Parvalbumin interneuron dendrites enhance gamma oscillations

Dendrites are essential determinants of the input-output relationship of single neurons, but their role in network computations is not well understood. Here, we use a combination of dendritic patch-clamp recordings and in silico modeling to determine how dendrites of parvalbumin (PV)-expressing bask...

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Veröffentlicht in:Cell reports (Cambridge) 2022-06, Vol.39 (11), p.110948-110948, Article 110948
Hauptverfasser: Kriener, Birgit, Hu, Hua, Vervaeke, Koen
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Sprache:eng
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Zusammenfassung:Dendrites are essential determinants of the input-output relationship of single neurons, but their role in network computations is not well understood. Here, we use a combination of dendritic patch-clamp recordings and in silico modeling to determine how dendrites of parvalbumin (PV)-expressing basket cells contribute to network oscillations in the gamma frequency band. Simultaneous soma-dendrite recordings from PV basket cells in the dentate gyrus reveal that the slope, or gain, of the dendritic input-output relationship is exceptionally low, thereby reducing the cell’s sensitivity to changes in its input. By simulating gamma oscillations in detailed network models, we demonstrate that the low gain is key to increase spike synchrony in PV basket cell assemblies when cells are driven by spatially and temporally heterogeneous synaptic inputs. These results highlight the role of inhibitory neuron dendrites in synchronized network oscillations. [Display omitted] •The gain of the input-output relationship of PV+ basket cell dendrites is very low•The low gain enhances spike synchrony in the gamma (40–110 Hz) frequency range•In highly heterogeneous networks, the low gain is key to preserve gamma oscillations By performing in vitro patch-clamp recordings from parvalbumin-expressing basket cell dendrites, Kriener et al. report that the gain of the dendritic input-output relationship is exceptionally low. Simulations indicate that this dendritic feature is key to enhancing the coherence of network activity in the gamma frequency range.
ISSN:2211-1247
2211-1247
DOI:10.1016/j.celrep.2022.110948