Max Planck Research Group Vision and Computational Cognition
How do we perceive the world around us and interact with it in a meaningful manner? An answer to that question may at first seem obvious. However, our ability to recognize and categorize objects and carry out decisions on them is in fact based on a complex cascade of perceptual and decision processes. Understanding these processes would not only aid the development of improved artificial intelligence (such as autonomous cars); it could also support the development of better treatment of patients with damage in visual and cognitive brain regions.
In our research group, we aim to unravel basic mechanisms of visual perception and understand the cascade from early processing in visual brain regions to decision-making processes about our environment. To achieve this goal, we acquire large amounts of data both in behavior and with human brain imaging. With these large datasets we can identify reproducible patterns which we can later target with classical laboratory experiments. We complement this approach with computational models such as deep neural networks that offer a versatile tool for the discovery of previously unknown properties of the human brain. In addition to using these models as a tool, we aim at developing them further to make them more similar to human brains.