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Critical Behavior of Neuronal Systems: an Information Theory Viewpoint
Soltani, Miaad | 2022
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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 55383 (04)
- University: Sharif University of Technology
- Department: Physics
- Advisor(s): Moghimi, Saman
- Abstract:
- Experiments conducted in recent two decades indicated critical behavior in neural activity at different scales. Theoretically occurrences of these critical and power-law behavior can significantly facilitate brain activities correspondent to computation and memory tasks, but attaining the critical point essentially demands externally fine-tuning which has not been established yet. This fine-tuning often lies with placing system at transition point. Recent studies of group showed that a transition from synchronous to asynchronous phase could be achievable by a change in external parameters. At the very transition point, neuronal avalanches statistically demonstrate a power-law behavior which is the indicator of criticality. Critical behavior has been studied in a number of neural systems such as eye neuron assembly in a different way. In this regard, there were much efforts to link the system with relevant ising spins by means of neural activeness in terms of statistics and to derive a Hamiltonian which would be appropriate to the study of this phase transition at different temperatures. In this dissertation we regard the neural population which is investigated before and attempt to classify state of activeness into two groups. Then assess whether a potential Hamiltonian suggested by information theory could be existed to show phase transition at the very point of synchronization. In other words, this would develop a practical ising-like model which is capable of mimicking some behavior of neural systems
- Keywords:
- Neural System Modeling ; Information Theory ; Phase Transition ; Statistical Mechanics ; Criticality ; Entropy ; Ising model ; Power Law Behaviour
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