight adults scanned five times over five weeks. We report on the task-based imaging data (n?=?7). In-scanner stop-signal (SST), monetary incentive delay (MID), and emotional n-back (EN-back) task behavioral performance did not change across sessions. Post-scan recognition memory for emotional n-back stimuli, however, did improve as participants became more familiar with the stimuli. Functional MRI analyses revealed that patterns of task-based activation reflecting inhibitory control in the SST, reward success in the MID task, and working memory in the EN-back task were more similar within individuals across repeated scan sessions than between individuals. Within-subject, activity was more consistent across sessions during the EN-back task than in the SST and MID task, demonstrating differences in fMRI data reliability as a function of task. The a-ABCD dataset provides a unique testbed for characterizing the reliability of brain function, structure, and behavior across imaging modalities in adulthood and benchmarking neurodevelopmental change observed in the open-access ABCD Study.

 

Empowering Data Sharing and Analytics through the Open Data Commons for Traumatic Brain Injury Research | Neurotrauma Reports

Abstract:  Traumatic brain injury (TBI) is a major public health problem. Despite considerable research deciphering injury pathophysiology, precision therapies remain elusive. Here, we present large-scale data sharing and machine intelligence approaches to leverage TBI complexity. The Open Data Commons for TBI (ODC-TBI) is a community-centered repository emphasizing Findable, Accessible, Interoperable, and Reusable data sharing and publication with persistent identifiers. Importantly, the ODC-TBI implements data sharing of individual subject data, enabling pooling for high-sample-size, feature-rich data sets for machine learning analytics. We demonstrate pooled ODC-TBI data analyses, starting with descriptive analytics of subject-level data from 11 previously published articles (N?=?1250 subjects) representing six distinct pre-clinical TBI models. Second, we perform unsupervised machine learning on multi-cohort data to identify persistent inflammatory patterns across different studies, improving experimental sensitivity for pro- versus anti-inflammation effects. As funders and journals increasingly mandate open data practices, ODC-TBI will create new scientific opportunities for researchers and facilitate multi-data-set, multi-dimensional analytics toward effective translation.

 

Neurosurgical publication – Should we publish at any cost? An in-depth analysis of costs incurred in publication. – ScienceDirect

Abstract:  Objectives

With the recent paradigm shift in neurosurgical publications, open access (OA) publishing is burgeoning along with traditional publishing methods. We aimed to explore costs of publication across 53 journals.

Methods

We identified 53 journals publishing neurosurgical work. Journal type, submission and open access charges, colour print fees, impact indicators, publisher, and subscription prices were obtained from journal and publisher websites. Costs were unified in American Dollars. Mean prices per journal were used to equilibrate membership and subscription discounts. Correlations were performed using Spearman Rho (?), p<0.05.

Results

Of the 53 journals, 12 are OA-only, 40 are hybrid, and 1 is traditional. 22 and 43 journals provide their submission costs by end of phase 1 and 2, respectively (prices always for phase 2; 26 free of charge, 4 under $500, and 1 under $1000). Median OA charge is $3286 (49 journals; range $0-$7827). 36 of the 53 journals did not list print fees for colour figures (29 in phase 2). Median fee estimate per figure is $422 (range $25-$1060). Median personal subscription for 1 year is $344 (range $60-$1158; 48 journals). Median institutional subscription for 1 year is $2082 (Range $38-$5510; 34 journals). There is mild positive correlation between journal impact factor and OA fees (?=0.287, p=0.046).

Conclusions

The lack of easily accessible information about Neurosurgical publications, such as submission costs, or OA charges create unnecessary hurdle and should be remedied. Publishing in Neurosurgery should be a pleasant learning experience for the cost anxiety should not be a limiting factor.

The Digital Brain Bank, an open access platform for post-mortem datasets | eLife

Abstract:  Post-mortem MRI provides the opportunity to acquire high-resolution datasets to investigate neuroanatomy, and validate the origins of image contrast through microscopy comparisons. We introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), a data release platform providing open access to curated, multimodal post-mortem neuroimaging datasets. Datasets span three themes – Digital Neuroanatomist: datasets for detailed neuroanatomical investigations; Digital Brain Zoo: datasets for comparative neuroanatomy; Digital Pathologist: datasets for neuropathology investigations. The first Digital Brain Bank release includes twenty one distinctive whole-brain diffusion MRI datasets for structural connectivity investigations, alongside microscopy and complementary MRI modalities. This includes one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired, whole-brain diffusion MRI in fourteen non-human primate species, and one of the largest post-mortem whole-brain cohort imaging studies in neurodegeneration. The Digital Brain Bank is the culmination of our lab’s investment into post-mortem MRI methodology and MRI-microscopy analysis techniques. This manuscript provides a detailed overview of our work with post-mortem imaging to date, including the development of diffusion MRI methods to image large post-mortem samples, including whole, human brains. Taken together, the Digital Brain Bank provides cross-scale, cross-species datasets facilitating the incorporation of post-mortem data into neuroimaging studies.

 

The Digital Brain Bank, an open access platform for post-mortem datasets | eLife

Abstract:  Post-mortem MRI provides the opportunity to acquire high-resolution datasets to investigate neuroanatomy, and validate the origins of image contrast through microscopy comparisons. We introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), a data release platform providing open access to curated, multimodal post-mortem neuroimaging datasets. Datasets span three themes – Digital Neuroanatomist: datasets for detailed neuroanatomical investigations; Digital Brain Zoo: datasets for comparative neuroanatomy; Digital Pathologist: datasets for neuropathology investigations. The first Digital Brain Bank release includes twenty one distinctive whole-brain diffusion MRI datasets for structural connectivity investigations, alongside microscopy and complementary MRI modalities. This includes one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired, whole-brain diffusion MRI in fourteen non-human primate species, and one of the largest post-mortem whole-brain cohort imaging studies in neurodegeneration. The Digital Brain Bank is the culmination of our lab’s investment into post-mortem MRI methodology and MRI-microscopy analysis techniques. This manuscript provides a detailed overview of our work with post-mortem imaging to date, including the development of diffusion MRI methods to image large post-mortem samples, including whole, human brains. Taken together, the Digital Brain Bank provides cross-scale, cross-species datasets facilitating the incorporation of post-mortem data into neuroimaging studies.

 

An Open Access Resource for Functional Brain Connectivity from Fully Awake Marmosets: Open Access Marmoset Functional Connectivity Resource – ScienceDirect

Abstract:  The common marmoset (Callithrix jacchus) is quickly gaining traction as a premier neuroscientific model. However, considerable progress is still needed in understanding the functional and structural organization of the marmoset brain to rival that documented in long-standing preclinical model species, like mice, rats, and Old World primates. To accelerate such progress, we present the Marmoset Functional Connectivity Resource (marmosetbrainconnectome.org), consisting of over 70 hours of resting-state fMRI (RS-fMRI) data acquired at 500 µm isotropic resolution from 31 fully awake marmosets in a common stereotactic space. Three-dimensional functional connectivity (FC) maps for every cortical and subcortical gray matter voxel are stored online. Users can instantaneously view, manipulate, and download any whole-brain functional connectivity (FC) topology (at the subject- or group-level) along with the raw datasets and preprocessing code. Importantly, researchers can use this resource to test hypotheses about FC directly – with no additional analyses required – yielding whole-brain correlations for any gray matter voxel on demand. We demonstrate the resource’s utility for presurgical planning and comparison with tracer-based structural connectivity as proof of concept. Complementing existing structural connectivity resources for the marmoset brain, the Marmoset Functional Connectivity Resource affords users the distinct advantage of exploring the connectivity of any voxel in the marmoset brain, not limited to injection sites nor constrained by regional atlases. With the entire raw database (RS-fMRI and structural images) and preprocessing code openly available for download and use, we expect this resource to be broadly valuable to test novel hypotheses about the functional organization of the marmoset brain.

 

Ethics Toolkit – the Canadian Open Neuroscience Platform

“In response to a growing need in the neuroscience community for concrete guidance concerning ethically sound and pragmatically feasible open data-sharing, the CONP has created an ‘Ethics Toolkit’, currently comprised of:

 

1. The CONP Consent Toolkit

 

2. The CONP Privacy and De-identification Toolkit

Together, these documents are meant to help researchers identify key elements in the design of their projects that are often required for the open sharing of neuroscience data, such as model consent language and approaches to de-identification….”

Brainiacs Journal of Brain Imaging And Computing Sciences

“Brain Health Alliance, a not-for-profit organization, manages and publishes the Brainiacs Journal of Brain Imaging And Computing Sciences, also called simply Brainiacs or the Brainiacs Journal as an online journal (LCCN 2021201717, ISSN 2766-6883) of scholarly research articles and electronic digital documents available via open access. All documents will be published fully open access and freely available without any page charges or publishing fees paid by authors and without any access fees paid by readers.”

The OpenNeuro resource for sharing of neuroscience data | eLife

Abstract:  The sharing of research data is essential to ensure reproducibility and maximize the impact of public investments in scientific research. Here we describe OpenNeuro, a BRAIN Initiative data archive that provides the ability to openly share data from a broad range of brain imaging data types following the FAIR principles for data sharing. We highlight the importance of the Brain Imaging Data Structure (BIDS) standard for enabling effective curation, sharing, and reuse of data. The archive presently shares more than 600 datasets including data from more than 20,000 participants, comprising multiple species and measurement modalities and a broad range of phenotypes. The impact of the shared data is evident in a growing number of published reuses, currently totalling more than 150 publications. We conclude by describing plans for future development and integration with other ongoing open science efforts.

 

Highlights from the Era of Open Source Web-Based Tools | Journal of Neuroscience

Abstract:  High digital connectivity and a focus on reproducibility are contributing to an open science revolution in neuroscience. Repositories and platforms have emerged across the whole spectrum of subdisciplines, paving the way for a paradigm shift in the way we share, analyze, and reuse vast amounts of data collected across many laboratories. Here, we describe how open access web-based tools are changing the landscape and culture of neuroscience, highlighting six free resources that span subdisciplines from behavior to whole-brain mapping, circuits, neurons, and gene variants.

 

Open science delivers a wealth of AD/ADRD research data to a portal near you | National Institute on Aging

“The COVID-19 pandemic mobilized the global research and development community to embrace open science practices to accelerate the development of effective treatments. As described in this recent commentary by law professor Richard Gold, the COVID-19 crisis is an opportunity to move toward an open science drug discovery model to combat existing and future pandemics.

During the NIH Alzheimer’s Disease Research Summits in 2012, 2015, and 2018, we heard similar calls for open science from a large multi-stakeholder community in Alzheimer’s disease and related dementias (AD/ADRD) research. The collective input was the impetus for NIA to develop an array of new translational infrastructure programs, including AMP-AD and affiliated target discovery consortia (M2OVE-AD, Resilience-AD, and Psych-AD), and the MODEL-AD and TREAT-AD centers — all of which operate under open science principles — to rapidly deliver data, knowledge, and research tools necessary to overcome key barriers to developing effective therapies….”

How data sharing is accelerating railway safety research

“Andre?’s dataset was shortlisted for the Mendeley Data FAIRest Datasets Award, which recognizes researchers who make their data available for the research community in a way that exemplifies the FAIR Data Principles – Findable, Accessible, Interoperable, Reusable. The dataset was applauded for a number of reasons, not least the provision of clear steps to reproduce the data. What’s more, the data was clearly catalogued and stored in sub folders, with additional links to Blender and GitHub, making the dataset easily available and reproducible for all….”

The Open Future of Neuroscience Research and Innovation – Western University

“Speaker: Dylan Roskams-Edris, Open Science Alliance Officer, Tanenbaum Open Science Institute, The Neuro 

In his role as Open Science Alliance Officer for TOSI and The Neuro, Dylan interfaces with the national and global open science communities to promote the uptake of open science tools and practices in Canadian neuroscience research. His background in Neuroscience, Health Ethics, and law gives him the breadth of expertise neeeded to recognize the critical challenges that face open neuroscience and promote the solutions needed to overcome them. Drawing from both global examples and the experience of The Neuro as the worlds first open science biomedical research institute, this talk he will discuss the importance of open science for the future of both basic neuroscience research and the translation from basic discoveries to healthcare innovations. …”