Ambiguity and nonidentifiability in the statistical analysis of neural codes.
Many experimental studies of neural coding rely on a statistical interpretation of the theoretical notion of the rate at which a neuron fires spikes. For example, neuroscientists often ask, "Does a population of neurons exhibit more synchronous spiking than one would expect from the covariability of their instantaneous firing rates?" For another example, "How much of a neuron's observed spiking variability is caused by the variability of its instantaneous firing rate, and how much is caused by spike timing variability?" However, a neuron's theoretical firing rate is not necessarily well-defined. Consequently, neuroscientific questions involving the theoretical firing rate do not have a meaning in isolation but can only be interpreted in light of additional statistical modeling choices. Ignoring this ambiguity can lead to inconsistent reasoning or wayward conclusions. We illustrate these issues with examples drawn from the neural-coding literature.
Department of Mathematics, The City College of New York, The City University of New York, New York, NY 10031; Departments of Biology and Psychology and CUNY Neuroscience Collaborative, The Graduate Center, The City University of New York, New York, NY 10016; and aamarasingham@ccny.cuny.edu stuart_geman@brown.edu.
Asohan
A
Amarasingham
Division of Applied Mathematics, Brown University, Providence, RI 02912 aamarasingham@ccny.cuny.edu stuart_geman@brown.edu.
Stuart
S
Geman
Division of Applied Mathematics, Brown University, Providence, RI 02912.
Matthew T
MT
Harrison
D000200:Action Potentials / Q000502:physiology; D003627:Data Interpretation, Statistical; D008959:Models, Neurological; D009446:Neurobiology / Q000379:methods*; D009435:Synaptic Transmission / Q000502:physiology*; D035501:Uncertainty
doubly stochastic; spike count variability; spike timing; temporal coding; trial-to-trial variability