Thomas Liu, PhD - US grants

Project Summary Since its introduction just over a decade ago, functional magnetic resonance imaging (fMRI) has rapidly become an indispensable tool for studies of the working human brain. The vast majority of fMRI studies utilize the blood oxygenation level dependent (BOLD) signal, which reflects the hemodynamic response to neural activity. In these studies, differences in the BOLD signal are typically interpreted as differences in neural activity. However, there is growing evidence that shifts in the baseline vascular state due to factors such as medication, age,and disease can significantly alter the amplitude and shape of the BOLD signal. These factors can increase the variability of the BOLD signal across subjects and experimental conditions and complicate the interpretation of fMRI experiments. The goal of this application is to determine whether non-invasive measures of the baseline vascular state can account for the variability in the BOLD signal that is caused by vasoactive agents and the aging process. The central hypothesis of this proposal, which is supported by strong preliminary data, is that a normalized measure of the power in low frequency components of the BOLD signal, referred to as the 0.1 Hz spectral index, can be used to probe the baseline vascular state and can account for a significant fraction of the variability in the BOLD response. The aims of this proposal are to (1) evaluate the ability of the 0.1 Hz spectral index and other measures of the baseline vascular state to account for the variability in the BOLD response caused by vasoactive agents, and (2) evaluate the ability of these measures to account for age-related variability in the BOLD response. These aims will be achieved using (1) studies that assess the impact of caffeine and hypercapnia on the baseline vascular state and the BOLD response and (2) studies that characterize the baseline vascular state and the BOLD response in young (20 to 45 years old)and old (65 to 95 years old) subjects. Relevance to Public Health The proposed studies are expected to provide the knowledge necessary for the application of the 0.1 Hz spectral index to the improved interpretation of fMRI studies. For example, once the predictive capability of the 0.1 Hz spectral index is demonstrated, it could be applied to studies evaluating the efficacy of various medications for mental illness. By enabling investigators to assess whether medication-related changes in the BOLD response reflect changes in neural activity or are primarily a reflection of the vascular effects of the medication, the 0.1 Hz spectral index would allow investigators to more effectively determine which medications are likely to be of clinical value.

DESCRIPTION (provided by applicant): Cerebral blood flow (CBF) is an important physiological quantity that reflects the delivery of blood to the brain. Measures of CBF can play a critical role in furthering our understanding of how the brain is altered by factors such as disease, age, and medication. In addition, there is a growing appreciation that changes in baseline CBF can significantly alter the amplitude and shape of the blood oxygenation level dependent (BOLD) signal that is measured in most functional magnetic resonance imaging (fMRI) studies of the brain. As a result, a growing number of NIH-funded fMRI studies are obtaining measures of baseline CBF as part of their protocols. These measures are typically obtained using arterial spin labeling (ASL), a magnetic resonance imaging (MRI) method that can provide quantitative measures of CBF in a relatively short amount of time (less than 10 minutes) without the need for external contrast agents. The increasing number of NIH-funded research studies acquiring ASL CBF measures presents a unique opportunity to create a comprehensive database of CBF measures spanning multiple groups and sites. The size and diversity of the combined data would greatly facilitate efforts to extend our understanding of how CBF varies with disease, age, race, ethnic origin, and medical treatment. The overall goal of this project is to create a comprehensive database of CBF measures that will allow investigators to share, analyze, mine, and interpret cerebral blood flow measures from multiple studies and sites. To achieve this goal we propose to build upon the infrastructure of the Biomedical Informatics Research Network (BIRN). The specific aims of the proposal are as follows: (1) Extend the BIRN Data Repository (BDR) to include a shared database of cerebral blood flow measures and associated data from a broad range of studies that are already funded by the NIH or other agencies. This aim will utilize and extend BIRN infrastructure tools, such as the Storage Resource Broker (SRB) for data storage and the Human Imaging Database (HID) environment for the storage, querying, and browsing of subject and image metadata. (2) Standardize protocols and tools for acquisition of ASL data. To ensure the quality of the data submitted to the database, we propose to implement and disseminate a comprehensive set of standardized scan protocols and quality assurance procedures to guide the correct acquisition of the CBF measures and facilitate the analysis and interpretation of the data.

Since its introduction over a decade ago, functional magnetic resonance imaging (fMRI) has revolutionized studies of the working human brain. While most fMRI studies measure the blood oxygenation level dependent (BOLD) response to a functional task, there has been growing interest in the use of resting-state BOLD fMRI, in which the connectivity between different brain regions is measured while the subject is at rest (e.g. not actively performing a task). Resting-state BOLD approaches may be particularly effective for clinical usage because they do not require the patient to perform a task and can be obtained in a short amount of time. A number of studies applying resting-state connectivity measures to the assessment of disease have reported significant disease-related changes in connectivity. However, the interpretation of these changes in connectivity is not straightforward, because the mechanisms underlying resting-state BOLD connectivity are not well understood. The BOLD signal represents the hemodynamic response to neural activity, and is a complicated function of changes in blood flow, blood volume, and oxygen metabolism. As a result, changes in resting-state connectivity can reflect a complex combination of neural, vascular, and metabolic factors. A better understanding of the primary factors that modulate resting-state connectivity is therefore critical for the accurate interpretation of resting-state measures. The goal of this proposal is to identify measures of neural power fluctuations and neurovascular coupling that can best account for changes in resting-state BOLD connectivity. The specific aims of this project are to identify the measures that most effectively explain changes in resting-state connectivity due to (a) caffeine usage and (b) inter-subject differences in physiology.

The Neuroimaging Core functions as a resource for instrumentation, data acquisition, processing, and analysis in support of the experiments conducted in Projects 1 and 2. This core will provide cutting edge neuroimaging advances and computational tools, which are important to optimize data processing. The director of this core, Dr. Thomas Liu, is also the Director of the UCSD Center for Functional Magnetic Resonance Imaging (fMRI) and, therefore, brings to bear the significant existing infrastructure of the UCSD Center for fMRI for this proposal. Moreover, Dr. Liu's expertise in perfusion imaging will help provide analysis approaches to determine whether general differences in blood perfusion across groups account for BOLD fMRI differences during the interoception and cue reactivity tasks, and will ensure high quality neuroimaging data. The specific aims of this core are: (1) To utilize neuroimaging procedures developed at the UCSD Center for fMRI to provide continued quality control of ongoing experiments. This aim will help us to optimize our imaging analyses steps and to have explicit quality control implemented similar to that of other large-scale fMRI studies. (2) To provide a core computational infrastructure to standardize and optimize the neuroimaging pipeline. This will help us to compare images obtained for Project 1 with those of Project 2 to better delineate the degree of dysregulated interoception across the addiction cycle. (3) To provide basic and advanced training for all CIDIA associated investigators for neuroimaging acquisition and analysis. This aim is focused primarily on combine educational and training activities in the Neuroimaging Core so as to economize our ability to bring in new investigators, maintain high level of expertise among neuroimaging investigators, and incorporate new insights from the literature to optimize the image analysis pathway. By accomplishing these aims, the core will primarily support Projects 1 and 2, which will make it easier and more appropriate to compare data sets across projects. However, we also envision that this core will begin to explore the possibility for future animal neuroimaging, which could be done in a full center extension of this initial project.

This SBIR Phase I project will develop a process for direct synthesis of silane utilizing silicon, hydrogen and a plasma arc.

The broader/commercial impact of the project will include the potential elimination of shipping of hazardous silane gas, and decreased production cost for silane gas. Both of these outcomes will have broad impact across the manufacturing of a wide variety of electronic equipment, computing equipment, solar power generation equipment, and other important products.

DESCRIPTION (provided by applicant): This shared instrumentation grant request funds to partially offset the cost of an upgrade of the current 3 Tesla whole body magnetic resonance imaging (MRI) system at the UCSD Center for Functional MRI (CFMRI). In comparison to our existing system, the upgrade is expected to provide significant improvements in performance in the following areas: (1) improved signal stability, (2) increased ability to perform demanding experimental protocols for functional MRI studies, and (3) a greater level of reliability, resulting in less down- time of the system. These improvements in performance will benefit over 30 currently funded NIH studies covering a diverse set of research areas, including the neurobiology of alcoholism, brain function in Alzheimer's disease, and the perception of pain in depression. The upgrade of the 3 Tesla system, which serves the needs of the San Diego research community, will allow the CFMRI to continue to support the cutting-edge research being performed at UCSD and its neighboring institutions. PUBLIC HEALTH RELEVANCE: The proposed system upgrade will greatly benefit ongoing NIH-funded studies that are focused on understanding the function of the brain in both health and disease. These studies are likely to result in the improved diagnosis and treatment of a number of health conditions, such as alcoholism, stroke, and Alzheimer's disease.

DESCRIPTION (provided by applicant): This shared instrumentation proposal request funds to support the upgrade of the 7T magnetic resonance imaging (MRI) magnet at the UCSD Center for Functional MRI (CFMRI). In specific, because performance issues with the current magnet have severely impacted the progress of over 20 currently funded NIH studies;we propose to acquire a modern and reliable magnet for use with our existing Bruker Avance II MRI console. The purchase of the 7 Tesla magnets is critical to a wide range of NIH-funded projects being performed at UCSD and its neighboring institutions, covering a diverse set of research areas, including studies of alcoholism, pulmonary disease, and cancer. Public Health Relevance: The proposed acquisition of the magnet is necessary to support ongoing NIH-funded studies that are focused on (1) developing new imaging methods for the diagnosis of disease and (2) achieving an understanding of the basic mechanisms underlying health and disease. These studies are likely to result in the improved diagnosis and treatment of a number of health conditions, such as alcoholism, cancer, and heart disease.

DESCRIPTION (provided by applicant): Resting-state functional connectivity magnetic resonance imaging (fcMRI) has recently emerged as a leading method for non-invasively characterizing the functional connections of the human brain. In fcMRI studies, a standard measure of connectivity between two brain regions is the temporal correlation between their respective resting-state functional MRI (fMRI) time series. For the computation of correlations, many studies use a pre-processing step known as global signal regression (GSR), in which a global mean signal is subtracted from all voxel time courses. While GSR can greatly improve the consistency and reliability of functional connectivity maps, its use is controversial because it may also introduce spurious negative correlations. Currently, there is not a clear consensus regarding how to best handle global signal confounds, with many fcMRI studies still continuing to use GSR, while others have adopted alternate methods due to concerns about GSR. This lack of agreement makes it difficult to compare fcMRI studies, as differing approaches can yield significantly different connectivity measures. The goals of this project are to develop a better understanding of the global signal and to use that knowledge to develop new methods for global signal correction. The aims of the study are to (1) Develop and evaluate a new approach for global signal correction and (2) Determine whether global signal variations reflect changes in underlying neuroelectric coherence.

DESCRIPTION (provided by applicant): In the context of increasing prevalence the brain bases of autism spectrum disorder (ASD) remain incompletely understood. There is growing consensus that ASD is a disorder of brain connectivity, but functional connectivity findings are inconsistent. Resting state functional MRI (rs-fMRI) data, considered ideal for the study of intrinsic functional connectivity, are being acquired by numerous groups and are now available in a large public database. However, known differences in behavioral and cognitive traits may significantly affect fMRI data collected in the 'resting state' and little is known about potential confounds that may result. This lack of knowledge is troubling in view of the ill-defined nature of the 'resting state', which largely eludes experimental control. Specifically, rs-fMRI connectivity has been solely examined using static approaches. The current proposal will use dynamic fMRI sliding window analyses in combination with EEG to investigate the dynamic variability of functional connectivity during the resting state. Samples of adolescents with ASD and matched typically developing (TD) participants from existing cohorts will be scanned using rs-fMRI with concurrent EEG. In two aims we will (1) test dynamic changes in connectivity across time, using a sliding window rs-fMRI analysis; and (2) use EEG data to examine dynamic changes in high temporal frequency bands and characterize temporal patterns observed in Aim 1 with respect to electrophysiological changes. We hypothesize that ASD participants will show greater variability of connectivity across time in and between several networks of interest (default mode, dorsal attention, saliency), accompanied by variability in electrophysiological states. The proposed project will be the first to combine fMRI and EEG for an in-depth investigation of dynamic changes during the 'resting state' in ASD. A better understanding of potentially systematic differences between ASD and TD participants in response to the resting state is a prerequisite for the adequate interpretation of group differences detected in rs-fMRI functional connectivity studies and is therefore urgently needed.

Project Summary Resting-state functional magnetic resonance imaging (rsfMRI) is a leading method for the non-invasive characterization of the functional connectivity and resting-state activity of the human brain. In our prior work we have found that rsfMRI measures of connectivity and signal variance can be significantly altered by the subject's vigilance state. Unless these differences in vigilance are taken into account, differences in connectivity strength and signal variance might be interpreted as a disease-related changes. Currently, electroencephalographic (EEG) measures of brain activity are considered the standard approach for the assessment of vigilance. However, their use in rsfMRI studies is limited due to the technical challenges and logistics involved in obtaining simultaneous rsfMRI and EEG measurements. An alternative approach that does not require the acquisition of EEG data would greatly facilitate the assessment of vigilance in a wide range of rsfMRI studies. The goal of this project is to develop and validate an rsfMRI-based measure of vigilance. The aims of the study are to (1) Develop and optimize rsfMRI-based measures of vigilance levels and fluctuations and (2) Perform a preliminary test of the efficacy of the method in a sample of subjects with schizophrenia.