Erik Fagerholm, King's College London
Labex Cortex
Models of neural dynamics have become so complicated that they are often computationally intractable and lack intuitive explanation. Structural metrics of brain networks rarely provide cross-scale descriptions and are often linearly dependent. Furthermore, information-theoretic measures are yet to provide insight into brain function and lack cohesion with existing models of the ways in which signals propagate through neural networks. These limitations are indicative of a field in need of a unifying theoretical foundation, which I am proposing to begin laying by continuing the work I began during my PhD. This foundation will simultaneously describe the dynamics (dynamical systems theory and complex systems), structure (network science and topology), and information transmission (information theory and statistical mechanics) in neural systems.
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