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Reference: Parker Jones, O, Voets, NL, Adcock, JE et al., (2016). Resting connectivity predicts task activation in pre-surgical populations. NeuroImage: Clinical, 13, 378–385.Citable link to this page:

 

Resting connectivity predicts task activation in pre-surgical populations

Abstract: Injury and disease affect neural processing and increase individual variations in patients when compared with healthy controls. Understanding this increased variability is critical for identifying the anatomical location of eloquent brain areas for pre-surgical planning. Here we show that precise and reliable language maps can be inferred in patient populations from resting scans of idle brain activity. We trained a predictive model on pairs of resting-state and task-evoked data and tested it to predict activation of unseen patients and healthy controls based on their resting-state data alone. A well-validated language task (category fluency) was used in acquiring the task-evoked fMRI data. Although patients showed greater variation in their actual language maps, our models successfully learned variations in both patient and control responses from the individual resting-connectivity features. Importantly, we further demonstrate that a model trained exclusively on the more-homogenous control group can be used to predict task activations in patients. These results are the first to show that resting connectivity robustly predicts individual differences in neural response in cases of pathological variability.

Publication status:PublishedPeer Review status:Peer reviewedVersion:Accepted manuscriptDate of acceptance:2016-12-22Notes:© 2017 Published by Elsevier Inc. Under a Creative Commons license

Bibliographic Details

Publisher: Elsevier

Publisher Website: http://www.elsevier.com/

Journal: NeuroImage: Clinicalsee more from them

Publication Website: http://www.sciencedirect.com/science/journal/22131582

Volume: 13

Extent: 378–385

Issue Date: 2016-12

pages:378–385Identifiers

Doi: https://doi.org/10.1016/j.nicl.2016.12.028

Issn: 2213-1582

Uuid: uuid:b5e63fdb-8be2-4007-b4b2-093990339707

Urn: uri:b5e63fdb-8be2-4007-b4b2-093990339707

Pubs-id: pubs:668690 Item Description

Type: journal-article;

Version: Accepted manuscriptKeywords: connectivity individual variation neural pathology resting-state fMRI

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Author: Parker Jones, O - Oxford, MSD, Clinical Neurosciences - - - Voets, NL - Oxford, MSD, Clinical Neurosciences fundingMedical Resear

Source: https://ora.ox.ac.uk/objects/uuid:b5e63fdb-8be2-4007-b4b2-093990339707



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