Krishn Bera

HSSM: A Widely Applicable Toolbox for Hierarchical Bayesian Neuro-cognitive Modeling

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

Model-based EEG phenotyping uncovers distinct neurocomputational mechanisms underlying learning impairments across psychopathologies

This paper uses model-based EEG analysis to identify distinct neurocomputational mechanisms of learning impairments in MDD, BP, and SCZ compared to controls.

Beyond Drift Diffusion Models: Fitting a broad class of decision and RL models with HDDM

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.