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      A supercritical density of fast Na + channels ensures rapid propagation of action potentials in GABAergic interneuron axons

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      Nature neuroscience

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          Abstract

          Fast-spiking, parvalbumin-expressing GABAergic interneurons/basket cells (BCs) play a key role in feedforward and feedback inhibition, gamma oscillations, and complex information processing. For these functions, fast propagation of action potentials (APs) from the soma to the presynaptic terminals is important. However, the functional properties of interneuron axons remain elusive. Here, we examined interneuron axons by confocally targeted subcellular patch-clamp recording in rat hippocampal slices. APs were initiated in the proximal axon ~20 μm from the soma, and propagated to the distal axon with high reliability and speed. Subcellular mapping revealed a stepwise increase of Na + conductance density from the soma to the proximal axon, followed by a further gradual increase in the distal axon. Active cable modeling and experiments with partial channel block indicated that low axonal Na + conductance density was sufficient for reliability, but high Na + density was necessary for both speed of propagation and fast-spiking AP phenotype. Our results suggest that a supercritical density of Na + channels compensates for the morphological properties of interneuron axons (small segmental diameter, extensive branching, and high bouton density), ensuring fast AP propagation and high-frequency repetitive firing.

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          Most cited references54

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          Synaptic mechanisms of synchronized gamma oscillations in inhibitory interneuron networks.

          Gamma frequency oscillations are thought to provide a temporal structure for information processing in the brain. They contribute to cognitive functions, such as memory formation and sensory processing, and are disturbed in some psychiatric disorders. Fast-spiking, parvalbumin-expressing, soma-inhibiting interneurons have a key role in the generation of these oscillations. Experimental analysis in the hippocampus and the neocortex reveals that synapses among these interneurons are highly specialized. Computational analysis further suggests that synaptic specialization turns interneuron networks into robust gamma frequency oscillators.
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            Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model.

            Fast neuronal oscillations (gamma, 20-80 Hz) have been observed in the neocortex and hippocampus during behavioral arousal. Using computer simulations, we investigated the hypothesis that such rhythmic activity can emerge in a random network of interconnected GABAergic fast-spiking interneurons. Specific conditions for the population synchronization, on properties of single cells and the circuit, were identified. These include the following: (1) that the amplitude of spike afterhyperpolarization be above the GABAA synaptic reversal potential; (2) that the ratio between the synaptic decay time constant and the oscillation period be sufficiently large; (3) that the effects of heterogeneities be modest because of a steep frequency-current relationship of fast-spiking neurons. Furthermore, using a population coherence measure, based on coincident firings of neural pairs, it is demonstrated that large-scale network synchronization requires a critical (minimal) average number of synaptic contacts per cell, which is not sensitive to the network size. By changing the GABAA synaptic maximal conductance, synaptic decay time constant, or the mean external excitatory drive to the network, the neuronal firing frequencies were gradually and monotonically varied. By contrast, the network synchronization was found to be high only within a frequency band coinciding with the gamma (20-80 Hz) range. We conclude that the GABAA synaptic transmission provides a suitable mechanism for synchronized gamma oscillations in a sparsely connected network of fast-spiking interneurons. In turn, the interneuronal network can presumably maintain subthreshold oscillations in principal cell populations and serve to synchronize discharges of spatially distributed neurons.
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              Enforcement of temporal fidelity in pyramidal cells by somatic feed-forward inhibition.

              The temporal resolution of neuronal integration depends on the time window within which excitatory inputs summate to reach the threshold for spike generation. Here, we show that in rat hippocampal pyramidal cells this window is very narrow (less than 2 milliseconds). This narrowness results from the short delay with which disynaptic feed-forward inhibition follows monosynaptic excitation. Simultaneous somatic and dendritic recordings indicate that feed-forward inhibition is much stronger in the soma than in the dendrites, resulting in a broader integration window in the latter compartment. Thus, the subcellular partitioning of feed-forward inhibition enforces precise coincidence detection in the soma, while allowing dendrites to sum incoming activity over broader time windows.
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                Author and article information

                Journal
                9809671
                21092
                Nat Neurosci
                Nat. Neurosci.
                Nature neuroscience
                1097-6256
                1546-1726
                11 December 2014
                23 March 2014
                May 2014
                07 January 2015
                : 17
                : 5
                : 686-693
                Affiliations
                IST Austria (Institute of Science and Technology Austria), Am Campus 1, A-3400 Klosterneuburg, Austria
                Author notes
                Corresponding authors: Dr. Peter Jonas, Dr. Hua Hu, IST Austria, Am Campus 1, A-3400 Klosterneuburg, Austria, Phone: ++43-2243-9000-3701, Fax: ++43-2243-9000-2007, peter.jonas@ 123456ist.ac.at , hua.hu@ 123456ist.ac.at

                AUTHOR CONTRIBUTIONS

                H.H. performed experiments and analyzed the data, P.J. performed modeling and wrote the paper. Both authors jointly revised the paper.

                Article
                EMS57103
                10.1038/nn.3678
                4286295
                24657965
                f189bcba-7c23-4d67-a901-7e6cda57b299
                History
                Categories
                Article

                Neurosciences
                Neurosciences

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