AUTHOR=Tomov Petar , Pena Rodrigo F. O. , Roque Antonio C. , Zaks Michael A. TITLE=Mechanisms of Self-Sustained Oscillatory States in Hierarchical Modular Networks with Mixtures of Electrophysiological Cell Types JOURNAL=Frontiers in Computational Neuroscience VOLUME=10 YEAR=2016 URL=https://www.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2016.00023 DOI=10.3389/fncom.2016.00023 ISSN=1662-5188 ABSTRACT=

In a network with a mixture of different electrophysiological types of neurons linked by excitatory and inhibitory connections, temporal evolution leads through repeated epochs of intensive global activity separated by intervals with low activity level. This behavior mimics “up” and “down” states, experimentally observed in cortical tissues in absence of external stimuli. We interpret global dynamical features in terms of individual dynamics of the neurons. In particular, we observe that the crucial role both in interruption and in resumption of global activity is played by distributions of the membrane recovery variable within the network. We also demonstrate that the behavior of neurons is more influenced by their presynaptic environment in the network than by their formal types, assigned in accordance with their response to constant current.