12 research outputs found
Type-specific dendritic integration in mouse retinal ganglion cells
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
Dendritic Spikes Expand the Range of Well Tolerated Population Noise Structures
Simulation of neuronal processing of noise-corrupted inputsNEURON simulation (http://neuron.yale.edu/neuron
Processing of noisy population activity by dendritic spikes
Simulation of neuronal processing of noise-corrupted inputs NEURON simulation (http://neuron.yale.edu/neuron
Dendritic Spikes Expand the Range of Well Tolerated Population Noise Structures
Simulation of neuronal processing of noise-corrupted inputsNEURON simulation (http://neuron.yale.edu/neuron)THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV