Magnetic Resonance Imaging and Spectroscopy Section – Publications

@article{Yang2015,
title = {Withdrawal from long-term methamphetamine self-administration 'normalizes' neurometabolites in rhesus monkeys: a (1) H MR spectroscopy study.},
author = {Shaolin Yang and Annabelle M Belcher and Svetlana Chefer and Bruce D Vaupel and Charles W Schindler and Elliot A Stein and Yihong Yang},
url = {https://www.ncbi.nlm.nih.gov/pubmed/23910722},
doi = {10.1111/adb.12078},
issn = {1369-1600 (Electronic); 1355-6215 (Linking)},
year = {2015},
date = {2015-01-01},
journal = {Addict Biol},
volume = {20},
number = {1},
pages = {69--79},
address = {Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, USA; Departments of Psychiatry, Radiology, and Bioengineering, University of Illinois at Chicago, Chicago, IL, USA.},
abstract = {(1) H magnetic resonance spectroscopy has demonstrated alterations in several neurometabolites in methamphetamine (METH)-dependent individuals in brain regions implicated in addiction. Yet, it is unclear whether these neurochemicals return to homeostatic levels after an individual abstains from drug use, a difficult question to address due to high recidivism and poor study retention in human subjects. We thus utilized a non-human primate model of addiction to explore the effects of long-term drug exposure and withdrawal on brain neurochemistry. Ten rhesus macaque monkeys on an active METH self-administration protocol (average use 4.6 +/- 0.8 years, average daily intake between 0.4 and 1.2 mg/kg) and 10 age- and sex-matched drug-naive controls (CONT) served as subjects. Concentrations of several neurochemicals were evaluated at several timepoints following withdrawal from drug availability (10 monkeys at 1 week and 1 and 3 months, and 6 monkeys at 6 and 12 months; CONT examined at one timepoint). At 1 week following METH withdrawal, we found increases in myo-inositol in anterior cingulate cortex in the METH group relative to CONT. These alterations showed a linear pattern of decreased levels ('normalization') by 1 year of abstinence. We also found decreases in glutamine and Glx (composed mainly of glutamate and glutamine) in the caudate-putamen of the same animals at early withdrawal that showed a similar linear pattern of increasing concentration by 1 year. These results demonstrate that despite protracted, long-term use, neurochemical changes seen following long-term drug administration do not persist following prolonged abstinence, suggesting therapeutic effects of long-term withdrawal from drug use.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Lerman2014,
title = {Large-scale brain network coupling predicts acute nicotine abstinence effects on craving and cognitive function.},
author = {Caryn Lerman and Hong Gu and James Loughead and Kosha Ruparel and Yihong Yang and Elliot A Stein},
url = {https://www.ncbi.nlm.nih.gov/pubmed/24622915},
doi = {10.1001/jamapsychiatry.2013.4091},
issn = {2168-6238 (Electronic); 2168-622X (Linking)},
year = {2014},
date = {2014-05-01},
journal = {JAMA Psychiatry},
volume = {71},
number = {5},
pages = {523--530},
address = {Center for Interdisciplinary Research on Nicotine Addiction, Department of Psychiatry, University of Pennsylvania, Philadelphia.},
abstract = {IMPORTANCE: Interactions of large-scale brain networks may underlie cognitive dysfunctions in psychiatric and addictive disorders. OBJECTIVES: To test the hypothesis that the strength of coupling among 3 large-scale brain networks--salience, executive control, and default mode--will reflect the state of nicotine withdrawal (vs smoking satiety) and will predict abstinence-induced craving and cognitive deficits and to develop a resource allocation index (RAI) that reflects the combined strength of interactions among the 3 large-scale networks. DESIGN, SETTING, AND PARTICIPANTS: A within-subject functional magnetic resonance imaging study in an academic medical center compared resting-state functional connectivity coherence strength after 24 hours of abstinence and after smoking satiety. We examined the relationship of abstinence-induced changes in the RAI with alterations in subjective, behavioral, and neural functions. We included 37 healthy smoking volunteers, aged 19 to 61 years, for analyses. INTERVENTIONS: Twenty-four hours of abstinence vs smoking satiety. MAIN OUTCOMES AND MEASURES: Inter-network connectivity strength (primary) and the relationship with subjective, behavioral, and neural measures of nicotine withdrawal during abstinence vs smoking satiety states (secondary). RESULTS: The RAI was significantly lower in the abstinent compared with the smoking satiety states (left RAI},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Miao2014,
title = {Detecting resting-state brain activity by spontaneous cerebral blood volume fluctuations using whole brain vascular space occupancy imaging.},
author = {Miao, Xinyuan and Gu, Hong and Yan, Lirong and Lu, Hanzhang and Wang, Danny J J and Zhou, Xiaohong Joe and Zhuo, Yan and Yang, Yihong},
url = {https://www.ncbi.nlm.nih.gov/pubmed/24055705},
doi = {10.1016/j.neuroimage.2013.09.019},
issn = {1095-9572 (Electronic); 1053-8119 (Linking)},
year = {2014},
date = {2014-01-01},
journal = {Neuroimage},
volume = {84},
pages = {575--584},
abstract = {Resting-state brain activity has been investigated extensively using BOLD contrast. However, BOLD signal represents the combined effects of multiple physiological processes and its spatial localization is less accurate than that of cerebral blood flow and volume (CBF and CBF, respectively). In this study, we demonstrate that resting-state brain activity can be reliably detected by spontaneous fluctuations of CBV-weighted signal using whole-brain gradient and spin echo (GRASE) based vascular space occupancy (VASO) imaging. Specifically, using independent component analysis, intrinsic brain networks, including default mode, salience, executive control, visual, auditory, and sensorimotor networks were revealed robustly by the VASO technique. We further demonstrate that task-evoked VASO signal aligned well with expected gray matter areas, while blood-oxygenation level dependent (BOLD) signal extended outside of these areas probably due to their different spatial specificity. The improved spatial localization of VASO is consistent with previous studies using animal models. Moreover, we showed that the 3D-GRASE VASO images had reduced susceptibility-induced signal voiding, compared to the BOLD technique. This is attributed to the fact that VASO does not require T2* weighting, thus the acquisition can use a shorter TE and can employ spin-echo scheme. Consequently VASO-based functional connectivity signals were well preserved in brain regions that tend to suffer from signal loss and geometric distortion in BOLD, such as orbital prefrontal cortex. Our study suggests that 3D-GRASE VASO imaging, with its improved spatial specificity and less sensitivity to susceptibility artifacts, may have advantages in resting-state fMRI studies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Zou2013,
title = {Intrinsic resting-state activity predicts working memory brain activation and behavioral performance.},
author = {Zou, Qihong and Ross, Thomas J and Gu, Hong and Geng, Xiujuan and Zuo, Xi-Nian and Hong, L Elliot and Gao, Jia-Hong and Stein, Elliot A and Zang, Yu-Feng and Yang, Yihong},
url = {https://www.ncbi.nlm.nih.gov/pubmed/22711376},
doi = {10.1002/hbm.22136},
issn = {1097-0193 (Electronic); 1065-9471 (Linking)},
year = {2013},
date = {2013-12-01},
journal = {Hum Brain Mapp},
volume = {34},
number = {12},
pages = {3204--3215},
abstract = {Although resting-state brain activity has been demonstrated to correspond with task-evoked brain activation, the relationship between intrinsic and evoked brain activity has not been fully characterized. For example, it is unclear whether intrinsic activity can also predict task-evoked deactivation and whether the rest-task relationship is dependent on task load. In this study, we addressed these issues on 40 healthy control subjects using resting-state and task-driven [N-back working memory (WM) task] functional magnetic resonance imaging data collected in the same session. Using amplitude of low-frequency fluctuation (ALFF) as an index of intrinsic resting-state activity, we found that ALFF in the middle frontal gyrus and inferior/superior parietal lobules was positively correlated with WM task-evoked activation, while ALFF in the medial prefrontal cortex, posterior cingulate cortex, superior frontal gyrus, superior temporal gyrus, and fusiform gyrus was negatively correlated with WM task-evoked deactivation. Further, the relationship between the intrinsic resting-state activity and task-evoked activation in lateral/superior frontal gyri, inferior/superior parietal lobules, superior temporal gyrus, and midline regions was stronger at higher WM task loads. In addition, both resting-state activity and the task-evoked activation in the superior parietal lobule/precuneus were significantly correlated with the WM task behavioral performance, explaining similar portions of intersubject performance variance. Together, these findings suggest that intrinsic resting-state activity facilitates or is permissive of specific brain circuit engagement to perform a cognitive task, and that resting activity can predict subsequent task-evoked brain responses and behavioral performance.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Hu2013,
title = {Resting-state glutamate and GABA concentrations predict task-induced deactivation in the default mode network.},
author = {Yuzheng Hu and Xi Chen and Hong Gu and Yihong Yang},
url = {https://www.ncbi.nlm.nih.gov/pubmed/24259578},
doi = {10.1523/JNEUROSCI.1973-13.2013},
issn = {1529-2401 (Electronic); 0270-6474 (Linking)},
year = {2013},
date = {2013-11-20},
journal = {J Neurosci},
volume = {33},
number = {47},
pages = {18566--18573},
address = {Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, Maryland 21224.},
abstract = {Deactivation of the human brain's default mode network (DMN) is regarded as suppression of endogenous activity to support exogenous task-related processes. This phenomenon has important functional relevance and insufficient DMN deactivation has been implicated in several neuropsychiatric disorders. However, the neurochemical mechanism of the DMN's deactivation remains largely unknown. In the present study, we test the hypothesis that the major excitatory and inhibitory neurotransmitters, glutamate and GABA, respectively, are associated with DMN deactivation. We used magnetic resonance spectroscopy to measure neurotransmitter concentrations in the posterior cingulate cortex/precuneus (PCC/PCu), a key component of the DMN, and functional magnetic resonance imaging to evaluate DMN deactivation induced by an n-back working memory task. Our results demonstrate significant associations of glutamate and GABA with DMN deactivation. Specifically, high regional GABA concentration in the PCC/PCu area is associated with enhanced deactivation induced by the task in the same region, whereas high glutamate concentration is associated with reduced deactivation. Furthermore, the association between GABA and DMN deactivation increases with the cognitive loads. These neurochemical characteristics of DMN deactivation may provide novel insights toward better understanding of the DMN's functions under normal physiological conditions and dysfunctions in neuropsychiatric disorders.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Belcher2013,
title = {Large-scale brain networks in the awake, truly resting marmoset monkey.},
author = {Belcher, Annabelle M and Yen, Cecil C and Stepp, Haley and Gu, Hong and Lu, Hanbing and Yang, Yihong and Silva, Afonso C and Stein, Elliot A},
url = {https://www.ncbi.nlm.nih.gov/pubmed/24133280},
doi = {10.1523/JNEUROSCI.3146-13.2013},
issn = {1529-2401 (Electronic); 0270-6474 (Linking)},
year = {2013},
date = {2013-10-16},
journal = {J Neurosci},
volume = {33},
number = {42},
pages = {16796--16804},
abstract = {Resting-state functional MRI is a powerful tool that is increasingly used as a noninvasive method for investigating whole-brain circuitry and holds great potential as a possible diagnostic for disease. Despite this potential, few resting-state studies have used animal models (of which nonhuman primates represent our best opportunity of understanding complex human neuropsychiatric disease), and no work has characterized networks in awake, truly resting animals. Here we present results from a small New World monkey that allows for the characterization of resting-state networks in the awake state. Six adult common marmosets (Callithrix jacchus) were acclimated to light, comfortable restraint using individualized helmets. Following behavioral training, resting BOLD data were acquired during eight consecutive 10 min scans for each conscious subject. Group independent component analysis revealed 12 brain networks that overlap substantially with known anatomically constrained circuits seen in the awake human. Specifically, we found eight sensory and "lower-order" networks (four visual, two somatomotor, one cerebellar, and one caudate-putamen network), and four "higher-order" association networks (one default mode-like network, one orbitofrontal, one frontopolar, and one network resembling the human salience network). In addition to their functional relevance, these network patterns bear great correspondence to those previously described in awake humans. This first-of-its-kind report in an awake New World nonhuman primate provides a platform for mechanistic neurobiological examination for existing disease models established in the marmoset.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Liu2013,
title = {Dorsolateral caudate nucleus differentiates cocaine from natural reward-associated contextual cues.},
author = {Hua-Shan Liu and Svetlana Chefer and Hanbing Lu and Karine Guillem and William Rea and Pradeep Kurup and Yihong Yang and Laura Peoples and Elliot A Stein},
url = {https://www.ncbi.nlm.nih.gov/pubmed/23431137},
doi = {10.1073/pnas.1207531110},
issn = {1091-6490 (Electronic); 0027-8424 (Linking)},
year = {2013},
date = {2013-03-05},
journal = {Proc Natl Acad Sci U S A},
volume = {110},
number = {10},
pages = {4093--4098},
address = {Neuroimaging Research Branch, National Institute on Drug Abuse, Intramural Research Program, National Institutes of Health, Baltimore, MD 21224, USA.},
abstract = {Chronic drug administration induces neuroplastic changes within brain circuits regulating cognitive control and/or emotions. Following repeated pairings between drug intake and environmental cues, increased sensitivity to or salience of these contextual cues provoke conscious or unconscious craving and enhance susceptibility to relapse. To explore brain circuits participating in such experience-induced plasticity, we combined functional MRI with a preclinical drug vs. food self-administration (SA) withdrawal model. Specifically, two groups of rats were trained to associate odor cues with the availability of i.v. cocaine or oral sucrose, respectively. After 20 d of cocaine or sucrose SA followed by prolonged (30 d) forced abstinence, animals were presented with odor cues previously associated with or without (S+/S-) reinforcer (cocaine/sucrose) availability while undergoing functional MRI scans. ANOVA results demonstrate that a learning effect distinguishing S+ from S- was seen in the insula and nucleus accumbens, with the insula response reflecting the individual history of cocaine SA intake. A main effect of group, distinguishing cocaine from sucrose, was seen in the medial prefrontal cortex (infralimbic, prelimbic, and cingulate cortex) and dorsolateral striatum. Critically, only the dorsomedial striatum demonstrated a double dissociation between the two SA groups and learning (S+ vs. S-). These findings demonstrate altered cortico-limbic-striatal reward-related processing to learned, environment reward-associated contextual odor cues, which may serve as potential biomarkers for therapeutic interventions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Liang2013,
title = {Coupling of functional connectivity and regional cerebral blood flow reveals a physiological basis for network hubs of the human brain.},
author = {Xia Liang and Qihong Zou and Yong He and Yihong Yang},
url = {https://www.ncbi.nlm.nih.gov/pubmed/23319644},
doi = {10.1073/pnas.1214900110},
issn = {1091-6490 (Electronic); 0027-8424 (Linking)},
year = {2013},
date = {2013-01-29},
journal = {Proc Natl Acad Sci U S A},
volume = {110},
number = {5},
pages = {1929--1934},
address = {Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD 21224, USA.},
abstract = {Human brain functional networks contain a few densely connected hubs that play a vital role in transferring information across regions during resting and task states. However, the relationship of these functional hubs to measures of brain physiology, such as regional cerebral blood flow (rCBF), remains incompletely understood. Here, we used functional MRI data of blood-oxygenation-level-dependent and arterial-spin-labeling perfusion contrasts to investigate the relationship between functional connectivity strength (FCS) and rCBF during resting and an N-back working-memory task. During resting state, functional brain hubs with higher FCS were identified, primarily in the default-mode, insula, and visual regions. The FCS showed a striking spatial correlation with rCBF, and the correlation was stronger in the default-mode network (DMN; including medial frontal-parietal cortices) and executive control network (ECN; including lateral frontal-parietal cortices) compared with visual and sensorimotor networks. Moreover, the relationship was connection-distance dependent; i.e., rCBF correlated stronger with long-range hubs than short-range ones. It is notable that several DMN and ECN regions exhibited higher rCBF per unit connectivity strength (rCBF/FCS ratio); whereas, this index was lower in posterior visual areas. During the working-memory experiment, both FCS-rCBF coupling and rCBF/FCS ratio were modulated by task load in the ECN and/or DMN regions. Finally, task-induced changes of FCS and rCBF in the lateral-parietal lobe positively correlated with behavioral performance. Together, our results indicate a tight coupling between blood supply and brain functional topology during rest and its modulation in response to task demands, which may shed light on the physiological basis of human brain functional connectome.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Wu2012,
title = {TE-dependent spatial and spectral specificity of functional connectivity.},
author = {Changwei W Wu and Hong Gu and Qihong Zou and Hanbing Lu and Elliot A Stein and Yihong Yang},
url = {https://www.ncbi.nlm.nih.gov/pubmed/22119650},
doi = {10.1016/j.neuroimage.2011.11.030},
issn = {1095-9572 (Electronic); 1053-8119 (Linking)},
year = {2012},
date = {2012-02-15},
journal = {Neuroimage},
volume = {59},
number = {4},
pages = {3075--3084},
address = {Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD 21224, USA.},
abstract = {Previous studies suggest that spontaneous fluctuations in the resting-state fMRI (RS-fMRI) signal may reflect fluctuations in transverse relaxation time (T(2)(*)) rather than spin density (S(0)). However, such S(0) and T(2)(*) features have not been well characterized. In this study, spatial and spectral characteristics of functional connectivity on sensorimotor, default-mode, dorsal attention, and primary visual systems were examined using a multiple gradient-echo sequence at 3T. In the spatial domain, we found broad, local correlations at short echo times (TE keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Geng2011,
title = {Diffeomorphic image registration of diffusion MRI using spherical harmonics.},
author = {Xiujuan Geng and Thomas J Ross and Hong Gu and Wanyong Shin and Wang Zhan and Yi-Ping Chao and Ching-Po Lin and Norbert Schuff and Yihong Yang},
url = {https://www.ncbi.nlm.nih.gov/pubmed/21134814},
doi = {10.1109/TMI.2010.2095027},
issn = {1558-254X (Electronic); 0278-0062 (Linking)},
year = {2011},
date = {2011-03-01},
journal = {IEEE Trans Med Imaging},
volume = {30},
number = {3},
pages = {747--758},
address = {Neuroimaging Research Branch, Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD 21224, USA. gengx@nida.nih.gov},
abstract = {Nonrigid registration of diffusion magnetic resonance imaging (MRI) is crucial for group analyses and building white matter and fiber tract atlases. Most current diffusion MRI registration techniques are limited to the alignment of diffusion tensor imaging (DTI) data. We propose a novel diffeomorphic registration method for high angular resolution diffusion images by mapping their orientation distribution functions (ODFs). ODFs can be reconstructed using q-ball imaging (QBI) techniques and represented by spherical harmonics (SHs) to resolve intra-voxel fiber crossings. The registration is based on optimizing a diffeomorphic demons cost function. Unlike scalar images, deforming ODF maps requires ODF reorientation to maintain its consistency with the local fiber orientations. Our method simultaneously reorients the ODFs by computing a Wigner rotation matrix at each voxel, and applies it to the SH coefficients during registration. Rotation of the coefficients avoids the estimation of principal directions, which has no analytical solution and is time consuming. The proposed method was validated on both simulated and real data sets with various metrics, which include the distance between the estimated and simulated transformation fields, the standard deviation of the general fractional anisotropy and the directional consistency of the deformed and reference images. The registration performance using SHs with different maximum orders were compared using these metrics. Results show that the diffeomorphic registration improved the affine alignment, and registration using SHs with higher order SHs further improved the registration accuracy by reducing the shape difference and improving the directional consistency of the registered and reference ODF maps.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}