ArticleFrontiers in neuroinformatics2010
Mining the mind research network: a novel framework for exploring large scale, heterogeneous translational neuroscience research data sources.
Article in Frontiers in neuroinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
38 citing papers in PubMed.
- Article
- A data integration method for new advances in development cognitive neuroscience.Developmental cognitive neuroscience · 2024Article
- Associations Between Age and Resting State Connectivity Are Partially Dependent Upon Cardiovascular Fitness.Frontiers in aging neuroscience · 2022Article
- The LORIS MyeliNeuroGene rare disease database for natural history studies and clinical trial readiness.Orphanet journal of rare diseases · 2021Article
- Dementia in Latin America: Paving the way toward a regional action plan.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2021Article
- Meta-Modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia.IEEE transactions on bio-medical engineering · 2020Article
- ANSH: Multimodal Neuroimaging Database Including MR Spectroscopic Data From Each Continent to Advance Alzheimer's Disease Research.Frontiers in neuroinformatics · 2020Article
- Multimodal Fusion With Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia.IEEE transactions on medical imaging · 2018Article
- Multimodal Neuroimaging in Schizophrenia: Description and Dissemination.Neuroinformatics · 2017Article
- Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls.NeuroImage · 2017Review
- Schizophrenia Shows Disrupted Links between Brain Volume and Dynamic Functional Connectivity.Frontiers in neuroscience · 2017Article
- Evolution of universal review and disclosure of MRI reports to research participants.Brain and behavior · 2016Review
- Interaction among subsystems within default mode network diminished in schizophrenia patients: A dynamic connectivity approach.Schizophrenia research · 2016Article
- SchizConnect: Mediating neuroimaging databases on schizophrenia and related disorders for large-scale integration.NeuroImage · 2016Article
- A Tool for Interactive Data Visualization: Application to Over 10,000 Brain Imaging and Phantom MRI Data Sets.Frontiers in neuroinformatics · 2016Article
- Functional MRI Evaluation of Multiple Neural Networks Underlying Auditory Verbal Hallucinations in Schizophrenia Spectrum Disorders.Frontiers in psychiatry · 2016Article
- Multimodal Classification of Schizophrenia Patients with MEG and fMRI Data Using Static and Dynamic Connectivity Measures.Frontiers in neuroscience · 2016Article
- Spatial Variance in Resting fMRI Networks of Schizophrenia Patients: An Independent Vector Analysis.Schizophrenia bulletin · 2016Article
- Application of ICA to realistically simulated (1)H-MRS data.Brain and behavior · 2015Article
- Stakeholder Opinions And Ethical Perspectives Support Complete Disclosure Of Incidental Findings In MRI Research.Ethics & behavior · 2015Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
A neuroinformatics (NI) system is critical to brain imaging research in order to shorten the time between study conception and results. Such a NI system is required to scale well when large numbers of subjects are studied. Further, when multiple sites participate in research projects organizational issues become increasingly difficult. Optimized NI applications mitigate these problems. Additionally, NI software enables coordination across multiple studies, leveraging advantages potentially leading to exponential research discoveries. The web-based, Mind Research Network (MRN), database system has been designed and improved through our experience with 200 research studies and 250 researchers from seven different institutions. The MRN tools permit the collection, management, reporting and efficient use of large scale, heterogeneous data sources, e.g., multiple institutions, multiple principal investigators, multiple research programs and studies, and multimodal acquisitions. We have collected and analyzed data sets on thousands of research participants and have set up a framework to automatically analyze the data, thereby making efficient, practical data mining of this vast resource possible. This paper presents a comprehensive framework for capturing and analyzing heterogeneous neuroscience research data sources that has been fully optimized for end-users to perform novel data mining.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.