Effects of Hebbian learning on networks of Kuramoto phase oscillators with time delay

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

Abstract

Neuronal oscillations are crucial for various cognitive functions, including
learning. Among neuronal populations, patterns of synchronization
can drive connectivity changes, in turn modifying oscillations and
synchronization. To study changes in oscillation patterns with learning,
we modeled brain processing using a directed random network
of phase-coupled oscillators interacting according to the Kuramoto
model
Original languageEnglish
Title of host publicationBMC Neurosci 2017, 18(Suppl 1):60
PublisherBioMed Central
Pages164-165
Number of pages2
Volume18
DOIs
Publication statusPublished - 18 Aug 2017

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