Abstract
Phase transitions involve sharp changes in large-scale order parameters, linked to instability of a pre-existing phase. In the neural context, such transitions and instabilities have been associated with changes of arousal state, anesthesia, onset of epilepsy, and other phenomena. Mean-field models are ideally suited to study phase transitions because of their ability to incorporate physiology from the microscale up to the whole brain in a theoretically and computationally tractable way, whereas spiking-neuron models are not feasible to study in sufficiently large assemblies to track global phase transitions. This chapter overviews a highly general and flexible class of physiologically based mean-field models, and summarizes a number of applications of them to neural phase transitions, especially in the areas of epilepsy and sleep.
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Robinson, P., Rennie, C., Phillips, A., Kim, J., Roberts, J. (2010). Phase transitions in physiologically-based multiscale mean-field brain models. In: Steyn-Ross, D., Steyn-Ross, M. (eds) Modeling Phase Transitions in the Brain. Springer Series in Computational Neuroscience, vol 4. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0796-7_8
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