Fri, Nov 20 (9.00 AM – 9.20 AM)

Neuroimaging Networks for Translational Neuroscience
Neuroimaging research has increasingly revealed the complex interplay of different brain networks in supporting different perceptual, affective and cognitive tasks.  However, an understanding how this interplay shapes individual differences in ability, personality, and neuropsychiatric illness is only beginning to emerge.  In this talk I will highlight features of circuits involved in motivated behavior and the ability of neuroimaging to provide a translation bridge from animal models to human behavior.  The new Center for Advanced Human Brain Imaging Research (CAHBIR) on the Busch campus aims to facilitate such translational research and build upon the unique confluence of basic neuroscience and clinical research across the Rutgers community.

Fri, Nov 20 (9.25 AM – 9.45 AM)

Reward Processing in the Human Brain
From winning a raffle to receiving praise from a colleague, the experience of reward elicits positive emotions, shapes our behavior and influences our emotional well-being.  Central to processing rewards is the role of the striatum – the input unit of the basal ganglia and a key node in a putative human reward circuit.  This talk will first describe early efforts aimed at characterizing a reward-related signal in the human striatum.   We will then discuss how this signal can impact decision making and highlight how the surrounding social context (i.e., the level of closeness between individuals) can change reward-related responses and the inherent experience of a reward.  Finally, we will focus on the beneficial effects that positive emotions can have on our ability to cope with negative affect elicited by acute stress.

Fri, Nov 20 (9.50 AM – 10.10 AM)

Data-Driven Methods for Understanding the Dynamics of Brain Function
The human brain is a highly complex dynamic system. Achieving a complete understanding of how its anatomical structure supports a diverse range of functions, such as action, perception, and cognition, has been one of the major goals of neuroscience, but it is still far from reach.  One of the obstacles in reaching this goal has been lack of computational techniques that can reliably describe the dynamic properties of the brain function when it is in action. In this talk, I will discuss the recent new computational techniques that have been developed in my lab for studying the dynamics of brain function and present their applications.