title: A non-linear regression analysis program for describing electrophysiological data with multiple functions using Microsoft Excel.
abstract: The objective of this present study was to demonstrate a method for fitting complex electrophysiological data with multiple functions using the SOLVER add-in of the ubiquitous spreadsheet Microsoft Excel. SOLVER minimizes the difference between the sum of the squares of the data to be fit and the function(s) describing the data using an iterative generalized reduced gradient method. While it is a straightforward procedure to fit data with linear functions, and we have previously demonstrated a method of non-linear regression analysis of experimental data based upon a single function, it is more complex to fit data with multiple functions, usually requiring specialized expensive computer software. In this paper we describe an easily understood program for fitting experimentally acquired data, in this case the stimulus-evoked compound action potential from the mouse optic nerve, with multiple Gaussian functions. The program is flexible and can be applied to describe data with a wide variety of user-input functions.
authors.affiliation: Department of Neurology, Box 356465, University of Washington School of Medicine, 1959 Pacific St. N.E., Seattle, WA 98195, USA. ambrown@nottingham.ac.uk
authors.forename: Angus M
authors.initials: AM
authors.lastname: Brown
mesh_terms: D001330:Electronic Data Processing / Q000379:methods*; D004594:Electrophysiology / Q000706:statistics & numerical data*; D012044:Regression Analysis; D012984:Software; D006113:United Kingdom