———————– Short-Course Announcement ———————–
Advanced Statistical Methods for Big Data Analysis of Neuroimaging
Applications to Brain Connectivity
Menara Razak
Universiti Teknologi Malaysia, Kuala Lumpur Campus,
Jalan Semarak, Kuala Lumpur.
9th Sept 2016 (Friday)
Speakers: Prof Dr Hernando Ombao
Department of Statistics, University of California at Irvine, US
Prof. Ir. Dr. Sheikh Hussain Shaikh Salleh and Dr. Chee-Ming Ting,
Center for Center for Biomedical Engineering
Organizer: Center for Biomedical Engineering, Universiti Teknologi Malaysia.
Advisor: Dato’ Prof Ir Dr Alias Mohd Noor
Organizing Chair: Prof. Ir. Dr. Sheikh Hussain Shaikh Salleh
Dear Datuk/Prof/Dr/Mr/Mrs/Miss,
We cordially invite you to a one-day short course entitled “Advanced Statistical Methods for Big Data Analysis of Neuroimaging Applications to Brain Connectivity” which will be held on 9th Sept 2016 (Friday) at Universiti Teknologi Malaysia, Kuala Lumpur.
This short course will introduce the fundamentals of a range of advanced statistical techniques for analyzing brain signals, in terms of modeling, estimation, inference and prediction of large neuroimaging data, e.g. functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) signals with state-of-the-art applications to brain connectivity analysis. Professor Hernando Ombao will present statistical exploratory approaches to modeling dependence between components of high-dimensional time series in designed experiments. These approaches could potentially impact neuroscience research that focus on functional connectivity between brain regions as a diagnostic marker for mental and neurological diseases and as a predictor for behavior. The major hurdle of high dimensionality in EEGs and fMRI will be addressed by using factor analysis and penalized regression such as LASSO method.
The course is organized into four lecture sections:
Session I and II: Prof Ombao will cover the following basic topics. These topics are essential to conducting a rigorous analysis of signals and to developing more sophisticated methods for modeling the complex features of the signals.
- Basic features in signals: mean, auto-correlation, cross-correlation
- Time domain models: white noise, auto-regressive (AR), autoregressive moving average (ARMA), vector auto-regressive (VAR)
- Spectral analysis: auto-spectra, cross-coherence
- Discrimination and classification
- Stationary vs non-stationary processes
- Statistical methods for testing differences between classes of signals
Session III: Prof Ombao will present various advanced research topics on “Exploratory Analysis of High Dimensional EEG and fMRI Time Series”
Session IV: Dr Ting will introduce fundamentals of state-space modeling approach to analyzing time-evolving, high-dimensional brain connectivity in both fMRI and EEG signals, using dynamic factor models and switching Kalman filtering.
COURSE SCHEDULE
====================
0800 – 0900 – Registration
0900 – 1030 – Lecture I: Basic Time Series Models and Estimation (Prof. Hernando Ombao)
1030 – 1045 – Tea Break
1045 – 1230 – Lecture II: Spectral and Non-stationary Analysis (Prof. Hernando Ombao)
1230 – 1430 – Lunch
1430 – 1530 – Lecture III: Exploratory Analysis of High Dimensional EEG and fMRI Time Series (Prof. Hernando Ombao)
1530 – 1545 – Tea Break
1545 – 1630 – Lecture IV: State-space Analysis of Connectivity in Neural Signals (Dr. Chee-Ming Ting)
1630 – 1700 – Open-Discussion on State-of-the-Arts(Prof. Dr. Sheikh Hussain Sheikh Salleh)
1700 – Closing
SPEAKER SHORT BIOGRAPHY
=========================
Prof Dr. Hernando Ombao
PhD (biostatistics), University of Michigan, Ann Arbor, US
Professor of Statistics, Dept. of Statistics, Uni.of California, Irvine
Professor of Cognitive Sciences, Dept of Cognitive Sciences, Uni.of California, Irvine
Associate Editor for the Journal of the American Statistical Association: Theory and Methods (2005-now), Journal of the Royal Statistical Society Series B (2011 – 2015), and the Statistical Analysis and Data Mining(2010 -2012).
Fellow of the American Statistical Association
Areas of Expertise: Theory, methods, and models for nonstationary multivariate time series and their applications to brain signals and images
Prof. Ir. Dr. Sheikh Hussain Shaikh Salleh
PhD, Uni.of Edinburgh
Deputy Director of Center for Biomedical Engineering (CBE), UTM
Chairman of National Technical Committee on Biometrics
Areas of Expertise: biomedical signal processing and instrumentation, cardiac signals, speech and speaker recognition and biometrics.
Dr. Chee-Ming Ting
PhD (Statistics), UTM
Senior Lecturer, Faculty of Biosciences and Medical Engineering, UTM
Research Fellow, Center for Biomedical Engineering (CBE), UTM.
Areas of Expertise: Statistical signal processing, time-series analysis, and high-dimensional statistics, neural signals.
REGISTRATION FEE
====================
Each participant: RM 500.00
(The registration fee includes lunch and printed lecture slides)
Registration Deadline: 1th Sept 2016
For detailed information, enclosed is the short-course announcement pamphlet.
For registration, please fill up the attached registration form at this link Advanced Statistical Methods for Big Data Analysis of Neuroimaging Applications to Brain Connectivity- 9 Sept 2016
and send the proof of payment to cmting@utm.my or evelyntanhuiru@gmail.com
If you have any inquiries, please contact me. We are looking forward to your participation. Thank you.
Yours Sincerely,
—–
Chee-Ming Ting, Ph.D.
Senior Lecturer
Center for Biomedical Engineering
Faculty of Biosciences & Medical Engineering
Universiti Teknologi Malaysia