A Reservoir of Timescales in Random Neural Network

dc.contributor.advisorMazzucato, Luca
dc.contributor.authorIstrate, Nicolae
dc.date.accessioned2022-10-04T19:29:46Z
dc.date.available2022-10-04T19:29:46Z
dc.date.issued2022-10-04
dc.description.abstractThe temporal activity of many biological systems, including neural circuits, exhibits fluctuations simultaneously varying over a large range of timescales. The mechanisms leading to this temporal heterogeneity are yet unknown. Here we show that random neural networks endowed with a distribution of self-couplings, representing functional neural clusters of different sizes, generate multiple timescales of activity spanning several orders of magnitude. When driven by a time-dependent broadband input, slow and fast neural clusters preferentially entrain slow and fast spectral components of the input, respectively, suggesting a potential mechanism for spectral demixing in cortical circuits.en_US
dc.identifier.urihttps://hdl.handle.net/1794/27559
dc.language.isoen_US
dc.publisherUniversity of Oregon
dc.rightsAll Rights Reserved.
dc.subjectClustersen_US
dc.subjectHeterogeneousen_US
dc.subjectNetworksen_US
dc.subjectRNNen_US
dc.subjectTimescalesen_US
dc.titleA Reservoir of Timescales in Random Neural Network
dc.typeElectronic Thesis or Dissertation
thesis.degree.disciplineDepartment of Physics
thesis.degree.grantorUniversity of Oregon
thesis.degree.leveldoctoral
thesis.degree.namePh.D.

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