Movement reveals shared visual coding rules in mouse and monkey brains
Seeing and moving are directly linked in the brain. When we stand still, the visual scene barely shifts. When we run, by contrast, the environment rushes past, so the signals reaching the eye become more variable and change faster. Because animals generate this movement themselves, the change is predictable, and the brain can adjust at the moment movement starts rather than waiting for new visual…
The visual systems of mice and monkeys follow the same fundamental evolutionary principle for processing information, according to a study published in Science Advances. Researchers Wiktor F. Młynarski and Jonathan M. Gant found that the differences between the two animal groups' vision lies in the inputs they receive, not in how their brains process those signals.
The efficient coding hypothesis, which posits that neurons have adapted over time to process typical patterns in their environment in the most energy-efficient way, was used to explain the observed effects on neuronal activity during movement. By simulating neuronal processing in mouse and primate visual cortices, the researchers were able to demonstrate that movement-induced changes in neural responses, their temporal dynamics, interactions between neighboring neurons, and the accuracy of the neural code are all better explained by this theory.
Młynarski and Gant further found that mouse visual neurons respond to larger, coarse patches of the scene, which are significantly affected by movement. In contrast, primates' foveal neurons, responsible for high-resolution visual processing, already have rapidly fluctuating signals at rest, so movement does not substantially alter them.
This explains why mice exhibit stronger movement-induced visual modulation compared to primates. The study highlights the role of theoretical neurobiology in explaining seemingly contradictory observations under common principles.
Written by urgent.news from Medical Xpress's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.