<p>I am a former researcher in behavioral neuroscience and animal learning. My focus was on the psychopharmacology of addiction and motivation with an emphasis on how stress and early-life environment affect drug-related outcomes in adulthood. I dealt primarily with alcohol and amphetamines in animal models of addiction but have done clinical research with humans for marijuana and nicotine. I deal with a lot of count data, operant data, as well as western blots relatively frequently. I also do some Physiologically-Based Pharmacokinetic (PBPK) modeling and whole brain c-fos expression analyses as well.</p>
<p>In many academic institutions, it seems behavioral neuroscience has not made as swift of a move towards judicious use of statistics to look at direction AND magnitude, as opposed to just direction. Some labs have embraced newer methods that are more accurate and demonstrably better than the old methods in many cases. Others, unfortunately, do not. I often find myself asking: &quot;<em>How much more</em> behavior was present across time? What was the <em>functional relationship?</em> If we know the dose-response function looks a certain way and we have the timing information, <em>why not model this relationship</em> instead of using an ANOVA to analyze it so we can have a higher degree of accuracy?&quot; The lack of attempts to model these kinds of relationships functionally may be slowing down the progress of the discipline. Thus, I do my best to counteract this problem by publishing papers that use and explain some of these methods, and by teaching those who wish to learn.</p>
<p>Data speaks. If I don't know how to listen, I figure out how.</p>

Thomas Wukitsch