S
Sonja Grün
Researcher at RWTH Aachen University
Publications - 152
Citations - 6326
Sonja Grün is an academic researcher from RWTH Aachen University. The author has contributed to research in topics: Spike (software development) & Spike train. The author has an hindex of 37, co-authored 137 publications receiving 5582 citations. Previous affiliations of Sonja Grün include RIKEN Brain Science Institute & Humboldt University of Berlin.
Papers
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Journal ArticleDOI
Spike Synchronization and Rate Modulation Differentially Involved in Motor Cortical Function
TL;DR: Findings indicate that internally generated synchronization of individual spike discharges may subserve the cortical organization of cognitive motor processes.
Journal ArticleDOI
Modeling the spatial reach of the LFP.
Henrik Lindén,Henrik Lindén,Tom Tetzlaff,Tobias C. Potjans,Klas H. Pettersen,Sonja Grün,Sonja Grün,Markus Diesmann,Gaute T. Einevoll +8 more
TL;DR: The size of the generating region depends on the neuron morphology, the synapse distribution, and the correlation in synaptic activity, and is investigated by simulating the LFP from a large number of neurons around the electrode.
Journal ArticleDOI
Cross-frequency interaction of the eye-movement related LFP signals in V1 of freely viewing monkeys.
TL;DR: The results suggest the presence of cross-frequency interactions in the form of phase-amplitude coupling (PAC) between slow (delta-theta) and faster (alpha-beta and low gamma) oscillations between slow and faster oscillations during natural viewing.
Journal ArticleDOI
Unitary events in multiple single-neuron spiking activity: I. detection and significance
TL;DR: A novel method to detect conspicuous patterns of coincident joint spike activity among simultaneously recorded single neurons, designed to deal with nonstationary firing rates is described.
BookDOI
Analysis of Parallel Spike Trains
Sonja Grün,Stefan Rotter +1 more
TL;DR: The present work focuses on the development of stochastic models for multivariate neural point processes: Collective dynamics and neural decoding for population-based approaches.