Lecture: Alayar Kangarlu


Friday, February 24, 2017


11:30 am


Sanders Physics 201-Physics Laboratory

Alayar Kangarlu
Columbia University and New York State Psychiatric Institute

Magnetic resonance imaging (MRI) has developed into a powerful diagnostic tool in medicine. MRI has also been used in research to probe into the human brain. Functional MRI (fMRI) offers imaging of the mind as well as the brain which makes it possible to localize the function of brain
structures. Complex computational tools are used to visualize brain
networks that offer a new powerful tool to study the brain and its disorders. Functional connectivity (fc) maps using resting state fMRI (rsfMRI) is computed by detecting temporal synchronicity of neuronal Computational Mapping of Human Brain*

Mactivation patterns of anatomically separated brain regions. But, a great
deal of technological advancement, both in hardware and software, had to be made to make computation of brain networks possible. The critical
technologies that made computational modeling of functional brain networks possible were high quality gradients for implantation of distortion free fMRI, faster pulse sequences and radio frequency (RF) coils to capture the fluctuation frequency of neuronal activity, and complex post processing
computation of brain networks. rsfMRI is capable of detecting brain
function that mediate higher cognitive processes in normal brain. We aim to
ultimately detect the disruption of this mediation in psychiatric patients.
We have already obtained functional connectivity in normal subjects using
fMRI data during resting state. We did this as a function of spatial
resolution to explore the required computational sources and susceptibility
effects on the sensitivity of fMRI to anatomic specialization.