Reducing variability in motor cortex activity by GABA (Hoshino et al. 2019)


Interaction between sensory and motor cortices is crucial for perceptual decision-making, in which intracortical inhibition might have an important role. We simulated a neural network model consisting of a sensory network (NS) and a motor network (NM) to elucidate the significance of their interaction in perceptual decision-making in association with the level of GABA in extracellular space: extracellular GABA concentration. Extracellular GABA molecules acted on extrasynaptic receptors embedded in membranes of pyramidal cells and suppressed them. A reduction in extracellular GABA concentration either in NS or NM increased the rate of errors in perceptual decision-making, for which an increase in ongoing-spontaneous fluctuations in subthreshold neuronal activity in NM prior to sensory stimulation was responsible. Feedback (NM-to-NS) signaling enhanced selective neuronal responses in NS, which in turn increased stimulus-evoked neuronal activity in NM. We suggest that GABA in extracellular space contributes to reducing variability in motor cortex activity at a resting state and thereby the motor cortex can respond correctly to a subsequent sensory stimulus. Feedback signaling from the motor cortex improves the selective responsiveness of the sensory cortex, which ensures the fidelity of information transmission to the motor cortex, leading to reliable perceptual decision-making.

Model Type: Realistic Network

Region(s) or Organism(s): Neocortex

Cell Type(s): Neocortex M1 interneuron basket PV GABA cell; Neocortex primary motor area pyramidal layer 5 corticospinal cell

Receptors: AMPA; GabaA

Transmitters: Glutamate; Gaba

Simulation Environment: C or C++ program

Implementer(s): Hoshino, Osamu [osamu.hoshino.507 at vc.ibaraki.ac.jp]

References:

Hoshino O, Kameno R, Watanabe K. (2019). Reducing variability in motor cortex activity at a resting state by extracellular GABA for reliable perceptual decision-making. Journal of computational neuroscience. 47 [PubMed]


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