Amsterdam, North Holland, Netherlands
I build computer models (computer simulations based on math) to help us understand how our brains work and why we behave the way we do. For example, I study decision-making by analyzing data from experiments where people play simple games while wearing sensors that record their brain activity (using electroencephalography; EEG). I use modern statistical methods to compare computer models to real data and work on improving these techniques. I work as an Associate Professor (UD1) in the Psychological Methods group at the University of Amsterdam in The Netherlands. I lead the Mathematical Cognitive Neuroscience Laboratory, and I am a member of the Amsterdam Mathematical Psychology Laboratory. I teach bachelor, master's, and PhD courses on statistics, programming, and model-based cognitive neuroscience. I am also a loving husband & father, and an enthusiastic rock climber. My expertise is in Bayesian statistical analysis, cognitive neuroscience, experimental design, scientific communication, and high-level programming (Python, R, and MATLAB). More academia-related information is available here: https://www.michaeldnunez.com
I develop my own research program on neurocognitive modeling, decision-making and other topics. I also teach graduate and undergraduate courses, as well as mentor master's students, PhDs, and Postdocs. I lead the Mathematical Cognitive Neuroscience Laboratory, and I am a member of the Amsterdam Mathematical Psychology Laboratory. I am a part of the Psychological Methods group within the Department of Psychology. *The title "Associate Professor" is the University of Amsterdam's recommended translation for Universitair docent 1 (UD1). However, the translation could also easily be “Senior Lecturer” or “Tenured Assistant Professor”.
I study neurocognitive models of human cognition with joint fMRI/EEG data and human behavior.
I studied decision making from recordings of neurons, intracranial data, and behavioral data in NHP.
I classified and statistically modeled markers of epilepsy in human patients using electric potentials recorded directly from the cortex.
I sought to estimate unidentified cognitive models of human decision making with experimental behavior and scalp-recorded EEG.
Primary Advisor: Ramesh Srinivasan Secondary Advisor: Joachim Vandekerckhove I tested the veracity of combined electrocortical and cognitive models of human decision making. This was typically performed in a hierarchical Bayesian statistical framework with statistical models of EEG and human behavior.
My research was on auditory EEG Event Related Potentials using Independent Component Analysis (ICA) to advance understanding of normal cognitive aging. Advisor: Ed Golob