Computational model
LGMD impedance (Dewell & Gabbiani 2019)
Richard Dewell
"How neurons filter and integrate their complex patterns of synaptic inputs is central to their role in neural information processing . Synaptic filtering and integration are shaped by the frequency-dependent neuronal membrane impedance. 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. This neuron, the lobula giant movement detector (LGMD), exhibits consistent impedance properties across frequencies and membrane potentials. 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 a model based on the LGMD's branching morphology increased the gain and decreased the delay associated with the mapping of synaptic input currents to membrane potential. More generally, this was true for a wide range of model neuron morphologies, including those of neocortical pyramidal neurons and cerebellar Purkinje cells. These findings show the unexpected role played by two widespread active conductances and by dendritic morphology in shaping synaptic integration."
  • Locust Lobula Giant Movement Detector (LGMD) neuron Show Other
  • Dewell, Richard Burkett [dewell at] Show Other
inductive leak
Other categories referring to LGMD impedance (Dewell & Gabbiani 2019)
Revisions: 14
Last Time: 8/15/2019 4:03:40 PM
Reviewer: Tom Morse - MoldelDB admin
Owner: Tom Morse - MoldelDB admin