Brains processes information through the coordinated efforts of billions of individual neurons, each encoding a small part of the overall information stream. Central to this is how neurons integrate and transform complex patterns of synaptic inputs. The neuronal membrane impedance sets the gain and timing for synaptic integration, determining a neuron's ability to discriminate between synaptic input patterns. Using single and dual dendritic recordings in vivo, pharmacology, and computational modeling, we characterized the membrane impedance of a collision detection neuron in the grasshopper, Schistocerca americana. We examined how the cellular properties of the lobula giant movement detector (LGMD) neuron are tuned to enable the discrimination of synaptic input patterns key to its role in collision detection. We found that two common active conductances gH and gM, mediated respectively by hyperpolarization-activated cyclic nucleotide gated (HCN) channels and by muscarine sensitive M-type K+ channels, promote broadband integration with high temporal precision over the LGMD's natural range of membrane potentials and synaptic input frequencies. Additionally, we found that the LGMD's branching morphology increased the gain and decreased delays associated with the mapping of synaptic input currents to membrane potential. We investigated whether other branching dendritic morphologies fulfill a similar function and found this to be true for a wide range of morphologies, including those of neocortical pyramidal neurons and cerebellar Purkinje cells. These findings further our understanding of the integration properties of individual neurons by showing the unexpected role played by two widespread active conductances and by dendritic morphology in shaping synaptic integration.
Calculation of capillary conductivity from pressure plate outflow data with non-negligible membrane impedance
