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  1. Article ; Online: From the Wet Lab to the Web Lab

    Anisha Keshavan / Jean-Baptiste Poline

    Frontiers in Neuroinformatics, Vol

    A Paradigm Shift in Brain Imaging Research

    2019  Volume 13

    Abstract: Web technology has transformed our lives, and has led to a paradigm shift in the computational sciences. As the neuroimaging informatics research community amasses large datasets to answer complex neuroscience questions, we find that the web is the best ... ...

    Abstract Web technology has transformed our lives, and has led to a paradigm shift in the computational sciences. As the neuroimaging informatics research community amasses large datasets to answer complex neuroscience questions, we find that the web is the best medium to facilitate novel insights by way of improved collaboration and communication. Here, we review the landscape of web technologies used in neuroimaging research, and discuss future applications, areas for improvement, and the limitations of using web technology in research. Fully incorporating web technology in our research lifecycle requires not only technical skill, but a widespread culture change; a shift from the small, focused “wet lab” to a multidisciplinary and largely collaborative “web lab.”
    Keywords neuroimaging ; open science ; infrastructure ; web browser ; collaboration ; communication ; Neurosciences. Biological psychiatry. Neuropsychiatry ; RC321-571
    Language English
    Publishing date 2019-03-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Nature abhors a paywall

    Elizabeth DuPre / Michael Hanke / Jean-Baptiste Poline

    NeuroImage, Vol 216, Iss , Pp 116330- (2020)

    How open science can realize the potential of naturalistic stimuli

    2020  

    Abstract: Naturalistic stimuli show significant potential to inform behavioral, cognitive, and clinical neuroscience. To date, this impact is still limited by the relative inaccessibility of both generated neuroimaging data as well as the supporting naturalistic ... ...

    Abstract Naturalistic stimuli show significant potential to inform behavioral, cognitive, and clinical neuroscience. To date, this impact is still limited by the relative inaccessibility of both generated neuroimaging data as well as the supporting naturalistic stimuli. In this perspective, we highlight currently available naturalistic datasets and technical solutions such as DataLad that continue to advance our ability to share this data. We also review scientific and sociological challenges in selecting naturalistic stimuli for reproducible research. Overall, we encourage researchers to share their naturalistic datasets to the full extent possible under local copyright law.
    Keywords Open science ; Data sharing ; Naturalistic stimuli ; Neurosciences. Biological psychiatry. Neuropsychiatry ; RC321-571
    Language English
    Publishing date 2020-08-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: On the open-source landscape of PLOS Computational Biology.

    Mathieu Boudreau / Jean-Baptiste Poline / Pierre Bellec / Nikola Stikov

    PLoS Computational Biology, Vol 17, Iss 2, p e

    2021  Volume 1008725

    Keywords Biology (General) ; QH301-705.5
    Language English
    Publishing date 2021-02-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Beyond advertising

    Elizabeth DuPre / Chris Holdgraf / Agah Karakuzu / Loïc Tetrel / Pierre Bellec / Nikola Stikov / Jean-Baptiste Poline

    PLoS Computational Biology, Vol 18, Iss 1, p e

    New infrastructures for publishing integrated research objects.

    2022  Volume 1009651

    Keywords Biology (General) ; QH301-705.5
    Language English
    Publishing date 2022-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Which fMRI clustering gives good brain parcellations?

    BertrandThirion / Jean-BaptistePoline

    Frontiers in Neuroscience, Vol

    2014  Volume 8

    Abstract: Analysis and interpretation of neuroimaging data often require one to divide the brain into a number of regions, or parcels, with homogeneous characteristics, be these regions defined in the brain volume or on on the cortical surface. While predefined ... ...

    Abstract Analysis and interpretation of neuroimaging data often require one to divide the brain into a number of regions, or parcels, with homogeneous characteristics, be these regions defined in the brain volume or on on the cortical surface. While predefined brain atlases do not adapt to the signal in the individual subjects images, parcellation approaches use brain activity (e.g. found in some functional contrasts of interest) and clustering techniques to define regions with some degree of signal homogeneity. In this work, we address the question of which clustering technique is appropriate and how to optimize the corresponding model. We use two principled criteria: goodness of fit (accuracy), and reproducibility of the parcellation across bootstrap samples. We study these criteria on both simulated and two task-based functional Magnetic Resonance Imaging datasets for the Ward, spectral and K-means clustering algorithms. We show that in general Ward’s clustering performs better than alternative methods with regards to reproducibility and accuracy and that the two criteria diverge regarding the preferred models (reproducibility leading to more conservative solutions), thus deferring the practical decision to a higher level alternative, namely the choice of a trade-off between accuracy and stability.
    Keywords Functional Neuroimaging ; Brain Atlas ; clustering ; Model selection ; Cross-validation ; group studies ; Neurosciences. Biological psychiatry. Neuropsychiatry ; RC321-571 ; Internal medicine ; RC31-1245 ; Medicine ; R
    Subject code 006
    Language English
    Publishing date 2014-07-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Standardizing workflows in imaging transcriptomics with the abagen toolbox

    Ross D Markello / Aurina Arnatkeviciute / Jean-Baptiste Poline / Ben D Fulcher / Alex Fornito / Bratislav Misic

    eLife, Vol

    2021  Volume 10

    Abstract: Gene expression fundamentally shapes the structural and functional architecture of the human brain. Open-access transcriptomic datasets like the Allen Human Brain Atlas provide an unprecedented ability to examine these mechanisms in vivo; however, a lack ...

    Abstract Gene expression fundamentally shapes the structural and functional architecture of the human brain. Open-access transcriptomic datasets like the Allen Human Brain Atlas provide an unprecedented ability to examine these mechanisms in vivo; however, a lack of standardization across research groups has given rise to myriad processing pipelines for using these data. Here, we develop the abagen toolbox, an open-access software package for working with transcriptomic data, and use it to examine how methodological variability influences the outcomes of research using the Allen Human Brain Atlas. Applying three prototypical analyses to the outputs of 750,000 unique processing pipelines, we find that choice of pipeline has a large impact on research findings, with parameters commonly varied in the literature influencing correlations between derived gene expression and other imaging phenotypes by as much as ρ ≥ 1.0. Our results further reveal an ordering of parameter importance, with processing steps that influence gene normalization yielding the greatest impact on downstream statistical inferences and conclusions. The presented work and the development of the abagen toolbox lay the foundation for more standardized and systematic research in imaging transcriptomics, and will help to advance future understanding of the influence of gene expression in the human brain.
    Keywords transcriptomics ; neuroimaging ; MRI ; processing variability ; software ; Medicine ; R ; Science ; Q ; Biology (General) ; QH301-705.5
    Subject code 020
    Language English
    Publishing date 2021-11-01T00:00:00Z
    Publisher eLife Sciences Publications Ltd
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Frontiers in Brain Imaging Methods Grand Challenge

    Jean-BaptistePoline / RussellAPoldrack

    Frontiers in Neuroscience, Vol

    2012  Volume 6

    Keywords Education ; brain imaging ; models ; Open access ; statistics ; data analysis ; methods ; data processing ; data acquisition ; reproducibility ; Open Data ; Open Code ; Neurosciences. Biological psychiatry. Neuropsychiatry ; RC321-571 ; Internal medicine ; RC31-1245 ; Medicine ; R
    Language English
    Publishing date 2012-07-01T00:00:00Z
    Publisher Frontiers
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Recommendations for repositories and scientific gateways from a neuroscience perspective

    Malin Sandström / Mathew Abrams / Jan G. Bjaalie / Mona Hicks / David N. Kennedy / Arvind Kumar / Jean-Baptiste Poline / Prasun K. Roy / Paul Tiesinga / Thomas Wachtler / Wojtek J. Goscinski

    Scientific Data, Vol 9, Iss 1, Pp 1-

    2022  Volume 5

    Abstract: Digital services such as repositories and science gateways have become key resources for the neuroscience community, but users often have a hard time orienting themselves in the service landscape to find the best fit for their particular needs. INCF has ... ...

    Abstract Digital services such as repositories and science gateways have become key resources for the neuroscience community, but users often have a hard time orienting themselves in the service landscape to find the best fit for their particular needs. INCF has developed a set of recommendations and associated criteria for choosing or setting up and running a repository or scientific gateway, intended for the neuroscience community, with a FAIR neuroscience perspective.
    Keywords Science ; Q
    Language English
    Publishing date 2022-05-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: Tools Matter

    Erin Dickie / Steven Hodge / R. Craddock / Jean-Baptiste Poline / David Kennedy

    Research Ideas and Outcomes, Vol 3, Iss , Pp 1-

    Comparison of Two Surface Analysis Tools Applied to the ABIDE Dataset

    2017  Volume 3

    Abstract: We examine the similarity of outputs from Freesurfer version 5.1, Freesurfer version 5.3 and ANTS for the ABIDEI dataset. ...

    Abstract We examine the similarity of outputs from Freesurfer version 5.1, Freesurfer version 5.3 and ANTS for the ABIDEI dataset.
    Keywords Brain Anatomy ; Scientific reproducibility ; MR ; Science ; Q
    Language English
    Publishing date 2017-05-01T00:00:00Z
    Publisher Pensoft Publishers
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article ; Online: Population heterogeneity in clinical cohorts affects the predictive accuracy of brain imaging.

    Oualid Benkarim / Casey Paquola / Bo-Yong Park / Valeria Kebets / Seok-Jun Hong / Reinder Vos de Wael / Shaoshi Zhang / B T Thomas Yeo / Michael Eickenberg / Tian Ge / Jean-Baptiste Poline / Boris C Bernhardt / Danilo Bzdok

    PLoS Biology, Vol 20, Iss 4, p e

    2022  Volume 3001627

    Abstract: Brain imaging research enjoys increasing adoption of supervised machine learning for single-participant disease classification. Yet, the success of these algorithms likely depends on population diversity, including demographic differences and other ... ...

    Abstract Brain imaging research enjoys increasing adoption of supervised machine learning for single-participant disease classification. Yet, the success of these algorithms likely depends on population diversity, including demographic differences and other factors that may be outside of primary scientific interest. Here, we capitalize on propensity scores as a composite confound index to quantify diversity due to major sources of population variation. We delineate the impact of population heterogeneity on the predictive accuracy and pattern stability in 2 separate clinical cohorts: the Autism Brain Imaging Data Exchange (ABIDE, n = 297) and the Healthy Brain Network (HBN, n = 551). Across various analysis scenarios, our results uncover the extent to which cross-validated prediction performances are interlocked with diversity. The instability of extracted brain patterns attributable to diversity is located preferentially in regions part of the default mode network. Collectively, our findings highlight the limitations of prevailing deconfounding practices in mitigating the full consequences of population diversity.
    Keywords Biology (General) ; QH301-705.5
    Subject code 610
    Language English
    Publishing date 2022-04-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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