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Kazuo Watanabe
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Journal Articles
Publisher: Journals Gateway
Neural Computation (2018) 30 (1): 184–215.
Published: 01 January 2018
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Learning of sensory cues is believed to rely on synchronous pre- and postsynaptic neuronal firing. Evidence is mounting that such synchronicity is not merely caused by properties of the underlying neuronal network but could also depend on the integrity of gap junctions that connect neurons and astrocytes in networks too. In this perspective, we set out to investigate the effect of astrocytic gap junctions on perceptual learning, introducing a model for coupled neuron-astrocyte networks. In particular, we focus on the fact that astrocytes are rich of GABA transporters (GATs) which can either uptake or release GABA depending on the astrocyte membrane potential, which is a function of local neural activity. We show that GABAergic signaling is a crucial component of intracolumnar neuronal synchronization, thereby promoting learning by neurons in the same cell assembly that are activated by a shared sensory cue. At the same time, we show that this effect can critically depend on astrocytic gap junctions insofar as these latter could synchronize extracellular GABA levels around many neurons and throughout entire cell assemblies. These results are supported by extensive computational arguments and predict that astrocytic gap junctions could improve perceptual learning by controlling extracellular GABA.
Journal Articles
Publisher: Journals Gateway
Neural Computation (2016) 28 (1): 187–215.
Published: 01 January 2016
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Variability is a prominent characteristic of cognitive brain function. For instance, different trials of presentation of the same stimulus yield higher variability in its perception: subjects sometimes fail in perceiving the same stimulus. Perceptual variability could be attributable to ongoing-spontaneous fluctuation in neuronal activity prior to sensory stimulation. Simulating a cortical neural network model, we investigated the underlying neuronal mechanism of perceptual variability in relation to variability in ongoing-spontaneous neuronal activity. In the network model, populations of principal cells (cell assemblies) encode information about sensory features. Each cell assembly is sensitive to one particular feature stimulus. Transporters on GABAergic interneurons regulate ambient GABA concentration in a neuronal activity-dependent manner. Ambient GABA molecules activate extrasynaptic GABA receptors on principal cells and interneurons, and provide them with tonic inhibitory currents. We controlled the variability of ongoing-spontaneous neuronal activity by manipulating the basal level of ambient GABA and assessed the perceptual performance of the network: detection of a feature stimulus. In an erroneous response, stimulus-irrelevant but not stimulus-relevant principal cells were activated, generating trains of action potentials. Perceptual variability, reflected in error rate in detecting the same stimulus that was presented repeatedly to the network, was increased as the variability in ongoing-spontaneous membrane potential among cell assemblies increased. Frequent, transient membrane depolarization below firing threshold was the major cause of the increased neuronal variability, for which a decrease in basal ambient GABA concentration was responsible. We suggest that ambient GABA in the brain may have a role in reducing the variability in ongoing-spontaneous neuronal activity, leading to a decrease in perceptual variability and therefore to reliable sensory perception.