title: Systems-based analysis of dendritic nonlinearities reveals temporal feature extraction in mouse L5 cortical neurons.
abstract: What do dendritic nonlinearities tell a neuron about signals injected into the dendrite? Linear and nonlinear dendritic components affect how time-varying inputs are transformed into action potentials (APs), but the relative contribution of each component is unclear. We developed a novel systems-identification approach to isolate the nonlinear response of layer 5 pyramidal neuron dendrites in mouse prefrontal cortex in response to dendritic current injections. We then quantified the nonlinear component and its effect on the soma, using functional models composed of linear filters and static nonlinearities. Both noise and waveform current injections revealed linear and nonlinear components in the dendritic response. The nonlinear component consisted of fast Na+spikes that varied in amplitude 10-fold in a single neuron. A functional model reproduced the timing and amplitude of the dendritic spikes and revealed that they were selective to a preferred input dynamic (~4.5 ms rise time). The selectivity of the dendritic spikes became wider in the presence of additive noise, which was also predicted by the functional model. A second functional model revealed that the dendritic spikes were weakly boosted before being linearly integrated at the soma. For both our noise and waveform dendritic input, somatic APs were dependent on the somatic integration of the stimulus, followed a subset of large dendritic spikes, and were selective to the same input dynamics preferred by the dendrites. Our results suggest that the amplitude of fast dendritic spikes conveys information about high-frequency features in the dendritic input, which is then combined with low-frequency somatic integration.NEW & NOTEWORTHYThe nonlinear response of layer 5 mouse pyramidal dendrites was isolated with a novel systems-based approach. In response to dendritic current injections, the nonlinear component contained mostly fast, variable-amplitude, Na+spikes. A functional model accounted for the timing and amplitude of the dendritic spikes and revealed that dendritic spikes are selective to a preferred input dynamic, which was verified experimentally. Thus, fast dendritic nonlinearities behave as high-frequency feature detectors that influence somatic action potentials.
authors.affiliation: Center for Learning and Memory, Department of Neuroscience, The University of Texas at Austin, Austin, Texas; and.
authors.forename: Brian E
authors.initials: BE
authors.lastname: Kalmbach
authors.affiliation: Center for Learning and Memory, Department of Neuroscience, The University of Texas at Austin, Austin, Texas; and.
authors.forename: Richard
authors.initials: R
authors.lastname: Gray
authors.affiliation: Center for Learning and Memory, Department of Neuroscience, The University of Texas at Austin, Austin, Texas; and.
authors.forename: Daniel
authors.initials: D
authors.lastname: Johnston
authors.affiliation: Centre for Mathematics in Bioscience and Medicine, Department of Physiology, McGill University, Montreal, Quebec, Canada erik.cook@mcgill.ca.
authors.forename: Erik P
authors.identifier: 0000-0002-6516-1927
authors.initials: EP
authors.lastname: Cook
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000818:Animals; D002414:Cations, Monovalent / Q000378:metabolism; D003712:Dendrites / Q000502:physiology*; D004558:Electric Stimulation; D016014:Linear Models; D008297:Male; D008810:Mice, Inbred C57BL; D008959:Models, Neurological; D017711:Nonlinear Dynamics; D018408:Patch-Clamp Techniques; D017397:Prefrontal Cortex / Q000502:physiology*; D017966:Pyramidal Cells / Q000502:physiology*; D012964:Sodium / Q000378:metabolism; D013997:Time Factors; D046509:Tissue Culture Techniques
chemical_list: D002414:Cations, Monovalent; D012964:Sodium
keywords: computational model; dendrite; electrophysiology; mouse; pyramidal neuron