Theoretical and Computational Neuroscience
Author: Federico Miceli | Email: micelifederico08@gmail.com
Federico Miceli1°, Marcelo A. Montemurro2°,Fernando F. Montani1°, Mauro Granado1°
1° Instituto de Fisica de La Plata CONICET
2° School of Mathematics & Statistics, Faculty of Science, Technology, Engineering & Mathematics, The Open University, Walton Hall, Milton Keynes MK7 6AA, United Kingdom.
A neurodegenerative disorder called Alzheimer’s disease (AD) causes cognitive performance to gradually deteriorate. Since there is currently no treatment for AD, it is imperative that we use scientific research to deepen our understanding of the disease’s mechanisms. Degeneration is frequently observed in several brain regions, including association areas, limbic system regions connected to memory and emotion, and memory itself. Alzheimer’s disease (AD) experiences a buildup of the illness’s pathology in their central nervous systems. In general, there is a clear pattern to this accumulation in terms of timing and place. Using information theory tools we characterize the evolution of complexity and Shannon entropy for different Alzeheimer’s disease states in mice over time and compare them with the dynamics of healthy tissues. Our methodology shows how neuronal dynamics differ in terms of spatial and temporal area as months pass, allowing us to speculate on possible biomarkers of Alzheimer’s disease.