Collective Dynamics For Heterogeneous Networks Of Theta Neurons

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dc.contributor.advisorSo, Paul
dc.contributor.authorLuke, Tanushree
dc.creatorLuke, Tanushree
dc.date.accessioned2014-08-28T03:14:41Z
dc.date.available2014-08-28T03:14:41Z
dc.date.issued2013-08
dc.description.abstractCollective behavior in neural networks has often been used as an indicator of communication between different brain areas. These collective synchronization and desynchronization patterns are also considered an important feature in understanding normal and abnormal brain function. To understand the emergence of these collective patterns, I create an analytic model that identifies all such macroscopic steady-states attainable by a network of Type-I neurons. This network, whose basic unit is the model ``theta'' neuron, contains a mixture of excitable and spiking neurons coupled via a smooth pulse-like synapse. Applying the Ott-Antonsen reduction method in the thermodynamic limit, I obtain a low-dimensional evolution equation that describes the asymptotic dynamics of the macroscopic mean field of the network. This model can be used as the basis in understanding more complicated neuronal networks when additional dynamical features are included.
dc.format.extent152 pages
dc.identifier.urihttps://hdl.handle.net/1920/8780
dc.language.isoen
dc.rightsCopyright 2013 Tanushree Luke
dc.subjectPhysics
dc.subjectChaos
dc.subjectDriver-Response System
dc.subjectMultipopulation
dc.subjectNetwork
dc.subjectNonlinear Dynamics
dc.subjectTheta Neuron
dc.titleCollective Dynamics For Heterogeneous Networks Of Theta Neurons
dc.typeDissertation
thesis.degree.disciplinePhysics
thesis.degree.grantorGeorge Mason University
thesis.degree.levelDoctoral

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