| Literature DB >> 32355170 |
Yanli Ran1,2, Ziwei Huang1,2, Tom Baden1,3, Timm Schubert1,2, Harald Baayen4, Philipp Berens1,2,5,6, Katrin Franke1,2,5, Thomas Euler7,8,9.
Abstract
Neural computation relies on the integration of synaptic inputs across a neuron's dendritic arbour. However, it is far from understood how different cell types tune this process to establish cell-type specific computations. Here, using two-photon imaging of dendritic Ca2+ signals, electrical recordings of somatic voltage and biophysical modelling, we demonstrate that four morphologically distinct types of mouse retinal ganglion cells with overlapping excitatory synaptic input (transient Off alpha, transient Off mini, sustained Off, and F-mini Off) exhibit type-specific dendritic integration profiles: in contrast to the other types, dendrites of transient Off alpha cells were spatially independent, with little receptive field overlap. The temporal correlation of dendritic signals varied also extensively, with the highest and lowest correlation in transient Off mini and transient Off alpha cells, respectively. We show that differences between cell types can likely be explained by differences in backpropagation efficiency, arising from the specific combinations of dendritic morphology and ion channel densities.Entities:
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Year: 2020 PMID: 32355170 PMCID: PMC7193577 DOI: 10.1038/s41467-020-15867-9
Source DB: PubMed Journal: Nat Commun ISSN: 2041-1723 Impact factor: 14.919