YINS & Kavli Institute, 10/28/15

YINS & Kavli Institute, 10/28/15

Talk Summary: 

Emily Finn: “Functional connectome fingerprinting: Identifying individuals and predicting behavior using patterns of brain connectivity”

While fMRI studies typically collapse data across many subjects, brain functional network organization varies between individuals. Using data from the Human Connectome Project, I will present evidence that patterns of functional brain connectivity act as a ‘fingerprint’ that can accurately identify individuals from a large group, regardless of how they are engaged during imaging. Features of these functional networks can also predict subjects’ level of fluid intelligence.

Monica Rosenberg: “A global measure of attention from whole-brain functional connectivity”

Although the ability to sustain attention varies widely and can have profound effects on daily life, researchers lack a simple way to measure how well a person maintains focus. Here we show that sustained attentional abilities—from how well an adult performs on an attention task to whether a child experiences symptoms of attention deficit hyperactivity disorder—can be predicted from spontaneous fluctuations in brain activity while individuals are simply resting. Thus, the intrinsic organization of the brain reflects one’s ability to sustain attention, and can potentially be used to make predictions about a wide variety of other traits.

Raphy Coifman: “Organizing and modeling observational Networks; questionnaires, neuronal activity and others”

We’ll illustrate joint network organization to map neuronal activity (in a mouse brain) across neurons, fast time, slow time, or experimental settings. This involves dynamic neuronal networks, as well as temporal and activity nets.  

Emily Finn, Monica Rosenberg, and Raphy Coifman