Publications from the Magnetic Resonance Imaging and Spectroscopy Section.
Zhai, Tianye; Salmeron, Betty Jo; Gu, Hong; Adinoff, Bryon; Stein, Elliot A; Yang, Yihong Functional connectivity of dorsolateral prefrontal cortex predicts cocaine relapse: implications for neuromodulation treatment Journal Article In: Brain communications, 3 (2), pp. fcab120–fcab120, 2021, ISBN: 2632-1297. Cover, Christopher G; Kesner, Andrew J; Ukani, Shehzad; Stein, Elliot A; Ikemoto, Satoshi; Yang, Yihong; Lu, Hanbing Whole brain dynamics during optogenetic self-stimulation of the medial prefrontal cortex in mice Journal Article In: Communications Biology, 4 (1), pp. 66, 2021, ISBN: 2399-3642. Tsai, Pei-Jung; Keeley, Robin J; Carmack, Stephanie A; Vendruscolo, Janaina C M; Lu, Hanbing; Gu, Hong; Vendruscolo, Leandro F; Koob, George F; Lin, Ching-Po; Stein, Elliot A; Yang, Yihong Converging structural and functional evidence for a rat salience network Journal Article In: Biological Psychiatry, 2020, ISBN: 0006-3223. Gu, Hong; Schulz, Kurt P; Fan, Jin; Yang, Yihong Temporal Dynamics of Functional Brain States Underlie Cognitive Performance Journal Article In: Cerebral Cortex, 31 (4), pp. 2125-2138, 2020, ISSN: 1047-3211. Hu, Yuzheng; Salmeron, Betty Jo; Krasnova, Irina N; Gu, Hong; Lu, Hanbing; Bonci, Antonello; Cadet, Jean L; Stein, Elliot A; Yang, Yihong Compulsive drug use is associated with imbalance of orbitofrontal- and prelimbic-striatal circuits in punishment-resistant individuals. Journal Article In: Proc Natl Acad Sci U S A, 116 (18), pp. 9066–9071, 2019, ISSN: 1091-6490 (Electronic); 0027-8424 (Linking). Gu, Hong; Hu, Yuzheng; Chen, Xi; He, Yong; Yang, Yihong Regional excitation-inhibition balance predicts default-mode network deactivation via functional connectivity. Journal Article In: Neuroimage, 185 , pp. 388–397, 2019, ISSN: 1095-9572 (Electronic); 1053-8119 (Linking). Meng, Qinglei; Jing, Li; Badjo, Jean Paul; Du, Xiaoming; Hong, Elliot; Yang, Yihong; Lu, Hanbing; Choa, Fow-Sen A novel transcranial magnetic stimulator for focal stimulation of rodent brain. Journal Article In: Brain Stimul, 11 (3), pp. 663–665, 2018, ISSN: 1876-4754 (Electronic); 1876-4754 (Linking). Geng, Xiujuan; Hu, Yuzheng; Gu, Hong; Salmeron, Betty Jo; Adinoff, Bryon; Stein, Elliot A; Yang, Yihong Salience and default mode network dysregulation in chronic cocaine users predict treatment outcome. Journal Article In: Brain, 140 (5), pp. 1513–1524, 2017, ISSN: 1460-2156 (Electronic); 0006-8950 (Linking). Hsu, Li-Ming; Liang, Xia; Gu, Hong; Brynildsen, Julia K; Stark, Jennifer A; Ash, Jessica A; Lin, Ching-Po; Lu, Hanbing; Rapp, Peter R; Stein, Elliot A; Yang, Yihong Constituents and functional implications of the rat default mode network. Journal Article In: Proc Natl Acad Sci U S A, 113 (31), pp. E4541-7, 2016, ISSN: 1091-6490 (Electronic); 0027-8424 (Linking). Hu, Yuzheng; Salmeron, Betty Jo; Gu, Hong; Stein, Elliot A; Yang, Yihong In: JAMA Psychiatry, 72 (6), pp. 584–592, 2015, ISSN: 2168-6238 (Electronic); 2168-622X (Linking).2021
@article{Zhai:2021tn,
title = {Functional connectivity of dorsolateral prefrontal cortex predicts cocaine relapse: implications for neuromodulation treatment},
author = {Tianye Zhai and Betty Jo Salmeron and Hong Gu and Bryon Adinoff and Elliot A Stein and Yihong Yang},
url = {https://pubmed.ncbi.nlm.nih.gov/34189458/},
doi = {10.1093/braincomms/fcab120},
isbn = {2632-1297},
year = {2021},
date = {2021-06-02},
journal = {Brain communications},
volume = {3},
number = {2},
pages = {fcab120--fcab120},
publisher = {Oxford University Press},
abstract = {Relapse is one of the most perplexing problems of addiction. The dorsolateral prefrontal cortex is crucially involved in numerous cognitive and affective processes that are implicated in the phenotypes of both substance use disorders and other neuropsychiatric diseases and has become the principal site to deliver transcranial magnetic stimulation for their treatment. However, the dorsolateral prefrontal cortex is an anatomically large and functionally heterogeneous region, and the specific dorsolateral prefrontal cortex locus and dorsolateral prefrontal cortex-based functional circuits that contribute to drug relapse and/or treatment outcome remain unknown. We systematically investigated the relationship of cocaine relapse with functional circuits from 98 dorsolateral prefrontal cortex regions-of-interest defined by evenly sampling the entire surface of bilateral dorsolateral prefrontal cortex in a cohort of cocaine dependent patients (n = 43, 5 Fr) following a psychosocial treatment intervention. Cox regression models were utilized to predict relapse likelihood based on dorsolateral prefrontal cortex functional connectivity strength. Functional connectivity from only 3 of the 98 dorsolateral prefrontal cortex loci, one in the left and two in the right hemisphere, significantly predicted cocaine relapse with an accuracy of 83.9%, 84.6% and 85.4%, respectively. Combining all three loci significantly improved prediction validity to 87.5%. Protective and risk circuits related to these dorsolateral prefrontal cortex loci were identified that have previously been implicated to support 'bottom up' drive to use drug and 'top down' control over behaviour together with social emotional, learning and memory processing. Three dorsolateral prefrontal cortex-centric circuits were identified that predict relapse to cocaine use with high accuracy. These functionally distinct dorsolateral prefrontal cortex-based circuits provide insights into the multiple roles played by the dorsolateral prefrontal cortex in cognitive and affective functioning that affects treatment outcome. The identified dorsolateral prefrontal cortex loci may serve as potential neuromodulation targets to be tested in subsequent clinical studies for addiction treatment and as clinically relevant biomarkers of its efficacy. Zhai et al. identify three dorsolateral prefrontal cortex (dlPFC)-centric circuits that predict cocaine relapse with high accuracy, providing insights into the multiple roles of the dlPFC in brain functioning that affects treatment outcome and suggesting the dlPFC loci as potential neuromodulation targets for addiction treatment.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
@article{Cover:2021vd,
title = {Whole brain dynamics during optogenetic self-stimulation of the medial prefrontal cortex in mice},
author = {Christopher G Cover and Andrew J Kesner and Shehzad Ukani and Elliot A Stein and Satoshi Ikemoto and Yihong Yang and Hanbing Lu},
url = {https://pubmed.ncbi.nlm.nih.gov/33446857/},
doi = {10.1038/s42003-020-01612-x},
isbn = {2399-3642},
year = {2021},
date = {2021-01-01},
journal = {Communications Biology},
volume = {4},
number = {1},
pages = {66},
abstract = {Intracranial self-stimulation, in which an animal performs an operant response to receive regional brain electrical stimulation, is a widely used procedure to study motivated behavior. While local neuronal activity has long been measured immediately before or after the operant, imaging the whole brain in real-time remains a challenge. Herein we report a method that permits functional MRI (fMRI) of brain dynamics while mice are cued to perform an operant task: licking a spout to receive optogenetic stimulation to the medial prefrontal cortex (MPFC) during a cue ON, but not cue OFF. Licking during cue ON results in activation of a widely distributed network consistent with underlying MPFC projections, while licking during cue OFF (without optogenetic stimulation) leads to negative fMRI signal in brain regions involved in acute extinction. Noninvasive whole brain readout combined with circuit-specific neuromodulation opens an avenue for investigating adaptive behavior in both healthy and disease models.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2020
@article{Tsai:kq,
title = {Converging structural and functional evidence for a rat salience network},
author = {Pei-Jung Tsai and Robin J Keeley and Stephanie A Carmack and Janaina C M Vendruscolo and Hanbing Lu and Hong Gu and Leandro F Vendruscolo and George F Koob and Ching-Po Lin and Elliot A Stein and Yihong Yang},
url = {https://doi.org/10.1016/j.biopsych.2020.06.023},
isbn = {0006-3223},
year = {2020},
date = {2020-06-24},
urldate = {2020-06-24},
booktitle = {Biological Psychiatry},
journal = {Biological Psychiatry},
publisher = {Elsevier},
abstract = {Background
The salience network (SN) is dysregulated in many neuropsychiatric disorders, including substance use disorder. Initially described in humans, identification of a rodent SN would provide the ability to mechanistically interrogate this network in preclinical models of neuropsychiatric disorders.
Methods
We used modularity analysis on resting-state functional MRI data of rats (n=32) to parcellate rat insula into functional subdivisions and to identify a potential rat SN based on functional connectivity patterns from the insular subdivisions. We then used mouse tract tracing data from the Allen brain atlas to confirm the network’s underlying structural connectivity. We next compared functional connectivity profiles of the SN across rat, marmoset (n=10) and humans (n=30). Finally, we assessed rat SN’s response to conditioned cues in rats (n=21) with a history of heroin self-administration.
Results
We identified a putative rat SN, which consists of primarily the ventral anterior insula and anterior cingulate cortex, based on functional connectivity patterns from the ventral anterior insular division. Functional connectivity architecture of the rat SN is supported by the mouse neuronal tracer data. Moreover, the anatomical profile of the identified rat SN is similar to that of non-human primates and humans. Finally, we demonstrate that the rat SN responds to conditioned cues and increases functional connectivity to the Default Mode Network during conditioned heroin withdrawal.
Conclusions
The neurobiological identification of a rat SN together with a demonstration of its functional relevance provides a novel platform with which to interrogate its functional significance in normative and neuropsychiatric disease models.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The salience network (SN) is dysregulated in many neuropsychiatric disorders, including substance use disorder. Initially described in humans, identification of a rodent SN would provide the ability to mechanistically interrogate this network in preclinical models of neuropsychiatric disorders.
Methods
We used modularity analysis on resting-state functional MRI data of rats (n=32) to parcellate rat insula into functional subdivisions and to identify a potential rat SN based on functional connectivity patterns from the insular subdivisions. We then used mouse tract tracing data from the Allen brain atlas to confirm the network’s underlying structural connectivity. We next compared functional connectivity profiles of the SN across rat, marmoset (n=10) and humans (n=30). Finally, we assessed rat SN’s response to conditioned cues in rats (n=21) with a history of heroin self-administration.
Results
We identified a putative rat SN, which consists of primarily the ventral anterior insula and anterior cingulate cortex, based on functional connectivity patterns from the ventral anterior insular division. Functional connectivity architecture of the rat SN is supported by the mouse neuronal tracer data. Moreover, the anatomical profile of the identified rat SN is similar to that of non-human primates and humans. Finally, we demonstrate that the rat SN responds to conditioned cues and increases functional connectivity to the Default Mode Network during conditioned heroin withdrawal.
Conclusions
The neurobiological identification of a rat SN together with a demonstration of its functional relevance provides a novel platform with which to interrogate its functional significance in normative and neuropsychiatric disease models.
@article{10.1093/cercor/bhaa350,
title = {Temporal Dynamics of Functional Brain States Underlie Cognitive Performance},
author = {Hong Gu and Kurt P Schulz and Jin Fan and Yihong Yang},
url = {https://pubmed.ncbi.nlm.nih.gov/33258911/},
doi = {10.1093/cercor/bhaa350},
issn = {1047-3211},
year = {2020},
date = {2020-01-01},
journal = {Cerebral Cortex},
volume = {31},
number = {4},
pages = {2125-2138},
abstract = {The functional organization of the human brain adapts dynamically in response to a rapidly changing environment. However, the relation of these rapid changes in functional organization to cognitive functioning is not well understood. This study used a graph-based time-frame modularity analysis approach to identify temporally recurrent functional configuration patterns in neural responses to an n-back working memory task during fMRI. Working memory load was manipulated to investigate the functional relevance of the identified brain states. Four distinct brain states were defined by the predominant patterns of activation in the task-positive, default-mode, sensorimotor, and visual networks. Associated with escalating working memory load, the occurrence of the task-positive state and the probability of transitioning into this state increased. In contrast, the occurrence of the default-mode and sensorimotor states and the probability of these 2 states transitioning away from the task-positive state decreased. The task-positive state occurrence rate and the probability of transitioning from the default-mode state back to the task-positive state explained a significant and unique portion of the variance in task performance. The results demonstrate that dynamic brain activities support successful cognitive functioning and may have heuristic value for understanding abnormal cognitive functioning associated with multiple neuropsychiatric disorders.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2019
@article{Hu:2019aa,
title = {Compulsive drug use is associated with imbalance of orbitofrontal- and prelimbic-striatal circuits in punishment-resistant individuals.},
author = {Yuzheng Hu and Betty Jo Salmeron and Irina N Krasnova and Hong Gu and Hanbing Lu and Antonello Bonci and Jean L Cadet and Elliot A Stein and Yihong Yang},
url = {https://www.ncbi.nlm.nih.gov/pubmed/30988198},
doi = {10.1073/pnas.1819978116},
issn = {1091-6490 (Electronic); 0027-8424 (Linking)},
year = {2019},
date = {2019-04-30},
urldate = {2019-04-30},
journal = {Proc Natl Acad Sci U S A},
volume = {116},
number = {18},
pages = {9066--9071},
address = {Neuroimaging Research Branch, National Institute on Drug Abuse, Intramural Research Programs, National Institutes of Health, Baltimore, MD 21224; yihongyang@intra.nida.nih.gov huyuzheng@zju.edu.cn.},
abstract = {Substance use disorders (SUDs) impose severe negative impacts upon individuals, their families, and society. Clinical studies demonstrate that some chronic stimulant users are able to curtail their drug use when faced with adverse consequences while others continue to compulsively use drugs. The mechanisms underlying this dichotomy are poorly understood, which hampers the development of effective individualized treatments of a disorder that currently has no Food and Drug Administration-approved pharmacological treatments. In the present study, using a rat model of methamphetamine self-administration (SA) in the presence of concomitant foot shocks, thought to parallel compulsive drug taking by humans, we found that SA behavior correlated with alterations in the balance between an increased orbitofrontal cortex-dorsomedial striatal "go" circuit and a decreased prelimbic cortex-ventrolateral striatal "stop" circuit. Critically, this correlation was seen only in rats who continued to self-administer at a relatively high rate despite receiving foot shocks of increasing intensity. While the stop circuit functional connectivity became negative after repeated SA in all rats, "shock-resistant" rats showed strengthening of this negative connectivity after shock exposure. In contrast, "shock-sensitive" rats showed a return toward their baseline levels after shock exposure. These results may help guide novel noninvasive brain stimulation therapies aimed at restoring the physiological balance between stop and go circuits in SUDs.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
@article{Gu:2019aa,
title = {Regional excitation-inhibition balance predicts default-mode network deactivation via functional connectivity.},
author = {Hong Gu and Yuzheng Hu and Xi Chen and Yong He and Yihong Yang},
url = {https://www.ncbi.nlm.nih.gov/pubmed/30359729},
doi = {10.1016/j.neuroimage.2018.10.055},
issn = {1095-9572 (Electronic); 1053-8119 (Linking)},
year = {2019},
date = {2019-01-15},
journal = {Neuroimage},
volume = {185},
pages = {388--397},
address = {Neuroimaging Research Branch, National Institute on Drug Abuse, Intramural Research Programs, National Institutes of Health, Baltimore, MD, 21224, USA.},
abstract = {Deactivation of the default mode network (DMN) is one of the most reliable observations from neuroimaging and has significant implications in development, aging, and various neuropsychiatric disorders. However, the neural mechanism underlying DMN deactivation remains elusive. As the coordination of regional neurochemical substrates and interregional neural interactions are both essential in support of brain functions, a quantitative description of how they impact DMN deactivation may provide new insights into the mechanism. Using an n-back working memory task fMRI and magnetic resonance spectroscopy, we probed the pairwise relationship between task-induced deactivation, interregional functional connectivity and regional excitation-inhibition balance (evaluated by glutamate/GABA ratio) in the posterior cingulate cortex/precuneus (PCC/PCu). Task-induced PCC/PCu deactivation correlated with its excitation-inhibition balance and interregional functional connectivity, where participants with lower glutamate/GABA ratio, stronger intra-DMN connections and stronger antagonistic DMN-SN (salience network)/ECN (executive control network) inter-network connections had greater PCC/PCu deactivation. Mediation analyses revealed that the DMN-SN functional interactions partially mediated the relationship between task-induced deactivation and the excitation-inhibition balance at the PCC/PCu. The triple-relationship discovered in the present study has the potential to bridge DMN-deactivation related findings from various neuroimaging modalities and may provide new insights into the neural mechanism of DMN deactivation. Moreover, this finding may have significant implications for neuropsychiatric disorders related to the DMN dysfunction and suggests an integrated application of pharmacological and neuromodulation-based strategies for rescuing DMN deactivation deficits.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2018
@article{Meng:2018aa,
title = {A novel transcranial magnetic stimulator for focal stimulation of rodent brain.},
author = {Qinglei Meng and Li Jing and Jean Paul Badjo and Xiaoming Du and Elliot Hong and Yihong Yang and Hanbing Lu and Fow-Sen Choa},
url = {https://www.ncbi.nlm.nih.gov/pubmed/29534946},
doi = {10.1016/j.brs.2018.02.018},
issn = {1876-4754 (Electronic); 1876-4754 (Linking)},
year = {2018},
date = {2018-06-01},
journal = {Brain Stimul},
volume = {11},
number = {3},
pages = {663--665},
address = {Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, MD, United States; Intramural Research Program, National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), Baltimore, MD, United States.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2017
@article{Geng2017,
title = {Salience and default mode network dysregulation in chronic cocaine users predict treatment outcome.},
author = {Xiujuan Geng and Yuzheng Hu and Hong Gu and Betty Jo Salmeron and Bryon Adinoff and Elliot A Stein and Yihong Yang},
url = {https://www.ncbi.nlm.nih.gov/pubmed/28334915},
doi = {10.1093/brain/awx036},
issn = {1460-2156 (Electronic); 0006-8950 (Linking)},
year = {2017},
date = {2017-05-01},
journal = {Brain},
volume = {140},
number = {5},
pages = {1513--1524},
address = {Neuroimaging Research Branch, National Institute on Drug Abuse, Intramural Research Program, National Institutes of Health, Baltimore, MD, USA.},
abstract = {While chronic cocaine use is associated with abnormalities in both brain structure and function within and interactions between regions, previous studies have been limited to interrogating structure and function independently, and the detected neural differences have not been applied to independent samples to assess the clinical relevance of results. We investigated consequences of structural differences on resting-state functional connectivity in cocaine addiction and tested whether resting-state functional connectivity of the identified circuits predict relapse in an independent cohort. Subjects included 64 non-treatment-seeking cocaine users (NTSCUs) and 67 healthy control subjects and an independent treatment-completed cohort (n = 45) of cocaine-dependent individuals scanned at the end of a 30-day residential treatment programme. Differences in cortical thickness and related resting-state functional connectivity between NTSCUs and healthy control subjects were identified. Survival analysis, applying cortical thickness of the identified regions, resting-state functional connectivity of the identified circuits and clinical characteristics to the treatment cohort, was used to predict relapse. Lower cortical thickness in bilateral insula and higher thickness in bilateral temporal pole were found in NTSCUs versus healthy control subjects. Whole brain resting-state functional connectivity analyses with these four different anatomical regions as seeds revealed eight weaker circuits including within the salience network (insula seeds) and between temporal pole and elements of the default mode network in NTSCUs. Applying these circuits and clinical characteristics to the independent cocaine-dependent treatment cohort, functional connectivity between right temporal pole and medial prefrontal cortex, combined with years of education, predicted relapse status at 150 days with 88% accuracy. Deficits in the salience network suggest an impaired ability to process physiologically salient events, while abnormalities in a temporal pole-medial prefrontal cortex circuit might speak to the social-emotional functional alterations in cocaine addiction. The involvement of the temporal pole-medial prefrontal cortex circuit in a model highly predictive of relapse highlights the importance of social-emotional functions in cocaine dependence, and provides a potential underlying neural target for therapeutic interventions, and for identifying those at high risk of relapse.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2016
@article{Hsu2016,
title = {Constituents and functional implications of the rat default mode network.},
author = {Li-Ming Hsu and Xia Liang and Hong Gu and Julia K Brynildsen and Jennifer A Stark and Jessica A Ash and Ching-Po Lin and Hanbing Lu and Peter R Rapp and Elliot A Stein and Yihong Yang},
url = {http://www.ncbi.nlm.nih.gov/pubmed/27439860},
doi = {10.1073/pnas.1601485113},
issn = {1091-6490 (Electronic); 0027-8424 (Linking)},
year = {2016},
date = {2016-08-02},
journal = {Proc Natl Acad Sci U S A},
volume = {113},
number = {31},
pages = {E4541-7},
address = {Neuroimaging Research Branch, National Institute on Drug Abuse, Baltimore, MD 21224; Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei 112, Taiwan;},
abstract = {The default mode network (DMN) has been suggested to support a variety of self-referential functions in humans and has been fractionated into subsystems based on distinct responses to cognitive tasks and functional connectivity architecture. Such subsystems are thought to reflect functional hierarchy and segregation within the network. Because preclinical models can inform translational studies of neuropsychiatric disorders, partitioning of the DMN in nonhuman species, which has previously not been reported, may inform both physiology and pathophysiology of the human DMN. In this study, we sought to identify constituents of the rat DMN using resting-state functional MRI (rs-fMRI) and diffusion tensor imaging. After identifying DMN using a group-level independent-component analysis on the rs-fMRI data, modularity analyses fractionated the DMN into an anterior and a posterior subsystem, which were further segregated into five modules. Diffusion tensor imaging tractography demonstrates a close relationship between fiber density and the functional connectivity between DMN regions, and provides anatomical evidence to support the detected DMN subsystems. Finally, distinct modulation was seen within and between these DMN subcomponents using a neurocognitive aging model. Taken together, these results suggest that, like the human DMN, the rat DMN can be partitioned into several subcomponents that may support distinct functions. These data encourage further investigation into the neurobiological mechanisms of DMN processing in preclinical models of both normal and disease states.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2015
@article{Hu2015,
title = {Impaired functional connectivity within and between frontostriatal circuits and its association with compulsive drug use and trait impulsivity in cocaine addiction.},
author = {Yuzheng Hu and Betty Jo Salmeron and Hong Gu and Elliot A Stein and Yihong Yang},
url = {https://www.ncbi.nlm.nih.gov/pubmed/25853901},
doi = {10.1001/jamapsychiatry.2015.1},
issn = {2168-6238 (Electronic); 2168-622X (Linking)},
year = {2015},
date = {2015-06-01},
journal = {JAMA Psychiatry},
volume = {72},
number = {6},
pages = {584--592},
address = {Neuroimaging Research Branch, Intramural Research Program National Institute on Drug Abuse, Baltimore, Maryland.},
abstract = {IMPORTANCE: Converging evidence has long identified both impulsivity and compulsivity as key psychological constructs in drug addiction. Although dysregulated striatal-cortical network interactions have been identified in cocaine addiction, the association between these brain networks and addiction is poorly understood. OBJECTIVES: To test the hypothesis that cocaine addiction is associated with disturbances in striatal-cortical communication as captured by resting-state functional connectivity (rsFC), measured from coherent spontaneous fluctuations in the blood oxygenation level-dependent functional magnetic resonance imaging signal, and to explore the relationships between striatal rsFC, trait impulsivity, and uncontrolled drug use in cocaine addiction. DESIGN, SETTING, AND PARTICIPANTS: A case-control, cross-sectional study was conducted at the National Institute on Drug Abuse Intramural Research Program outpatient magnetic resonance imaging facility. Data used in the present study were collected between December 8, 2005, and September 30, 2011. Participants included 56 non-treatment-seeking cocaine users (CUs) (52 with cocaine dependence and 3 with cocaine abuse) and 56 healthy individuals serving as controls (HCs) matched on age, sex, years of education, race, estimated intelligence, and smoking status. MAIN OUTCOMES AND MEASURES: Voxelwise statistical parametric analysis testing the rsFC strength differences between CUs and HCs in brain regions functionally connected to 6 striatal subregions defined a priori. RESULTS: Increased rsFC strength was observed predominantly in striatal-frontal circuits; decreased rsFC was found between the striatum and cingulate, striatal, temporal, hippocampal/amygdalar, and insular regions in the CU group compared with the HCs. Increased striatal-dorsal lateral prefrontal cortex connectivity strength was positively correlated with the amount of recent cocaine use (uncorrected P < .046) and elevated trait impulsivity in the CUs (uncorrected P < .012), and an index reflecting the balance between striatal-dorsal anterior cingulate cortex and striatal-anterior prefrontal/orbitofrontal cortex circuits was significantly associated with loss of control over cocaine use (corrected P < .012). CONCLUSIONS AND RELEVANCE: Cocaine addiction is associated with disturbed rsFC in several specific striatal-cortical circuits. Specifically, compulsive cocaine use, a defining characteristic of dependence, was associated with a balance of increased striatal-anterior prefrontal/orbitofrontal and decreased striatal-dorsal anterior cingulate connectivity; trait impulsivity, both a risk factor for and a consequence of cocaine use, was associated with increased dorsal striatal-dorsal lateral prefrontal cortex connectivity uniquely in CUs. These findings provide new insights toward the neurobiological mechanisms of addiction and suggest potential novel therapeutic targets for treatment.},
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pubstate = {published},
tppubtype = {article}
}