Alexander Fengler

HSSM provides a Python toolbox for hierarchical Bayesian neuro-cognitive modeling, enabling fast parameter estimation and model simulation through simulation-based inference.

This study shows that slower transitions between cognitive control states in older adults reduce cognitive flexibility, despite preserved ability to reach target states when given sufficient time.

The paper shows that mice, like humans, exhibit choice history bias in perceptual decision-making, using Diffusion Decision Models across species.

The paper extends the HDDM toolbox to fit a broader class of decision and reinforcement learning models using likelihood-free inference and hierarchical Bayesian regression.

This paper introduces neural networks to approximate likelihoods for generative models in cognitive neuroscience, enabling fast posterior sampling and accurate parameter recovery.

This study uses fMRI to show that items with higher predicted utility are remembered with greater fidelity in working memory, even without concurrent memory load.