Signals sent from the retina to the brain have a lot of background noise, yet we see the world clearly. Researchers show that to achieve visual clarity the brain must accurately measure how this noise is distributed across neurons when processing the signals sent down the optic nerve. These results are likely to shape the design of future retinal prosthetics and other brain-machine interfaces.

They are what an engineer would call ‘noisy’ — there is variance between cells and from one moment to the next. And yet, when we see a photograph of a beautiful flower, it looks sharp and colorful and we know what it is.

The brain’s visual centers must be adept at filtering out the noise from the retinal cells to get to the true signal, and those filters have to constantly adapt to light conditions to keep the signal clear. Prosthetic retinas and neural implants are going to need this same kind of adaptive noise-filtering to succeed, new research suggests.

«Neurons in the brain are noisy — meaning that when the same stimulus is presented, the neurons do not produce the same response each time,» said Greg Field, an assistant professor of neurobiology at Duke University, who has coauthored a new study in Nature Communications with a Canadian colleague on how the brain compensates for visual noise.

«If brain-machine interfaces do not account for noise correlations among neurons, they are likely to perform poorly,» Field said.

Working in a special darkroom inside Field’s laboratory, Duke graduate student Kiersten Ruda exposed small squares of living rat retina to patterns and videos under varying light conditions while an array of more than 500 tiny electrodes beneath the retinal cells recorded the signals that are normally sent down the optic nerve to the brain.

Story Source:
Materials provided by Duke University. Original written by Karl Leif Bates. Note: Content may be edited for style and length.