title: Cross-frequency transfer in a stochastically driven mesoscopic neuronal model.
abstract: The brain is known to operate in multiple coexisting frequency bands. Increasing experimental evidence suggests that interactions between those distinct bands play a crucial role in brain processes, but the dynamical mechanisms underlying this cross-frequency coupling are still under investigation. Two approaches have been proposed to address this issue. In the first one distinct nonlinear oscillators representing the brain rhythms involved are coupled actively (bidirectionally), whereas in the second one the oscillators are coupled unidirectionally and thus the driving between them is passive. Here we elaborate the latter approach by implementing a stochastically driven network of coupled neural mass models that operate in the alpha range. This model exhibits a broadband power spectrum with 1/f(b) form, similar to those observed experimentally. Our results show that such a model is able to reproduce recent experimental observations on the effect of slow rocking on the alpha activity associated with sleep. This suggests that passive driving can account for cross-frequency transfer in the brain, as a result of the complex nonlinear dynamics of its underlying oscillators.
authors.affiliation: Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya Barcelona, Spain ; Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona Barcelona, Spain.
authors.forename: Maciej
authors.initials: M
authors.lastname: Jedynak
authors.affiliation: Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya Barcelona, Spain.
authors.forename: Antonio J
authors.initials: AJ
authors.lastname: Pons
authors.affiliation: Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona Barcelona, Spain.
authors.forename: Jordi
authors.initials: J
authors.lastname: Garcia-Ojalvo
keywords: Jansen-Rit model; Ornstein-Uhlenbeck noise; cross-frequency coupling; driven oscillators; mesoscopic brain dynamics; neural mass model; neuronal oscillations; stochastic