Malvestio, IreneKreuz, ThomasAndrzejak, Ralph Gregor2017-08-292017-08-292017Malvestio I, Kreuz T, Andrzejak RG. Robustness and versatility of a nonlinear interdependence method for directional coupling detection from spike trains. Phys. Rev. E. 2017 Aug 3;96:022203. DOI: 10.1103/PhysRevE.96.0222032470-0045http://hdl.handle.net/10230/32713The detection of directional couplings between dynamics based onmeasured spike trains is a crucial problem in the understanding of many different systems. In particular, in neuroscience it is important to assess the connectivity between neurons.One of the approaches that can estimate directional coupling from the analysis of point processes is the nonlinear interdependence measure L. Although its efficacy has already been demonstrated, it still needs to be tested under more challenging and realistic conditions prior to an application to real data. Thus, in this paper we use the Hindmarsh-Rose model system to test the method in the presence of noise and for different spiking regimes.We also examine the influence of different parameters and spike train distances. Our results show that the measure L is versatile and robust to various types of noise, and thus suitable for application to experimental data.application/pdfeng© American Physical Society. Published article available at https://journals.aps.org/pre/abstract/10.1103/PhysRevE.96.022203Robustness and versatility of a nonlinear interdependence method for directional coupling detection from spike trainsinfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1103/PhysRevE.96.022203Coupled oscillatorsSynchronizationChaotic systemsDynamical systemsNeuronal network modelsTime series analysisInterdisciplinary physicsNetworksNonlinear dynamicsinfo:eu-repo/semantics/openAccess