| SSIP 2011 Home |
 |
|---|---|
Registration |
Georg Langs: Studying the Structure of Cognition: Machine Learning and Neuroimaging |
Understanding how our brain performs cognition and perception is a challenging endeavor. Recently, machine learning approaches have emerged as an interesting direction to study our cognitive architecture based on imaging techniques such as functional magnetic resonance imaging (fMRI). In this talk I will discuss two approaches that aim to capture and describe functional interaction patterns that emerge during specific cognitive processes and can span the entire brain.
In the first part we explore if the predictive power of fMRI signals with regard to an experimental condition (such as different objects shown to a person) can serve as a marker of specific activation patterns of functional processes involving multiple regions in the brain. The second part of the talk will focus on the exploratory analysis of the interaction patterns in fMRI data. We use a diffusion process on the set of fMRI voxels and a corresponding spectral embedding to establish a distance that captures the functional relationship between different cerebral regions. The resulting geometry captures the global interaction pattern within the brain. It makes the exploration of the entirety of functional interactions, and the mutual roles of individual regions possible.
To illustrate the approaches and highlight the open questions I will discuss three applications: a study of migration mechanisms caused by tumor growth that affects language areas; a comparison of the functional architecture involved in reward recognition between control subjects and cocaine abusers; and the structure of high-level human object category recognition in the visual pathway.
|
|
|
Page
last modified: |
Please send
comments to ssip2011@inf.u-szeged.hu |