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Interregional compensatory mechanisms of motor functioning in progressing preclinical neurodegeneration

Understanding brain reserve in preclinical stages of neurodegenerative disorders allows determination of which brain regions contribute to normal functioning despite accelerated neuronal loss. Besides the recruitment of additional regions, a reorganisation and shift of relevance between normally eng...

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Autores principales: Scheller, Elisa, Abdulkadir, Ahmed, Peter, Jessica, Tabrizi, Sarah J., Frackowiak, Richard S.J., Klöppel, Stefan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3899022/
https://www.ncbi.nlm.nih.gov/pubmed/23501047
http://dx.doi.org/10.1016/j.neuroimage.2013.02.058
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author Scheller, Elisa
Abdulkadir, Ahmed
Peter, Jessica
Tabrizi, Sarah J.
Frackowiak, Richard S.J.
Klöppel, Stefan
author_facet Scheller, Elisa
Abdulkadir, Ahmed
Peter, Jessica
Tabrizi, Sarah J.
Frackowiak, Richard S.J.
Klöppel, Stefan
author_sort Scheller, Elisa
collection PubMed
description Understanding brain reserve in preclinical stages of neurodegenerative disorders allows determination of which brain regions contribute to normal functioning despite accelerated neuronal loss. Besides the recruitment of additional regions, a reorganisation and shift of relevance between normally engaged regions are a suggested key mechanism. Thus, network analysis methods seem critical for investigation of changes in directed causal interactions between such candidate brain regions. To identify core compensatory regions, fifteen preclinical patients carrying the genetic mutation leading to Huntington's disease and twelve controls underwent fMRI scanning. They accomplished an auditory paced finger sequence tapping task, which challenged cognitive as well as executive aspects of motor functioning by varying speed and complexity of movements. To investigate causal interactions among brain regions a single Dynamic Causal Model (DCM) was constructed and fitted to the data from each subject. The DCM parameters were analysed using statistical methods to assess group differences in connectivity, and the relationship between connectivity patterns and predicted years to clinical onset was assessed in gene carriers. In preclinical patients, we found indications for neural reserve mechanisms predominantly driven by bilateral dorsal premotor cortex, which increasingly activated superior parietal cortices the closer individuals were to estimated clinical onset. This compensatory mechanism was restricted to complex movements characterised by high cognitive demand. Additionally, we identified task-induced connectivity changes in both groups of subjects towards pre- and caudal supplementary motor areas, which were linked to either faster or more complex task conditions. Interestingly, coupling of dorsal premotor cortex and supplementary motor area was more negative in controls compared to gene mutation carriers. Furthermore, changes in the connectivity pattern of gene carriers allowed prediction of the years to estimated disease onset in individuals. Our study characterises the connectivity pattern of core cortical regions maintaining motor function in relation to varying task demand. We identified connections of bilateral dorsal premotor cortex as critical for compensation as well as task-dependent recruitment of pre- and caudal supplementary motor area. The latter finding nicely mirrors a previously published general linear model-based analysis of the same data. Such knowledge about disease specific inter-regional effective connectivity may help identify foci for interventions based on transcranial magnetic stimulation designed to stimulate functioning and also to predict their impact on other regions in motor-associated networks.
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spelling pubmed-38990222014-01-24 Interregional compensatory mechanisms of motor functioning in progressing preclinical neurodegeneration Scheller, Elisa Abdulkadir, Ahmed Peter, Jessica Tabrizi, Sarah J. Frackowiak, Richard S.J. Klöppel, Stefan Neuroimage Article Understanding brain reserve in preclinical stages of neurodegenerative disorders allows determination of which brain regions contribute to normal functioning despite accelerated neuronal loss. Besides the recruitment of additional regions, a reorganisation and shift of relevance between normally engaged regions are a suggested key mechanism. Thus, network analysis methods seem critical for investigation of changes in directed causal interactions between such candidate brain regions. To identify core compensatory regions, fifteen preclinical patients carrying the genetic mutation leading to Huntington's disease and twelve controls underwent fMRI scanning. They accomplished an auditory paced finger sequence tapping task, which challenged cognitive as well as executive aspects of motor functioning by varying speed and complexity of movements. To investigate causal interactions among brain regions a single Dynamic Causal Model (DCM) was constructed and fitted to the data from each subject. The DCM parameters were analysed using statistical methods to assess group differences in connectivity, and the relationship between connectivity patterns and predicted years to clinical onset was assessed in gene carriers. In preclinical patients, we found indications for neural reserve mechanisms predominantly driven by bilateral dorsal premotor cortex, which increasingly activated superior parietal cortices the closer individuals were to estimated clinical onset. This compensatory mechanism was restricted to complex movements characterised by high cognitive demand. Additionally, we identified task-induced connectivity changes in both groups of subjects towards pre- and caudal supplementary motor areas, which were linked to either faster or more complex task conditions. Interestingly, coupling of dorsal premotor cortex and supplementary motor area was more negative in controls compared to gene mutation carriers. Furthermore, changes in the connectivity pattern of gene carriers allowed prediction of the years to estimated disease onset in individuals. Our study characterises the connectivity pattern of core cortical regions maintaining motor function in relation to varying task demand. We identified connections of bilateral dorsal premotor cortex as critical for compensation as well as task-dependent recruitment of pre- and caudal supplementary motor area. The latter finding nicely mirrors a previously published general linear model-based analysis of the same data. Such knowledge about disease specific inter-regional effective connectivity may help identify foci for interventions based on transcranial magnetic stimulation designed to stimulate functioning and also to predict their impact on other regions in motor-associated networks. Academic Press 2013-07-15 /pmc/articles/PMC3899022/ /pubmed/23501047 http://dx.doi.org/10.1016/j.neuroimage.2013.02.058 Text en © 2013 Elsevier Inc. https://creativecommons.org/licenses/by/3.0/ Open Access under CC BY 3.0 (https://creativecommons.org/licenses/by/3.0/) license
spellingShingle Article
Scheller, Elisa
Abdulkadir, Ahmed
Peter, Jessica
Tabrizi, Sarah J.
Frackowiak, Richard S.J.
Klöppel, Stefan
Interregional compensatory mechanisms of motor functioning in progressing preclinical neurodegeneration
title Interregional compensatory mechanisms of motor functioning in progressing preclinical neurodegeneration
title_full Interregional compensatory mechanisms of motor functioning in progressing preclinical neurodegeneration
title_fullStr Interregional compensatory mechanisms of motor functioning in progressing preclinical neurodegeneration
title_full_unstemmed Interregional compensatory mechanisms of motor functioning in progressing preclinical neurodegeneration
title_short Interregional compensatory mechanisms of motor functioning in progressing preclinical neurodegeneration
title_sort interregional compensatory mechanisms of motor functioning in progressing preclinical neurodegeneration
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3899022/
https://www.ncbi.nlm.nih.gov/pubmed/23501047
http://dx.doi.org/10.1016/j.neuroimage.2013.02.058
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