Klaudia P. Szatko

The paper introduces a large-scale dataset of functional responses from mouse ganglion cells, enabling population-level analyses and computational modeling of retinal computation.

The paper identifies a retinal ganglion cell type that detects visual context changes by responding selectively to chromatic contrast transitions.

The paper tests a drug to reduce noise in retinal circuits of mice with retinitis pigmentosa, finding it preserves visual sensitivity while decreasing circuit noise.

This study improves neural system identification by incorporating efficient coding principles, showing better performance and biologically plausible filters in retinal neuron response prediction.

This paper develops a domain adaptation framework to remove inter-experimental variability in systems neuroscience data while preserving biological signals, showing improved performance over existing methods.

The paper uses a UV-green camera to study mouse visual environments and finds that natural scene statistics shape color discrimination and retinal processing in the upper visual field.

The paper investigates neural circuits in the mouse retina and finds that color-opponent cells are predominantly located in the ventral retina, supporting color vision in the upper visual field.

The paper develops a method to image the entire inner plexiform layer of the retina at once, revealing response speed gradients in bipolar cells and isolating experimental batch effects.

This paper introduces a flexible spatial visual stimulator with arbitrary spectrum control for use in vision research, demonstrating its application in mouse and zebrafish models.