Big Data Initiatives in Psychiatry: Global Neuroimaging Studies

Thompson, Paul M.; Ching, Christopher R. K.; Dennis, Emily; Salminen, Lauren E.; Turner, Jessica A.; Erp, Theo G.M. van; Jahanshad, Neda

doi:10.1007/978-3-030-35206-6_21

Cited by 8 publications

(7 citation statements)

References 51 publications

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“…Trauma is one form of severe stress, but we do not know how more minor stress may affect tapetum organization. Smaller hippocampal volume has been reported across disorders, suggesting that it may be a nonspecific marker of disease [78].…”

Section: Discussionmentioning

confidence: 99%

Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium

et al. 2019

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Section: Discussionmentioning

confidence: 99%

Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium

et al. 2019

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“…Here we extend previous studies by using an individual mega-analytic approach and a newer more anatomically robust hippocampal subfield FreeSurfer segmentation algorithm to determine whether alterations in specific hippocampal subfields can explain the previously reported lower overall hippocampal volume in BD. By this, we also address the need for replication of neuroimaging studies in clinical samples (Open Science Collaboration, 2015;Thompson et al, 2020). We include secondary analyses of the effects of diagnostic subtype, medication use, and clinical characteristics on hippocampal subfield volumes.…”

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confidence: 99%

In vivo hippocampal subfield volumes in bipolar disorder—A mega‐analysis from The Enhancing Neuro Imaging Genetics through Meta‐Analysis Bipolar Disorder Working Group

Haukvik¹,

Gurholt²,

Nerland³

et al. 2020

Human Brain Mapping

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“…The reproducibility crisis has led to an increased demand for standardized workflows to conduct both the preprocessing and postprocessing stages of fMRI analysis. The recent introduction and widespread adoption of standardized pipelines for fMRI data preprocessing have provided the research community with much‐needed high‐quality tools that have improved reproducibility (Thompson et al, 2020). The four ingredients that are essential to data analysis and reproducible results are: (a) data and metadata availability, (b) code usage and transparency, (c) software installability, and (d) re‐creation of the runtime environment.…”

Section: Introductionmentioning

confidence: 99%

ENIGMA HALFpipe: Interactive, reproducible, and efficient analysis for resting‐state and task‐based fMRI data

Waller

Erk

Pozzi

et al. 2022

Human Brain Mapping

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The reproducibility crisis in neuroimaging has led to an increased demand for standardized data processing workflows. Within the ENIGMA consortium, we developed HALFpipe (Harmonized Analysis of Functional MRI pipeline), an open‐source, containerized, user‐friendly tool that facilitates reproducible analysis of task‐based and resting‐state fMRI data through uniform application of preprocessing, quality assessment, single‐subject feature extraction, and group‐level statistics. It provides state‐of‐the‐art preprocessing using fMRIPrep without the requirement for input data in Brain Imaging Data Structure (BIDS) format. HALFpipe extends the functionality of fMRIPrep with additional preprocessing steps, which include spatial smoothing, grand mean scaling, temporal filtering, and confound regression. HALFpipe generates an interactive quality assessment (QA) webpage to rate the quality of key preprocessing outputs and raw data in general. HALFpipe features myriad post‐processing functions at the individual subject level, including calculation of task‐based activation, seed‐based connectivity, network‐template (or dual) regression, atlas‐based functional connectivity matrices, regional homogeneity (ReHo), and fractional amplitude of low‐frequency fluctuations (fALFF), offering support to evaluate a combinatorial number of features or preprocessing settings in one run. Finally, flexible factorial models can be defined for mixed‐effects regression analysis at the group level, including multiple comparison correction. Here, we introduce the theoretical framework in which HALFpipe was developed, and present an overview of the main functions of the pipeline. HALFpipe offers the scientific community a major advance toward addressing the reproducibility crisis in neuroimaging, providing a workflow that encompasses preprocessing, post‐processing, and QA of fMRI data, while broadening core principles of data analysis for producing reproducible results. Instructions and code can be found at https://github.com/HALFpipe/HALFpipe.

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Big Data Initiatives in Psychiatry: Global Neuroimaging Studies

Cited by 8 publications

References 51 publications

Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium

Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium

In vivo hippocampal subfield volumes in bipolar disorder—A mega‐analysis from The Enhancing Neuro Imaging Genetics through Meta‐Analysis Bipolar Disorder Working Group

ENIGMA HALFpipe: Interactive, reproducible, and efficient analysis for resting‐state and task‐based fMRI data

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