CCNS: Transition Workshop: May 4-6, 2016

Registration for this workshop is currently closed.


This workshop will be held at SAMSI in RTP.


The transition workshop for the Computational Neuroscience program is an opportunity for the active working groups in the program to exchange results and share their perspectives on common issues. This workshop is focused on recent research progress that has been made in connection with the many research areas spanned by the CCNS program. Sessions of talks dedicated to each working group will feature presentations by active members. The workshop also seeks to facilitate planning for continuing collaborations on further research questions to extend beyond the period of the CCNS program.

All CNCS participants are asked to acknowledge support in any relevant publications and presentations, “This material was based upon work partially supported by the National Science Foundation under Grant DMS-1127914 to the Statistical and Applied Mathematical Sciences Institute.” See

Schedule and Supporting Media

Speaker Titles Abstracts
Poster Titles
Participant List

Wednesday, May 4th
SAMSI Room 150

Time Description Speaker
8:15 Shuttle
8:45– 9:00 Opening Remarks by SAMSI Associate Director Thomas Witelski
9:00 –9:30 Modeling the Muscular Response to Motor Neuron Spike-Trains Laura Miller and Katie Newhall, UNC
9:30-10:00 A New Template for Walking Tirthabir Biswas, Loyola
10:00-10:30 Neuromuscular Control of Jellyfish Turning Alexander Hoover, Tulane
10:30– 11:00 Break
Big Data Integration, Part 1
11:00–11:30 The Future Outlook in EEG Analysis Hernando Ombao, UC Irvine
11:30– 11:45 Discussion
11:45– 1:15 Lunch
Big Data Integration, Part 2
1:15-1:45 Estimating Brain Pathway Effects Using Large-scale Multilevel Models Xi Luo, Brown
1:45-2:15 Joint and Individual Variation Explained (JIVE)Integration of HCP Data Qunqun Yu, UNC
2:15-2:45 PCA Leverage: Outlier Detection for High-Dimensional fMRI Data Amanda Mejia, Johns Hopkins
2:45-3:00 Discussion
3:00-3:30 Break
Optical Imaging
Issues in Data Analysis for Optical Imaging
Mark Reimers, Michigan State
4:30-5:00 Discussion
5:00 Shuttle departs to hotel

Thursday, May 5th
SAMSI Room 150

Time Description Speaker
8:30 Shuttle
Inverse Problems
9:00–9:30 Computational Methods for Large-Scale Inverse Problems Julianne Chung, Virginia Tech
9:30-9:50 Reduced Order Modeling in Photoacoustic Tomography Sarah Vallelian, SAMSI
9:50-10:10 Efficient Markov Chain Monte Carlo Methods for Hierarchical Bayesian Inverse Problems Andrew Brown, Clemson
10:10-10:30 Simultaneous Image Segmentation and Deconvolution Hoang Duy Thai, SAMSI
10:30–11:00 Break
MRI Processing Part 1
11:00–11:10 A Gentle Introduction to Image Processing and Reconstruction in FMRI Daniel Rowe Marquette
11:10-11:40  Quantifying Correlations Artificially Induced in fcMRI Data by the SENSE pMRI Model Iain Bruce, Duke
11:40-12:10 Examination of Artifacts from Multiband Imaging Benjamin Risk, SAMSI
12:10–1:30 Lunch
MRI Processing Part 2
1:30-2:00 A Method to Mitigate Inter-slice Signal Leakage in SMS-fMRI Mary Kociuba, Marquette
2:00-2:20 Topology and fMRI Data Adam Jaeger, SAMSI
2:20-2:30 The Current State of Image Processing and Reconstruction with Future Directions Daniel Rowe Marquette
2:30-3:00 Break
Structural Connectivity
3:00-3:30 Disentangling Brain Graphs: the Conflation of Network and Connectivity Analyses Sean Simpson, Wake Forest School of Medicine
3:30-4:00 Mapping Tissue Microstructure using Spherical Polar Fourier Diffusion MRI Jian Cheng, NIH
4:00-4:30 Robust Human Brain Structural Connectivity Analysis Zhengwu Zhang, SAMSI
4:30-5:00 Bayesian Network-Response Regression Lu Wang, Duke
5:00-7:00 Poster Session and Reception
7:00 Shuttle departs to hotel

Friday, May 6th
SAMSI Room 150

Time Description Speaker
8:30 Shuttle
Imaging Genetics
9:00-9:30 Integrative Bayesian Modeling Approaches to Imaging Genetics Michele Guindani, MD Anderson
9:30–10:00 Imaging Genetics toward Mechanistic Understanding of Psychiatric Disorders Yihong Zhao, NYU
10:00–10:30 Break
10:30-11:00 Identifying Genetic Variants for Learning Ability with Neuroimaging Chintan Mehta, Yale
11:00-11:30 Imaging Genetic Analysis for PNC Behavioral Data Jasmine Yang, UNC
11:30-12:00  Functional Analysis of  Large-scale Neuroimaging and Genetic Data Hongtu Zhu, UNC
12:00 Closing Remarks and Box Lunch
1:00 Shuttle to RDU Airport