Cocaine addiction is a brain disorder that takes a large societal and economical toll in the United States. Although neuroimaging has been increasingly used to assess neural substrates critical for drug addiction by examining brain activity in response to drug or drug cues, much less attention has been paid to spontaneous brain activity (SBA) in the absence of an exogenous stimulus. In fact, SBA is the major component of the whole brain activity that accounts for most of brain energy consumption, and is inevitably altered by the chronic and substantial neurobiological interference of cocaine addiction. Assessing SBA may therefore provide a versatile biomarker of disease progression or treatment effects. However, SBA still remains new to cocaine addiction with only two papers published to date reporting the seed-based resting functional connectivity difference in cocaine dependent brain. The use of blood-oxygen-level-dependent (BOLD) fMRI to assess SBA represents a major research activity that has seen an intensive period of growth recently. A large number of BOLD fMRI-derived SBA patterns have been demonstrated, and many of them appear to be modulated by disease states, carrying a great potential for drug addiction study as well. However, those patterns are generally based on relative measures, providing no quantitative information for clinical applications.
AIM 1 of this study is to derive a quantitative measure for characterizing the temporal fluctuations of SBA based on our recent pilot investigations. We will evaluate the measure using synthetic data and thousands of normal subjects'data from the 1000 Functional Connectomes Project.
AIM 2 is to identify SBA alterations in cocaine dependent brain. Our center has acquired resting BOLD fMRI data and resting arterial spin labeling (ASL) perfusion fMRI data from a large cohort of cocaine patients, providing an opportunity to investigate SBA questions that were not covered in the original data collection project. We will reuse those data to find both the temporal fluctuation changes and magnitude changes of SBA in cocaine patients as reflected by the proposed quantitative SBA measure and regional cerebral blood flow (CBF) measured by ASL MRI. Moreover, we will assess the functional connection network wise alterations in the cocaine addicted brain. Finally, we will (AIM 3) explore the utility of SBA (including the temporal dynamics and magnitude and the functional connection network properties) for predicting clinical outcomes including drug craving and relapse to cocaine use. The feasibility of the proposed aims is evidenced by the substantial preliminary investigations. The broad technical impact of this project is that the resulting quantitative temporal SBA measure will benefit not only addiction study, but also to the general resting fMRI-based SBA research in normal and clinical populations. The clinical impact of this project is that it will offer the first evidence that cocaine addiction is associated with altered temporal SBA and resting CBF and the entire functional connectivity network. It will also provide information about SBA-based craving and relapse to drug use prediction.
This project will assess the utility of spontaneous brain activity (SBA) measurements obtained using functional MRI for cocaine addiction study in conjunction with novel data analysis strategies. This study will provide the first quantitative insights int alterations in SBA and resting CBF in patients with cocaine addiction.
| Wang, Ze; Suh, Jesse; Duan, Dingna et al. (2017) A hypo-status in drug-dependent brain revealed by multi-modal MRI. Addict Biol 22:1622-1631 |
| Li, Zhengjun; Zang, Yu-Feng; Ding, Jianping et al. (2017) Assessing the mean strength and variations of the time-to-time fluctuations of resting-state brain activity. Med Biol Eng Comput 55:631-640 |
| Li, Zhengjun; Fang, Zhuo; Hager, Nathan et al. (2016) Hyper-resting brain entropy within chronic smokers and its moderation by Sex. Sci Rep 6:29435 |
| Wang, Ze; Suh, Jesse; Li, Zhengjun et al. (2015) A hyper-connected but less efficient small-world network in the substance-dependent brain. Drug Alcohol Depend 152:102-8 |
