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Paul So
Researcher at Krasnow Institute for Advanced Study
Publications - 39
Citations - 2175
Paul So is an academic researcher from Krasnow Institute for Advanced Study. The author has contributed to research in topics: Attractor & Chaotic. The author has an hindex of 22, co-authored 39 publications receiving 2015 citations. Previous affiliations of Paul So include George Mason University & University of Maryland, College Park.
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Detecting dynamical interdependence and generalized synchrony through mutual prediction in a neural ensemble
TL;DR: Dynamical interdependence, perhaps generalized synchrony, was identified in this neuronal network between simultaneous single unit firings, between units and the population, and betweenunits and intracellular EPSP’s.
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Exact results for the Kuramoto model with a bimodal frequency distribution.
TL;DR: This work derives the system's stability diagram for the special case where the bimodal distribution consists of two equally weighted Lorentzians and shows that in this case the infinite-dimensional problem reduces exactly to a flow in four dimensions.
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Complete classification of the macroscopic behavior of a heterogeneous network of theta neurons
TL;DR: The dynamics of a large network of theta neurons, which are idealized type I neurons, are designed and analyzed and it is found that the network typically tends toward the two macroscopic equilibrium states when the neuron's intrinsic dynamics and the network interactions reinforce one another.
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Synchronization in networks of networks: the onset of coherent collective behavior in systems of interacting populations of heterogeneous oscillators
TL;DR: The critical condition for the onset of coherent collective behavior is determined, and the illustrative case in which the oscillator frequencies are drawn from a set of (possibly different) Cauchy-Lorentz distributions is developed.
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Wave Chaos Experiments with and without Time Reversal Symmetry: GUE and GOE Statistics
TL;DR: The first experimental test of the prediction that in the semiclassical regime the level statistics of a classically chaotic system correspond to that of the Gaussian unitary ensemble (GUE) of random matrices when time reversal symmetry is broken is presented.