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Wen X, Yue L, Du Z, Li L, Zhu Y, Yu D, Yuan K. Implications of neuroimaging findings in addiction. PSYCHORADIOLOGY 2023; 3:kkad006. [PMID: 38666116 PMCID: PMC10917371 DOI: 10.1093/psyrad/kkad006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Revised: 04/14/2023] [Accepted: 04/28/2023] [Indexed: 04/28/2024]
Affiliation(s)
- Xinwen Wen
- School of Life Science and Technology, Xidian University, Xi'an 710126, China
| | - Lirong Yue
- School of Life Science and Technology, Xidian University, Xi'an 710126, China
| | - Zhe Du
- School of Life Science and Technology, Xidian University, Xi'an 710126, China
| | - Linling Li
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen University, Shenzhen 518060, China
| | - Yuanqiang Zhu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
| | - Dahua Yu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou 014010, China
| | - Kai Yuan
- School of Life Science and Technology, Xidian University, Xi'an 710126, China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xidian University, Xi'an 710126, China
- Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an 710126, China
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2
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Lu L, Yang W, Zhao D, Wen X, Liu J, Liu J, Yuan K. Brain recovery of the NAc fibers and prediction of craving changes in person with heroin addiction: A longitudinal study. Drug Alcohol Depend 2023; 243:109749. [PMID: 36565569 DOI: 10.1016/j.drugalcdep.2022.109749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 11/14/2022] [Accepted: 12/07/2022] [Indexed: 12/23/2022]
Abstract
BACKGROUND Progress have been made in brain function recovery after long-term abstinence in person with heroin addiction (PHA). However, less is known about whether the nucleus accumbens (NAc) white matter pathways can recover in PHA by prolonged abstinence. METHODS Forty-two PHA and Thirty-nine age- and gender- matched healthy controls (HCs) were recruited. Two MRI scans were obtained at baseline (PHA1) and 8-month follow-up (PHA2). We employed tractography atlas-based analysis (TABS) method to investigate fractional anisotropy (FA) changes in NAc fiber tracts (i.e., Insula-NAc, ventral tegmental area (VTA)-NAc, medial prefrontal cortex (MPFC)-NAc) in PHA. A partial least square regression (PLSR) analysis was carried to explore whether FA of NAc fiber tracts can predict longitudinal craving changes. RESULTS Relative to HCs, lower FA was found in the right Insula-NAc and VTA-NAc fiber tracts in PHA1, and PHA2 showed increased FA values in these tracts compared with PHA1. Furthermore, changes of FA of NAc fiber tracts can predict longitudinal craving changes (r = 0.51). Additionally, craving changes can also be predicted from FA changes in the left Insula-NAc (r = 0.601) and VTA-NAc (r = 0.384) fiber alone. CONCLUSIONS Results indicated that the right Insula-NAc and VTA-NAc fiber tracts are potential biomarkers for brain recovery. Prediction of craving changes highlighted the utility of structural markers to inform clinical decision-making of treatment for PHA.
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Affiliation(s)
- Ling Lu
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, 710071, China
| | - Wenhan Yang
- Department of Radiology, Second Xiangya Hospital of Central South University, Changsha, China
| | - Desheng Zhao
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, 710071, China
| | - Xinwen Wen
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, 710071, China
| | - Jun Liu
- Department of Radiology, Second Xiangya Hospital of Central South University, Changsha, China.
| | - Jixin Liu
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, 710071, China.
| | - Kai Yuan
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, 710071, China; International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China; Information Processing Laboratory, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, China.
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3
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Cai S, Guo Z, Wang X, Huang K, Yuan K, Huang L. Cortical thickness differences are associated with cellular component morphogenesis of astrocytes and excitatory neurons in nonsuicidal self-injuring youth. Cereb Cortex 2023; 33:811-822. [PMID: 35253859 DOI: 10.1093/cercor/bhac103] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 02/16/2022] [Accepted: 02/17/2022] [Indexed: 02/03/2023] Open
Abstract
Nonsuicidal self-injury (NSSI) generally occurs in youth and probably progresses to suicide. An examination of cortical thickness differences (ΔCT) between NSSI individuals and controls is crucial to investigate potential neurobiological correlates. Notably, ΔCT are influenced by specific genetic factors, and a large proportion of cortical thinning is associated with the expression of genes that overlap in astrocytes and pyramidal cells. However, in NSSI youth, the mechanisms underlying the relations between the genetic and cell type-specific transcriptional signatures to ΔCT are unclear. Here, we studied the genetic association of ΔCT in NSSI youth by performing a partial least-squares regression (PLSR) analysis of gene expression data and 3D-T1 brain images of 45 NSSI youth and 75 controls. We extracted the top-10 Gene Ontology terms for the enrichment results of upregulated PLS component 1 genes related to ΔCT to conduct the cell-type classification and enrichment analysis. Enrichment of cell type-specific genes shows that cellular component morphogenesis of astrocytes and excitatory neurons accounts for the observed NSSI-specific ΔCT. We validated the main results in independent datasets to verify the robustness and specificity. We concluded that the brain ΔCT is associated with cellular component morphogenesis of astrocytes and excitatory neurons in NSSI youth.
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Affiliation(s)
- Suping Cai
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, PR China
| | - Zitong Guo
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, PR China
| | - Xuwen Wang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, PR China
| | - Kexin Huang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, PR China
| | - Kai Yuan
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, PR China.,School of Life Science andTechnology, Xidian University, Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi 710071, PR China.,Information Processing Laboratory, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia 014010, PR China.,Xi'an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, PR China
| | - Liyu Huang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, PR China
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4
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Amlung M, Owens MM, Hargreaves T, Gray JC, Murphy CM, MacKillop J, Sweet LH. Neuroeconomic predictors of smoking cessation outcomes: A preliminary study of delay discounting in treatment-seeking adult smokers. Psychiatry Res Neuroimaging 2022; 327:111555. [PMID: 36327864 PMCID: PMC9729436 DOI: 10.1016/j.pscychresns.2022.111555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 08/31/2022] [Accepted: 10/17/2022] [Indexed: 12/04/2022]
Abstract
Large proportions of smokers are unsuccessful in evidence-based smoking cessation treatment and identifying prognostic predictors may inform improvements in treatment. Steep discounting of delayed rewards (delay discounting) is a robust predictor of poor smoking cessation outcome, but the underlying neural predictors have not been investigated. Forty-one treatment-seeking adult smokers completed a functional magnetic resonance imaging (fMRI) delay discounting paradigm prior to initiating a 9-week smoking cessation treatment protocol. Behavioral performance significantly predicted treatment outcomes (verified 7-day abstinence, n = 18; relapse, n = 23). Participants in the relapse group exhibited smaller area under the curve (d = 1.10) and smaller AUC was correlated with fewer days to smoking relapse (r = 0.56, p < 0.001) Neural correlates of discounting included medial and dorsolateral prefrontal cortex, posterior cingulate, precuneus and anterior insula, and interactions between choice type and relapse status were present for the dorsolateral prefrontal cortex, precuneus and the striatum. This initial investigation implicates differential neural activity in regions associated with frontal executive and default mode activity, as well as motivational circuits. Larger samples are needed to improve the resolution in identifying the neural underpinnings linking steep delay discounting to smoking cessation.
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Affiliation(s)
- Michael Amlung
- Department of Applied Behavioral Science, University of Kansas, Lawrence, KS, United States of America; Cofrin Logan Center for Addiction Research and Treatment, University of Kansas, Lawrence, KS, United States of America.
| | - Max M Owens
- Department of Psychiatry and Behavioural Neuroscience, McMaster University, Hamilton, ON Canada; Peter Boris Centre for Addictions Research, McMaster University, Hamilton, ON, Canada
| | - Tegan Hargreaves
- Peter Boris Centre for Addictions Research, McMaster University, Hamilton, ON, Canada
| | - Joshua C Gray
- Department of Medical and Clinical Psychology, Uniformed Services University, Bethesda, MD, United States of America
| | - Cara M Murphy
- Behavioral and Social Sciences, Brown University, Providence, RI, United States of America
| | - James MacKillop
- Department of Psychiatry and Behavioural Neuroscience, McMaster University, Hamilton, ON Canada; Peter Boris Centre for Addictions Research, McMaster University, Hamilton, ON, Canada
| | - Lawrence H Sweet
- Department of Psychology, University of Georgia, Athens, GA United States of America
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Yip SW, Lichenstein SD, Garrison K, Averill CL, Viswanath H, Salas R, Abdallah CG. Effects of Smoking Status and State on Intrinsic Connectivity. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:895-904. [PMID: 33618016 PMCID: PMC8373998 DOI: 10.1016/j.bpsc.2021.02.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 01/18/2021] [Accepted: 02/02/2021] [Indexed: 01/21/2023]
Abstract
BACKGROUND Smoking behavior during the first 24 hours of a quit attempt is a significant predictor of longer-term abstinence, yet little is known about the neurobiology of early tobacco abstinence. Specifically, the effects of acute tobacco deprivation and reinstatement on brain function-particularly at the level of large-scale network dynamics and assessed across the entire brain-remain incompletely understood. To address this gap, this study used a mixed within- and between-subjects design to assess the effects of smoking status (yes/no smoker) and state (deprived vs. satiated) on whole-brain patterns of intrinsic connectivity. METHODS Participants included 42 tobacco smokers who underwent resting-state functional magnetic resonance imaging following overnight abstinence (deprived state) and following smoking reinstatement (satiated state, randomized order across participants). Sixty healthy control nonsmokers underwent a single resting-state scan using the same acquisition parameters. Functional connectivity data were analyzed using both a canonical network-of-interest approach and a whole-brain, data-driven approach, i.e., intrinsic connectivity distribution. RESULTS Network-of-interest-based analyses indicated decreased functional connectivity within frontoparietal and salience networks among smokers relative to nonsmokers as well as effects of smoking state on default mode connectivity. In addition, intrinsic connectivity distribution analyses identified novel between-group differences in subcortical-cerebellar and corticocerebellar networks that were largely smoking state dependent. CONCLUSIONS These data demonstrate the importance of considering smoking state and the utility of using both theory- and data-driven analysis approaches. These data provide much-needed insight into the functional neurobiology of early abstinence, which may be used in the development of novel treatments.
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Affiliation(s)
- Sarah W Yip
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut.
| | - Sarah D Lichenstein
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Kathleen Garrison
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Christopher L Averill
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut; Clinical Neurosciences Division, Veterans Administration National Center for PTSD, West Haven, Connecticut; Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas; Michael E. DeBakey Veterans Affairs Medical Center, Houston, Texas
| | - Humsini Viswanath
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas
| | - Ramiro Salas
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas; Michael E. DeBakey Veterans Affairs Medical Center, Houston, Texas
| | - Chadi G Abdallah
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut; Clinical Neurosciences Division, Veterans Administration National Center for PTSD, West Haven, Connecticut; Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas; Michael E. DeBakey Veterans Affairs Medical Center, Houston, Texas
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6
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Lu L, Yang W, Zhang X, Tang F, Du Y, Fan L, Luo J, Yan C, Zhang J, Li J, Liu J, von Deneen KM, Yu D, Liu J, Yuan K. Potential brain recovery of frontostriatal circuits in heroin users after prolonged abstinence: A preliminary study. J Psychiatr Res 2022; 152:326-334. [PMID: 35785575 DOI: 10.1016/j.jpsychires.2022.06.036] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Revised: 06/23/2022] [Accepted: 06/24/2022] [Indexed: 11/16/2022]
Abstract
Neuroscientists have devoted efforts to explore potential brain recovery after prolonged abstinence in heroin users (HU). However, not much is known about whether frontostriatal circuits can recover after prolonged abstinence in HU. An eight-month longitudinal study was carried out for HU. Two MRI scans were obtained at baseline (HU1) and 8-month follow-up (HU2). The functional and structural connectivities of dorsal and ventral frontostriatal pathways were measured by resting-state functional connectivity (RSFC) and diffusion tensor imaging (DTI). Correlation analyses were employed to reveal the associations between neuroimaging and behavioral changes. Results suggested that relative to healthy controls (HCs), HU1 showed lower fractional anisotropy (FA) in the right dorsolateral prefrontal cortex (DLPFC)-to-caudate tracts and medial orbitofrontal cortex (mOFC)-to-nucleus accumbens (NAc) tracts as well as decreased RSFC in the left mOFC-NAc circuits. Longitudinal results revealed reduced craving and enhanced cognitive control in HU2 compared with HU1. After prolonged abstinence, HU2 showed increased FA values in the right DLPFC-caudate and mOFC-NAc tracts as well as increased RSFC strength in the bilateral mOFC-NAc circuits compared with HU1. In addition, changes in RSFC and FA values in the right mOFC-NAc circuit were negatively correlated with craving score changes. Similarly, negative correlations were also found between changes of RSFC in the bilateral DLPFC-caudate circuits and TMT-A scores. We provided scientific evidence for brain recovery of the dorsal and ventral frontostriatal circuits in HU after prolonged abstinence, and these circuits may be potential neuroimaging biomarkers for cognition and craving changes.
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Affiliation(s)
- Ling Lu
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China; Engineering Research Center of Molecular and Neuroimaging, Ministry of Education, Xi'an, Shaanxi, 710071, China
| | - Wenhan Yang
- Department of Radiology, Second Xiangya Hospital of Central South University, Changsha, China
| | - Xiaozi Zhang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China; Engineering Research Center of Molecular and Neuroimaging, Ministry of Education, Xi'an, Shaanxi, 710071, China
| | - Fei Tang
- Department of Radiology, Second Xiangya Hospital of Central South University, Changsha, China
| | - Yanyao Du
- Department of Radiology, Second Xiangya Hospital of Central South University, Changsha, China
| | - Li Fan
- Department of Radiology, Second Xiangya Hospital of Central South University, Changsha, China
| | - Jing Luo
- Department of Radiology, Second Xiangya Hospital of Central South University, Changsha, China
| | - Cui Yan
- Department of Radiology, Second Xiangya Hospital of Central South University, Changsha, China
| | - Jun Zhang
- Hunan Judicial Police Academy, Changsha, China
| | - Jun Li
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China; Engineering Research Center of Molecular and Neuroimaging, Ministry of Education, Xi'an, Shaanxi, 710071, China
| | - Jixin Liu
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China; Engineering Research Center of Molecular and Neuroimaging, Ministry of Education, Xi'an, Shaanxi, 710071, China
| | - Karen M von Deneen
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China
| | - Dahua Yu
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China
| | - Jun Liu
- Department of Radiology, Second Xiangya Hospital of Central South University, Changsha, China.
| | - Kai Yuan
- Center for Brain Imaging, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China; Engineering Research Center of Molecular and Neuroimaging, Ministry of Education, Xi'an, Shaanxi, 710071, China; International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710126, China; Information Processing Laboratory, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, China.
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Zhou M, Hu Y, Huang R, Zhou Y, Xie X, Zhang S, Jia S, Zhang Y, Xue T, Dong F, Lu X, Yuan K, Yu D. Right arcuate fasciculus and left uncinate fasciculus abnormalities in young smoker. Addict Biol 2022; 27:e13132. [PMID: 35229948 DOI: 10.1111/adb.13132] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Revised: 12/01/2021] [Accepted: 12/07/2021] [Indexed: 11/29/2022]
Abstract
Previous diffusion tensor imaging (DTI) studies had investigated the white matter (WM) integrity abnormalities in smokers. Exposure to nicotine disrupts neurodevelopment during adolescence, possibly by disrupting the trophic effects of acetylcholine. However, little is known about the diffusion parameters of specific fibre bundles at multiple locations in young smokers. Thirty-seven young smokers and 29 age-, education- and gender-matched healthy non-smokers participated in this study. Automated Fibre Quantification (AFQ) was employed to investigate the WM microstructure in young smokers by integrating multiple indices. Diffusion parameters, that is, fractional anisotropy (FA), axial diffusion (AD), radial diffusion (RD) and mean diffusion (MD), were calculated at 100 points along the length of 18 major brain tracts. The relationships between neuroimaging differences and smoking behaviours were explored, including Fagerström Test of Nicotine Dependence (FTND) and pack-years. Compared with non-smokers, young smokers showed significantly increased FA, AD and decreased RD in the left uncinate fasciculus (UF) and right thalamic radiation (TR), increased AD, RD and decreased FA in the right arcuate fasciculus (Arc). Correlation analyses revealed that FA values of the left UF and RD values of the right Arc were negatively correlated with FTND score in smokers and FA values of the right Arc were positively correlated with FTND scores. Positive correlation was observed between AD values of the left UF and pack-years in smokers. The findings enhanced our understanding of the potential effect of adolescent smoking on WM microstructure.
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Affiliation(s)
- Mi Zhou
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
| | - Yiting Hu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
| | - Ruoyan Huang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
| | - Yang Zhou
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
| | - Xiaoyan Xie
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
| | - Shidi Zhang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
| | - Shaodi Jia
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
| | - Yunmiao Zhang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
| | - Ting Xue
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
| | - Fang Dong
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
| | - Xiaoqi Lu
- School of Information Engineering Inner Mongolia University of Technology Huhhot China
| | - Kai Yuan
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
- School of Life Science and Technology Xidian University Xi'an China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education Xi'an China
| | - Dahua Yu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
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von Deneen KM, Hussain H, Waheed J, Xinwen W, Yu D, Yuan K. Comparison of frontostriatal circuits in adolescent nicotine addiction and internet gaming disorder. J Behav Addict 2022; 11:26-39. [PMID: 35049521 PMCID: PMC9109629 DOI: 10.1556/2006.2021.00086] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 11/08/2021] [Accepted: 12/16/2021] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Recently, there has been significantly increased participation in online gaming and other addictive behaviors particularly in adolescents. Tendencies to avoid social interaction and become more involved in technology-based activities pose the danger of creating unhealthy addictions. Thus, the presence of relatively immature cognitive control and high risk-taking properties makes adolescence a period of major changes leading to an increased rate of emotional disorders and addiction. AIMS The critical roles of frontostriatal circuits in addiction have become the primary focus associated with reward in the striatum and cognitive control in the PFC. Internet gaming disorder (IGD) and nicotine addiction are currently becoming more and more serious. METHODS In the light of neuroimaging, the similarity between brain mechanisms causing substance use disorder (SUD) and IGD have been described in previous literature. RESULTS In particular, two distinct brain systems affect the way we act accounting for uncharacteristic neural function in addiction: the affective system comprises of the striatum driven by emotional, reward-related, and internal stimuli, and a cognitive system consisting of the prefrontal cortex (PFC) supporting the ventral affective system's actions via inhibitory control. DISCUSSION AND CONCLUSION Therefore, as a novel concept, we focused on the implication of frontostriatal circuits in nicotine addiction and IGD by reviewing the main findings from our studies compared to those of others. We hope that all of these neuroimaging findings can lead to effective intervention and treatment for addiction especially during this critical period.
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Affiliation(s)
- Karen M. von Deneen
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, Peoples R China,Corresponding authors. E-mail: (), ,
| | - Hadi Hussain
- Xi'an Jiaotong University, 74 Yanta Street, Yanta District, Xi'an, Shaanxi 710001, Peoples R China
| | - Junaid Waheed
- Xi'an Jiaotong University, 74 Yanta Street, Yanta District, Xi'an, Shaanxi 710001, Peoples R China
| | - Wen Xinwen
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, Peoples R China
| | - Dahua Yu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia 014010, Peoples R China,Corresponding authors. E-mail: (), ,
| | - Kai Yuan
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, Peoples R China,Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia 014010, Peoples R China,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, 710071, Peoples R China,Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, Peoples R China,Corresponding authors. E-mail: (), ,
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9
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Li X, Dong F, Zhang Y, Wang J, Wang Z, Sun Y, Zhang M, Xue T, Ren Y, Lv X, Yuan K, Yu D. Altered resting-state electroencephalography microstate characteristics in young male smokers. Front Psychiatry 2022; 13:1008007. [PMID: 36267852 PMCID: PMC9577082 DOI: 10.3389/fpsyt.2022.1008007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Accepted: 09/06/2022] [Indexed: 11/24/2022] Open
Abstract
The development of nicotine addiction was associated with the abnormalities of intrinsic functional networks during the resting state in young adult smokers. As a whole-brain imaging approach, EEG microstate analysis treated multichannel EEG recordings as a series of quasi-steady microscopic states which were related to the resting-state networks (RSNs) found by fMRI. The aim of this study was to examine whether the resting-state EEG microstate analysis may provide novel insights into the abnormal temporal properties of intrinsic brain activities in young smokers. We used 64-channel resting-state EEG datasets to investigate alterations in microstate characteristics between twenty-five young smokers and 25 age- and gender-matched non-smoking controls. Four classic EEG microstates (microstate A, B, C, and D) were obtained, and the four temporal parameters of each microstate were extracted, i.e., duration, occurrence, coverage, and transition probabilities. Compared with non-smoking controls, young smokers showed decreased occurrence of microstate C and increased duration of microstate D. Furthermore, both the duration and coverage of microstate D were significantly negatively correlated with Fagerstrom Test of Nicotine Dependence (FTND) in young smoker group. The complex changes in the microstate time-domain parameters might correspond to the abnormalities of RSNs in analyses of FC measured with fMRI in the previous studies and indicate the altered specific brain functions in young smokers. Microstate D could be potentially represented as a selective biomarker for predicting the dependence degree of adolescent smokers on cigarettes. These results suggested that EEG microstate analysis might detect the deviant functions of large-scale cortical activities in young smokers and provide a new perspective for the study of brain networks of adolescent smokers.
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Affiliation(s)
- Xiaojian Li
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Fang Dong
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Yunmiao Zhang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Juan Wang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Zhengxi Wang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Yaning Sun
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Ming Zhang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Ting Xue
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Yan Ren
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Xiaoqi Lv
- College of Information Engineering, Inner Mongolia University of Technology, Hohhot, China
| | - Kai Yuan
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China.,School of Life Sciences and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Dahua Yu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
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10
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Wu F, Dong P, Wu G, Deng J, Ni Z, Gao X, Li P, Li B, Yuan J, Sun H. Impulsive trait mediates the relationship between white matter integrity of prefrontal-striatal circuits and the severity of dependence in alcoholism. Front Psychiatry 2022; 13:985948. [PMID: 36159935 PMCID: PMC9490322 DOI: 10.3389/fpsyt.2022.985948] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 08/15/2022] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Alcohol dependence (AD) remains one of the major public health concerns. Impulsivity plays a central role in the transfer from recreational alcohol use to dependence and relapse. White matter dysfunction has been implicated in alcohol addiction behaviors and impulsivity. However, little is known about the role of systematic striatal structural connections underlying the mechanism of impulsive traits in AD. METHODS In our study, we used seed-based classification by probabilistic tractography with five target masks of striatal circuits to explore the differences in white matter integrity (fractional anisotropy, FA) in AD male patients (N = 51) and healthy controls (N = 27). We mainly explored the correlation between FA of the striatal circuits and impulsive traits (Barratt Impulsiveness Scale, BIS-11), and the mediation role of impulsivity in white matter integrity and the severity of alcohol dependence. RESULTS Compared with healthy controls, AD showed much lower FA in the left and right striatum-supplementary motor area (SMA) and left striatum-amygdala. We also found the decreased FA of right striatum-vlPFC was correlated with higher impulsivity. Besides, the relationship between reduced FA of right striatum-vlPFC and severity of dependence could be mediated by impulsivity. CONCLUSION In our study, we found disrupted white matter integrity in systematic striatal circuits in AD and the decreased FA of right striatum-vlPFC was correlated with higher impulsivity in AD. Our main findings provide evidence for reduced white matter integrity of systematic striatal circuits and the underlying mechanisms of impulsivity in male AD individuals.
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Affiliation(s)
- Fei Wu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Ping Dong
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Guowei Wu
- Chinese Institute for Brain Research, Beijing, China
| | - Jiahui Deng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Zhaojun Ni
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Xuejiao Gao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Peng Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Bing Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Junliang Yuan
- Department of Neurology, Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Hongqiang Sun
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
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11
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Xu Y, Wang S, Chen L, Shao Z, Zhang M, Liu S, Wen X, Li Y, Yang W, Tang F, Luo J, Fan L, Yan C, Liu J, Yuan K. Reduced midbrain functional connectivity and recovery in abstinent heroin users. J Psychiatr Res 2021; 144:168-176. [PMID: 34662755 DOI: 10.1016/j.jpsychires.2021.10.011] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 09/24/2021] [Accepted: 10/10/2021] [Indexed: 11/28/2022]
Abstract
Dopaminergic pathways from the midbrain to striatum as well as cortex are involved in addiction. However, the alternations of these pathways and whether the recoveries of aberrant circuits would be detected after prolonged abstinence in heroin users are rarely known. The resting-state functional connectivity (RSFC) patterns of midbrain (i.e., the ventral tegmental area (VTA) and substantia nigra (SN)) were compared between 40 abstinent heroin users with opioid use disorder (HUs) and 35 healthy controls (HCs). Then, we tested the functional recovery hypothesis by both cross-sectional and longitudinal design. For cross-sectional design, HUs were separated into short-term abstainers (STs) (3-15 days) and long-term abstainers (LTs) (>15 days). With regard to longitudinal design, 22 subjects among HUs were followed up for 10 months. A sandwich estimator method was used to analyze the differences between baseline HUs and follow-up HUs. HUs showed lower RSFC between midbrain and several cortical areas (medial orbitofrontal cortex (mOFC) and anterior cingulate cortex) compared with HCs. Besides, lower RSFC of VTA-right nucleus accumbens circuit as well as right SN- caudate circuit was also found in HUs. The enhanced RSFC value of VTA-left mOFC circuit was observed in LTs, compared with STs. Additionally, longitudinal design also revealed the increased RSFC values of the midbrain with frontal cortex after 10 months prolonged abstinence. We revealed abnormal functional organizations of midbrain-striato and midbrain-cortical circuits in HUs. More importantly, partially recovery of these dysfunctions can be found after long-term abstinence.
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Affiliation(s)
- Yan Xu
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, China
| | - Shicong Wang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, China
| | - Longmao Chen
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, China
| | - Ziqiang Shao
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, China
| | - Min Zhang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, China
| | - Shuang Liu
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, China
| | - Xinwen Wen
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, China
| | - Yangding Li
- Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, Hunan, China
| | - Wenhan Yang
- Department of Radiology, Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Fei Tang
- Department of Radiology, Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jing Luo
- Department of Radiology, Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Li Fan
- Department of Radiology, Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Cui Yan
- Department of Radiology, Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jun Liu
- Department of Radiology, Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
| | - Kai Yuan
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, China.
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12
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Hong T, He C, Gu ZK, Xie JJ, Lu Q, Li YQ, Xu XJ, Shen Y, Wang YQ, Zheng H. Psychometric investigation of the Chinese version of the Habit, Reward and Fear Scale (HRFS). Brain Behav 2021; 11:e2364. [PMID: 34554655 PMCID: PMC8613424 DOI: 10.1002/brb3.2364] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 08/14/2021] [Accepted: 08/31/2021] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Tobacco use is one of the most important risk factors for health, and China is the largest producer and consumer of tobacco in the world. Monitoring and controlling the tobacco epidemic is an important issue. However, the motivation underlying smoking behavior is complex and specific to the individual. The Habit, Reward and Fear Scale (HRFS) is a feasible tool to evaluate this complex motivation. OBJECTIVES To validate the psychometric properties of the HRFS Chinese version (HRFS-C) and to assess the relationship between motivation and smoking behavior. METHOD We recruited 967 participants through social media and assessed their smoking behavior with three instruments: the Fagerstrom Test for Nicotine Dependence-Chinese version (FTND-C), the Questionnaire on Smoking Urges-Brief Scale-Chinese version (QSU-brief-C), and the HRFS-C. Ultimately, we retained 700 valid data points. Cronbach's α and split-half tests were used to evaluate the reliability. Confirmatory factor analysis, Pearson's r and an analysis of variance (ANOVA) were used to evaluate the validity. In addition, linear regression was used to explore the relationship among the three instruments. The HRFS-C showed good homogeneity (α = 0.965), concurrent validity, and discriminant validity. A significant linear relationship was observed among the FTND-C, QSU-brief-C, and HRFS-C (p < .001). CONCLUSION The motivation measured by the HRFS-C can significantly predict nicotine dependence and craving in the smoking population. The HRFS-C can be used to carry out targeted interventions for addicted patients (e.g., motivational enhancement therapy).
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Affiliation(s)
- Tu Hong
- Department of Rehabilitation Medicine, The Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, China.,College of Psychology, Nanjing Normal University, Nanjing, China
| | - Chuan He
- Department of Rehabilitation Medicine, The Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, China
| | - Zhong-Ke Gu
- Department of Sport and Health Sciences, Nanjing Sport Institute, Nanjing, China
| | - Jun-Jie Xie
- College of Psychology, Nanjing Normal University, Nanjing, China
| | - Qian Lu
- Department of Rehabilitation Medicine, The Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, China
| | - Yong-Qiang Li
- Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xing-Jun Xu
- Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Ying Shen
- Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yun-Qiang Wang
- College of Psychology, Nanjing Normal University, Nanjing, China
| | - Hui Zheng
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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13
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Bi Y, Hu L. Magnetic resonance imaging for smoking abstinence: symptoms, mechanisms, and interventions. BRAIN SCIENCE ADVANCES 2021. [DOI: 10.26599/bsa.2021.9050016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
Tobacco smoking is the leading preventable cause of morbidity and mortality worldwide. Although a number of smokers are aware of the adverse outcomes of smoking and express a strong desire to stop smoking, most smoking quit attempts end in relapse within the first few days of abstinence, primarily resulting from the aversive aspects of the nicotine withdrawal syndrome. Therefore, studying the neural mechanisms of smoking abstinence, identifying smokers with heightened relapse vulnerability prior to quit attempts, and developing effective smoking cessation treatments appear to be promising strategies for improving the success of quit attempts. In recent years, with the development of magnetic resonance imaging, the neural substrates of smoking abstinence have become extensively studied. In this review, we first introduce the psychophysiological changes induced by smoking abstinence, including affective, cognitive, and somatic signs. We then provide an overview of the magnetic resonance imaging-based evidence regarding abstinence-related functional changes accompanied by these psychophysiological changes. We conclude with a discussion of the neural markers that could predict relapse during quit attempts and a summary of the psychophysiological interventions that are currently often used to help with smoking cessation. This review extends our understanding of the role of the central nervous system in smoking abstinence.
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Affiliation(s)
- Yanzhi Bi
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Li Hu
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100101, China
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14
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Abstract
To date, our understanding of the role of abnormal hippocampal volume in imaging studies of insomnia disorders (ID) has remained in apparent contradiction. Given that hippocampal function can be mapped to anatomically defined substructures, the hippocampal substructure volume can be examined in detail at present. In this study, we examined the volumes of hippocampal substructures between IDs and healthy controls (HC) to accurately find hippocampal markers of ID. First, we used the automated hippocampal substructure module in FreeSurfer6.0 to inspect T1-weighted magnetic resonance images between 22 IDs and 30 HC. Then, 12 hippocampal substructures were computed. Volumetric assessment was performed at the hippocampal substructure level between groups. Our study revealed significant reduced volume of the bilateral fimbria in IDs compared with HC (p < 0.05/12, Bonferroni corrected), although there was no difference in the total volume of hippocampus. In addition, the correlation analysis showed that the total hippocampal volume of the left hemisphere was negatively correlated with Pittsburgh Sleep Quality Index (PSQI) scores. With regard to hippocampal substructure results, negative correlations were detected between bilateral fimbria volume and clinical variables (i.e., PSQI, SDS, and SAS) in all subjects. Taken together, we revealed marked differences in the volume of the hippocampal substructure between IDs and HC, which provided a more accurate structural imaging marker for the pathological of ID.
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15
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Brain responses to drug cues predict craving changes in abstinent heroin users: A preliminary study. Neuroimage 2021; 237:118169. [PMID: 34000396 DOI: 10.1016/j.neuroimage.2021.118169] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 04/25/2021] [Accepted: 05/12/2021] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Loss of control over drug intake occurring in drug addiction is believed to result from disruption of reward circuits, including reduced responsiveness to natural rewards (e.g., monetary, sex) and heightened responsiveness to drug reward. Yet few studies have assessed reward deficiency and related brain responses in abstinent heroin users with opioid use disorder, and less is known whether the brain responses can predict cue-induced craving changes following by prolonged abstinence. METHOD 31 heroin users (age: 44.13±7.68 years, male: 18 (58%), duration of abstinence: 85.2 ± 52.5 days) were enrolled at a mandatory detoxification center. By employing a cue-reactivity paradigm including three types of cues (drug, sexual, neutral), brain regional activations and circuit-level functional coupling were extracted. Among the 31 heroin users, 15 were followed up longitudinally to assess cue induced craving changes in the ensuing 6 months. RESULTS One way analysis of variance results showed that heroin users have differential brain activations to the three cues (neutral, drug and sexual) in the left dorsolateral prefrontal cortex (DLPFC), insula, orbiotofrontal cortex (OFC) and the bilateral thalamus. Drug cue induced greater activations in left DLPFC, insula and OFC compared to sexual cue. The psychophysiological interactions (PPI) analysis revealed negative couplings of the left DLPFC and the left OFC, bilateral thalamus, putamen in heroin users during drug cue exposure. In the 6-month follow-up study, both drug cue induced activation of the left DLPFC and the functional coupling of the left DLPFC-bilateral thalamus at baseline was correlated with craving reductions, which were not found for sexual cues. CONCLUSION Our preliminary study provided novel evidence for the reward deficiency theory of opioid use disorder. Our findings also have clinical implications, as drug cue induced activation of the left DLPFC and functional coupling of left DLPFC-bilateral thalamus may be potential neuroimaging markers for craving changes during prolonged abstinence. Evidently, the findings in the current preliminary study should be confirmed by large sample size in the future.
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16
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Zhang M, Liu S, Wang S, Xu Y, Chen L, Shao Z, Wen X, Yang W, Liu J, Yuan K. Reduced thalamic resting-state functional connectivity and impaired cognition in acute abstinent heroin users. Hum Brain Mapp 2021; 42:2077-2088. [PMID: 33459459 PMCID: PMC8046054 DOI: 10.1002/hbm.25346] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 01/05/2021] [Accepted: 01/07/2021] [Indexed: 12/13/2022] Open
Abstract
As a critical component of cortico-striato-thalamo-cortical loop in addiction, our understanding of the thalamus in impaired cognition of heroin users (HU) has been limited. Due to the complex thalamic connection with cortical and subcortical regions, thalamus was divided into prefrontal (PFC), occipital (OC), premotor, primary motor, sensory, temporal, and posterior parietal association subregions according to white matter tractography. We adopted seven subregions of bilateral thalamus as regions of interest to systematically study the implications of distinct thalamic nuclei in acute abstinent HU. The volume and resting-state functional connectivity (RSFC) differences of the thalamus were investigated between age-, gender-, and alcohol-matched 37 HU and 33 healthy controls (HCs). Trail making test-A (TMT-A) was adopted to assess cognitive function deficits, which were then correlated with neuroimaging findings. Although no significant different volumes were found, HU group showed decreased RSFC between left PFC_thalamus and middle temporal gyrus as well as between left OC_thalamus and inferior frontal gyrus and supplementary motor area relative to HCs. Meanwhile, the higher TMT-A scores in HU were negatively correlated with PFC_thalamic RSFC with inferior temporal gyrus, fusiform, and precuneus. Craving scores were negatively correlated with OC_thalamic RSFC with accumbens, hippocampus, and insula. Opiate Withdrawal Scale scores were negatively correlated with left PFC/OC_thalamic RSFC with orbitofrontal cortex and medial PFC. We indicated two thalamus subregions separately involvement in cognitive control and craving to reveal the implications of thalamic subnucleus in pathology of acute abstinent HU.
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Affiliation(s)
- Min Zhang
- School of Life Science and TechnologyXidian UniversityXi'anShaanxiPeople's Republic of China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of EducationXi'anPeople's Republic of China
| | - Shuang Liu
- School of Life Science and TechnologyXidian UniversityXi'anShaanxiPeople's Republic of China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of EducationXi'anPeople's Republic of China
| | - Shicong Wang
- School of Life Science and TechnologyXidian UniversityXi'anShaanxiPeople's Republic of China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of EducationXi'anPeople's Republic of China
| | - Yan Xu
- School of Life Science and TechnologyXidian UniversityXi'anShaanxiPeople's Republic of China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of EducationXi'anPeople's Republic of China
| | - Longmao Chen
- School of Life Science and TechnologyXidian UniversityXi'anShaanxiPeople's Republic of China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of EducationXi'anPeople's Republic of China
| | - Ziqiang Shao
- School of Life Science and TechnologyXidian UniversityXi'anShaanxiPeople's Republic of China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of EducationXi'anPeople's Republic of China
| | - Xinwen Wen
- School of Life Science and TechnologyXidian UniversityXi'anShaanxiPeople's Republic of China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of EducationXi'anPeople's Republic of China
| | - Wenhan Yang
- Department of RadiologySecond Xiangya Hospital, Central South UniversityChangshaChina
| | - Jun Liu
- Department of RadiologySecond Xiangya Hospital, Central South UniversityChangshaChina
| | - Kai Yuan
- School of Life Science and TechnologyXidian UniversityXi'anShaanxiPeople's Republic of China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of EducationXi'anPeople's Republic of China
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17
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Zhao M, Liu J, Cai W, Li J, Zhu X, Yu D, Yuan K. Support vector machine based classification of smokers and nonsmokers using diffusion tensor imaging. Brain Imaging Behav 2021; 14:2242-2250. [PMID: 31428924 DOI: 10.1007/s11682-019-00176-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Despite significant progress in treatments for smoking cessation, smoking continues to be a significant public health concern, especially in young adulthood. Thus, developing a predictive model that can classify and characterize the brain-based biomarkers predicting smoking status would be imperative to improving treatment development. In this study, we applied a support vector machine-based classification method to discriminate 70 young male smokers and 70 matched nonsmokers using their diffusion tensor imaging (DTI) data. The classification procedure achieved an average accuracy of 88.6% and an average area under the curve of 0.95. The most discriminative features that contributed to the classification were primarily located in the sagittal stratum (SS), external capsule (EC), superior longitudinal fasciculus (SLF), anterior corona radiata (ACR) and inferior front-occipital fasciculus (IFOF). The following regression analysis showed a significant negatively correlation between the average RD values of the left ACR (r = -0.247, p = 0.039) and FTND. The average MD values in the right EC (r = -0.254, p = 0.034) and RD values in the right IFOF (r = -0.240, p = 0.046) were inversely associated with pack-years. Our findings indicate that the discriminative white matter (WM) features as brain biomarkers provide great predictive power for smoking status and suggest that machine learning techniques can reveal underlying smoking-related neurobiology.
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Affiliation(s)
- Meng Zhao
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, People's Republic of China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, People's Republic of China
| | - Jingjing Liu
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, People's Republic of China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, People's Republic of China
| | - Wanye Cai
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, People's Republic of China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, People's Republic of China
| | - Jun Li
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, People's Republic of China
| | - Xueling Zhu
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China.
| | - Dahua Yu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, People's Republic of China.
| | - Kai Yuan
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, People's Republic of China. .,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, People's Republic of China. .,Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, People's Republic of China.
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18
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Disrupted frontostriatal connectivity in primary insomnia: a DTI study. Brain Imaging Behav 2021; 15:2524-2531. [PMID: 33651331 DOI: 10.1007/s11682-021-00454-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Revised: 12/28/2020] [Accepted: 01/10/2021] [Indexed: 12/20/2022]
Abstract
Dysfunction of the sleep-wake transition is considered to be associated with the pathology of patients with primary insomnia (PI). Previous animal study had reported that brain circuits between the striatum and cortex can regulate sleep-wake transitions. So far, few studies have systematically explored the structural connectivity of the striatum-centered circuits and their potential roles in patients with PI. In this study, we chosen the striatum as the seed and 10 priori target regions as masks to assess the structural connectivity by using seed-based classification with a diffusion tensor imaging (DTI) probabilistic tractography method. Track strengths of the striatum-centered circuits were compared between 22 patients with PI (41.27 ± 9.21 years) and 30 healthy controls (HC) (35.2 ± 8.14 years). Pittsburgh Sleep Quality Index (PSQI) was used to measure the sleep quality in all participants. Lower track strengths (left striatum- anterior cingulate cortex (ACC), left striatum- dorsal anterior cingulate cortex (dACC), left striatum-Hippocampus, and right striatum-Hippocampus) were observed in patients with PI compared to HC. Additionally, the lower track strengths of brain circuits mentioned above were negatively correlated with PSQI. Taken together, our findings revealed the lower tract strength of frontostriatal circuits in patients with PI and HC, which provided the implications of the system-level structural connections of frontostriatal circuits in the pathology of PI. We suggested that the track strengths of the frontostriatal circuits calculated from DTI can be the potential neuroimaging biomarkers of the sleep quality in patients with PI.
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19
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Yang W, Wang S, Shao Z, Yang R, Tang F, Luo J, Yan C, Zhang J, Chen J, Liu J, Yuan K. Novel circuit biomarker of impulsivity and craving in male heroin-dependent individuals. Drug Alcohol Depend 2021; 219:108485. [PMID: 33360853 DOI: 10.1016/j.drugalcdep.2020.108485] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 11/14/2020] [Accepted: 11/17/2020] [Indexed: 01/12/2023]
Abstract
INTRODUCTION The striatum mediates reward processing in addiction, and previous fMRI (functional Magnetic Resonance Imaging) studies have revealed abnormal striatofrontal functional connectivity in heroin addiction. However, little is known about whether there is abnormal structural connectivity of the striatal circuit in heroin addiction. This study investigated the structural connectivity of striatal circuits in abstinent heroin-dependent individuals (HDIs) without methadone treatment. METHODS Forty-three (age: 38.8 ± 7.1) male HDIs and twenty-one (age: 42.4 ± 7.9) matched healthy controls underwent high-resolution T1 and whole-brain diffusion tensor imaging (64 directions) magnetic resonance imaging. Connectivity-based seed classification probabilistic tractography was used to detect the tract strengths of striatal circuits with 10 a priori target masks. Tract strengths were compared between groups and correlated with impulsivity behavior, evaluated using the Barratt Impulsivity Scale (BIS), and craving, measured on visual analogue scale (VAS). RESULTS HDIs showed significantly weaker tract strength of the left striatum-medial orbitofrontal cortex (mOFC) (Bonferroni corrected, p < 0.05/20 = 0.0025) and significantly higher BIS total, attention, motor, and non-planning scores (Bonferroni corrected, p < 0.05/4 = 0.0125) than controls. In HDIs, negative correlations were observed between the left striatum- mOFC tract strengths and the BIS total, attention and non-planning scores (r1=-0.410, p1 = 0.005; r2=-0.432, p2 = 0.003; r3=-0.506, p3<0.001) and between the right striatum-posterior cingulate cortex (PCC) tract strengths and craving scores (r=-0.433, p = 0.009) in HDIs. CONCLUSION HDIs displayed decreased structural connectivity of the striatum-mOFC circuit and higher impulsivity. Higher impulsive behavior was associated with decreased left striatal circuit connectivity. These findings suggest that the striatal circuit tract strengths might be a novel potential biomarker in heroin and, potentially, general opioid addiction.
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Affiliation(s)
- Wenhan Yang
- Department of Radiology, Second Xiangya Hospital of Central South University, Changsha, China
| | - Shicong Wang
- School of Life Science and Technology, Xidian University, Xi'an, 710071, China
| | - Ziqiang Shao
- School of Life Science and Technology, Xidian University, Xi'an, 710071, China
| | - Ru Yang
- Department of Radiology, Second Xiangya Hospital of Central South University, Changsha, China
| | - Fei Tang
- Department of Radiology, Second Xiangya Hospital of Central South University, Changsha, China
| | - Jing Luo
- Department of Radiology, Second Xiangya Hospital of Central South University, Changsha, China
| | - Cui Yan
- Department of Radiology, Second Xiangya Hospital of Central South University, Changsha, China
| | - Jun Zhang
- Hunan Judicial Police Academy, Changsha, China
| | - Jiyuan Chen
- Hunan Judicial Police Academy, Changsha, China
| | - Jun Liu
- Department of Radiology, Second Xiangya Hospital of Central South University, Changsha, China.
| | - Kai Yuan
- School of Life Science and Technology, Xidian University, Xi'an, 710071, China; Engineering Research Center of Molecular and Neuroimaging, Ministry of Education, Xi'an, China.
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20
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Wang S, Zhang M, Liu S, Xu Y, Shao Z, Chen L, Li J, Yang W, Liu J, Yuan K. Impulsivity in heroin-dependent individuals: structural and functional abnormalities within frontostriatal circuits. Brain Imaging Behav 2021; 15:2454-2463. [PMID: 33528803 DOI: 10.1007/s11682-020-00445-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2020] [Revised: 12/09/2020] [Accepted: 12/28/2020] [Indexed: 12/31/2022]
Abstract
High levels of impulsivity are a risk factor for the initiation of heroin use and a core behavioral characteristic of heroin dependence. Impulsivity also contributes to the maintenance of drug use and hinders effective therapy. Here we sought to identify neuroimaging markers of impulsivity in heroin-dependent individuals (HDI), with a focus on the nucleus accumbens (NAc), a key region implicated in impulsivity and drug addiction generally. Volume and resting-state functional connectivity (RSFC) differences of the bilateral NAc were investigated between 21 HDI and 21 age-, gender-, nicotine-, alcohol-matched healthy controls (HC). The neuroimaging results were then correlated with the Barratt Impulsivity Scales (BIS-11). Higher motor impulsivity (t = 2.347, p = 0.0253) and larger right NAc volume (F (1,38) = 4.719, p = 0.036) was observed in HDI. The right NAc volume was positively correlated with BIS total (r = 0.6196, p = 0.0239) /motor (r = 0.5921, p = 0.0330) scores in HC and BIS motor (r = 0.5145, p = 0.0170) score in HDI. A negative correlation was found between RSFC of the right NAc-bilateral superior frontal gyrus (SFG) and motor impulsivity in HDI (left: r=-0.6537, p = 0.0013; right: r=-0.6167, p = 0.0029) and HC (left: r=-0.6490,p = 0.0164; right: r=-0.6993, p = 0.0078). We aimed to reveal novel multimodality neuroimaging biomarkers of the higher impulsivity in HDI by focusing on the NAc and corresponding functional circuits. Higher motor impulsivity was observed in HDI. Furthermore, the volume of the right NAc and the RSFC strength of right NAc-SFG could be neuroimaging biomarkers for the severity of impulsivity in HDI. These potential biomarkers could be a target for novel treatments in HDI.
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Affiliation(s)
- Shicong Wang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, People's Republic of China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, People's Republic of China
| | - Min Zhang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, People's Republic of China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, People's Republic of China
| | - Shuang Liu
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, People's Republic of China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, People's Republic of China
| | - Yan Xu
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, People's Republic of China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, People's Republic of China
| | - Ziqiang Shao
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, People's Republic of China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, People's Republic of China
| | - Longmao Chen
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, People's Republic of China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, People's Republic of China
| | - Jun Li
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, People's Republic of China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, People's Republic of China
| | - Wenhan Yang
- Department of Radiology, Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jun Liu
- Department of Radiology, Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
| | - Kai Yuan
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, People's Republic of China. .,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, People's Republic of China.
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21
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Gu Z, Zheng H, Yin Z, Cai H, Li Y, Zhao C, Zhai Y, Xu K, Xue L, Xu X, Shen Y, Yuan TF. Pictures Library of Smoking Cravings: Development and Verification of Smokers and Non-smokers. Front Psychiatry 2021; 12:719782. [PMID: 34484007 PMCID: PMC8415710 DOI: 10.3389/fpsyt.2021.719782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 07/21/2021] [Indexed: 11/13/2022] Open
Abstract
Background: The cue-induced craving by addiction related materials is commonly employed in addiction research; however, no existing standardized picture database based on the expectation model of craving has been developed. We prepared and validated a Pictures Library of Smoking Cravings (PLSC) in this study. Methods: We captured pictures 366 smoking and 406 control pictures (matched in content). We selected 109 smoking pictures and 115 control pictures and asked participants to provide ratings of craving, familiarity, valence, and arousal induced in them. Participants were divided into three groups: non-smokers (n = 211), light smokers (n = 504), and heavy smokers (n = 101). Results: The results showed that smoking pictures evoked a greater craving, familiarity, and arousal than control pictures in smokers (ps < 0.01). In addition, craving caused by smoking pictures was positively associated with the Fagerström test for nicotine dependence score in dependent smokers. Conclusions: Overall, the contemporary results showed that PLSC is effective and can be used in smoking-related studies.
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Affiliation(s)
- Zhongke Gu
- Department of Sport and Health Sciences, Nanjing Sport Institute, Nanjing, China
| | - Hui Zheng
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhifei Yin
- Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Huiting Cai
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yongqiang Li
- Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Chunchun Zhao
- Department of Sport and Health Sciences, Nanjing Sport Institute, Nanjing, China
| | - Yujia Zhai
- Department of Psychology, Zhejiang Normal University, Jinhua, China
| | - Kai Xu
- Department of Sport and Health Sciences, Nanjing Sport Institute, Nanjing, China
| | - Lian Xue
- Scientific Experiment Center, Nanjing Sport Institute, Nanjing, China
| | - Xingjun Xu
- Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Ying Shen
- Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Ti-Fei Yuan
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Co-innovation Center of Neuroregeneration, Nantong University, Nantong, China.,Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine, Shanghai, China
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22
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Liu W, Zhang X, Qiao Y, Cai Y, Yin H, Zheng M, Zhu Y, Wang H. Functional Connectivity Combined With a Machine Learning Algorithm Can Classify High-Risk First-Degree Relatives of Patients With Schizophrenia and Identify Correlates of Cognitive Impairments. Front Neurosci 2020; 14:577568. [PMID: 33324147 PMCID: PMC7725002 DOI: 10.3389/fnins.2020.577568] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 10/21/2020] [Indexed: 12/21/2022] Open
Abstract
Schizophrenia (SCZ) is an inherited disease, with the familial risk being among the most important factors when evaluating an individual's risk for SCZ. However, robust imaging biomarkers for the disease that can be used for diagnosis and determination of the prognosis are lacking. Here, we explore the potential of functional connectivity (FC) for use as a biomarker for the early detection of high-risk first-degree relatives (FDRs). Thirty-eight first-episode SCZ patients, 38 healthy controls (HCs), and 33 FDRs were scanned using resting-state functional magnetic resonance imaging. The subjects' brains were parcellated into 200 regions using the Craddock atlas, and the FC between each pair of regions was used as a classification feature. Multivariate pattern analysis using leave-one-out cross-validation achieved a correct classification rate of 88.15% [sensitivity 84.06%, specificity 92.18%, and area under the receiver operating characteristic curve (AUC) 0.93] for differentiating SCZ patients from HCs. FC located within the default mode, frontal-parietal, auditory, and sensorimotor networks contributed mostly to the accurate classification. The FC patterns of each FDR were input into each classification model as test data to obtain a corresponding prediction label (a total of 76 individual classification scores), and the averaged individual classification score was then used as a robust measure to characterize whether each FDR showed an SCZ-type or HC-type FC pattern. A significant negative correlation was found between the average classification scores of the FDRs and their semantic fluency scores. These findings suggest that FC combined with a machine learning algorithm could help to predict whether FDRs are likely to show an SCZ-specific or HC-specific FC pattern.
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Affiliation(s)
- Wenming Liu
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Xiao Zhang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Yuting Qiao
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Yanhui Cai
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Minwen Zheng
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Yuanqiang Zhu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi’an, China
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23
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Shao Z, Xu Y, Chen L, Wang S, Zhang M, Liu S, Wen X, Yu D, Yuan K. Dysfunction of the NAc-mPFC circuit in insomnia disorder. Neuroimage Clin 2020; 28:102474. [PMID: 33395968 PMCID: PMC7606871 DOI: 10.1016/j.nicl.2020.102474] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 10/13/2020] [Accepted: 10/17/2020] [Indexed: 12/14/2022]
Abstract
BACKGROUND Insomnia disorder (ID) is a prevalent sleep disorder, which seriously affects people's daily life and was found to be associated with increased frequency of sleep stage shifts. Previous findings had revealed the critical role of the nucleus accumbens (NAc) in sleep-wake transition. However, the neuroimaging studies of the NAc in patients with ID have been rare. We hypothesized that structural and functional abnormalities of the NAc would be implicated in ID. METHODS Twenty-six ID patients and 36 matched healthy controls (HC) were included in the current study. The volumes and corresponding resting-state functional connectivity (RSFC) of the bilateral NAc were compared between the two groups. The abnormal RSFC in ID were then correlated with Pittsburgh Sleep Quality Index (PSQI). RESULTS Compared with HC, ID patients showed significantly increased volume of right NAc. Several brain regions showed increased RSFC with the NAc in ID patients, such as medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), caudate and putamen. Meanwhile, the occipital gyrus and temporal gyrus showed decreased RSFC with the NAc. Additionally, the increased RSFC strength between bilateral NAc and left mPFC was significant correlated with PSQI scores in ID patients. CONCLUSION Dysfunctions of the NAc-mPFC circuit were found in ID patients, which were associated with sleep quality measured by PSQI. The two patterns of increase and decrease of RSFC in ID patients observed in our study may reflect the state of hyperarousal and potential impairment of cognitive function in the patients, respectively. It is hoped that our study focusing on NAc-mPFC circuits could provide new insights for the neural mechanisms of ID and potential novel therapeutic targets for treatment of ID patients.
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Affiliation(s)
- Ziqiang Shao
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, People's Republic of China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, People's Republic of China
| | - Yan Xu
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, People's Republic of China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, People's Republic of China
| | - Longmao Chen
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, People's Republic of China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, People's Republic of China
| | - Shicong Wang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, People's Republic of China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, People's Republic of China
| | - Min Zhang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, People's Republic of China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, People's Republic of China
| | - Shuang Liu
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, People's Republic of China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, People's Republic of China
| | - Xinwen Wen
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, People's Republic of China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, People's Republic of China
| | - Dahua Yu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, People's Republic of China.
| | - Kai Yuan
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, People's Republic of China; Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, People's Republic of China; Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, People's Republic of China.
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24
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Xue T, Dong F, Huang R, Tao Z, Tang J, Cheng Y, Zhou M, Hu Y, Li X, Yu D, Ju H, Yuan K. Dynamic Neuroimaging Biomarkers of Smoking in Young Smokers. Front Psychiatry 2020; 11:663. [PMID: 32754067 PMCID: PMC7367415 DOI: 10.3389/fpsyt.2020.00663] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Accepted: 06/26/2020] [Indexed: 01/06/2023] Open
Abstract
OBJECTIVE To examine potential changes in the dynamic characteristics of regional neural activity in young smokers and to detect whether the changes were associated with smoking behavior. METHODS The dynamic regional homogeneity (dReHo) and dynamic amplitude of low-frequency fluctuations (dALFF) in 40 young smokers and 42 nonsmokers were compared. Correlation analyses were also performed between dReHo and dALFF in areas showing group differences and smoking behavior [e.g., the Fagerström Test for Nicotine dependence (FTND) scores and pack-years]. RESULTS Significantly differences in dReHo variability were observed in the inferior frontal gyrus (IFG), superior frontal gyrus (SFG), medial frontal gyrus (MFG), insula, cuneus, postcentral gyrus, inferior semi-lunar lobule, orbitofrontal gyrus, and inferior temporal gyrus (ITG). Young smokers also showed significantly increased dALFF variability in the anterior cingulate cortex (ACC) and ITG. Furthermore, a significant positive correlation was found between dALFF variability in the ACC and the pack-years; whereas a significant negative correlation between dReHo variability in the IFG and the FTND scores was found in young smokers. CONCLUSION The pattern of resting state regional neural activity variability was different between young smokers and nonsmokers. Dynamic regional indexes might be a novel neuroimaging biomarker of smoking behavior in young smokers.
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Affiliation(s)
- Ting Xue
- School of Science, Inner Mongolia University of Science and Technology, Baotou, China
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Fang Dong
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Ruoyan Huang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Zhanlong Tao
- School of Science, Inner Mongolia University of Science and Technology, Baotou, China
| | - Jun Tang
- School of Science, Inner Mongolia University of Science and Technology, Baotou, China
| | - Yongxin Cheng
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Mi Zhou
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Yiting Hu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Xiaojian Li
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Dahua Yu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Haitao Ju
- Department of Neurosurgery, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China
| | - Kai Yuan
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
- Life Sciences Research Center, School of Life Science and Technology, Xidian University, Xi’an, China
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25
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Cai W, Zhao M, Liu J, Liu B, Yu D, Yuan K. Right arcuate fasciculus and superior longitudinal fasciculus abnormalities in primary insomnia. Brain Imaging Behav 2020; 13:1746-1755. [PMID: 31327125 DOI: 10.1007/s11682-019-00160-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Primary insomnia (PI) is a very common phenomenon and associated with functional impairments of attention, memory and mood regulation. However, its neurobiology is poorly understood. To date, the studies about integrity of white matter (WM) tracts in PI patients have been still rare. In the present study, we used Automated Fiber Quantification (AFQ), which reliably and efficiently quantified diffusion measurements at multiple locations along the WM trajectory based on diffusion tensor imaging (DTI), to assess WM diffusion properties differences between 23 PI patients and 32 matched healthy controls in 18 tracts. The relationships between neuroimaging differences and sleep behaviors were explored, including Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index Scale (ISI). Compared with healthy control group, right arcuate fasciculus (Arc) and superior longitudinal fasciculus (SLF) showed significant higher fractional anisotropy (FA), mean diffusivity (MD) and radial diffusivity (RD) along tract length in PI patients (FWE corrected, p < 0.01). Axial diffusivity (AD) for PI patients was higher in right Arc and lower in right SLF. Correlation analyses revealed that FA of right Arc and MD of right SLF were negatively correlated with PSQI score in PI patients, and AD of right Arc and FA of right SLF were positively correlated with PSQI score. Negative correlation was observed between FA of right Arc and AD of right SLF and ISI score in PI patients. Our findings can help us to improve the understanding of the neural mechanisms of primary insomnia at abnormalities in WM microstructure.
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Affiliation(s)
- Wanye Cai
- School of Life Science and Technology, Xidian University, Xi'an, Shanxi, 710071, People's Republic of China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, People's Republic of China
| | - Meng Zhao
- School of Life Science and Technology, Xidian University, Xi'an, Shanxi, 710071, People's Republic of China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, People's Republic of China
| | - Jingjing Liu
- School of Life Science and Technology, Xidian University, Xi'an, Shanxi, 710071, People's Republic of China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, People's Republic of China
| | - Bo Liu
- Department of Neurology, The First Affiliated Hospital of Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, People's Republic of China
| | - Dahua Yu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, Information Processing Laboratory, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, People's Republic of China.
| | - Kai Yuan
- School of Life Science and Technology, Xidian University, Xi'an, Shanxi, 710071, People's Republic of China. .,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, People's Republic of China. .,Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, Information Processing Laboratory, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, People's Republic of China.
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26
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Licheri V, Eckernäs D, Bergquist F, Ericson M, Adermark L. Nicotine-induced neuroplasticity in striatum is subregion-specific and reversed by motor training on the rotarod. Addict Biol 2020; 25:e12757. [PMID: 30969011 PMCID: PMC7187335 DOI: 10.1111/adb.12757] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Revised: 03/12/2019] [Accepted: 03/18/2019] [Indexed: 11/28/2022]
Abstract
Nicotine is recognized as one of the most addictive drugs, which in part could be attributed to progressive neuroadaptations and rewiring of dorsal striatal circuits. Since motor‐skill learning produces neuroplasticity in the same circuits, we postulate that rotarod training could be sufficient to block nicotine‐induced rewiring and thereby prevent long‐lasting impairments of neuronal functioning. To test this hypothesis, Wistar rats were subjected to 15 days of treatment with either nicotine (0.36 mg/kg) or vehicle. After treatment, a subset of animals was trained on the rotarod. Ex vivo electrophysiology was performed 1 week after the nicotine treatment period and after up to 3 months of withdrawal to define neurophysiological transformations in circuits of the striatum and amygdala. Our data demonstrate that nicotine alters striatal neurotransmission in a distinct temporal and spatial sequence, where acute transformations are initiated in dorsomedial striatum (DMS) and nucleus accumbens (nAc) core. Following 3 months of withdrawal, synaptic plasticity in the form of endocannabinoid‐mediated long‐term depression (eCB‐LTD) is impaired in the dorsolateral striatum (DLS), and neurotransmission is altered in DLS, nAc shell, and the central nucleus of the amygdala (CeA). Training on the rotarod, performed after nicotine treatment, blocks neurophysiological transformations in striatal subregions, and prevents nicotine‐induced impairment of eCB‐LTD. These datasets suggest that nicotine‐induced rewiring of striatal circuits can be extinguished by other behaviors that induce neuroplasticity. It remains to be determined if motor‐skill training could be used to prevent escalating patterns of drug use in experienced users or facilitate the recovery from addiction.
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Affiliation(s)
- Valentina Licheri
- Addiction Biology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska AcademyUniversity of Gothenburg Gothenburg Sweden
| | - Daniel Eckernäs
- Department of Pharmacology, Institute of Neuroscience and Physiology, The Sahlgrenska AcademyUniversity of Gothenburg Gothenburg Sweden
| | - Filip Bergquist
- Department of Pharmacology, Institute of Neuroscience and Physiology, The Sahlgrenska AcademyUniversity of Gothenburg Gothenburg Sweden
| | - Mia Ericson
- Addiction Biology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska AcademyUniversity of Gothenburg Gothenburg Sweden
| | - Louise Adermark
- Addiction Biology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska AcademyUniversity of Gothenburg Gothenburg Sweden
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27
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Lesage E, Sutherland MT, Ross TJ, Salmeron BJ, Stein EA. Nicotine dependence (trait) and acute nicotinic stimulation (state) modulate attention but not inhibitory control: converging fMRI evidence from Go-Nogo and Flanker tasks. Neuropsychopharmacology 2020; 45:857-865. [PMID: 31995811 PMCID: PMC7075893 DOI: 10.1038/s41386-020-0623-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Revised: 12/29/2019] [Accepted: 01/17/2020] [Indexed: 12/29/2022]
Abstract
Cognitive deficits during nicotine withdrawal may contribute to smoking relapse. However, interacting effects of chronic nicotine dependence and acute nicotine withdrawal on cognitive control are poorly understood. Here we examine the effects of nicotine dependence (trait; smokers (n = 24) vs. non-smoking controls; n = 20) and acute nicotinic stimulation (state; administration of nicotine and varenicline, two FDA-approved smoking cessation aids, during abstinence), on two well-established tests of inhibitory control, the Go-Nogo task and the Flanker task, during fMRI scanning. We compared performance and neural responses between these four pharmacological manipulations in a double-blind, placebo-controlled crossover design. As expected, performance in both tasks was modulated by nicotine dependence, abstinence, and pharmacological manipulation. However, effects were driven entirely by conditions that required less inhibitory control. When demand for inhibitory control was high, abstinent smokers showed no deficits. By contrast, acutely abstinent smokers showed performance deficits in easier conditions and missed more trials. Go-Nogo fMRI results showed decreased inhibition-related neural activity in right anterior insula and right putamen in smokers and decreased dorsal anterior cingulate cortex activity on nicotine across groups. No effects were found on inhibition-related activity during the Flanker task or on error-related activity in either task. Given robust nicotinic effects on physiology and behavioral deficits in attention, we are confident that pharmacological manipulations were effective. Thus findings fit a recent proposal that abstinent smokers show decreased ability to divert cognitive resources at low or intermediate cognitive demand, while performance at high cognitive demand remains relatively unaffected, suggesting a primary attentional deficit during acute abstinence.
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Affiliation(s)
- E Lesage
- Neuroimaging Research Branch, National Institute on Drug Abuse, Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
- Department of Experimental Psychology, Gent University, Ghent, Belgium
| | - M T Sutherland
- Neuroimaging Research Branch, National Institute on Drug Abuse, Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
- Department of Psychology, Florida International University, Miami, FL, USA
| | - T J Ross
- Neuroimaging Research Branch, National Institute on Drug Abuse, Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | - B J Salmeron
- Neuroimaging Research Branch, National Institute on Drug Abuse, Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | - E A Stein
- Neuroimaging Research Branch, National Institute on Drug Abuse, Intramural Research Program, National Institutes of Health, Baltimore, MD, USA.
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28
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Cui Y, Dong F, Li X, Xie D, Cheng Y, Tian S, Xue T, Li Y, Zhang M, Ren Y, Yuan K, Yu D. Electrophysiological Evidence of Event-Related Potential Changes Induced by 12 h Abstinence in Young Smokers Based on the Flanker Study. Front Psychiatry 2020; 11:424. [PMID: 32528322 PMCID: PMC7258559 DOI: 10.3389/fpsyt.2020.00424] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 04/27/2020] [Indexed: 11/23/2022] Open
Abstract
The cognitive control processes may be disrupted by abstinence in smokers, which may be helpful in the development and maintenance of addictive behavior. The purpose of this study was to measure the performance of cognitive task after 12 h of smoking abstinence by using event-related potentials (ERPs), including the error-related negativity (ERN) and the error positivity (Pe). In Eriksen flanker task, electroencephalography (EEG) signals of 24 smokers were recorded in two conditions: satiety and 12 h abstinence. In the behavioral data, both conditions exhibited more errors and more time on the incongruent trials than congruence. Meantime, the Minnesota Nicotine Withdrawal Scale (MNWS) score was increased during abstinence. Smokers showed reduced ERN and Pe after 12 h of abstinence, compared with satiety condition. The results indicate that the diminished error processing in young smokers after 12 h of abstinence. It may be related to increased withdrawal symptoms. In conclusion, the disrupted neurophysiological indexes in the general behavior monitoring system may be caused by abstinence. The results of this study may provide us with new ideas about the effects of short-term abstinence on brain cognitive neuroscience and be helpful for the solution of relapse.
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Affiliation(s)
- Yongting Cui
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Fang Dong
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Xiaojian Li
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Dongdong Xie
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Yongxin Cheng
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Shiyu Tian
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Ting Xue
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Yangding Li
- College of Information Science and Engineering, Hunan Normal University, Changsha, China
| | - Ming Zhang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Yan Ren
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Kai Yuan
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China.,Life Sciences Research Center, School of Life Science and Technology, Xidian University, Xi'an, China
| | - Dahua Yu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
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29
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Shen Q, Heikkinen N, Kärkkäinen O, Gröhn H, Könönen M, Liu Y, Kaarre O, Zhang Z, Tan C, Tolmunen T, Vanninen R. Effects of long-term adolescent alcohol consumption on white matter integrity and their correlations with metabolic alterations. Psychiatry Res Neuroimaging 2019; 294:111003. [PMID: 31726326 DOI: 10.1016/j.pscychresns.2019.111003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2019] [Revised: 10/24/2019] [Accepted: 10/25/2019] [Indexed: 12/28/2022]
Abstract
Alcohol-related white matter (WM) microstructural changes have not been fully elucidated in adolescents. We aimed to investigate influences of subclinical alcohol use during adolescence on WM microstructure and to characterize those with serum metabolic alterations. 35 moderate-to-heavy drinkers (15 males, 20 females) and 27 controls (12 males, 15 females) were selected based on their ten-year Alcohol Use Disorders Identification Test scores measured at three time points. Magnetic resonance imaging was conducted at endpoint time. Whole brain analysis of fractional anisotropy (FA) was performed. Diffusivity indices in the significant regions were computed for between-group comparisons and correlation analyses with serum metabolite concentrations. Decreased FA was found in moderate-to-heavy drinking men in anterior corpus callosum, superior/anterior corona radiata and right inferior fronto-occipital fasciculus, accompanied by increased radial diffusivity and a smaller area of reduced axial diffusivity, which correlated with serum metabolites playing roles in energy metabolism, myelination and axonal degeneration. No significant difference in FA was detected between female or mixed-gender moderate-to-heavy drinking subjects and controls, supporting gender differences in the relationship between adolescent alcohol use and neurodevelopmental trajectories. Future researches with longitudinal imaging data are warranted for comprehensive evaluation on potentially reversible effects of alcohol use over adolescent brain.
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Affiliation(s)
- Qin Shen
- Department of Radiology, the Second Xiangya Hospital of Central South University, Changsha, China; Department of Clinical Radiology, Kuopio University Hospital, Kuopio, Finland
| | - Noora Heikkinen
- Department of Clinical Radiology, Kuopio University Hospital, Kuopio, Finland; Doctoral Programme of Clinical Research, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Olli Kärkkäinen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland; Department of Forensic Psychiatry, University of Eastern Finland, Niuvanniemi Hospital, Finland; School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Heidi Gröhn
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Mervi Könönen
- Department of Clinical Radiology, Kuopio University Hospital, Kuopio, Finland; Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio, Finland
| | - Yawu Liu
- Department of Clinical Radiology, Kuopio University Hospital, Kuopio, Finland; Department of Neurology, University of Kuopio, Kuopio, Finland
| | - Outi Kaarre
- Doctoral Programme of Clinical Research, School of Medicine, University of Eastern Finland, Kuopio, Finland; Department of Adolescent Psychiatry, Kuopio University Hospital, Kuopio, Finland
| | - Zishu Zhang
- Department of Radiology, the Second Xiangya Hospital of Central South University, Changsha, China
| | - Changlian Tan
- Department of Radiology, the Second Xiangya Hospital of Central South University, Changsha, China
| | - Tommi Tolmunen
- Department of Psychiatry, Kuopio University Hospital, Kuopio, Finland; Department of Psychiatry, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Ritva Vanninen
- Department of Clinical Radiology, Kuopio University Hospital, Kuopio, Finland; Department of Clinical Radiology, School of Medicine, University of Eastern Finland, Kuopio, Finland.
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30
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Qian W, Huang P, Shen Z, Wang C, Yang Y, Zhang M. Brain Gray Matter Volume and Functional Connectivity Are Associated With Smoking Cessation Outcomes. Front Hum Neurosci 2019; 13:361. [PMID: 31680913 PMCID: PMC6803765 DOI: 10.3389/fnhum.2019.00361] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Accepted: 09/26/2019] [Indexed: 11/13/2022] Open
Abstract
Smoking cessation is critical for reducing the risk of respiratory, cardiovascular diseases and cancers. However, most cessation attempts resulted in failure. In the present study, we aim to explore whether alterations of brain gray matter (GM) volume and functional connectivity (FC) are related to cessation outcomes, in hope of providing evidence for improving smoking cessation outcomes. Seventy-three smokers and 41 non-smokers were enrolled in the present study. All smokers participated in a 12-week smoking cessation treatment during which Varenicline was used to aid cessation. At the end of treatment, the smokers were divided into quitters and relapsers based on their abstinence performance. Structural magnetic resonance imaging (MRI) and voxel-based morphometry were applied to quantify the differences of regional brain volumes among the three groups at baseline. In addition, resting-state FC was used to investigate the related functional changes. In comparison with non-smokers, the smokers showed smaller GM volume in the left dorsal medial thalamus. Among the 73 smokers, 29 subjects successfully quitted smoking. The quitters showed greater GM volume than the relapsers in the right postcentral gyrus, right putamen\caudate nucleus and left orbitofrontal cortex (OFC). The GM volume in the left OFC was found to be negatively correlated with the pack years and daily smoking amount in the quitters. Furthermore, we found significantly reduced FC between left thalamus and left cerebellum in the relapsers. These findings extended our knowledge of the neural mechanism of smoking cessation, and suggested that brain structural and functional changes were related to smoking cessation outcomes.
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Affiliation(s)
- Wei Qian
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhujing Shen
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Chao Wang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yihong Yang
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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31
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Lei X, Zhong M, Zhang B, Yang H, Peng W, Liu Q, Zhang Y, Yao S, Tan C, Yi J. Structural and Functional Connectivity of the Anterior Cingulate Cortex in Patients With Borderline Personality Disorder. Front Neurosci 2019; 13:971. [PMID: 31572119 PMCID: PMC6753388 DOI: 10.3389/fnins.2019.00971] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Accepted: 08/29/2019] [Indexed: 12/17/2022] Open
Abstract
Background Emerging evidences supported the hypothesis that emotional dysregulation results from aberrant connectivity within the fronto-limbic neural networks in patients with borderline personality disorder (BPD). Considering its important role in emotional regulation, the anterior cingulate cortex (ACC) has not yet been fully explored in BPD patients. Therefore, using the seed-based resting state functional connectivity (rsFC) and probabilistic fiber tracking, we aimed to explore the alterations of functional and structural connectivity (SC) of the ACC in patients with BPD. Methods A cohort of 50 unmedicated, young BPD patients and 54 sex-, age-, and education-matched healthy controls (HCs) completed psychological tests and underwent rs-fMRI and diffuse tensor imaging (DTI) scanning. Rs-FC analysis and probabilistic fiber tracking were used to plot SC and FC of the ACC. Results With the left ACC selected as a seed, BPD patients exhibited increased rsFC and abnormal SC with the right middle frontal gyrus (MFG), and decreased rsFC with the left middle temporal gyrus (MTG), compared with HCs. Additionally, negative cognitive emotion regulation and depressive symptoms both correlated negatively with the rsFC of the left ACC in BPD patients. Conclusion Abnormal SC and FC of the ACC underlie the deficient emotional regulation circuitry in BPD patients. Such alterations may be important biomarkers of BPD and thus could point to potential BPD treatment targets.
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Affiliation(s)
- Xiaoxia Lei
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Mingtian Zhong
- Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, China
| | - Bowen Zhang
- Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, China
| | - Huihui Yang
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Wanrong Peng
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Qian Liu
- Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, China
| | - Yu Zhang
- Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, China
| | - Shuqiao Yao
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China.,Medical Psychological Institute, Central South University, Changsha, China
| | - Changlian Tan
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Jinyao Yi
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China.,Medical Psychological Institute, Central South University, Changsha, China
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32
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Liu C, Dong F, Li Y, Ren Y, Xie D, Wang X, Xue T, Zhang M, Ren G, von Deneen KM, Yuan K, Yu D. 12 h Abstinence-Induced ERP Changes in Young Smokers: Electrophysiological Evidence From a Go/NoGo Study. Front Psychol 2019; 10:1814. [PMID: 31474901 PMCID: PMC6703154 DOI: 10.3389/fpsyg.2019.01814] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2019] [Accepted: 07/22/2019] [Indexed: 11/13/2022] Open
Abstract
Decreased inhibition control ability and increased craving may be the most important causes of relapsing in smoking. Although inhibition control defects in young smokers were investigated, the effects of short-term abstinence on inhibition control in young smokers were still unclear. Thirty young smokers participated in the present study. The EEG signals during the Go/NoGo task were recorded in both satiety and 12 h abstinence conditions. The task performances were observed and compared between the two conditions. Event-related potential (ERP) analysis was used to investigate changes in N200 and P300 amplitude and latency induced by 12 h of abstinence. After 12 h of abstinence, the latency of N200 was prolonged in young smokers. No significant changes were found in the number of NoGo errors and the response time of Go in young smokers after 12 h of abstinence. Correlation analysis showed that the N200 latency of abstinence condition was significantly correlated with the number of NoGo errors and the response time of Go in the abstinence condition. The present findings may improve the understanding of the effect of short-term abstinence in young smokers. We suggested that the latency of N200 may be associated with inefficient inhibitory control of the abstinence condition in young smokers. Our results may contribute new insights into the neural mechanism of nicotine abstinence in young smokers.
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Affiliation(s)
- Chang Liu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Fang Dong
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Yangding Li
- Guangxi Key Laboratory of Multi-Source Information Mining and Security, Guangxi Normal University, Guilin, China
| | - Yan Ren
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Dongdong Xie
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Xianfu Wang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Ting Xue
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Ming Zhang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Guoyin Ren
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | | | - Kai Yuan
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
- Guangxi Key Laboratory of Multi-Source Information Mining and Security, Guangxi Normal University, Guilin, China
- School of Life Sciences and Technology, Xidian University, Xi’an, China
| | - Dahua Yu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
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33
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McCarthy JM, Dumais KM, Zegel M, Pizzagalli DA, Olson DP, Moran LV, Janes AC. Sex differences in tobacco smokers: Executive control network and frontostriatal connectivity. Drug Alcohol Depend 2019; 195:59-65. [PMID: 30592997 PMCID: PMC6625360 DOI: 10.1016/j.drugalcdep.2018.11.023] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2018] [Revised: 11/19/2018] [Accepted: 11/19/2018] [Indexed: 01/02/2023]
Abstract
BACKGROUND Women experience greater difficulty quitting smoking than men, which may be explained by sex differences in brain circuitry underlying cognitive control. Prior work has linked reduced interhemispheric executive control network (ECN) coupling with poor executive function, shorter time to relapse, and greater substance use. Lower structural connectivity between a key ECN hub, the dorsolateral prefrontal cortex (DLPFC), and the dorsal striatum (DS) also contributes to less efficient cognitive control recruitment, and reduced intrahemispheric connectivity between these regions has been associated with smoking relapse. Therefore, sex differences were probed by evaluating interhemispheric ECN and intrahemispheric DLPFC-DS connectivity. To assess the potential sex by nicotine interaction, a pilot sample of non-smokers was evaluated following acute nicotine and placebo administration. METHODS Thirty-five smokers (19 women) completed one resting state functional magnetic resonance imaging scan. Seventeen non-smokers (8 women) were scanned twice using a repeated measures design where they received 2 and 0 mg nicotine. RESULTS In smokers, women had less interhemispheric ECN and DLPFC-DS coupling than men. In non-smokers, there was a drug x sex interaction where women, relative to men, had weaker ECN coupling following nicotine but not placebo administration. CONCLUSIONS The current work indicates that nicotine-dependent women, versus men, have weaker connectivity in brain networks critically implicated in cognitive control. How these connectivity differences contribute to the behavioral aspects of smoking requires more testing. However, building on the literature, it is likely these deficits in functional connectivity contribute to the lower abstinence rates noted in women relative to men.
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Affiliation(s)
- Julie M McCarthy
- McLean Imaging Center, McLean Hospital, 115 Mill St., Belmont, MA, 02478, USA; Department of Psychiatry, Harvard Medical School, 401 Park Drive, Boston, MA, 02215, USA.
| | - Kelly M Dumais
- McLean Imaging Center, McLean Hospital, 115 Mill St., Belmont, MA, 02478, USA; Department of Psychiatry, Harvard Medical School, 401 Park Drive, Boston, MA, 02215, USA
| | - Maya Zegel
- McLean Imaging Center, McLean Hospital, 115 Mill St., Belmont, MA, 02478, USA
| | - Diego A Pizzagalli
- McLean Imaging Center, McLean Hospital, 115 Mill St., Belmont, MA, 02478, USA; Department of Psychiatry, Harvard Medical School, 401 Park Drive, Boston, MA, 02215, USA
| | - David P Olson
- McLean Imaging Center, McLean Hospital, 115 Mill St., Belmont, MA, 02478, USA; Department of Psychiatry, Harvard Medical School, 401 Park Drive, Boston, MA, 02215, USA
| | - Lauren V Moran
- McLean Imaging Center, McLean Hospital, 115 Mill St., Belmont, MA, 02478, USA; Department of Psychiatry, Harvard Medical School, 401 Park Drive, Boston, MA, 02215, USA
| | - Amy C Janes
- McLean Imaging Center, McLean Hospital, 115 Mill St., Belmont, MA, 02478, USA; Department of Psychiatry, Harvard Medical School, 401 Park Drive, Boston, MA, 02215, USA
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34
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Tan Y, Chen J, Liao W, Qian Z. Brain Function Network and Young Adult Smokers: A Graph Theory Analysis Study. Front Psychiatry 2019; 10:590. [PMID: 31543831 PMCID: PMC6728894 DOI: 10.3389/fpsyt.2019.00590] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Accepted: 07/25/2019] [Indexed: 11/24/2022] Open
Abstract
Cigarette smoking is associated with abnormalities in the widespread inter-regional functional connectivity of the brain. However, few studies focused on the abnormalities in the topological organization of brain functional networks in young smokers. In the current study, resting-state functional magnetic resonance images were acquired from 30 young male smokers and 32 age-, gender-, and education-matched healthy male nonsmokers. A functional network was constructed by calculating the Pearson correlation coefficients among 246 subregions in the human Brainnetome Atlas. The topological parameters were compared between smokers and nonsmokers. The results showed that the functional network of both young smokers and nonsmokers had small-world topology. Compared to nonsmokers, young smokers exhibited a decreased clustering coefficient (Cp) and local network efficiency (Elocal). Cp and Elocal were negatively correlated with the duration of cigarette use. In addition, increased nodal efficiency (Enodal) was mainly located in the prefrontal cortex (PFC), cingulate gyrus, insula, and caudate. Decreased connectivities among the PFC, cingulate gyrus, insula, basal ganglia (of specific node), and thalamus were also observed. In sum, we revealed the abnormal topological organization of brain functional networks in young smokers, which may improve our understanding of the neural mechanism of young smokers from a brain functional network topological organization perspective.
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Affiliation(s)
- Ying Tan
- Health Management Center, Xiangya Hospital, Central South University, Changsha, China
| | - Jing Chen
- Center of Stomatology, Xiangya Hospital, Central South University, Changsha, China
| | - Weiwei Liao
- Health Management Center, Xiangya Hospital, Central South University, Changsha, China
| | - Zhaoxin Qian
- Department of Emergency, Xiangya Hospital, Central South University, Changsha, China
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