Computational modelling of pathogenic protein spread in neurodegenerative diseases.
Pathogenic protein accumulation and spread are fundamental principles of neurodegenerative diseases and ultimately account for the atrophy patterns that distinguish these diseases clinically. However, the biological mechanisms that link pathogenic proteins to specific neural network damage patterns...
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2018-01-01
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doaj-e19919b1a9db4c029d6e5d5db808d8782021-03-04T12:40:28ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-01132e019251810.1371/journal.pone.0192518Computational modelling of pathogenic protein spread in neurodegenerative diseases.Konstantinos GeorgiadisSelina WraySébastien OurselinJason D WarrenMarc ModatPathogenic protein accumulation and spread are fundamental principles of neurodegenerative diseases and ultimately account for the atrophy patterns that distinguish these diseases clinically. However, the biological mechanisms that link pathogenic proteins to specific neural network damage patterns have not been defined. We developed computational models for mechanisms of pathogenic protein accumulation, spread and toxic effects in an artificial neural network of cortical columns. By varying simulation parameters we assessed the effects of modelled mechanisms on network breakdown patterns. Our findings suggest that patterns of network breakdown and the convergence of patterns follow rules determined by particular protein parameters. These rules can account for empirical data on pathogenic protein spread in neural networks. This work provides a basis for understanding the effects of pathogenic proteins on neural circuits and predicting progression of neurodegeneration.https://doi.org/10.1371/journal.pone.0192518 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Konstantinos Georgiadis Selina Wray Sébastien Ourselin Jason D Warren Marc Modat |
spellingShingle |
Konstantinos Georgiadis Selina Wray Sébastien Ourselin Jason D Warren Marc Modat Computational modelling of pathogenic protein spread in neurodegenerative diseases. PLoS ONE |
author_facet |
Konstantinos Georgiadis Selina Wray Sébastien Ourselin Jason D Warren Marc Modat |
author_sort |
Konstantinos Georgiadis |
title |
Computational modelling of pathogenic protein spread in neurodegenerative diseases. |
title_short |
Computational modelling of pathogenic protein spread in neurodegenerative diseases. |
title_full |
Computational modelling of pathogenic protein spread in neurodegenerative diseases. |
title_fullStr |
Computational modelling of pathogenic protein spread in neurodegenerative diseases. |
title_full_unstemmed |
Computational modelling of pathogenic protein spread in neurodegenerative diseases. |
title_sort |
computational modelling of pathogenic protein spread in neurodegenerative diseases. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2018-01-01 |
description |
Pathogenic protein accumulation and spread are fundamental principles of neurodegenerative diseases and ultimately account for the atrophy patterns that distinguish these diseases clinically. However, the biological mechanisms that link pathogenic proteins to specific neural network damage patterns have not been defined. We developed computational models for mechanisms of pathogenic protein accumulation, spread and toxic effects in an artificial neural network of cortical columns. By varying simulation parameters we assessed the effects of modelled mechanisms on network breakdown patterns. Our findings suggest that patterns of network breakdown and the convergence of patterns follow rules determined by particular protein parameters. These rules can account for empirical data on pathogenic protein spread in neural networks. This work provides a basis for understanding the effects of pathogenic proteins on neural circuits and predicting progression of neurodegeneration. |
url |
https://doi.org/10.1371/journal.pone.0192518 |
work_keys_str_mv |
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1714801954463416320 |