# High accuracy decoding of dynamical motion from a large retinal population

arXiv: https://arxiv.org/abs/1408.3028 · HTML: https://mlsanity.com/paper/1408.3028/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Aug 2014.

## Built on by (most cited first, 1 of 1)

- [ML-PWS: Estimating the Mutual Information Between Experimental Time Series Using Neural Networks](https://mlsanity.com/paper/2508.16509/) (2025)

## Abstract (arXiv)

Motion tracking is a challenge the visual system has to solve by reading out the retinal population. Here we recorded a large population of ganglion cells in a dense patch of salamander and guinea pig retinas while displaying a bar moving diffusively. We show that the bar position can be reconstructed from retinal activity with a precision in the hyperacuity regime using a linear decoder acting on 100+ cells. The classical view would have suggested that the firing rates of the cells form a moving hill of activity tracking the bar's position. Instead, we found that ganglion cells fired sparsely over an area much larger than predicted by their receptive fields, so that the neural image did not track the bar. This highly redundant organization allows for diverse collections of ganglion cells to represent high-accuracy motion information in a form easily read out by downstream neural circuits.