Neural Network Degeneration and its Relationship to the Brain
This work addresses neurodegenerative diseases such as Alzheimer's and Parkinson's for researchers, but it appears incremental as it applies existing degradation methods to a new biological context.
The paper tackles the problem of understanding neurodegenerative diseases by applying degradation techniques like weight degradation and scrambling to neural networks as models of brain segments, resulting in insights into memory loss and learning dysfunction through monitoring error functions.
This report discusses the application of neural networks (NNs) as small segments of the brain. The networks representing the biological connectome are altered both spatially and temporally. The degradation techniques applied here are "weight degradation", "weight scrambling", and variable activation function. These methods aim to shine light on the study of neurodegenerative diseases such as Alzheimer's, Huntington's and Parkinson's disease as well as strokes and brain tumors disrupting the flow of information in the brain's network. Fundamental insights to memory loss and generalized learning dysfunction are gained by monitoring the network's error function during network degradation. The biological significance of each facet is also discussed.