title: Dynamic spike threshold and nonlinear dendritic computation for coincidence detection in neuromorphic circuits.
abstract: We present an electronic cortical neuron incorporating dynamic spike threshold and active dendritic properties. The circuit is simulated using a carbon nanotube field-effect transistor SPICE model. We demonstrate that our neuron has lower spike threshold for coincident synaptic inputs; however when the synaptic inputs are not in synchrony, it requires larger depolarization to evoke the neuron to fire. We also demonstrate that a dendritic spike is key to precisely-timed input-output transformation, produces reliable firing and results in more resilience to input jitter within an individual neuron.
authors.forename: Chih-Chieh
authors.initials: CC
authors.lastname: Hsu
authors.forename: Alice C
authors.initials: AC
authors.lastname: Parker
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D003712:Dendrites / Q000502:physiology*; D008959:Models, Neurological; D037742:Nanotubes, Carbon
chemical_list: D037742:Nanotubes, Carbon