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1
Utilising a systematic review-based approach to create a database of individual participant data for meta- and network meta-analyses: The RELEASE database of aphasia after stroke
In: Research outputs 2014 to 2021 (2022)
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2
Training flexible conceptual retrieval in post-stroke aphasia
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3
Language Disorder in Progressive Supranuclear Palsy and Corticobasal Syndrome: Neural Correlates and Detection by the MLSE Screening Tool. ...
Peterson, Katie A; Jones, P Simon; Patel, Nikil. - : Apollo - University of Cambridge Repository, 2021
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4
Auditory beat perception is related to speech output fluency in post-stroke aphasia ...
Stefaniak, James D.; Lambon Ralph, Matthew A.; De Dios Perez, Blanca. - : Apollo - University of Cambridge Repository, 2021
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5
Language Disorder in Progressive Supranuclear Palsy and Corticobasal Syndrome: Neural Correlates and Detection by the MLSE Screening Tool ...
Peterson, Katie A.; Jones, P. Simon; Patel, Nikil. - : Apollo - University of Cambridge Repository, 2021
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6
Language Disorder in Progressive Supranuclear Palsy and Corticobasal Syndrome: Neural Correlates and Detection by the MLSE Screening Tool
In: Front Aging Neurosci (2021)
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7
Training flexible conceptual retrieval in post-stroke aphasia
In: ISSN: 0960-2011 ; Neuropsychological Rehabilitation (2021) pp. 1-27 (2021)
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8
Auditory beat perception is related to speech output fluency in post-stroke aphasia
Stefaniak, James D.; Lambon Ralph, Matthew A.; De Dios Perez, Blanca. - : Nature Publishing Group UK, 2021. : Scientific Reports, 2021
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9
Language Disorder in Progressive Supranuclear Palsy and Corticobasal Syndrome: Neural Correlates and Detection by the MLSE Screening Tool
Peterson, Katie A.; Jones, P. Simon; Patel, Nikil. - : Frontiers Media S.A., 2021. : Frontiers in Aging Neuroscience, 2021
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10
Language Disorder in Progressive Supranuclear Palsy and Corticobasal Syndrome: Neural Correlates and Detection by the MLSE Screening Tool.
In: essn: 1663-4365 ; nlmid: 101525824 (2021)
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11
The neural bases of resilient semantic system: evidence of variable neuro-displacement in cognitive systems
In: Brain Struct Funct (2021)
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12
Multiple dimensions underlying the functional organization of the language network
In: Neuroimage (2021)
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13
Graded, multidimensional intra- and intergroup variations in primary progressive aphasia and post-stroke aphasia.
In: Brain : a journal of neurology, vol 143, iss 10 (2020)
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14
RELEASE: A protocol for a systematic review based, individual participant data, meta- and network meta-analysis, of complex speech-language therapy interventions for stroke-related aphasia
In: Research outputs 2014 to 2021 (2020)
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15
Bipartite Functional Fractionation within the Default Network Supports Disparate Forms of Internally Oriented Cognition
In: Cereb Cortex (2020)
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16
RELEASE: a protocol for a systematic review based, individual participant data, meta- and network meta-analysis, of complex speech-language therapy interventions for stroke-related aphasia
Brady, Marian C.; Ali, Myzoon; VandenBerg, Kathryn. - : Taylor & Francis, 2020
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17
A unified neurocomputational bilateral model of spoken language production in healthy participants and recovery in poststroke aphasia
In: Proc Natl Acad Sci U S A (2020)
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18
Investigating the effect of changing parameters when building prediction models in post-stroke aphasia
In: Nat Hum Behav (2020)
Abstract: Neuroimaging has radically improved our understanding of how speech and language abilities map to the brain in normal and impaired participants, including the diverse, graded variations observed in post-stroke aphasia. A handful of studies have begun to explore the reverse inference: creating brain-to-behaviour prediction models. In this study, we explored the effect of three critical parameters on model performance: (1) brain partitions as predictive features; (2) combination of multimodal neuroimaging; and (3) type of machine learning algorithms. We explored the influence of these factors while predicting four principal dimensions of language and cognition variation in post-stroke aphasia. Across all four behavioural dimensions, we consistently found that prediction models derived from diffusion weighted data did not improve performance over and above models using structural measures extracted from T1 scans. Our results provide a set of principles to guide future work aiming to predict outcomes in neurological patients from brain imaging data.
Keyword: Article
URL: https://doi.org/10.1038/s41562-020-0854-5
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7116235/
http://www.ncbi.nlm.nih.gov/pubmed/32313234
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19
Redefining the multidimensional clinical phenotypes of frontotemporal lobar degeneration syndromes
In: Brain (2020)
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20
Establishing two principal dimensions of cognitive variation in logopenic progressive aphasia
In: Brain Commun (2020)
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