A tutorial on fitting joint models of M/EEG and behavior to understand cognition


We present motivation and practical steps necessary to find parameter estimates of joint models of behavior and neural electrophysiological data. This tutorial is written for researchers wishing to build joint models of human behavior and scalp and intracranial electroencephalographic (EEG) or magnetoencephalographic (MEG) data, and more specifically those researchers who seek to understand human cognition. Although these techniques could easily be applied to animal models. Joint modeling of M/EEG and behavior requires some knowledge of existing computational and cognitive theories, M/EEG artifact correction, M/EEG analysis techniques, cognitive modeling, and programming for statistical modeling implementation. This paper seeks to give an introduction to these techniques as they apply to estimating parameters from neurocognitive models of M/EEG and human behavior, and to evaluate model results and compare models. Due to our research and knowledge on the subject matter, our examples in this paper will focus on testing specific hypotheses in human decision-making theory. However most of the motivation and discussion of this paper applies across many modeling procedures and applications.


    title   = {{A} tutorial on fitting joint models of {M}/{E}{E}{G} and behavior to understand cognition},
    author  = {Nunez, Michael and Vandekerckhove, Joachim and Srinivasan, Ramesh},
    year    = {preprint},
    journal = {PsyArxiv}