The diffusion model is a commonly used tool to infer latent psychological processes
underlying decision making, and to link them to neural mechanisms based on reaction times. …

Probabilistic programming allows for automatic Bayesian inference on user-defined
probabilistic models. Recent advances in Markov chain Monte Carlo (MCMC) sampling allow …

Planning and executing volitional actions in the face of conflicting habitual responses is a
critical aspect of human behavior. At the core of the interplay between these 2 control systems …

For many years the Diffusion Decision Model (DDM) has successfully accounted for behavioral
data from a wide range of domains. Important contributors to the DDM’s success are the …

It takes effort and time to tame one's impulses. Although medial prefrontal cortex (mPFC) is
broadly implicated in effortful control over behavior, the subthalamic nucleus (STN) is …

Can you predict what people are going to do just by watching them? This is certainly difficult:
it would require a clear mapping between observable indicators and unobservable …

PyMC is a probabilistic programming library for Python that provides tools for constructing
and fitting Bayesian models. It offers an intuitive, readable syntax that is close to the natural …

Humans survive and thrive through social exchange. Yet, social dependency also comes at
a cost. Perceived social isolation, or loneliness, affects physical and mental health, cognitive …

What are the neural dynamics of choice processes during reinforcement learning? Two
largely separate literatures have examined dynamics of reinforcement learning (RL) as a …

Psychiatric research is in crisis. We highlight efforts to overcome current challenges by focusing
on the emerging field of computational psychiatry, which might enable the field to move …