Postdoctoral Fellow Seminars

Introductory Talks from SAMSI Postdoctoral Fellows

September 14, 2016, 1:15pm – 2:15pm
Room 150
Speaker: Benjamin Risk, Sarah Vallelian, Zhengwu Zhang, Duy Thai, David Jones, Hyungsuk Tak, David Stenning, Ahmed Attia, Sercan Yildiz, Peter Diao

Abstract

Each of our Postdoctoral fellows will perform a short introductory talk discussing their areas of academic interest and possibly an overview of their upcoming lectures throughout the fall.

References

To Be Determined


Lecture: Spurious Activation from Multiband Acquisition fMRI

September 21, 2016, 1:15pm – 2:15pm
Room 150
Speaker: Benjamin Risk

Abstract

In fMRI, conventional pulse sequences collect two-dimensional data one slice at a time and consequently require up to six seconds to acquire the dozens of slices composing a single volume with whole-brain coverage. Multiband acquisition techniques collect multiple slices in a single shot and can be used to decrease the time between acquisition of fMRI volumes, which can increase statistical power and better characterize the temporal dynamics of the blood-oxygen level dependent
(BOLD) signal. The technique requires an additional processing step in which the slices are separated, or unaliased, to recover the whole brain volume. However, this may result in signal leakage between aliased locations and lead to spurious activation (false positives). We examine the Slice-GRAPPA algorithm for image reconstruction at different acceleration factors. We found a high incidence of spurious activation in simulations. Perversely, more time points actually increase the detection of spurious activation, such that longer acquisition times can lead to poorer estimates of activation. We also show evidence of artifacts in fMRI data from the Human Connectome Project, which uses a higher acceleration factor than most studies and thus may be more susceptible to spurious activation.

References

To Be Determined


Lecture: Computationally efficient Markov chain Monte Carlo methods for hierarchical Bayesian inverse problems

September 28, 2016, 1:15pm – 2:15pm
Room 150
Speaker: Sarah Vallelian

Abstract

In Bayesian inverse problems, the posterior distribution can be used to quantify uncertainty about the reconstructed solution. In practice, approximating the posterior requires Markov chain Monte Carlo (MCMC) algorithms, but these can be computationally expensive. We present a computationally efficient MCMC sampling scheme for ill-posed Bayesian inverse problems.

References

To Be Determined


Lecture: Nonparametric Bayes Models of Fiber Curves Connecting Brain Regions

October 5, 2016, 1:15pm – 2:15pm
Room 150
Speaker: Zhengwu Zhang

Abstract

In studying structural inter-connections in the human brain, it is common to first estimate fiber bundles connecting different regions of the brain relying on diffusion tensor imaging. These fiber bundles act as three-dimensional highways for neural activity and communication, snaking through the brain and connecting different regions. Current statistical methods for analyzing these fibers reduce the rich information into an adjacency matrix, with the elements containing a count of the number of connections between pairs of regions. The goal of this article is to avoid discarding the rich functional data on the shape, size and orientation of fibers, developing flexible models for characterizing the population distribution of fibers between brain regions of interest within and across different individuals. We start by efficiently decomposing each fiber in each individual’s brain into a corresponding rotation matrix, shape and translation from a global reference curve. These components can then be viewed as data lying on a product space composed of different Euclidean spaces and manifolds. To non-parametrically model the distribution within and across individuals, we rely on a hierarchical mixture of product kernels specific to the component spaces. Taking a Bayesian approach to inference, we develop an efficient method for posterior sampling. The approach automatically produces clusters of fibers within and across individuals, and yields interesting new insight into variation in fiber tracks, while providing a useful starting point for more elaborate models relating fibers to covariates and neuropsychiatric traits.

References

To Be Determined


Lecture: Title Ongoing

October 12, 2016, 1:15pm – 2:15pm
Room 150
Speaker: Duy Thai

Abstract

Abstract for this talk has not been provided. Please stay tuned for more details as our event gets closer.

References

To Be Determined


Lecture: Title Ongoing

October 19, 2016, 1:15pm – 2:15pm
Room 150
Speaker: David Jones

Abstract

Abstract for this talk has not been provided. Please stay tuned for more details as our event gets closer.

References

To Be Determined


Lecture: Title Ongoing

October 26, 2016, 1:15pm – 2:15pm
Room 150
Speaker: Hyungsuk Tak

Abstract

Abstract for this talk has not been provided. Please stay tuned for more details as our event gets closer.

References

To Be Determined


Lecture: Title Ongoing

November 9, 2016, 1:15pm – 2:15pm
Room 150
Speaker: David Stenning

Abstract

Abstract for this talk has not been provided. Please stay tuned for more details as our event gets closer.

References

To Be Determined


Lecture: Title Ongoing

November 16, 2016, 1:15pm – 2:15pm
Room 150
Speaker: Ahmed Attia

Abstract

Abstract for this talk has not been provided. Please stay tuned for more details as our event gets closer.

References

To Be Determined


Lecture: Title Ongoing

November 30, 2016, 1:15pm – 2:15pm
Room 150
Speaker: Sercan Yildiz

Abstract

Abstract for this talk has not been provided. Please stay tuned for more details as our event gets closer.

References

To Be Determined


Lecture: Title Ongoing

December 7, 2016, 1:15pm – 2:15pm
Room 150
Speaker: Peter Diao

Abstract

Abstract for this talk has not been provided. Please stay tuned for more details as our event gets closer.

References

To Be Determined