2012 BESIP Projects

Brain Imaging and Modeling Section
Voice, Speech and Language Branch
National Institute on Deafness and Other Communication Disorders (NIDCD)

Section Chief
Barry Horwitz, Ph.D.

Mentor
Barry Horwitz, Ph.D.

Contact Information
Email: horwitzb@mail.nih.gov
Tel: (301) 594-7755
Fax: (301) 480-5625
http://www.nidcd.nih.gov/research/scientists/pages/horwitzb.aspx

Laboratory and Project Description

Our laboratory uses functional brain imaging [functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG)] to study the neurobiological basis for auditory and language function in normal subjects and in various patient groups. My primary research focuses on understanding how the brain constructs networks of interacting regions (i.e., neural networks) to perform cognitive tasks, especially those associated with audition and language, and how these networks are altered in brain disorders. These issues are addressed by combining computational neuroscience techniques with data obtained using fMRI and MEG. To understand the relationship between what is observed in functional neuroimaging studies and the underlying neural dynamics, we have developed large-scale computer models of neuronal dynamics, consisting of multiple, interconnected brain regions, that perform some tasks similar to those designed for fMRI/MEG studies. The goal of this type of research is to provide a mechanism for integrating neural data from multiple modalities and for generating coherent neuroscientific accounts of various cognitive functions.

The project that the summer intern would work on centers on assessing whether certain quantitative measures of brain activity, obtained from fMRI data, have the potential to be useful biomarkers of neurological and psychiatric brain disorders. Recently, a number of groups have used a mathematical method called graph theory for the quantitative analysis of complex network organization, including brain networks. The problem with exploiting this approach for studying brain disorders is that it is uncertain which graph theoretic measures are appropriate for which disorders. A useful approach for dealing with this problem is to employ large-scale brain modeling in which a variety of abnormalities can be simulated.

The project that the summer intern would undertake would entail running these simulations and generating the various graph theoretic measures. In order to do this, the intern will:

• become familiar with the basics of functional magnetic resonance imaging
• become familiar with the neural abnormalities associated with number of neurologic and psychiatric disorders
• become familiar with graph theory and its application to network analysis
• perform simulations and subsequent data analysis.

The student will be supervised by the mentor and by two experts in graph theoretic analysis of brain networks and their relation to brain disorders.