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  • 1
    Online Resource
    Online Resource
    Resting-State Glutamate and GABA Concentrations Predict Task-Induced Deactivation in the Default Mode Network
    Society for Neuroscience ; 2013
    In:  The Journal of Neuroscience Vol. 33, No. 47 ( 2013-11-20), p. 18566-18573
    Details
    In: The Journal of Neuroscience, Society for Neuroscience, Vol. 33, No. 47 ( 2013-11-20), p. 18566-18573
    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.
    Type of Medium: Online Resource
    ISSN: 0270-6474 , 1529-2401
    URL: Article
    DOI: 10.1523/JNEUROSCI.1973-13.2013
    Language: English
    Publisher: Society for Neuroscience
    Publication Date: 2013
    detail.hit.zdb_id: 1475274-8
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  • 2
    Online Resource
    Online Resource
    Interactions between the Salience and Default-Mode Networks Are Disrupted in Cocaine Addiction
    Society for Neuroscience ; 2015
    In:  The Journal of Neuroscience Vol. 35, No. 21 ( 2015-05-27), p. 8081-8090
    Details
    In: The Journal of Neuroscience, Society for Neuroscience, Vol. 35, No. 21 ( 2015-05-27), p. 8081-8090
    Abstract: Cocaine dependence is a complex neuropsychiatric disorder manifested as dysregulation of multiple behavioral, emotional, and cognitive constructs. Neuroimaging studies have begun to identify specific neurobiological circuit impairments in cocaine-dependent (CD) individuals that may underlie these symptoms. However, whether, where, and how the interactions within and between these circuits are disrupted remain largely unknown. We used resting-state fMRI and modularity network analysis to identify brain modules of a priori interest (default-mode network [DMN], salience network [SN] , executive control network [ECN], medial temporal lobe [MTL] , and striatum) in 47 CD and 47 matched healthy control (HC) participants and explored alterations within and between these brain modules as a function of addiction. At the module level, intermodule connectivity decreased between DMN and SN in CD. At the nodal level, several regions showed decreased connections with multiple modules in CD: the rostral anterior cingulate connection strength was reduced with SN and MTL; the posterior cingulate had reduced connections with ECN; and the bilateral insula demonstrated decreased connections with DMN. Furthermore, alexithymia, a personality trait previously associated with addiction, correlated negatively with intramodule connectivity within SN only in cocaine users. Our results indicate that cocaine addiction is associated with disrupted interactions among DMN, MTL, and SN, which have been implicated, respectively, in self-referential functions, emotion and memory, and coordinating between internal and external stimuli, providing novel and important insights into the neurobiological mechanisms of cocaine addiction.
    Type of Medium: Online Resource
    ISSN: 0270-6474 , 1529-2401
    URL: Article
    DOI: 10.1523/JNEUROSCI.3188-14.2015
    Language: English
    Publisher: Society for Neuroscience
    Publication Date: 2015
    detail.hit.zdb_id: 1475274-8
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  • 3
    Online Resource
    Online Resource
    Structural Abnormalities in the Brains of Human Subjects Who Use Methamphetamine
    Society for Neuroscience ; 2004
    In:  The Journal of Neuroscience Vol. 24, No. 26 ( 2004-06-30), p. 6028-6036
    Details
    In: The Journal of Neuroscience, Society for Neuroscience, Vol. 24, No. 26 ( 2004-06-30), p. 6028-6036
    Abstract: We visualize, for the first time, the profile of structural deficits in the human brain associated with chronic methamphetamine (MA) abuse. Studies of human subjects who have used MA chronically have revealed deficits in dopaminergic and serotonergic systems and cerebral metabolic abnormalities. Using magnetic resonance imaging (MRI) and new computational brain-mapping techniques, we determined the pattern of structural brain alterations associated with chronic MA abuse in human subjects and related these deficits to cognitive impairment. We used high-resolution MRI and surface-based computational image analyses to map regional abnormalities in the cortex, hippocampus, white matter, and ventricles in 22 human subjects who used MA and 21 age-matched, healthy controls. Cortical maps revealed severe gray-matter deficits in the cingulate, limbic, and paralimbic cortices of MA abusers (averaging 11.3% below control; p 〈 0.05). On average, MA abusers had 7.8% smaller hippocampal volumes than control subjects ( p 〈 0.01; left, p = 0.01; right, p 〈 0.05) and significant white-matter hypertrophy (7.0%; p 〈 0.01). Hippocampal deficits were mapped and correlated with memory performance on a word-recall test ( p 〈 0.05). MRI-based maps suggest that chronic methamphetamine abuse causes a selective pattern of cerebral deterioration that contributes to impaired memory performance. MA may selectively damage the medial temporal lobe and, consistent with metabolic studies, the cingulate-limbic cortex, inducing neuroadaptation, neuropil reduction, or cell death. Prominent white-matter hypertrophy may result from altered myelination and adaptive glial changes, including gliosis secondary to neuronal damage. These brain substrates may help account for the symptoms of MA abuse, providing therapeutic targets for drug-induced brain injury.
    Type of Medium: Online Resource
    ISSN: 0270-6474 , 1529-2401
    URL: Article
    DOI: 10.1523/JNEUROSCI.0713-04.2004
    Language: English
    Publisher: Society for Neuroscience
    Publication Date: 2004
    detail.hit.zdb_id: 1475274-8
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  • 4
    Online Resource
    Online Resource
    Large-Scale Brain Networks in the Awake, Truly Resting Marmoset Monkey
    Society for Neuroscience ; 2013
    In:  The Journal of Neuroscience Vol. 33, No. 42 ( 2013-10-16), p. 16796-16804
    Details
    In: The Journal of Neuroscience, Society for Neuroscience, Vol. 33, No. 42 ( 2013-10-16), p. 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.
    Type of Medium: Online Resource
    ISSN: 0270-6474 , 1529-2401
    URL: Article
    DOI: 10.1523/JNEUROSCI.3146-13.2013
    Language: English
    Publisher: Society for Neuroscience
    Publication Date: 2013
    detail.hit.zdb_id: 1475274-8
    SSG: 12
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  • 5
    Online Resource
    Online Resource
    Intrinsic Functional Connectivity Patterns Predict Consciousness Level and Recovery Outcome in Acquired Brain Injury
    Society for Neuroscience ; 2015
    In:  The Journal of Neuroscience Vol. 35, No. 37 ( 2015-09-16), p. 12932-12946
    Details
    In: The Journal of Neuroscience, Society for Neuroscience, Vol. 35, No. 37 ( 2015-09-16), p. 12932-12946
    Abstract: For accurate diagnosis and prognostic prediction of acquired brain injury (ABI), it is crucial to understand the neurobiological mechanisms underlying loss of consciousness. However, there is no consensus on which regions and networks act as biomarkers for consciousness level and recovery outcome in ABI. Using resting-state fMRI, we assessed intrinsic functional connectivity strength (FCS) of whole-brain networks in a large sample of 99 ABI patients with varying degrees of consciousness loss (including fully preserved consciousness state, minimally conscious state, unresponsive wakefulness syndrome/vegetative state, and coma) and 34 healthy control subjects. Consciousness level was evaluated using the Glasgow Coma Scale and Coma Recovery Scale-Revised on the day of fMRI scanning; recovery outcome was assessed using the Glasgow Outcome Scale 3 months after the fMRI scanning. One-way ANOVA of FCS, Spearman correlation analyses between FCS and the consciousness level and recovery outcome, and FCS-based multivariate pattern analysis were performed. We found decreased FCS with loss of consciousness primarily distributed in the posterior cingulate cortex/precuneus (PCC/PCU), medial prefrontal cortex, and lateral parietal cortex. The FCS values of these regions were significantly correlated with consciousness level and recovery outcome. Multivariate support vector machine discrimination analysis revealed that the FCS patterns predicted whether patients with unresponsive wakefulness syndrome/vegetative state and coma would regain consciousness with an accuracy of 81.25%, and the most discriminative region was the PCC/PCU. These findings suggest that intrinsic functional connectivity patterns of the human posteromedial cortex could serve as a potential indicator for consciousness level and recovery outcome in individuals with ABI. SIGNIFICANCE STATEMENT Varying degrees of consciousness loss and recovery are commonly observed in acquired brain injury patients, yet the underlying neurobiological mechanisms remain elusive. Using a large sample of patients with varying degrees of consciousness loss, we demonstrate that intrinsic functional connectivity strength in many brain regions, especially in the posterior cingulate cortex and precuneus, significantly correlated with consciousness level and recovery outcome. We further demonstrate that the functional connectivity pattern of these regions can predict patients with unresponsive wakefulness syndrome/vegetative state and coma would regain consciousness with an accuracy of 81.25%. Our study thus provides potentially important biomarkers of acquired brain injury in clinical diagnosis, prediction of recovery outcome, and decision making for treatment strategies for patients with severe loss of consciousness.
    Type of Medium: Online Resource
    ISSN: 0270-6474 , 1529-2401
    URL: Article
    DOI: 10.1523/JNEUROSCI.0415-15.2015
    Language: English
    Publisher: Society for Neuroscience
    Publication Date: 2015
    detail.hit.zdb_id: 1475274-8
    SSG: 12
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