Lakshmi Narasimhan Govindarajan

The paper develops task-optimized models of sensory uncertainty and shows human confidence judgments align with model-derived uncertainty estimates in sound localization and pitch perception.

This paper develops a high-density epidural stimulation paddle with integrated electronics and evaluates its long-term performance in sheep.

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

The paper develops FLLIT, a machine-learning tool for automated leg tracking in Drosophila, revealing distinct gait and tremor signatures in PD and SCA3 models.