Samuele Virgili

The paper shows that adaptive mechanisms in retinal ganglion cells reshape feature selectivity to detect homogeneous regions in natural scenes.

The paper shows VIP+ amacrine cells in the retina both inhibit and excite specific ganglion cells, coordinating their activity through gap junctions and GABAergic synapses.

The paper shows that specific ganglion cells respond selectively to contrast changes near moving object edges, suggesting they could serve as primitives for motion segmentation.

The paper shows that retinal ganglion cells can detect the sign of defocus by using spatial contrast, which is affected by optical aberrations.

openretina provides a standardized framework for training and evaluating retinal models across datasets and species, revealing unexplained variance in current models.

This paper develops a scalable Gaussian process model for predicting neural responses to natural images, outperforming deep neural networks on small datasets and enabling efficient model learning and comparison.

This study investigates how retinal ganglion cells respond to natural scenes, finding that their ON-OFF selectivity varies with the image and is due to non-linear retinal circuit pathways.