Computational modelling of pathogenic protein spread in neurodegenerative diseases

Konstantinos Georgiadis*, Selina Wray, Sébastien Ourselin, Jason D. Warren, Marc Modat

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)
144 Downloads (Pure)


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.

Original languageEnglish
Article numberY
JournalPLoS ONE
Issue number2
Publication statusPublished - 1 Feb 2018


Dive into the research topics of 'Computational modelling of pathogenic protein spread in neurodegenerative diseases'. Together they form a unique fingerprint.

Cite this