title: Facilitation of neuronal responses by intrinsic default mode network activity.
abstract: Default mode network (DMN) shows intrinsic, high-level activity at rest. We tested a hypothesis proposed for its role in sensory information processing: Intrinsic DMN activity facilitates neural responses to sensory input. A neural network model, consisting of a sensory network (Nsen) and a DMN, was simulated. The Nsen contained cell assemblies. Each cell assembly comprised principal cells, GABAergic interneurons (Ia, Ib), and glial cells. We let the Nsen carry out a perceptual task: detection of sensory stimuli. During DMN activation, glial cells were hyperpolarized by Ia-to-glia circuitry, by which glial membrane transporters imported GABA molecules from the extracellular space and decreased ambient GABA concentration. Acting on extrasynaptic GABA receptors, the decrease in ambient GABA concentration reduced inhibitory current in a tonic manner. This depolarized principal cells below their firing threshold during the ongoing spontaneous time period and accelerated their reaction speed to a sensory stimulus. During the stimulus presentation period, the Nsen inhibited the DMN and caused DMN deactivation. The DMN deactivation made Nsen Ia cells cease firing, thereby stopping the glial membrane hyperpolarization, quitting the GABA import, returning to the basal ambient GABA level, and thus enhancing global inhibition. Notably, the stimulus-relevant P cell firing could be maintained when GABAergic gliotransmission via Ia-glia signaling worked, decreasing ambient GABA concentration around the stimulus-relevant P cells. This enabled the Nsen to reliably detect the stimulus. We suggest that intrinsic default model network activity may accelerate the reaction speed of the sensory network by modulating its ongoing-spontaneous activity in a subthreshold manner. Ambient GABA contributes to achieve an optimal ongoing spontaneous subthreshold neuronal state, in which GABAergic gliotransmission triggered by the intrinsic default model network activity may play an important role.
authors.affiliation: Department of Intelligent Systems Engineering, Ibaraki University, Hitachi, Ibaraki, 316-8511, Japan rinnakyarotto@hotmail.co.jp.
authors.forename: Hiroakira
authors.initials: H
authors.lastname: Matsui
authors.forename: Meihong
authors.initials: M
authors.lastname: Zheng
authors.forename: Osamu
authors.initials: O
authors.lastname: Hoshino
mesh_terms: D000818:Animals; D001703:Biophysics; D006801:Humans; D008564:Membrane Potentials / Q000502:physiology*; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009433:Neural Inhibition / Q000502:physiology; D016571:Neural Networks, Computer; D009457:Neuroglia / Q000502:physiology; D009474:Neurons / Q000502:physiology*; D013569:Synapses / Q000502:physiology; D005680:gamma-Aminobutyric Acid / Q000378:metabolism
chemical_list: D005680:gamma-Aminobutyric Acid