The PLORAS Database: A data repository for Predicting Language Outcome and Recovery After Stroke☆

The PLORAS Database: A data repository for Predicting Language Outcome and Recovery After Stroke☆

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 h...

Full description

Bibliographic Details
Main Authors: Seghier, Mohamed L., Patel, Elnas, Prejawa, Susan, Ramsden, Sue, Selmer, Andre, Lim, Louise, Browne, Rachel, Rae, Johanna, Haigh, Zula, Ezekiel, Deborah, Hope, Thomas M.H., Leff, Alex P., Price, Cathy J.
Format: Online
Language:English
Published: Academic Press 2016
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4658335/
id pubmed-4658335
recordtype oai_dc
spelling pubmed-46583352016-01-11 The PLORAS Database: A data repository for Predicting Language Outcome and Recovery After Stroke☆ Seghier, Mohamed L. Patel, Elnas Prejawa, Susan Ramsden, Sue Selmer, Andre Lim, Louise Browne, Rachel Rae, Johanna Haigh, Zula Ezekiel, Deborah Hope, Thomas M.H. Leff, Alex P. Price, Cathy J. Article 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. Academic Press 2016-01-01 /pmc/articles/PMC4658335/ /pubmed/25882753 http://dx.doi.org/10.1016/j.neuroimage.2015.03.083 Text en Crown Copyright © 2015 Published by Elsevier Inc. All rights reserved. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
repository_type Open Access Journal
institution_category Foreign Institution
institution US National Center for Biotechnology Information
building NCBI PubMed
collection Online Access
language English
format Online
author Seghier, Mohamed L.
Patel, Elnas
Prejawa, Susan
Ramsden, Sue
Selmer, Andre
Lim, Louise
Browne, Rachel
Rae, Johanna
Haigh, Zula
Ezekiel, Deborah
Hope, Thomas M.H.
Leff, Alex P.
Price, Cathy J.
spellingShingle Seghier, Mohamed L.
Patel, Elnas
Prejawa, Susan
Ramsden, Sue
Selmer, Andre
Lim, Louise
Browne, Rachel
Rae, Johanna
Haigh, Zula
Ezekiel, Deborah
Hope, Thomas M.H.
Leff, Alex P.
Price, Cathy J.
The PLORAS Database: A data repository for Predicting Language Outcome and Recovery After Stroke☆
author_facet Seghier, Mohamed L.
Patel, Elnas
Prejawa, Susan
Ramsden, Sue
Selmer, Andre
Lim, Louise
Browne, Rachel
Rae, Johanna
Haigh, Zula
Ezekiel, Deborah
Hope, Thomas M.H.
Leff, Alex P.
Price, Cathy J.
author_sort Seghier, Mohamed L.
title The PLORAS Database: A data repository for Predicting Language Outcome and Recovery After Stroke☆
title_short The PLORAS Database: A data repository for Predicting Language Outcome and Recovery After Stroke☆
title_full The PLORAS Database: A data repository for Predicting Language Outcome and Recovery After Stroke☆
title_fullStr The PLORAS Database: A data repository for Predicting Language Outcome and Recovery After Stroke☆
title_full_unstemmed The PLORAS Database: A data repository for Predicting Language Outcome and Recovery After Stroke☆
title_sort ploras database: a data repository for predicting language outcome and recovery after stroke☆
description 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.
publisher Academic Press
publishDate 2016
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4658335/
_version_ 1613505542661079040

Similar Items