title: Cellularly-driven differences in network synchronization propensity are differentially modulated by firing frequency.
abstract: Spatiotemporal pattern formation in neuronal networks depends on the interplay between cellular and network synchronization properties. The neuronal phase response curve (PRC) is an experimentally obtainable measure that characterizes the cellular response to small perturbations, and can serve as an indicator of cellular propensity for synchronization. Two broad classes of PRCs have been identified for neurons: Type I, in which small excitatory perturbations induce only advances in firing, and Type II, in which small excitatory perturbations can induce both advances and delays in firing. Interestingly, neuronal PRCs are usually attenuated with increased spiking frequency, and Type II PRCs typically exhibit a greater attenuation of the phase delay region than of the phase advance region. We found that this phenomenon arises from an interplay between the time constants of active ionic currents and the interspike interval. As a result, excitatory networks consisting of neurons with Type I PRCs responded very differently to frequency modulation compared to excitatory networks composed of neurons with Type II PRCs. Specifically, increased frequency induced a sharp decrease in synchrony of networks of Type II neurons, while frequency increases only minimally affected synchrony in networks of Type I neurons. These results are demonstrated in networks in which both types of neurons were modeled generically with the Morris-Lecar model, as well as in networks consisting of Hodgkin-Huxley-based model cortical pyramidal cells in which simulated effects of acetylcholine changed PRC type. These results are robust to different network structures, synaptic strengths and modes of driving neuronal activity, and they indicate that Type I and Type II excitatory networks may display two distinct modes of processing information.
authors.affiliation: Department of Physics, University of Michigan, Ann Arbor, Michigan, United States of America. tcgfink@umich.edu
authors.forename: Christian G
authors.initials: CG
authors.lastname: Fink
authors.forename: Victoria
authors.initials: V
authors.lastname: Booth
authors.forename: Michal
authors.initials: M
authors.lastname: Zochowski
mesh_terms: D000200:Action Potentials / Q000502:physiology; D002540:Cerebral Cortex / Q000502:physiology; D003198:Computer Simulation; D003344:Cortical Synchronization / Q000502:physiology; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology; D017966:Pyramidal Cells / Q000502:physiology