Computational Analysis Methods and Issues in Human Cognitive Neuroscience
Google Tech Talk
January 14, 2010
Presented by Bradley Voytek.
There is a massive, relatively uncoordinated effort underway to map out the relationship between brain and behavior. Human neuroimaging experiments abound with approximately 30,000 neuroimaging studies performed in 2008 alone. Most of the data from these experiments are analyzed on an individual desktop or small, local cluster. Neuroimaging data contains information about neural activity in both time and space and can easily exceed 1GB per subject. In order to analyze the functional properties of neuronal networks these data can be decomposed in a variety of ways (behavioral condition, principal and independent components, phase and frequency components, graphs and digraphs, etc.). This exponentially increases analysis time and database sizes creating bottlenecks in the analysis work flow. I will discuss a variety of neuroimaging methods in terms of the sources of the signals measured, what these signals actually inform us about how the brain gives rise to cognition and behavior, and how this information can inform medical diagnosis and treatment. Furthermore I will highlight how advances in computational processing have improved data analysis and discuss the computational roadblocks that impede research progress.