Computational modelling to predict course of amyotrophic lateral sclerosis


  • Computational modelling accurately predicts disease progression and survival times in patients with amyotrophic lateral sclerosis (ALS).

Why this matters

  • In ALS, white matter impairment spreads from the primary motor regions to other brain regions in a progressive way leading to network integrity changes.

  • Researchers have used brain network analyses in neurodegenerative diseases to predict progression; however, this has not yet been applied in ALS.

  • Computational modelling based on brain white matter connection patterns may be useful in predicting staging, progression and survival in ALS.