RT Journal Article
SR Electronic
T1 Type-specific dendritic integration in mouse retinal ganglion cells
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 753335
DO 10.1101/753335
A1 Yanli Ran
A1 Ziwei Huang
A1 Tom Baden
A1 Harald Baayen
A1 Philipp Berens
A1 Katrin Franke
A1 Thomas Euler
YR 2019
UL http://biorxiv.org/content/early/2019/09/03/753335.abstract
AB Neural computation relies on the integration of synaptic inputs across a neuron’s dendritic arbour. However, the fundamental rules that govern dendritic integration are far from understood. In particular, it is still unclear how cell type-specific differences in dendritic integration arise from general features of neural morphology and membrane properties. Here, retinal ganglion cells (RGCs), which relay the visual system’s first computations to the brain, represent an exquisite model. They are functionally and morphologically diverse yet defined, and they allow studying dendritic integration in a functionally relevant context. Here, we show how four morphologically distinct types of mouse RGC with shared excitatory synaptic input (transient Off alpha, transient Off mini, sustained Off, and F-miniOff) exhibit distinct dendritic integration rules. Using two-photon imaging of dendritic calcium signals and biophysical modelling, we demonstrate that these RGC types strongly differ in their spatio-temporal dendritic integration: In transient Off alpha cells, dendritic receptive fields displayed little spatial overlap, indicative of a dendritic arbour that is partitioned in largely isolated regions. In contrast, dendritic receptive fields in the other three RGCs overlapped greatly and were offset to the soma, suggesting strong synchronization of dendritic signals likely due to backpropagation of somatic signals. Also temporal correlation of dendritic signals varied extensively among these types, with transient Off mini cells displaying the highest correlation across their dendritic arbour. Modelling suggests that morphology alone cannot explain these differences in dendritic integration, but instead specific combinations of dendritic morphology and ion channel densities are required. Together, our results reveal how neurons exhibit distinct dendritic integration profiles tuned towards their type-specific computations in their circuits, with the interplay between morphology and ion channel complement as a key contributor.