Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) is an essential tool for mapping human brain activity in the medical and scientific communities. Despite its indispensable role, BOLD fMRI has not been routinely used to map sub-millimeter functional structures due to draining vein contributions, a relatively broad point spread function, and low neural activity-specific signal sensitivity. Multipe approaches to overcome these problems have included the use of ultrahigh magnetic fields, improved imaging techniques, and continuous cyclic stimulation paradigm (vs. block design). During the last grant period, optical imaging of intrinsic signals (OIS) confirmed that with these improvements, high BOLD fMRI responses co- localize with active orientation columns, thus demonstrating that functional columns can be mapped with hemodynamic-based fMRI. However, even with these approaches, the physiological source of columnar- resolution BOLD fMRI signals is unclear and there is relatively poor signal contrast between active and inactive columns. High-specificity fMRI techniques must be further explored and optimized before they can be more widely applied to the study of basic mechanisms with relevance to human brain. In this competitive renewal application investigating a well-established orientation column model of the cat visual cortex at 9.4 Tesla, we aim to systematically determine the physiological source of columnar-resolution BOLD fMRI signals, and investigate whether these signals can be enhanced non-invasively.
Specific Aim #1 is to determine the physiological source of columnar-resolution BOLD fMRI signals. There is an apparent discrepancy between BOLD and OIS results for neuronally-active vs. neighboring inactive columns;BOLD results suggest highest hyper-oxygenation in active columns, while OIS studies suggest highest hyper-oxygenation in inactive columns. To determine the physiological sources of columnar-resolution BOLD fMRI signals, BOLD fMRI, tissue oxygen tension, multi-unit activity, and OIS will be measured whether highest hyper-oxygenation occurs during stimulation at preferred or at non-preferred orientations. We hypothesize that change in the blood oxygenation levels are not the dominant contribution to column-specific BOLD fMRI responses.
Specific Aim #2 is to enhance sub-millimeter column-specific fMRI signals by non-invasive methods. BOLD fMRI has relatively poor sub-millimeter column-specific signal, thus its sensitivity may be enhanced with cerebral blood flow (CBF)-weighted fMRI and cerebral blood volume (CBV)-weighted fMRI. Thus, we propose to compare non-invasive, sub-millimeter column-specific responses for multiple techniques including BOLD fMRI, arterial CBV-enhanced fMRI with magnetization transfer effect, and CBF-enhanced fMRI. We hypothesize that non- invasive arterial CBV-weighted and CBF-weighted fMRI techniques will show enhanced fMRI responses from sub-millimeter functional structures. The long-term goal of these investigations is to improve the capability of mapping responses from fine functional structures in both animals and humans non-invasively.

Public Health Relevance

Blood oxygenation level dependent (BOLD) fMRI is a critical tool in the medical and scientific communities, but its utility for mapping small functional structures is not clear. Proposed investigations aim to investigate the specificity and sensitivity of submillimeter columnar-resolution fMRI and to improve the capability of mapping cortical columns, which will be important for functional development and reorganization in normal subjects and patients.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
5R01EB003324-12
Application #
8606658
Study Section
Medical Imaging Study Section (MEDI)
Program Officer
Liu, Guoying
Project Start
2000-12-01
Project End
2016-01-31
Budget Start
2014-02-01
Budget End
2015-01-31
Support Year
12
Fiscal Year
2014
Total Cost
$310,987
Indirect Cost
$92,737
Name
University of Pittsburgh
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
004514360
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Jin, Tao; Iordanova, Bistra; Hitchens, T Kevin et al. (2018) Chemical exchange-sensitive spin-lock (CESL) MRI of glucose and analogs in brain tumors. Magn Reson Med 80:488-495
Jin, Tao; Mehrens, Hunter; Wang, Ping et al. (2018) Chemical exchange-sensitive spin-lock MRI of glucose analog 3-O-methyl-d-glucose in normal and ischemic brain. J Cereb Blood Flow Metab 38:869-880
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
Vazquez, Alberto L; Fukuda, Mitsuhiro; Kim, Seong-Gi (2018) Inhibitory Neuron Activity Contributions to Hemodynamic Responses and Metabolic Load Examined Using an Inhibitory Optogenetic Mouse Model. Cereb Cortex 28:4105-4119
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
Lohani, S; Poplawsky, A J; Kim, S-G et al. (2017) Unexpected global impact of VTA dopamine neuron activation as measured by opto-fMRI. Mol Psychiatry 22:585-594
Poplawsky, Alexander John; Fukuda, Mitsuhiro; Kim, Seong-Gi (2017) Foundations of layer-specific fMRI and investigations of neurophysiological activity in the laminarized neocortex and olfactory bulb of animal models. Neuroimage :
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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