Humans have an amazing ability to selectively process information. At any point in time we are bombarded by a cacophony of signals from the external world and by vast numbers of memories from internal sources. And yet our brains have the almost magical capacity to ignore most of these inputs and focus on the small set of relevant information. The goal of the Gottlieb laboratory is to understand how the brain guides selective information processing as a function of learning, expectations and current task goals.

Our work examines visual attention – our ability to look at or attend to objects in a visual scene. We view these acts of attention as mental actions whose goal is to inform subsequent decisions. For instance, when we attend to a traffic light at an intersection, we seek to reduce the uncertainty of the subsequent decision (e.g., whether to stop or continue crossing the street). Using this simple idea, we can dissect the mechanisms that control selective information processing in a range of behavioral paradigms.

Dr. Gottlieb’s research has the potential to impact many areas in which attention is important. For instance, her research may identify ways to help individuals with ADHD, depression, anxiety, and drug addiction better control their mental focus and make better decisions. Her research may offer a new understanding in fundamental and important concepts like curiosity, creativity, and exploration which will lead to developments in tools in many fields including education and management. Because selective information processing is such an integral part of human intelligence and functioning, the incredible research of Dr. Gottlieb may one day trickle down to applications in nearly everything we do!

Current research includes:

• Population dynamics of reward and uncertainty: Dr. Gottlieb and her team record and analyze the activity dynamics of large populations of neurons in the frontal and parietal lobes, in order to understand how these populations encode expectations about rewards and uncertainty reduction to find the stimuli that are relevant to a task.
• Visual learning: using behavioral and neuronal measures, we examine how the brain learns the significance of visual cues (for instance, that red light means stop and green light means go) and how this knowledge is used to guide attention.
• Curiosity and intrinsic motivation: we often direct attention spontaneously, based on mere interest or curiosity, even when we are not performing an obvious task. Using behavioral studies, computational modeling and neural recordings, we seek to understand what makes information interesting and exciting in its own right, and how this varies according to an individual’s knowledge and other emotional and cognitive traits.