Although there is growing interest in understanding the resting-state fluctuations, the underlying neural mechanisms by which these oscillations arise remain unknown.Ĭhanges in the ion concentrations have been suggested to modulate network activity ( 25– 34) and extracellular potassium concentrations ( o) have been shown to fluctuate during resting-state or background activity over a long time period ( 35). Several neurological and psychiatric disorders, such as epilepsy and schizophrenia, have been shown to correlate with altered resting-state fluctuations and functional connectivity ( 4, 18– 22). The resting-state activity across wide brain regions forms functional networks, such as the default-mode network, that vary with brain state and type of cognitive activity ( 2, 5, 15, 18). The spontaneous resting-state activity in fMRI signal is a robust phenomenon that has been widely used to evaluate brain network properties, from determining functional connectivity during cognitive tasks to identifying altered functional connectivity in various conscious and disease states ( 2, 4, 5, 15, 18, 19). Resting-state or spontaneous background fluctuations, in the frequency range of 0.01–0.2 Hz ( 1– 16), are reported by a wide range of neuroimaging methods, including electrophysiological, optical, EEG, and fMRI ( 2, 4, 5, 8, 14, 17). Overall, our study proposes that ion concentration dynamics mediated by neuronal and glial activity may contribute to the generation of very slow spontaneous fluctuations of brain activity that are reported as the resting-state fluctuations in fMRI and EEG recordings. Further, in a large-scale network with long-range connections based on CoCoMac connectivity data, the infra-slow fluctuations became synchronized among remote clusters similar to the resting-state activity observed in vivo. The amplitude and peak frequency of this activity were modulated by the Na +/K + pump, AMPA/GABA synaptic currents, and glial properties. Holding K + concentration constant prevented generation of the infra-slow fluctuations. In the network model simulating resting awake-like brain state, we observed infra-slow fluctuations in the extracellular K + concentration, Na +/K + pump activation, firing rate of neurons, and local field potentials. The computational model implemented dynamics for intra- and extracellular K + and Na + and intracellular Cl − ions, Na +/K + exchange pump, and KCC2 cotransporter. Here, using a detailed computational model of the brain network, we show that spontaneous infra-slow (<0.05 Hz) activity could originate due to the ion concentration dynamics. However, the origin of these infra-slow resting-state fluctuations remains unknown. These fluctuations were found to be correlated across brain regions and are thought to reflect neuronal activity fluctuations between functionally connected areas of the brain.
Resting- or baseline-state low-frequency (0.01–0.2 Hz) brain activity is observed in fMRI, EEG, and local field potential recordings.