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  The PLORAS database: A data repository for predicting language outcome and recovery after stroke

Seghier, M. L., Patel, E., Prejawa, S., Ramsden, S., Selmer, A., Lim, L., et al. (2016). The PLORAS database: A data repository for predicting language outcome and recovery after stroke. NeuroImage, 124(Part B), 1208-1212. doi:10.1016/j.neuroimage.2015.03.083.

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 Creators:
Seghier, Mohamed L.1, Author
Patel, Elnas1, Author
Prejawa, Suse1, Author              
Ramsden, Sue1, Author
Selmer, Andre1, Author
Lim, Louise1, Author
Browne, Rachel1, Author
Rae, Johanna1, Author
Haigh, Zula1, Author
Ezekiel, Deborah1, Author
Hope, Thomas M. H.1, Author
Leff, Alex P.1, Author
Price, Cathy J.1, Author
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1Wellcome Trust Centre for Neuroimaging, University College London, United Kingdom, ou_persistent22              

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 Abstract: The PLORAS Database is a relational repository of anatomical and functional imaging data that has primarily been acquired from stroke survivors, along with standardized scores on a wide range of sensory, motor and cognitive abilities, demographic details and medical history. As of January 2015, we have data from 750 patients with an expected accrual rate of 200 patients per year. Expansion will accelerate as we extend our collaborations. The main aim of the database is to Predict Language Outcome and Recovery After Stroke (PLORAS) on the basis of a single structural (anatomical) brain scan that indexes the stereotactic location and extent of brain damage. Predictions are made for individual patients by indicating how other patients with the most similar brain damage, cognitive abilities and demographic details recovered their language skills over time. Predictions are validated by longitudinal follow-ups of patients who initially presented with speech and language difficulties. The PLORAS Database can also be used to predict recovery of other cognitive abilities on the basis of anatomical brain scans. The functional imaging data can be used to understand the neural mechanisms that support recovery from brain damage; and all the data can be used to understand the main sources of inter-subject variability in structure–function mappings in the human brain. Data will be made available for sharing, subject to: funding, ethical approval and patient consent.

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Language(s): eng - English
 Dates: 2015-03-292015-03-292015-04-142016-01-01
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.neuroimage.2015.03.083
PMID: 25882753
PMC: PMC4658335
Other: Epub 2015
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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 124 (Part B) Sequence Number: - Start / End Page: 1208 - 1212 Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166