Varsha Ramakrishna

The paper shows that modifying images used for optogenetic stimulation can make retinal ganglion cell responses more similar to natural photoreceptor-driven responses in mice.

The paper develops a spatial contrast model to capture nonlinear spatial integration in primate retinal ganglion cells using natural and artificial stimuli, showing improved performance over linear models.

This study examines how primate retinal ganglion cells adapt their spatial processing to natural versus artificial stimuli, finding that some cell types adjust receptive fields and surrounds, but efficient coding only partially explains these changes.

This paper introduces STR, a method combining super-resolution and tomography to identify receptive field subunits in retinal ganglion cells, validated in primate recordings.

The paper introduces an accelerated version of spike-triggered non-negative matrix factorization to identify coordinated subunit mosaics in primate ganglion cells.

This study compares predictive models for retinal ganglion cell responses, finding that CNNs outperform LN models, while LN models show better cross-stimulus generalization.