Researchers from Johannes Gutenberg University Mainz have identified the neuronal networks and mechanisms that allow for rapid and reliable perception of contrasts even when light levels vary. When light conditions change rapidly, such as when driving through areas with alternating stretches of shadows and sunlight, our eyes need to respond quickly to maintain stable visual processing. Professor Marion Silies and her team have identified a corrective ‘gain control’ mechanism in fruit flies that enables them to sustain stable visual processing in changing light conditions. Their research, recently published in Nature Communications, has identified the algorithms and neuronal networks that underlie this mechanism.
Vision needs to function accurately in various situations, including when an object moves from light into shade. This is necessary for humans and many animal species that rely on vision for navigation. Rapid changes in luminance also present challenges for inanimate objects, such as camera-based navigation systems. Animals are able to adjust to changing light conditions without additional technology, making them a valuable model for studying how visual information is stably processed under varying lighting conditions. Marion Silies and her team are investigating how animals achieve this stability.
Using a combination of theoretical and experimental approaches, the researchers studied the compound eye of the fruit fly Drosophila melanogaster to understand how contrasts are determined between objects and their backgrounds. They found that the contrast responses are determined postsynaptically of the photoreceptors, and that without gain control, changes in luminance could affect subsequent stages of visual processing. By using two-photon microscopy, they were able to identify specific neuronal cell types that are critical for generating stable contrast responses in rapidly changing light conditions.
The research team identified a cell type, Dm12, that pools luminance signals over a specific radius to correct contrast responses between objects and their backgrounds in changing light conditions. This cell type responds only locally to visual information and is able to accurately compute contrast by pooling luminance information spatially. Through a computational model implemented by Dr. Luisa Ramirez, the team was able to predict the optimal radius for capturing background luminance in images of natural environments. This discovery provides insights into how the visual system processes information in dynamically changing lighting conditions.
Marion Silies, who has been studying the visual system of fruit flies for over 15 years, believes that the mechanisms identified in this research may also be present in mammals, including humans. She suggests that luminance gain control in mammals is likely implemented in a similar manner, as the necessary neuronal substrate is available. By understanding how animals are able to stabilize vision in changing light conditions, researchers can gain insights into the underlying mechanisms that support reliable visual processing in various species.
Overall, the research conducted by Marion Silies and her team at Johannes Gutenberg University Mainz has provided valuable insights into the neuronal networks and mechanisms that enable rapid and reliable perception of contrasts in dynamically changing light conditions. By studying the visual system of fruit flies, the researchers have identified specific cell types and algorithms that contribute to stable visual processing in response to rapid changes in luminance. These findings have implications for understanding how vision is maintained in varying lighting conditions and may have broader applications in the development of technologies such as camera-based navigation systems.