Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) provides a critical tool to the medical and scientific communities. Despite the indispensable role of the BOLD fMRI technique in mapping human brain function, BOLD fMRI cannot be readily used to map sub-millimeter functional columnar architecture due to the contribution of draining veins and to the relatively broad point spread function. Therefore, the exact spatial source of hemodynamic signals acquired at """"""""columnar resolution"""""""" has been controversial. During the last grant period, we began to investigate the intrinsic spatial specificity of hemodynamic responses at a columnar level, and improved the specificity of BOLD measurements. Based on cerebral blood flow (CBF) and cerebral blood volume (CBV)-based fMRI measurements, we found that column-like functional structures are detected in the visual cortex and the hemodynamic responses appear to be reasonably specific to sub-millimeter functional architecture. Our current interpretations are that CBF and CBV-weighted fMRI indeed map columnar structures and that the regions with high intensity signal changes in fMRI maps indicate the location of neuronally-active cortical columns. However, these interpretations are questionable until a direct confirmation of fMRI results has been performed. Therefore, it is absolutely critical to validate our interpretations of fMRI maps by comparison with conventional in vivo techniques such as optical imaging of intrinsic signals, and/or electrophysiology. In this competitive renewal application, we aim to determine the accurate interpretation of fMRI maps at columnar resolution, and further to investigate the spatial specificity and sensitivity of various high-resolution fMRI techniques using a well-established orientation column model at an ultra-high field of 9.4 Tesla. The hypotheses to be tested are (i) that regions of high intensity change in CBV-weighted fMRI mark the location of active cortical columns, and (ii) that a complex dependency of cerebral oxygen consumption, CBF,and CBV responses reduces the specificity of BOLD fMRI relative to CBF-orCBV- weighted fMRI. The long-term goal of these investigations is to examine the spatial specificity of existing fMRI techniques to ultimately yield the capability of mapping columnar structures in both animals and humans non-invasively. Further insight into functional columnar organization in animals and humans will greatly facilitate our basic understanding of the structure, development and plasticity of cortical columns.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
5R01EB003324-09
Application #
7568896
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Liu, Guoying
Project Start
2000-12-01
Project End
2011-02-28
Budget Start
2009-03-01
Budget End
2011-02-28
Support Year
9
Fiscal Year
2009
Total Cost
$306,823
Indirect Cost
Name
University of Pittsburgh
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
004514360
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Iordanova, Bistra; Vazquez, Alberto; Kozai, Takashi Dy et al. (2018) Optogenetic investigation of the variable neurovascular coupling along the interhemispheric circuits. J Cereb Blood Flow Metab 38:627-640
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Poplawsky, Alexander John; Fukuda, Mitsuhiro; Kang, Bok-Man et al. (2017) Dominance of layer-specific microvessel dilation in contrast-enhanced high-resolution fMRI: Comparison between hemodynamic spread and vascular architecture with CLARITY. Neuroimage :
Jin, Tao; Wang, Ping; Hitchens, T Kevin et al. (2017) Enhancing sensitivity of pH-weighted MRI with combination of amide and guanidyl CEST. Neuroimage 157:341-350
Vasireddi, Anil K; Vazquez, Alberto L; Whitney, David E et al. (2016) Functional Connectivity of Resting Hemodynamic Signals in Submillimeter Orientation Columns of the Visual Cortex. Brain Connect :
Murphy, Matthew C; Poplawsky, Alexander J; Vazquez, Alberto L et al. (2016) Improved spatial accuracy of functional maps in the rat olfactory bulb using supervised machine learning approach. Neuroimage 137:1-8

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