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Zhang X, Huang M, Yu Y, Zhong X, Dai S, Dai Y, Jiang C. Is Transcranial Direct Current Stimulation Effective for Cognitive Dysfunction in Substance Use Disorders? A Systematic Review. Brain Sci 2024; 14:754. [PMID: 39199449 PMCID: PMC11352984 DOI: 10.3390/brainsci14080754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Revised: 07/13/2024] [Accepted: 07/25/2024] [Indexed: 09/01/2024] Open
Abstract
Patients with substance use disorders (SUDs) often suffer from cognitive dysfunction (CD), affecting their quality of life and daily functioning. Current treatments, including pharmacotherapy and psychotherapy, have limited efficacy and notable side effects. Transcranial direct current stimulation (tDCS), a non-invasive technique that modulates cortical activity, shows promise in improving cognitive function with minimal side effects and low cost, and could potentially serve as a valuable adjunct to existing therapies. This systematic review aims to evaluate the literature on the effectiveness of tDCS for CD in SUD patients to inform clinical practice and future research. Following PRISMA guidelines, the review includes studies that used tDCS for SUD-related CD. The criteria for inclusion encompassed participants aged 18 and older with a diagnosis of SUD, the use of tDCS (either conventional or high-definition), control groups receiving sham stimulation or no intervention, and cognitive outcome measures for substance-related cognitive function using validated tools. Databases searched were Ovid MEDLINE, PubMed, Web of Science, Embase, Scopus, and PsycINFO, with specific keywords. Twenty-two studies met the criteria, suggesting tDCS can improve cognitive functions in SUD patients, though results varied. Effectiveness may depend on the brain area targeted, stimulation parameters, task requirements, and individual differences. tDCS shows potential in treating SUD-related CD, but further research is needed to optimize stimulation protocols and address study variability. Future studies should use functional magnetic resonance imaging to explore the brain mechanisms by which tDCS improves cognitive function in SUDs and focus on larger, long-term trials to confirm efficacy and refine tDCS treatment parameters.
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Affiliation(s)
- Xinbi Zhang
- The Center of Neuroscience and Sports, Capital University of Physical Education and Sports, Beijing 100191, China; (X.Z.)
- School of Kinesiology and Health, Capital University of Physical Education and Sports, Beijing 100191, China
| | - Mingming Huang
- The Center of Neuroscience and Sports, Capital University of Physical Education and Sports, Beijing 100191, China; (X.Z.)
- School of Kinesiology and Health, Capital University of Physical Education and Sports, Beijing 100191, China
| | - Ying Yu
- Key Laboratory of Sport Training of General Administration of Sport of China, Beijing Sport University, Beijing 100084, China
- Sports, Exercise and Brain Sciences Laboratory, Beijing Sport University, Beijing 100084, China
| | - Xiaoke Zhong
- The Center of Neuroscience and Sports, Capital University of Physical Education and Sports, Beijing 100191, China; (X.Z.)
- School of Physical Education and Sport Science, Fujian Normal University, No. 18, Wulongjiang Middle Avenue, Shangjie Town, Minhou County, Fuzhou 350108, China
| | - Shengyu Dai
- The Center of Neuroscience and Sports, Capital University of Physical Education and Sports, Beijing 100191, China; (X.Z.)
- School of Kinesiology and Health, Capital University of Physical Education and Sports, Beijing 100191, China
| | - Yuanfu Dai
- The Center of Neuroscience and Sports, Capital University of Physical Education and Sports, Beijing 100191, China; (X.Z.)
- School of Kinesiology and Health, Capital University of Physical Education and Sports, Beijing 100191, China
| | - Changhao Jiang
- The Center of Neuroscience and Sports, Capital University of Physical Education and Sports, Beijing 100191, China; (X.Z.)
- School of Kinesiology and Health, Capital University of Physical Education and Sports, Beijing 100191, China
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Wardle MC, Webber HE, Yoon JH, Heads AM, Stotts AL, Lane SD, Schmitz JM. Behavioral therapies targeting reward mechanisms in substance use disorders. Pharmacol Biochem Behav 2024; 240:173787. [PMID: 38705285 DOI: 10.1016/j.pbb.2024.173787] [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: 01/17/2024] [Revised: 04/04/2024] [Accepted: 05/02/2024] [Indexed: 05/07/2024]
Abstract
Behavioral therapies are considered best practices in the treatment of substance use disorders (SUD) and used as first-line approaches for SUDs without FDA-approved pharmacotherapies. Decades of research on the neuroscience of drug reward and addiction have informed the development of current leading behavioral therapies that, while differing in focus and technique, have in common the overarching goal of shifting reward responding away from drug and toward natural non-drug rewards. This review begins by describing key neurobiological processes of reward in addiction, followed by a description of how various behavioral therapies address specific reward processes. Based on this review, a conceptual 'map' is crafted to pinpoint gaps and areas of overlap, serving as a guide for selecting and integrating behavioral therapies.
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Affiliation(s)
- Margaret C Wardle
- Department of Psychology, University of Illinois at Chicago, Chicago, IL, United States of America
| | - Heather E Webber
- Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, United States of America
| | - Jin H Yoon
- Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, United States of America
| | - Angela M Heads
- Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, United States of America
| | - Angela L Stotts
- Department of Family and Community Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, United States of America
| | - Scott D Lane
- Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, United States of America
| | - Joy M Schmitz
- Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
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Chan YH, Chang HM, Lu ML, Goh KK. Targeting cravings in substance addiction with transcranial direct current stimulation: insights from a meta-analysis of sham-controlled trials. Psychiatry Res 2024; 331:115621. [PMID: 38043411 DOI: 10.1016/j.psychres.2023.115621] [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: 06/24/2023] [Revised: 10/06/2023] [Accepted: 11/19/2023] [Indexed: 12/05/2023]
Abstract
Addiction is a substantial health concern; craving-the core symptom of addiction-is strongly associated with relapse. Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique that reduces cravings by altering cortical excitability and connectivity in brain regions. This systematic review and meta-analysis was conducted (following the PRISMA guidelines) to evaluate the efficacy of tDCS in reducing cravings for substances. Our analysis included 43 randomized, sham-controlled trials involving 1,095 and 913 participants receiving tDCS and sham stimulation, respectively. We analyzed the changes in craving scores and found that tDCS led to a moderate reduction in cravings compared with the sham effects. This effect was particularly pronounced when bilateral stimulation was used, the anodal electrode was placed on the right dorsolateral prefrontal cortex, current intensities ranged from 1.5 to 2 mA, stimulation sessions lasted 20 minutes, and the electrodes size was ≥35 cm². Notably, tDCS effectively reduced cravings for opioids, methamphetamine, cocaine, and tobacco but not for alcohol or cannabis. Our findings indicate tDCS as a promising, noninvasive, and low-risk intervention for reducing cravings for opioids, methamphetamine, cocaine, and tobacco. Additional studies are warranted to refine stimulation parameters and evaluate the long-term efficacy of tDCS in managing substance cravings.
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Affiliation(s)
- Yi-Hsun Chan
- Department of Psychiatry, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan
| | - Hu-Ming Chang
- Department of Addiction Sciences, Taipei City Psychiatric Center, Taipei City Hospital, Taipei, Taiwan; Psychiatric Research Center, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan
| | - Mong-Liang Lu
- Department of Psychiatry, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan; Psychiatric Research Center, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan; Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Kah Kheng Goh
- Department of Psychiatry, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan; Psychiatric Research Center, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan; Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan; Graduate Institute of Injury Prevention and Control, College of Public Health, Taipei Medical University, Taipei, Taiwan; The Innovative and Translational Research Center for Brain Consciousness, Taipei Medical University, Taipei, Taiwan.
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Chen YH, Yang J, Wu H, Beier KT, Sawan M. Challenges and future trends in wearable closed-loop neuromodulation to efficiently treat methamphetamine addiction. Front Psychiatry 2023; 14:1085036. [PMID: 36911117 PMCID: PMC9995819 DOI: 10.3389/fpsyt.2023.1085036] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 02/03/2023] [Indexed: 02/25/2023] Open
Abstract
Achieving abstinence from drugs is a long journey and can be particularly challenging in the case of methamphetamine, which has a higher relapse rate than other drugs. Therefore, real-time monitoring of patients' physiological conditions before and when cravings arise to reduce the chance of relapse might help to improve clinical outcomes. Conventional treatments, such as behavior therapy and peer support, often cannot provide timely intervention, reducing the efficiency of these therapies. To more effectively treat methamphetamine addiction in real-time, we propose an intelligent closed-loop transcranial magnetic stimulation (TMS) neuromodulation system based on multimodal electroencephalogram-functional near-infrared spectroscopy (EEG-fNIRS) measurements. This review summarizes the essential modules required for a wearable system to treat addiction efficiently. First, the advantages of neuroimaging over conventional techniques such as analysis of sweat, saliva, or urine for addiction detection are discussed. The knowledge to implement wearable, compact, and user-friendly closed-loop systems with EEG and fNIRS are reviewed. The features of EEG and fNIRS signals in patients with methamphetamine use disorder are summarized. EEG biomarkers are categorized into frequency and time domain and topography-related parameters, whereas for fNIRS, hemoglobin concentration variation and functional connectivity of cortices are described. Following this, the applications of two commonly used neuromodulation technologies, transcranial direct current stimulation and TMS, in patients with methamphetamine use disorder are introduced. The challenges of implementing intelligent closed-loop TMS modulation based on multimodal EEG-fNIRS are summarized, followed by a discussion of potential research directions and the promising future of this approach, including potential applications to other substance use disorders.
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Affiliation(s)
- Yun-Hsuan Chen
- CenBRAIN Neurotech Center of Excellence, School of Engineering, Westlake University, Hangzhou, China
- Institute of Advanced Technology, Westlake Institute for Advanced Study, Hangzhou, China
| | - Jie Yang
- CenBRAIN Neurotech Center of Excellence, School of Engineering, Westlake University, Hangzhou, China
- Institute of Advanced Technology, Westlake Institute for Advanced Study, Hangzhou, China
| | - Hemmings Wu
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Kevin T. Beier
- Department of Physiology and Biophysics, University of California, Irvine, Irvine, CA, United States
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, United States
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
- Department of Pharmaceutical Sciences, University of California, Irvine, Irvine, CA, United States
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, United States
| | - Mohamad Sawan
- CenBRAIN Neurotech Center of Excellence, School of Engineering, Westlake University, Hangzhou, China
- Institute of Advanced Technology, Westlake Institute for Advanced Study, Hangzhou, China
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Li M, Qiu M, Kong W, Zhu L, Ding Y. Fusion Graph Representation of EEG for Emotion Recognition. SENSORS (BASEL, SWITZERLAND) 2023; 23:1404. [PMID: 36772444 PMCID: PMC9919892 DOI: 10.3390/s23031404] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 01/21/2023] [Accepted: 01/22/2023] [Indexed: 06/18/2023]
Abstract
Various relations existing in Electroencephalogram (EEG) data are significant for EEG feature representation. Thus, studies on the graph-based method focus on extracting relevancy between EEG channels. The shortcoming of existing graph studies is that they only consider a single relationship of EEG electrodes, which results an incomprehensive representation of EEG data and relatively low accuracy of emotion recognition. In this paper, we propose a fusion graph convolutional network (FGCN) to extract various relations existing in EEG data and fuse these extracted relations to represent EEG data more comprehensively for emotion recognition. First, the FGCN mines brain connection features on topology, causality, and function. Then, we propose a local fusion strategy to fuse these three graphs to fully utilize the valuable channels with strong topological, causal, and functional relations. Finally, the graph convolutional neural network is adopted to represent EEG data for emotion recognition better. Experiments on SEED and SEED-IV demonstrate that fusing different relation graphs are effective for improving the ability in emotion recognition. Furthermore, the emotion recognition accuracy of 3-class and 4-class is higher than that of other state-of-the-art methods.
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Affiliation(s)
- Menghang Li
- College of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China
- Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province, Hangzhou 310018, China
| | - Min Qiu
- College of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China
- Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province, Hangzhou 310018, China
| | - Wanzeng Kong
- College of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China
- Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province, Hangzhou 310018, China
| | - Li Zhu
- College of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China
- Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province, Hangzhou 310018, China
| | - Yu Ding
- Netease Fuxi AI Lab, Hangzhou 310018, China
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Bel-Bahar TS, Khan AA, Shaik RB, Parvaz MA. A scoping review of electroencephalographic (EEG) markers for tracking neurophysiological changes and predicting outcomes in substance use disorder treatment. Front Hum Neurosci 2022; 16:995534. [PMID: 36325430 PMCID: PMC9619053 DOI: 10.3389/fnhum.2022.995534] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Accepted: 09/20/2022] [Indexed: 11/24/2022] Open
Abstract
Substance use disorders (SUDs) constitute a growing global health crisis, yet many limitations and challenges exist in SUD treatment research, including the lack of objective brain-based markers for tracking treatment outcomes. Electroencephalography (EEG) is a neurophysiological technique for measuring brain activity, and although much is known about EEG activity in acute and chronic substance use, knowledge regarding EEG in relation to abstinence and treatment outcomes is sparse. We performed a scoping review of longitudinal and pre-post treatment EEG studies that explored putative changes in brain function associated with abstinence and/or treatment in individuals with SUD. Following PRISMA guidelines, we identified studies published between January 2000 and March 2022 from online databases. Search keywords included EEG, addictive substances (e.g., alcohol, cocaine, methamphetamine), and treatment related terms (e.g., abstinence, relapse). Selected studies used EEG at least at one time point as a predictor of abstinence or other treatment-related outcomes; or examined pre- vs. post-SUD intervention (brain stimulation, pharmacological, behavioral) EEG effects. Studies were also rated on the risk of bias and quality using validated instruments. Forty-four studies met the inclusion criteria. More consistent findings included lower oddball P3 and higher resting beta at baseline predicting negative outcomes, and abstinence-mediated longitudinal decrease in cue-elicited P3 amplitude and resting beta power. Other findings included abstinence or treatment-related changes in late positive potential (LPP) and N2 amplitudes, as well as in delta and theta power. Existing studies were heterogeneous and limited in terms of specific substances of interest, brief times for follow-ups, and inconsistent or sparse results. Encouragingly, in this limited but maturing literature, many studies demonstrated partial associations of EEG markers with abstinence, treatment outcomes, or pre-post treatment-effects. Studies were generally of good quality in terms of risk of bias. More EEG studies are warranted to better understand abstinence- or treatment-mediated neural changes or to predict SUD treatment outcomes. Future research can benefit from prospective large-sample cohorts and the use of standardized methods such as task batteries. EEG markers elucidating the temporal dynamics of changes in brain function related to abstinence and/or treatment may enable evidence-based planning for more effective and targeted treatments, potentially pre-empting relapse or minimizing negative lifespan effects of SUD.
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Affiliation(s)
- Tarik S. Bel-Bahar
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Anam A. Khan
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Riaz B. Shaik
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Muhammad A. Parvaz
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
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