Adam C. Lammert

This paper introduces a method for generating sparse stimuli to improve reverse correlation efficiency and interpretability, showing benefits in reconstruction quality, sample size efficiency, and subjective interpretability.

This study investigates how different subject instructions affect the quality of auditory representation characterization using reverse correlation, finding that detecting a hidden signal in stimuli yields the best reconstruction.

This paper applies compressive sensing to reverse correlation to reduce the number of stimulus-response pairs needed for cognitive representation reconstruction without bias.

This paper improves reverse correlation efficiency using stimulus whitening, achieving greater than 85% efficiency improvement and two-to-five-fold accuracy increase in simulations.

This paper reviews speech motor control models, comparing their architectures and properties, highlighting differences in control mechanisms and commonalities in higher-level planning and feedback use.