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Neurodegenerative diseases and traumatic brain injuries (TBI) are among themain causes of cognitive dysfunction in humans. Both manifestations exhibit theextensive presence of focal axonal swellings (FAS). FAS compromises theinformation encoded in spike trains, thus leading to potentially severefunctional deficits. Complicating our understanding of the impact of FAS is ourinability to access small scale injuries with non-invasive methods, the overallcomplexity of neuronal pathologies, and our limited knowledge of how networksprocess biological signals. Building on Hopfield's pioneering work, we extend amodel for associative memory to account for FAS and its impact on memoryencoding. We calibrate all FAS parameters from biophysical observations oftheir statistical distribution and size, providing a framework to simulate theeffects of brain disorders on memory recall performance. A face recognitionexample is used to demonstrate and validate the functionality of the novelmodel. Our results link memory recall ability to observed FAS statistics,allowing for a description of different stages of brain disorders withinneuronal networks. This provides a first theoretical model to bridgeexperimental observations of FAS in neurodegeneration and TBI with compromisedmemory recall, thus closing the large gap between theory and experiment on howbiological signals are processed in damaged, high-dimensional functionalnetworks. The work further lends new insight into positing diagnostic tools tomeasure cognitive deficits.

Associative Memory Impairments arising from Neurodegenerative Diseases and Traumatic Brain Injuries in a Hopfield Network Model