Researchers are exploring the use of multi-factorial computational models to better understand the mechanisms of neurodegenerative diseases. Studies are utilizing various methods, including non-negative matrix factorization and integration of molecular and neuroimaging data, to identify key factors in disease progression. The approaches aim to move beyond traditional understandings of these diseases, such as Parkinson's, by considering complex interactions and multiple data types.