This course will teach modeling and processing approaches for using diffuse optical methods for mapping brain function in humans. This includes near-infrared light propagation modeling in tissue using the freely distributed NIRFAST software package as well as temporal data processing and image reconstruction using the NeuroDOT software package. NIRFAST is a widely-used, user-friendly package for modeling NIR light propagation in tissue and recovering images of optical parameters in arbitrarily-shaped tissue volumes. This course will use a combination of instructor lecturing and hands-on exercises using publically available high fidelity data to teach both conceptual and practical aspects of NIR imaging using the NIRFAST and NeuroDOT software packages. Attendees will be running and visualizing light propagation models of the human head and will also learn and develop skills using image reconstruction algorithms. All of the training will be centered upon providing knowledge, training and tools for volumetric imaging of functional brain activations based on contrasts of hemoglobin concentration as measured using Diffuse Optical data. The class will review the basic physics and biology of the approach, step through how the software works, and train attendees how to use the software through user exercises. More information about NIRFAST can be found at http://www.nirfast.org, and more information about NeuroDOT is available at https://github.com/WUSTL-ORL/NeuroDOT_Beta.

Learning Outcomes: This course will enable you to:

• Describe the fundamental principles behind diffuse light propagation in biological tissue

• Calculate point spread functions of different optical array geometries

• Utilize real experimental data for Diffuse Optical Mapping of Human Brain Function

• Evaluate inversion parameters with respect to image smoothness and resolution

• Estimate optically-measured brain responses to varying stimulus paradigms with real data

• Design and construct models of source and detector arrays on a head and compare their relative sensitivity to brain function