Resting state functional connectivity (RSFC) analysis is a novel approach for mapping functional brain organization that promises integration of the cognitive sciences with clinical neurology. The discovery that functionally-related brain regions have correlated spontaneous neural and hemodynamic activity in absence of tasks means that brain networks can be studied even in patients with severe brain- injury, including unconscious, anesthetized, or very young patients. In addition to being task-less, functional connectivity Magnetic Resonance Imaging (fcMRI) is also efficient in time, mapping the entire brain in as little as several minutes. As these functional connectivity methods advance, a gap continues to grow between the non- invasive functional brain mapping methodologies used in humans and the invasive molecular and genetic methodologies commonly used in mouse models of disease. An efficient functional connectivity method applicable in the mouse could provide a critical link between human evaluation of disease and mouse studies of disease mechanisms and therapies. While fMRI has been extended to some animal models (primates and to a lesser extent rats), thus far fcMRI remains elusive in the mouse due to stringent demands in resolution and signal-to-noise. Recently the RSFC methods have been extended to optical technology with functional connectivity diffuse optical tomography (fcDOT) demonstrated in humans. An advantage for mouse imaging is that optical methods readily scale to smaller volumes. In this grant we will extend fcDOT to the mouse - developing both a high-performance mouse specific DOT instrument and complementary imaging algorithms. The small size of the mouse brain provides an opportunity for DOT methods to far exceed the relative image quality of that obtained in humans. Leveraging this opportunity requires a new design approach. We propose using multiple camera views combined with structured illumination to increase the speed of camera based DOT by >100x. Functional connectivity methods, including correlation analysis and cortical parcellation will be developed and established in mouse models using genetic, behavioral and surgical manipulations of functional connectivity, and validation against stimulated responses and histology. To test fcDOT in a brain injury model, we will examine ischemic stroke. Recent fcMRI studies in ischemic stroke patients have demonstrated that bilateral homotopic connectivity, measured within 2 weeks after stroke, was a predictor of long-term recovery. We will serially measure bilateral connectivity in mice in a model of stroke recovery using fcDOT. Mice strains genetically lacking contralateral connectivity will be used to determine if transcallosal connectivity directly influences post-stroke recovery. The mouse fcDOT developed in this grant will enable new paradigms linking human neuroscience to genetic mouse models.

Public Health Relevance

Functional connectivity analysis in humans is a novel approach to mapping the functional organization of the brain organization that promises integration of the cognitive sciences with clinical neurology. An efficient functional connectivity method applicable in the mouse could provide a critical link between evaluations in human and mouse studies of disease mechanisms and therapies. This grant will develop non-invasive optical imaging technology and functional connectivity analysis methods for broad application in studies of neurological diseases, and establish the feasibility of the methods in a model of stroke recovery.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS078223-03
Application #
8696899
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Koenig, James I
Project Start
2012-09-15
Project End
2017-07-31
Budget Start
2014-08-01
Budget End
2015-07-31
Support Year
3
Fiscal Year
2014
Total Cost
$520,407
Indirect Cost
$178,034
Name
Washington University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Hassanpour, Mahlega S; White, Brian R; Eggebrecht, Adam T et al. (2014) Statistical analysis of high density diffuse optical tomography. Neuroimage 85 Pt 1:104-16
Bauer, Adam Q; Kraft, Andrew W; Wright, Patrick W et al. (2014) Optical imaging of disrupted functional connectivity following ischemic stroke in mice. Neuroimage 99:388-401
Eggebrecht, Adam T; Ferradal, Silvina L; Robichaux-Viehoever, Amy et al. (2014) Mapping distributed brain function and networks with diffuse optical tomography. Nat Photonics 8:448-454