Audio/Visual Representation of Resting State fMRI
This video was created from real functional magnetic resonance imaging data from the human connectome project. Wavelet decomposition analysis performed on the data from different brain regions separated the MRI signal into time-frequency components. Frequency bands were mapped into audible frequency ranges and chords were written to midi commands. Chords from brain networks or cooperative brain regions were then assigned to instrumental groups.
Van Essen, D. C., Smith, S. M., Barch, D. M., Behrens, T. E. J., Yacoub, E., & Ugurbil, K. (2013). The WU-Minn Human Connectome Project: an overview. NeuroImage, 80, 62–79. http://doi.org/10.1016/j.neuroimage.2013.05.041
Van Essen, D. C., Smith, S. M., Barch, D. M., Behrens, T. E. J., Yacoub, E., & Ugurbil, K. (2013). The WU-Minn Human Connectome Project: an overview. NeuroImage, 80, 62–79. http://doi.org/10.1016/j.neuroimage.2013.05.041
Research
Default Mode Network
The Default mode network is a collection of brain areas that collectively have high metabolic activity during periods of low cognitive demand. The network exhibits decreases in activity associated with the performance of a wide range of task conditions. The role of this network in cognition and the reason for its high level of activity at rest is not well understood. Whatever the role of these key brain region, altered patterns of activity in these brain areas is associated with many mental disorders including autism, schizophrenia and depression. My current research aims to understand the task-evoked temporal dynamics of brain activity in these regions in terms of their interaction with other brain areas. To this end, I have used diffusion weighted imaging to map the large scale connections of these regions throughout the brain and have built a dynamic systems model based on these structural connections.