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

Speaker: Emily Finn
Interdepartmental Neuroscience Program, Todd Constable Lab

Talk Summary: 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.

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

Speaker: Monica Rosenberg
Psychology, Marvin Chun Lab

Talk Summary: 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.

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

Speaker: Raphy Coifman
Math and Computer Science

Talk Summary: 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.