Cheng Xue is currently a staff scientist in Marlene Cohen’s lab in the Department of Neurobiology at the University of Chicago. Xue received his bachelor’s and master’s degrees in physics from Nanjing University in China. He subsequently carried out his doctoral work at the German Primate Center, before joining the Cohen Lab as a postdoctoral researcher, where he is now a staff scientist. Xue is interested in decision-making behavior in the broad sense. He uses multi-faceted approaches including behaving monkey electrophysiology, computational modeling, and human psychophysics to study decisions in various aspects. Through these research experiences, Xue developed a keen interest in the apparently suboptimal decision-making strategies that are used by every species. Many of them may have cognitive origins, and therefore can potentially become a window to reveal important neuronal constraints in perception or decision-making. He believes research in this direction will inspire new treatment for various neurological disorders. Additionally, understanding how and why our brains do not produce the most accurate perception or the best judgments can inform better decision-making strategies.
Principal Investigator: Marlene Cohen
Fellow: Lamrot Jinfessa
Undergraduate Fellow Project:
How do we make choices? When do we make bad choices and why? The Cohen Lab studies perceptual decision-making and its underlying neuronal basis. We will build a “game-room” for our experimental animals in their home environment and record their choices when they voluntarily engage with our decision-making game. We will investigate choice behavior of the animals, and test two non-exclusive hypotheses about suboptimal choices: 1) that the perceived value of different options is contaminated by irrelevant processes (like visual images that are attention-grabbing), even when that does not help the animal get more rewards, and 2) that maintaining the flexibility required to switch between choice strategies imposes a neuronal cost worsens choice behavior in the short-term. The prospective student will help design and build the experiment system, collect and analyze data, use computational modeling to generate hypotheses about neuronal basis of this behavior, and work in tandem with ongoing rig-based electrophysiology projects to test model predictions.