William Bosl, PhD

Department	Medicine Informatics Program
Hospital Title	Research Scientist
Academic Title	Instructor in Pediatrics
Phone	617-919-2517
Fax
Email	William Bosl
Location	300 Longwood Avenue Enders 150.5 Boston, MA 02115

Research Overview

Research in my lab is focused on clinical neuroinformatics--the use of computer methods and software to analyze and store measurements of functional brain data, and to diagnose and monitor neuropsychiatric disorders and cognitive development.

The rapid development of technologies for measuring brain function allows us to begin studying how measured brain activity is related to behavior. This requires software tools that can compute relevant information from abstract measurements of brain activity, and databases to contain relevant neuropsychiatric assessments and other medical data. Discovering relationships between brain data and behavioral disorders also requires artificial intelligence methods, many of which were developed for decision support systems in other branches of medicine. While many neuroscience research programs study the brain, our focus is explicitly on creating methods that are practically useful in the clinic.

Our primary research tool is the electroencephalogram (EEG), measuring brain electrical activity. This tool has long provided valuable information for neuroscience research, but may be underutilized for clinical applications in neurology and psychiatry. We aim to fully exploit EEG data, developing methods for discovering subtle or nonlinear patterns to gain a deeper understanding of the relationship between emergent signal features and the underlying neurophysiology. EEG is particularly promising for routine clinical monitoring of brain activity because it is relatively inexpensive, completely safe for all ages, including infants, and may provide the most direct noninvasive measurement of the brain's electrical activity. The explosive growth of neuroimaging studies that link functional brain activity to behavior promises exciting opportunities for measuring nonlinear brain activity that may indicate abnormalities or allow response to therapy to be monitored.

Our work is highly collaborative. We work with psychologists, psychiatrists and neurologists in several labs that have direct contact with patients, our primary source of clinical data. Our collaborators are based in Boston and extend around the world, reflecting our interest in health issues in the developing world and in contributing innovative technology for global mental health care.

Much of our work has been with the Laboratories of Cognitive Neuroscience in the Division of Developmental Medicine at Children's Hospital, directed by Charles Nelson, PhD. The major focus is to discover early biomarkers for autism spectrum disorder. This research is motivated by evidence that complex mental disorders such as autism are associated with abnormal brain wiring and that EEG signals may carry information about neural connectivity patterns.

A new collaboration with Dr. Charles Newton and the Kenya Medical Research Institute in Kilifi, Kenya, will study the cognitive effects of HIV infection on children undergoing antiretroviral therapy. The developing brains of children who have acquired HIV through vertical infection are particularly vulnerable to insults either directly, through secondary infections or from side effects of antiretroviral therapies. Our goal is to discover biomarkers that indicate the greatest risk for brain disorders in HIV-infected children.

In a project with the Research Program on Children and Global Adversity at the Harvard School of Public Health, directed by Dr. Theresa Betancourt, we are creating a platform for using mobile phones to collect neuropsychological assessment data in remote villages of Sierra Leone. This project is part of an ongoing longitudinal study of former child soldiers in Sierra Leone, and seeks to build evidence to drive policy reforms supporting improved protections and services for children and families facing adversity due to armed conflict.

About William Bosl

William Bosl is a computational physicist with extensive background in scientific computing and data analysis. Before coming to Boston Children's Hospital, he worked in the Center for Applied Scientific Computing at Lawrence Livermore National Lab on environmental modeling and remote sensing problems, and in the Geophysics Department at Stanford University. At Stanford he invented and developed a method for computing properties of porous materials from CT scans, which led to the commercialization of new technology that is replacing laboratory core analysis globally.

In 2005, Bosl came to Children's and Harvard Medical School to work in bioinformatics and medical technology. Initially, his research focused on creating a complex systems biology approach to modeling biochemical pathways, and led to the development of a "fuzzy logic" method for simulating cellular processes. He soon turned his attention to the most complex system known, the brain. The focus of his work is on developing clinically useful technology for analyzing brain function and using advanced informatics methods for extracting psychiatric biomarkers from measurements of brain activity. He collaborates with several laboratories and clinics that work with pediatric neurological and psychiatric disorders. Bosl completed his PhD at Stanford University in 1999, and completed additional advanced graduate training in clinical neuroscience, child neuropsychology and neurotechnology at Harvard and MIT.

Key Publications

Bosl W, Tager-Flusberg H, Tierney A, Nelson CA. EEG complexity as a biomarker for autism spectrum disorder risk. BMC Medicine. In Press.
Bosl W, Li R. The role of noise and positive feedback in the onset of autosomal dominant diseases. BMC Syst Biol 2010 Jun 29; 4:93. PMID: PMC2902440.
Bosl W. Multiscale data reduction with flexible saliency criterion for biological image analysis. Proceedings of the IEEE International Conference on Engineering in Medicine and Biology Society. Minneapolis, September 2009.
Bosl W. Systems biology by the rules: hybrid intelligent systems for pathway discovery and analysis. BMC Systems Biology 2007 Feb 15; 1:13. PMID: PMC1839891
Bosl W, Li R. Mitotic exit control as an evolved complex system. Cell. 2005 May 6; 121(3):325-33. PMID: 15882616.

For a list of William Bosl's publications on PubMed, click here.