title: Inferring presynaptic population spiking from single-trial membrane potential recordings.
abstract: BACKGROUND
  The time-varying membrane potential of a cortical neuron contains important information about the network activity. Extracting this information requires separating excitatory and inhibitory synaptic inputs from single-trial membrane potential recordings without averaging across trials.
  
  
  METHODS
  We propose a method to extract the time course of excitatory and inhibitory synaptic inputs to a neuron from a single-trial membrane potential recording. The method takes advantage of the differences in the time constants and the reversal potentials of the excitatory and inhibitory synaptic currents, which allows the untangling of the two conductance types.
  
  
  RESULTS
  We evaluate the applicability of the method on a leaky integrate-and-fire model neuron and find high quality of estimation of excitatory synaptic conductance changes and presynaptic population spikes. Application of the method to a real cortical neuron with known synaptic inputs in a brain slice returns high-quality estimation of the time course of the excitatory synaptic conductance. Application of the method to membrane potential recordings from a cortical pyramidal neuron of an intact brain reveals complex network activity.
  
  
  METHODS
  Existing methods are based on repeated trials and thus are limited to estimating the statistical features of synaptic conductance changes, or, when based on single trials, are limited to special cases, have low temporal resolution, or are impractically complicated.
  
  
  CONCLUSIONS
  We propose and test an efficient method for estimating the full time course of excitatory and inhibitory synaptic conductances from single-trial membrane potential recordings. The method is sufficiently simple to ensure widespread use in neuroscience.
authors.affiliation: Department of Physics, Campus Box 1105, Washington University, Saint Louis, MO 63130-4899, USA. Electronic address: tanselbaranyasar@gmail.com.
authors.forename: Tansel Baran
authors.initials: TB
authors.lastname: Yaşar
authors.affiliation: Department of Physics, Campus Box 1105, Washington University, Saint Louis, MO 63130-4899, USA. Electronic address: nathanielcwright@wustl.edu.
authors.forename: Nathaniel Caleb
authors.initials: NC
authors.lastname: Wright
authors.affiliation: Department of Physics, Campus Box 1105, Washington University, Saint Louis, MO 63130-4899, USA. Electronic address: rw@physics.wustl.edu.
authors.forename: Ralf
authors.initials: R
authors.lastname: Wessel
mesh_terms: D000465:Algorithms; D000818:Animals; D002540:Cerebral Cortex / Q000166:cytology / Q000502:physiology*; D003198:Computer Simulation; D051379:Mice; D008959:Models, Neurological; D017966:Pyramidal Cells / Q000502:physiology*; D013569:Synapses / Q000502:physiology*; D055366:Synaptic Potentials / Q000502:physiology*; D013997:Time Factors; D014426:Turtles
keywords: Excitation; Fluctuations; Inhibition; Membrane potential; Network activity; Synaptic inputs