Electrophysiological Data Analysis

OctavioRuiz - 11 Nov 2004

We record action potentials ("spikes") from awake animals.  Each spike signals the firing of a neuron.
The firing obeys to complicated non-stationary non-linear dynamic probably deterministic processes 
within the neuron, that we cannot measure. The rate of spikes change during certain experimental 
manipulations, and the change exhibits variability.

First problem (difficult): Estimate physiologically relevant parameters of the underlying process within 
the cell from the spike data.

Second problem (easier): Assess the effect of the experimental manipulations on the activity of the 
cell during different conditions, as measured in terms of the cell spike rate.  The conditions are:
  A:  No stimulus --> Basal activity
      Stimulus A  --> Response to A
  B:  No stimulus --> Basal activity
      Stimulus B  --> Response to B
Each condition is repeated several times in a block design (e.g. A: 20 trials;  B: 20 trials;  A: other 
20 trials or so, B: ...).  The basal activity, and the response to the stimuli may change along time, 
sometimes monotonically, sometimes exhibiting a convex shape.  The experiment is repeated for different 
cells from the same animal (never the same cell), from two or three animals.

The problem will then be (1) found the relative effect of condition A and condition B on the population 
of cells, regardless of non-stationarities, and intertrial, cell-to-cell, and animal-to-animal 
variability, and (2) asses if the sample contains atypical response cells, i.e. cells for which
Resp(A) is significantly larger / smaller than Resp(B), with a given level of confidence.

Any suggestions?

DavidAirey 12 Nov 2004: You bring to the table a fundamental analysis paradigm in neurophysiology that I had a running argument about with two editors in chief of the Journal of Neurophysiology, to get them to defend appropriate and inappropriate analysis of subsampling from intact organisms exposed to multiple treatment conditions. Or at least publish guidelines. They have only just instituted some guidelines for the Journal, but ignored the questions raised by you and I. The problem is that with subsampling organisms in the way described, results in two sources of systematic error that lead to data clustering (TIME and ANIMAL) such that failure to deal with this complex error structure will have consequences on your ability to make correct inferences. What really needs to be done in this field is to assess the intraclass correlation for in vivo neurophysiological data, to assess the extent to which the animal correlations are weak enough to warrant making inferences on the population of neurons from the population of animals by ignoring variation at the level of the animal or having a very sparse (N = 3) level to the data set. My personal opinion is that there is something fundamental that has gone unaddressed in the field of non-human primate neurophysiology work. An early opinion of mine, which has changed a little since posted, can be read at http://homepage.mac.com/david.airey/vita/pooling.htm. I am trying to rework this piece for the Journal of Neuroscience Methods and would be happy to collaborate. I personally think poking the same exact 10 neurons (they are numbered you know) in the worm C. elegans from different genetic strains would be informative, in that a good ICC could be estimated. I invite the Department of Biostatistics to weigh in on this question with their expertise. The field of neurophysiology is very sophisticated for within-animal analysis.

FrankHarrell: Yu-Chieh Yang, Anna Liu, and Yuedong Wang have done some nice work on pulsatile hormone release that may possibly relate. See http://www.google.com/search?hl=en&lr=&ie=ISO-8859-1&q=statistics+pulsatile&btnG=Search and their R software. Dan Keenan at the University of Virginia has also done some nice work, with Johannes Veldhuis.

DavidAirey 14 Nov 2004: Seems the thing to do is to set up a formal interaction with a statistician from Biostatistics. I'm sure you will eventually get answers that satisfy your requirements. My own opinions (above) are not informed by expertise in your field, but are motivated by the need to critically evaluate published results. I just looked up the Keenan and Veldhuis work on Entrez. They typically have many more patients than a non-human primate electrophysiology experiment can hope to have. I've also skimmed the paper of Wang's (2004). In this paper they discuss data from 72 patients. Here are some other interesting articles, and another typical paper in the Journal of Neurophysiology with 2 monkeys.

1. Woolrich MW, Behrens TE, Beckmann CF, Jenkinson M, Smith SM.  Multilevel linear modelling for FMRI group analysis using Bayesian inference.  Neuroimage. 2004 Apr;21(4):1732-47. doi: 10.1016/j.neuroimage.2003.12.023.
2. Handwerker DA, Ollinger JM, D'Esposito M.  Variation of BOLD hemodynamic responses across subjects and brain regions and their effects on statistical analyses.  Neuroimage. 2004 Apr;21(4):1639-51. doi: 10.1016/j.neuroimage.2003.11.029.
3. Bisley JW, Zaksas D, Droll JA, Pasternak T.  Activity of neurons in cortical area MT during a memory for motion task.  J Neurophysiol. 2004 Jan;91(1):286-300. doi: 10.1152/jn.00870.2003. Epub 2003 Oct 1.