title: Cortical Resonance Frequencies Emerge from Network Size and Connectivity.
abstract: Neural oscillations occur within a wide frequency range with different brain regions exhibiting resonance-like characteristics at specific points in the spectrum. At the microscopic scale, single neurons possess intrinsic oscillatory properties, such that is not yet known whether cortical resonance is consequential to neural oscillations or an emergent property of the networks that interconnect them. Using a network model of loosely-coupled Wilson-Cowan oscillators to simulate a patch of cortical sheet, we demonstrate that the size of the activated network is inversely related to its resonance frequency. Further analysis of the parameter space indicated that the number of excitatory and inhibitory connections, as well as the average transmission delay between units, determined the resonance frequency. The model predicted that if an activated network within the visual cortex increased in size, the resonance frequency of the network would decrease. We tested this prediction experimentally using the steady-state visual evoked potential where we stimulated the visual cortex with different size stimuli at a range of driving frequencies. We demonstrate that the frequency corresponding to peak steady-state response inversely correlated with the size of the network. We conclude that although individual neurons possess resonance properties, oscillatory activity at the macroscopic level is strongly influenced by network interactions, and that the steady-state response can be used to investigate functional networks.
authors.affiliation: Faculty of Medical and Human Sciences, University of Manchester, Manchester, United Kingdom.
authors.forename: Caroline A
authors.initials: CA
authors.lastname: Lea-Carnall
authors.affiliation: Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom.
authors.forename: Marcelo A
authors.initials: MA
authors.lastname: Montemurro
authors.affiliation: Faculty of Medical and Human Sciences, University of Manchester, Manchester, United Kingdom.
authors.forename: Nelson J
authors.initials: NJ
authors.lastname: Trujillo-Barreto
authors.affiliation: Faculty of Medical and Human Sciences, University of Manchester, Manchester, United Kingdom.
authors.forename: Laura M
authors.initials: LM
authors.lastname: Parkes
authors.affiliation: Faculty of Medical and Human Sciences, University of Manchester, Manchester, United Kingdom.|School of Biomedical Engineering, University of Valparaiso, Valparaiso, Chile.
authors.forename: Wael
authors.initials: W
authors.lastname: El-Deredy
mesh_terms: D019295:Computational Biology; D003198:Computer Simulation; D005074:Evoked Potentials, Visual / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D014793:Visual Cortex / Q000502:physiology*