Statistical analysis of dose-response curves in extracellular electrophysiological studies of single neurons.
The application of polynomial regression and the analysis of covariance (ANCOVA) to dose-response (DR) data derived from extracellular electrophysiological studies of midbrain dopamine neurons and noradrenergic locus coeruleus neurons in vivo is demonstrated and discussed. Third-order polynomial regression was found to be a better method for estimating ED50 values than probit analysis of linear regression. ANCOVA provides a more powerful statistical method than ANOVA for detecting significant differences in ED50 values or DR curves when a confounding variable such as basal discharge rate is present. The methods of analysis presented herein should be useful in the analysis of other types of neurons in electrophysiological studies.
Pitts
D K
DK
Laboratory of Neurophysiology, Center for Cell Biology, Sinai Research Institute, Detroit, Michigan.
Kelland
M D
MD
Shen
R Y
RY
Freeman
A S
AS
Chiodo
L A
LA
D000200:Action Potentials / Q000187:drug effects; D000818:Animals; D001058:Apomorphine / Q000493:pharmacokinetics / Q000494:pharmacology*; D001921:Brain / Q000378:metabolism / Q000502:physiology*; D002395:Catecholamines / Q000502:physiology*; D004305:Dose-Response Relationship, Drug; D004594:Electrophysiology / Q000379:methods*; D008959:Models, Neurological; D051381:Rats; D012044:Regression Analysis
D002395:Catecholamines; D001058:Apomorphine