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Abstract The dynamic association between stochastic processes provides crucial information to science and industrial enterprises. Classic methods only provide a fixed and static metric that represents the global association of the stochastic processes. The metric that characterizes the dynamic association is still lacking. Developing such a metric is challenging since the temporal dependence of the stochastic processes could introduce an additional layer of complexity.
Abstract γ-aminobutyric acid (GABA) is an abundant neurotransmitter that plays multiple roles in the vertebrate central nervous system (CNS). In the early developing CNS, GABAergic signaling acts to depolarize cells. It mediates several aspects of neural development, including cell proliferation, neuronal migration, neurite growth, and synapse formation, as well as the development of critical periods.
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