We are interested in understanding how the three pounds (~ 1.5kg) of meat we have in our skulls allow us to infer the state of the environment (i.e., perception), and enable adaptive and flexible behaviors (i.e., cognition and action). We believe that a starting point to answering the how question is usually to first observe behavior, and answering the why question (a normative approach).

We believe that to understand brain function, we ought to study fundamental, domain-general computations. Indeed, our work is most impactful when asking a specific question, but the answer applies throughout domains. We also realize that the brain operates in closed-loop with our bodies and the environment, and thus we ought to study the brain in this context.

We are interested in understanding how we map observations to latent (i.e., hidden) variables. In perception and the field of multi-sensory integration, we may call this causal inference. In cognition, this is related to the concept of cognitive maps, or contextual inference. We are also interested in probabilistic coding, predictive and efficient coding, perceptual decision-making, the updating of Bayesian priors (i.e., expectations), and the coding of the space immediately adjacent to and surrounding our bodies (i.e., our peri-personal space).

We are interested in applying a neuroscience perspective to the study of psychiatric and neurodevelopmental conditions. A large focus of our work has been on Autism Spectrum Disorders (ASD), but have also worked in Schizophrenia and Disorders of Consciousness (DOC). Given our focus on “perception as inference”, we are interested in Psychosis and hallucinations.

All methods have their advantages and disadvantages. Thus, we attempt to use as many of the techniques available to cognitive and systems neuroscience today. The lab has expertise in human psychophysics, virtual reality, eye-tracking, and electrophysiology (EEG/iEEG/ECOG), both in neurotypical and atypical populations. We also conduct behavioral studies, large-scale neurophysiology (i.e., single neurons)and optogenetics in animal models. To bridge between these techniques, we employ tools (and sometimes even create new ones!) from computational neuroscience and psychiatry, such as neural networks and Bayesian modeling. We are always interested in expanding our toolbox, so please reach out if you’d like to collaborate and/or join the lab to bring a new technique to the table!