As of June 21, 2021 I have left my job as a biostatistician at Virginia Tech and joined UC Davis Computational Cognitive Neuroscience lab lab as a postdoc! I cannot express how exciting it has been to discover this kind of research but to also land an opportunity to train and do it myself. The lab has a variety of ongoing research involving biologically-constrained spiking and rate coded neural networks in the Leabra framework (github). There is an excellent textbook written and published for free online by the PI, Randy O’Reilly.
The research brings together the cellular, anatomical, statistical (information-processing), and behavioral aspects of psychology into unified theoretical models. The models simulate the tasks normally performed by human or other mammal subjects in behavioral experiments. Having worked in such labs that study various molecular and genetic aspects of schizophrenia and drug addiction, it is like I have been simply observing arrangements of chess pieces on boards for many years. Reading the CCN textbook is like finally being told the rules of the game. Specifically, the rules are the statistical functions of the neural population that lead to perceptions and actions.
So far there has been some interest in Bayesian data analysis and hierarchical models, so I will continue building my library of example models and tutorials.