Subthreshold Dendritic Signal Processing and Coincidence Detection in Dentate Gyrus Granule Cells

Schmidt-Hieber, Christoph; Jónás, Péter; Bischofberger, Josef

doi:10.1523/jneurosci.1787-07.2007

Cited by 178 publications

(267 citation statements)

References 60 publications

(122 reference statements)

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“…Our results indicate that the specific cable parameters of BCs differ from those of principal neurons, especially regarding a low and nonuniform R m (27,28,30,32). How do these unique cable properties affect the signaling characteristics of BCs?…”

Section: Resultsmentioning

confidence: 84%

“…1 A-C). A major advantage of this configuration is that the fast components of charge redistribution can be accurately measured at the voltage recording electrode, as required for reliable estimation of R i (32).…”

Section: Resultsmentioning

confidence: 99%

“…Furthermore, the axonal arborization was not included in any of these studies, and a possible nonuniformity of R m was not considered (27, 28). However, complete passive cable models will be necessary for understanding the mechanisms of both dendritic integration and action potential initiation in GABAergic interneurons (13,29).To address these questions, we developed detailed passive cable models (27,28,(30)(31)(32) of BCs in the dentate gyrus. To obtain accurate measurement of R i and somatodendritic nonuniformity of R m , both dual somatic and somatodendritic recordings were performed.…”

mentioning

confidence: 99%

“…To address these questions, we developed detailed passive cable models (27,28,(30)(31)(32) of BCs in the dentate gyrus. To obtain accurate measurement of R i and somatodendritic nonuniformity of R m , both dual somatic and somatodendritic recordings were performed.…”

mentioning

confidence: 99%

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Distinct nonuniform cable properties optimize rapid and efficient activation of fast-spiking GABAergic interneurons

Nörenberg

Vida

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

122

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Fast-spiking, parvalbumin-expressing basket cells (BCs) play a key role in feedforward and feedback inhibition in the hippocampus. However, the dendritic mechanisms underlying rapid interneuron recruitment have remained unclear. To quantitatively address this question, we developed detailed passive cable models of BCs in the dentate gyrus based on dual somatic or somatodendritic recordings and complete morphologic reconstructions. Both specific membrane capacitance and axial resistivity were comparable to those of pyramidal neurons, but the average somatodendritic specific membrane resistance (R m ) was substantially lower in BCs. Furthermore, R m was markedly nonuniform, being lowest in soma and proximal dendrites, intermediate in distal dendrites, and highest in the axon. Thus, the somatodendritic gradient of R m was the reverse of that in pyramidal neurons. Further computational analysis revealed that these unique cable properties accelerate the time course of synaptic potentials at the soma in response to fast inputs, while boosting the efficacy of slow distal inputs. These properties will facilitate both rapid phasic and efficient tonic activation of BCs in hippocampal microcircuits.cable models | dendrites | hippocampus | basket cell F ast-spiking, parvalbumin-expressing basket cells (BCs) play an important role in feedforward and feedback inhibition, providing rapid control over the frequency and timing of action potential initiation in principal neuron ensembles (1-6). Although inhibition comprises several steps, including activation of excitatory input synapses on BCs, dendritic integration of excitatory postsynaptic potentials (EPSPs), action potential initiation and propagation, and GABA release from output synapses, the kinetics of disynaptic inhibition can be very rapid, with ≈2 ms total onset time at physiologic temperature (3, 7). Several synaptic specializations contribute to the remarkable speed of feedforward and feedback inhibition. At the glutamatergic input synapses of BCs, the fast clearance of transmitter from the synaptic cleft and the expression of molecularly specialized L-α-amino-3-hydroxy-5-methyl-4-isoxazolepropionate receptors (AMPARs) contribute to rapid signaling (8, 9). At the GABAergic output synapses of BCs, the use of rapidly gated P/Qtype Ca 2+ channels and the tight coupling of these channels to the Ca 2+ sensors of exocytosis may serve a similar function (10, 11). Thus, functional specializations at both input and output synapses maximize the speed of BC-mediated disynaptic inhibition.Synaptic location, dendritic structure, and electrical cable properties will also contribute to rapid signaling in GABAergic interneurons. For example, the proximal location of excitatory synapses may promote rapid activation of BCs. The significance of this factor, however, is unclear, because many glutamatergic synapses terminate on distal dendrites of BCs (12). Furthermore, rapid signaling could be promoted by the extensive axon, which may accelerate the somatic EPSP decay time course by ge...

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Section: Resultsmentioning

confidence: 84%

Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Distinct nonuniform cable properties optimize rapid and efficient activation of fast-spiking GABAergic interneurons

Nörenberg

Vida

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

122

166

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“…Importantly, although the GC has historically been among the most heavily studied neurons in the brain, the discovery that GCs are actually a mixed population of immature and mature neurons occurred after the DG received much of this attention. For instance, although there have been several studies of dendritic integration of individual GCs (Carnevale et al 1997;Aradi and Holmes 1999;Schmidt-Hieber et al 2007), there have not been equivalent studies of individual young neurons using computational single-neuron models with high levels of biological fidelity. This is in spite of considerable anatomical and physiological characterization of developing neurons showing that they are unique at different ages (Esposito et al 2005;Zhao et al 2006;Marin-Burgin et al 2012).…”

Section: Granule Cells Young and Oldmentioning

confidence: 99%

Computational Modeling of Adult Neurogenesis

Aimone¹

2016

Cold Spring Harb Perspect Biol

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The restriction of adult neurogenesis to only a handful of regions of the brain is suggestive of some shared requirement for this dramatic form of structural plasticity. However, a common driver across neurogenic regions has not yet been identified. Computational studies have been invaluable in providing insight into the functional role of new neurons; however, researchers have typically focused on specific scales ranging from abstract neural networks to specific neural systems, most commonly the dentate gyrus area of the hippocampus. These studies have yielded a number of diverse potential functions for new neurons, ranging from an impact on pattern separation to the incorporation of time into episodic memories to enabling the forgetting of old information. This review will summarize these past computational efforts and discuss whether these proposed theoretical functions can be unified into a common rationale for why neurogenesis is required in these unique neural circuits.T he importance of neurogenesis will be ultimately tied to its impact on the computational function of the overall circuit within which it resides. Notably, the two mammalian regions where neurogenesis is typically studied, the olfactory bulb (OB) and the dentate gyrus (DG) region of the hippocampus, have considerably different functions. The OB is a primary sensory region, essentially the equivalent of the processing layers of the retina, providing an initial transformation of raw olfactory inputs to the brain. In contrast, the hippocampus is one of the deepest structures in the brain, residing many layers away from sensory inputs and vital for episodic memory formation.Interestingly, as noted throughout this collection, although OB and DG neurogenesis share some similarities, there are sufficient differences to make it difficult to generalize across the two systems, not the least of which is the recent observation that humans likely lack OB neurogenesis. This is somewhat supported by a comparative perspective. As with mammals, neurogenesis in birds is limited to several structures with certain species, including neurogenesis in well-studied birdsong regions. Vertebrates with arguably less advanced nervous systems, such as reptiles and fish, have more widespread neurogenesis, suggesting that broad evolutionary pressures to attenuate neurogenesis in other areas of the brain led to the relative isolation of the OB and hippocampus as opposed to an evolutionary gain-of-function process common to the OB and DG. This subtle distinction has implications on how far one can hope for a shared function between these areas and, for this reason, it is not surprising that most computational studies investigating

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