Managed by UT-Battelle for the Department of Energy 1 Advanced Brain-Wave Analysis For Early Diagnosis of Alzheimer’s Disease (AD) Presented by Jaron Murphy Research Alliance in Math and Science Dr. Lee Hively & Dr. Nancy Munro Computational Sciences and Engineering August 13, 2008 Oak Ridge, Tennessee

Managed by UT-Battelle for the Department of Energy 2 Overview  Background  Purpose  Research Objectives  Implementation  Current Status  Challenges  Future Applications

Managed by UT-Battelle for the Department of Energy 3 What is Alzheimer’s disease (AD)?  AD is a neurodegenerative disease of the nervous system that: –Affects the cognitive abilities of a person –Renders the person functionally useless in society –Progressive worsens over time and is fatal –Is presently incurable

Managed by UT-Battelle for the Department of Energy 4 Symptoms  Symptoms that may occur in the early stage of AD: –Confusion –Short-term memory disruption or loss –Problems with attention and spatial orientation –Personality changes –Language difficulties –Unexplained mood swings

Managed by UT-Battelle for the Department of Energy 5 AD Facts According to the 2008 Alzheimer’s Disease Facts and Figures*: –As many as 5.2 million people in the United States are living with AD –10 million baby boomers will develop AD in their lifetime –Every 71 seconds, someone develops AD –Alzheimer’s is the 6 th leading cause of death in the United States, surpassing diabetes [reported by the Centers for Disease Control and Prevention on June 12, 2008] –Direct and indirect costs of Alzheimer's and other dementias to Medicare, Medicaid and businesses amount to more than $148 billion each year *Published by the Alzheimer’s Association

Managed by UT-Battelle for the Department of Energy 6 Purpose  Improve detection of early diagnosis of Alzheimer’s disease and related diseases (ADRD)  Develop a portable software that will execute on supercomputers as well as PDA’s, cellular devices, and other mobile equipment without modifying original coding

Managed by UT-Battelle for the Department of Energy 7 Research Objectives  Implement qEEG Methodology of Dr. Shankle and Sneddon in Java  Analyze University of Kentucky EEG data to determine if Shankle and Sneddon’s results can be confirmed  Demonstrate early detection of Diffuse Lewy Body disease (DLB) for the first time via qEEG –Causes cognitive problems similar to AD and motor problems like those in Parkinson's –Incurable and progressive disease like AD

Managed by UT-Battelle for the Department of Energy 8 qEEG Methodology  Electroencephalography (EEG) –the scalp recording of the brain’s electrical activity  Quantitative EEG (qEEG) method –Developed by Dr. Robert Sneddon and Dr. William Shankle (University of California, Irvine)

Managed by UT-Battelle for the Department of Energy 9 Delayed Recognition Tasks  Two delayed recognition tasks, each consisting of: –Working memory task  Display sets of 2 visual stimulus at a time; 10 sets total  Subjects must indicate (yes/no) whether stimuli match –Recognition memory task  Presents 20 visual stimuli – 10 from the working memory task  Subjects must indicate whether a given stimuli was shown in the WMT

Managed by UT-Battelle for the Department of Energy 10 Analysis consists of data from 4 channels that correspond to movement of information in the brain: –Anterior Channels – AF3 and AF4 –Posterior Channels – P3 and P4

Managed by UT-Battelle for the Department of Energy 11 Data Source Anterior Channels Posterior Channels

Managed by UT-Battelle for the Department of Energy 12 Sneddon and Shankle hypothesize that a normal brain would create a higher level of information after integrating incoming sensory information, than brains with ADRD

Managed by UT-Battelle for the Department of Energy 13 Java Program Design Divided code into three classes: –Data reader class  Read and allocates space for the data –qEEG Calculations class  Performs the critical points, variance, and ratio calculations –Data Artifact filter class  Filters out artifacts such as eye blinks and muscle movement

Managed by UT-Battelle for the Department of Energy 14 Current Status  Debugging the dataReader and qEEGCalc classes  Translating dataFilter code from FORTRAN to Java  Calibrating parameters of data input

Managed by UT-Battelle for the Department of Energy 15 Challenges  Developing code structure –Divide code into various tasks –Determine the function of those tasks –Figure out how those tasks will communicate together  Deciphering Sneddon’s code  Finding the maxima and minima –Non-linear analysis of data  Analyzing gigabytes of data

Managed by UT-Battelle for the Department of Energy 16 Future Applications  Anticipate a clinical device in the next 5 to 10 years that could be used by a physician to provide early diagnosis of AD in 5 months before AD onset  Ability to provide early diagnosis of neurological diseases: Parkinson’s disease Diffuse Lewy Body disease Clinical Depression Bi-Polar Disorder

Managed by UT-Battelle for the Department of Energy 17 Collaborations  Dr. Yang Jiang, University of Kentucky School of Medicine - EEG Data Samples  Dr. Robert Sneddon, University of California, Irvine – Tsallis Entropy - MatLab Code

Managed by UT-Battelle for the Department of Energy 18 Acknowledgments The Research Alliance in Math and Science program is sponsored by the Office of Advanced Scientific Computing Research, U.S. Department of Energy. The work was performed at the Oak Ridge National Laboratory, which is managed by UT-Battelle, LLC under Contract No. De-AC05-00OR This work has been authored by a contractor of the U.S. Government, accordingly, the U.S. Government retains a non-exclusive, royalty-free license to publish or reproduce the published form of this contribution, or allow others to do so, for U.S. Government purposes. I would like to thank George Seweryniak for sponsoring RAMS and giving students like myself the opportunity to venture into the realm of research and Mrs. Debbie McCoy for managing the RAMS program even through her times of hardship. I would also like to thank my mentors for their guidance and advice during my research.

Managed by UT-Battelle for the Department of Energy 19 Questions 19Managed by UT-Battelle for the Department of Energy Any Questions or Comments? UTBOG_Computing_0801