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Modeling the effects of neuronal morphology on dendritic chloride diffusion and GABAergic inhibition
(2014)
Poster presentation at the Twenty Third Annual Computational Neuroscience Meeting: CNS*2014 Québec City, Canada. 26-31 July 2014.
Gamma-aminobutyric acid receptors (GABAARs) are ligand-gated chloride (Cl−) channels which mediate the majority of inhibitory neurotransmission in the CNS. Spatiotemporal changes of intracellular Cl− concentration alter the concentration gradient for Cl− across the neuronal membrane and thus affect the current flow through GABAARs and the efficacy of GABAergic inhibition. However, the impact of complex neuronal morphology on Cl− diffusion and the redistribution of intracellular Cl− is not well understood. Recently, computational models for Cl− diffusion and GABAAR-mediated inhibition in realistic neuronal morphologies became available [1-3]. Here we have used computational models of morphologically complex dendrites to test the effects of spines on Cl− diffusion. In all dendritic morphologies tested, spines slowed down longitudinal Cl− diffusion along dendrites and decreased the amount and spatial spread of synaptically evoked Cl− changes. Spine densities of 2-10 spines/µm decreased the longitudinal diffusion coefficient of Cl− to 80-30% of its value in smooth dendrites, respectively. These results suggest that spines are able to limit short-term ionic plasticity [4] at dendritic GABAergic synapses.
The nervous system probably cannot display macroscopic quantum (i.e. classically impossible) behaviours such as quantum entanglement, superposition or tunnelling (Koch and Hepp, Nature 440:611, 2006). However, in contrast to this quantum "mysticism" there is an alternative way in which quantum events might influence the brain activity. The nervous system is a nonlinear system with many feedback loops at every level of its structural hierarchy. A conventional wisdom is that in macroscopic objects the quantum fluctuations are self-averaging and thus not important. Nevertheless this intuition might be misleading in the case of nonlinear complex systems. Because of a high sensitivity to initial conditions, in chaotic systems the microscopic fluctuations may be amplified upward and thereby affect the system’s output. In this way stochastic quantum dynamics might sometimes alter the outcome of neuronal computations, not by generating classically impossible solutions, but by influencing the selection of many possible solutions (Satinover, Quantum Brain, Wiley & Sons, 2001). I am going to discuss recent theoretical proposals and experimental findings in quantum mechanics, complexity theory and computational neuroscience suggesting that biological evolution is able to take advantage of quantum-computational speed-up. I predict that the future research on quantum complex systems will provide us with novel interesting insights that might be relevant also for neurobiology and neurophilosophy.