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Sangchooli A, Zare-Bidoky M, Fathi Jouzdani A, Schacht J, Bjork JM, Claus ED, Prisciandaro JJ, Wilson SJ, Wüstenberg T, Potvin S, Ahmadi P, Bach P, Baldacchino A, Beck A, Brady KT, Brewer JA, Childress AR, Courtney KE, Ebrahimi M, Filbey FM, Garavan H, Ghahremani DG, Goldstein RZ, Goudriaan AE, Grodin EN, Hanlon CA, Haugg A, Heilig M, Heinz A, Holczer A, Van Holst RJ, Joseph JE, Juliano AC, Kaufman MJ, Kiefer F, Khojasteh Zonoozi A, Kuplicki RT, Leyton M, London ED, Mackey S, McClernon FJ, Mellick WH, Morley K, Noori HR, Oghabian MA, Oliver JA, Owens M, Paulus MP, Perini I, Rafei P, Ray LA, Sinha R, Smolka MN, Soleimani G, Spanagel R, Steele VR, Tapert SF, Vollstädt-Klein S, Wetherill RR, Witkiewitz K, Yuan K, Zhang X, Verdejo-Garcia A, Potenza MN, Janes AC, Kober H, Zilverstand A, Ekhtiari H. Parameter Space and Potential for Biomarker Development in 25 Years of fMRI Drug Cue Reactivity: A Systematic Review. JAMA Psychiatry 2024; 81:414-425. [PMID: 38324323 PMCID: PMC11304510 DOI: 10.1001/jamapsychiatry.2023.5483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/08/2024]
Abstract
Importance In the last 25 years, functional magnetic resonance imaging drug cue reactivity (FDCR) studies have characterized some core aspects in the neurobiology of drug addiction. However, no FDCR-derived biomarkers have been approved for treatment development or clinical adoption. Traversing this translational gap requires a systematic assessment of the FDCR literature evidence, its heterogeneity, and an evaluation of possible clinical uses of FDCR-derived biomarkers. Objective To summarize the state of the field of FDCR, assess their potential for biomarker development, and outline a clear process for biomarker qualification to guide future research and validation efforts. Evidence Review The PubMed and Medline databases were searched for every original FDCR investigation published from database inception until December 2022. Collected data covered study design, participant characteristics, FDCR task design, and whether each study provided evidence that might potentially help develop susceptibility, diagnostic, response, prognostic, predictive, or severity biomarkers for 1 or more addictive disorders. Findings There were 415 FDCR studies published between 1998 and 2022. Most focused on nicotine (122 [29.6%]), alcohol (120 [29.2%]), or cocaine (46 [11.1%]), and most used visual cues (354 [85.3%]). Together, these studies recruited 19 311 participants, including 13 812 individuals with past or current substance use disorders. Most studies could potentially support biomarker development, including diagnostic (143 [32.7%]), treatment response (141 [32.3%]), severity (84 [19.2%]), prognostic (30 [6.9%]), predictive (25 [5.7%]), monitoring (12 [2.7%]), and susceptibility (2 [0.5%]) biomarkers. A total of 155 interventional studies used FDCR, mostly to investigate pharmacological (67 [43.2%]) or cognitive/behavioral (51 [32.9%]) interventions; 141 studies used FDCR as a response measure, of which 125 (88.7%) reported significant interventional FDCR alterations; and 25 studies used FDCR as an intervention outcome predictor, with 24 (96%) finding significant associations between FDCR markers and treatment outcomes. Conclusions and Relevance Based on this systematic review and the proposed biomarker development framework, there is a pathway for the development and regulatory qualification of FDCR-based biomarkers of addiction and recovery. Further validation could support the use of FDCR-derived measures, potentially accelerating treatment development and improving diagnostic, prognostic, and predictive clinical judgments.
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Affiliation(s)
- Arshiya Sangchooli
- Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Australia
| | - Mehran Zare-Bidoky
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | - Ali Fathi Jouzdani
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | - Joseph Schacht
- Department of Psychiatry, University of Colorado School of Medicine, Aurora
| | - James M Bjork
- Institute for Drug and Alcohol Studies, Department of Psychiatry, Virginia Commonwealth University, Richmond
| | - Eric D Claus
- Department of Biobehavioral Health, The Pennsylvania State University, University Park
| | - James J Prisciandaro
- Addiction Sciences Division, Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston
| | - Stephen J Wilson
- Department of Psychology, The Pennsylvania State University, State College
| | - Torsten Wüstenberg
- Field of Focus IV, Core Facility for Neuroscience of Self-Regulation (CNSR), Heidelberg University, Heidelberg, Germany
| | - Stéphane Potvin
- Department of Psychiatry and Addiction, Université de Montréal, Montréal, Quebec, Canada
| | - Pooria Ahmadi
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Patrick Bach
- Department of Addictive Behaviour and Addiction Medicine, Central Institute of Mental Health (CIMH), Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Alex Baldacchino
- School of Medicine, University of St Andrews, St Andrews, Scotland
| | - Anne Beck
- Faculty of Health, Health and Medical University, Potsdam, Germany
- Department of Psychiatry and Neurosciences, Charité Campus Mitte, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Kathleen T Brady
- Addiction Sciences Division, Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston
| | - Judson A Brewer
- Department of Behavioral and Social Sciences, Brown University School of Public Health, Providence, Rhode Island
| | | | | | - Mohsen Ebrahimi
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | - Francesca M Filbey
- Center for BrainHealth, School of Behavioral and Brain Sciences, University of Texas at Dallas
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont, Burlington
| | - Dara G Ghahremani
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
| | - Rita Z Goldstein
- Departments of Psychiatry and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Anneke E Goudriaan
- Department of Psychiatry, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Erica N Grodin
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
| | - Colleen A Hanlon
- Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, North Carolina
- BrainsWay Inc, Winston-Salem, North Carolina
| | - Amelie Haugg
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Markus Heilig
- Center for Social and Affective Neuroscience, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Andreas Heinz
- Department of Psychiatry and Neurosciences, Charité Campus Mitte, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Adrienn Holczer
- Department of Neurology, Albert Szent-Györgyi Health Centre, University of Szeged, Szeged, Hungary
| | - Ruth J Van Holst
- Amsterdam Institute for Addiction Research, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Jane E Joseph
- Department of Neuroscience, Medical University of South Carolina, Charleston
| | | | - Marc J Kaufman
- McLean Hospital, Harvard Medical School, Belmont, Massachusetts
| | - Falk Kiefer
- Department of Addictive Behaviour and Addiction Medicine, Central Institute of Mental Health (CIMH), Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Arash Khojasteh Zonoozi
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | | | - Marco Leyton
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Edythe D London
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
| | - Scott Mackey
- Department of Psychiatry, University of Vermont, Burlington
| | - F Joseph McClernon
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
| | - William H Mellick
- Addiction Sciences Division, Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston
| | - Kirsten Morley
- Specialty of Addiction Medicine, Faculty of Medicine and Health, Sydney Medical School, University of Sydney, Sydney, Australia
| | - Hamid R Noori
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge
| | - Mohammad Ali Oghabian
- Neuroimaging and Analysis Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
| | - Jason A Oliver
- TSET Health Promotion Research Center, University of Oklahoma Health Sciences Center, Oklahoma City
| | - Max Owens
- Department of Psychiatry, University of Vermont, Burlington
| | | | - Irene Perini
- Center for Social and Affective Neuroscience, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Parnian Rafei
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | - Lara A Ray
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
| | - Rajita Sinha
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Michael N Smolka
- Department of Psychiatry, Technische Universität Dresden, Dresden, Germany
| | - Ghazaleh Soleimani
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis
| | - Rainer Spanagel
- Institute of Psychopharmacology, Central Institute of Mental Health, Mannheim, Germany
| | - Vaughn R Steele
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Susan F Tapert
- Department of Psychiatry, University of California, San Diego
| | - Sabine Vollstädt-Klein
- Department of Addictive Behaviour and Addiction Medicine, Central Institute of Mental Health (CIMH), Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | | | | | - Kai Yuan
- School of Life Science and Technology, Xidian University, Xi'an, China
| | - Xiaochu Zhang
- Department of Psychology, School of Humanities and Social Science, University of Science and Technology of China, Anhui, China
| | | | - Marc N Potenza
- Department of Psychiatry, Technische Universität Dresden, Dresden, Germany
| | - Amy C Janes
- Cognitive and Pharmacological Neuroimaging Unit, National Institute on Drug Abuse, Baltimore, Maryland
| | - Hedy Kober
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Anna Zilverstand
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis
| | - Hamed Ekhtiari
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis
- Laureate Institute for Brain Research, Tulsa, Oklahoma
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Sofat N, Lambarth A. Can we achieve pain stratification in musculoskeletal conditions? Implications for clinical practice. FRONTIERS IN PAIN RESEARCH 2024; 5:1362757. [PMID: 38524267 PMCID: PMC10958789 DOI: 10.3389/fpain.2024.1362757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Accepted: 02/26/2024] [Indexed: 03/26/2024] Open
Abstract
In the last few years there has been an increased appreciation that pain perception in rheumatic and musculoskeletal diseases (RMDs) has several mechanisms which include nociceptive, inflammatory, nociplastic and neuropathic components. Studies in specific patient groups have also demonstrated that the pain experienced by people with specific diagnoses can present with distinctive components over time. For example, the pain observed in rheumatoid arthritis has been widely accepted to be caused by the activation of nociceptors, potentiated by the release of inflammatory mediators, including prostaglandins, leukotrienes and cytokine networks in the joint environment. However, people with RA may also experience nociplastic and neuropathic pain components, particularly when treatments with disease modifying anti-rheumatic drugs (DMARDs) have been implemented and are insufficient to control pain symptoms. In other RMDs, the concept of pain sensitisation or nociplastic pain in driving ongoing pain symptoms e.g. osteoarthritis and fibromyalgia, is becoming increasingly recognised. In this review, we explore the hypothesis that pain has distinct modalities based on clinical, pathophysiological, imaging and genetic factors. The concept of pain stratification in RMD is explored and implications for future management are also discussed.
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Affiliation(s)
- Nidhi Sofat
- Institute for Infection and Immunity, St George’s, University of London, London, United Kingdom
- Department of Rheumatology, St George’s University Hospitals NHS Foundation Trust, London, United Kingdom
| | - Andrew Lambarth
- Institute for Infection and Immunity, St George’s, University of London, London, United Kingdom
- Department of Rheumatology, St George’s University Hospitals NHS Foundation Trust, London, United Kingdom
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Hu L, Katz ES, Stamoulis C. Modulatory effects of fMRI acquisition time of day, week and year on adolescent functional connectomes across spatial scales: Implications for inference. Neuroimage 2023; 284:120459. [PMID: 37977408 DOI: 10.1016/j.neuroimage.2023.120459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 11/06/2023] [Accepted: 11/14/2023] [Indexed: 11/19/2023] Open
Abstract
Metabolic, hormonal, autonomic and physiological rhythms may have a significant impact on cerebral hemodynamics and intrinsic brain synchronization measured with fMRI (the resting-state connectome). The impact of their characteristic time scales (hourly, circadian, seasonal), and consequently scan timing effects, on brain topology in inherently heterogeneous developing connectomes remains elusive. In a cohort of 4102 early adolescents with resting-state fMRI (median age = 120.0 months; 53.1 % females) from the Adolescent Brain Cognitive Development Study, this study investigated associations between scan time-of-day, time-of-week (school day vs weekend) and time-of-year (school year vs summer vacation) and topological properties of resting-state connectomes at multiple spatial scales. On average, participants were scanned around 2 pm, primarily during school days (60.9 %), and during the school year (74.6 %). Scan time-of-day was negatively correlated with multiple whole-brain, network-specific and regional topological properties (with the exception of a positive correlation with modularity), primarily of visual, dorsal attention, salience, frontoparietal control networks, and the basal ganglia. Being scanned during the weekend (vs a school day) was correlated with topological differences in the hippocampus and temporoparietal networks. Being scanned during the summer vacation (vs the school year) was consistently positively associated with multiple topological properties of bilateral visual, and to a lesser extent somatomotor, dorsal attention and temporoparietal networks. Time parameter interactions suggested that being scanned during the weekend and summer vacation enhanced the positive effects of being scanned in the morning. Time-of-day effects were overall small but spatially extensive, and time-of-week and time-of-year effects varied from small to large (Cohen's f ≤ 0.1, Cohen's d<0.82, p < 0.05). Together, these parameters were also positively correlated with temporal fMRI signal variability but only in the left hemisphere. Finally, confounding effects of scan time parameters on relationships between connectome properties and cognitive task performance were assessed using the ABCD neurocognitive battery. Although most relationships were unaffected by scan time parameters, their combined inclusion eliminated associations between properties of visual and somatomotor networks and performance in the Matrix Reasoning and Pattern Comparison Processing Speed tasks. Thus, scan time of day, week and year may impact measurements of adolescent brain's functional circuits, and should be accounted for in studies on their associations with cognitive performance, in order to reduce the probability of incorrect inference.
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Affiliation(s)
- Linfeng Hu
- Department of Pediatrics, Division of Adolescent and Young Adult Medicine, Boston Children's Hospital, Boston, MA 02115, USA; Harvard School of Public Health, Department of Biostatistics, Boston, MA 02115, USA
| | - Eliot S Katz
- Johns Hopkins All Children's Hospital, St. Petersburg, FL 33701, USA
| | - Catherine Stamoulis
- Department of Pediatrics, Division of Adolescent and Young Adult Medicine, Boston Children's Hospital, Boston, MA 02115, USA; Harvard Medical School, Department of Pediatrics, Boston, MA 02115, USA.
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Voets NL, Bartsch AJ, Plaha P. Functional MRI applications for intra-axial brain tumours: uses and nuances in surgical practise. Br J Neurosurg 2023; 37:1544-1559. [PMID: 36148501 DOI: 10.1080/02688697.2022.2123893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 09/07/2022] [Indexed: 11/02/2022]
Abstract
PURPOSE Functional MRI (fMRI) has well-established uses to inform risks and plan maximally safe approaches in neurosurgery. In the field of brain tumour surgery, however, fMRI is currently in a state of clinical equipoise due to debate around both its sensitivity and specificity. MATERIALS AND METHODS In this review, we summarise the role and our experience of fMRI in neurosurgery for gliomas and metastases. We discuss nuances in the conduct and interpretation of fMRI that, based on our practise, most directly impact fMRI's usefulness in the neurosurgical setting. RESULTS Illustrated examples in which fMRI in our hands directly influences the neurosurgical treatment of brain tumours include evaluating the probability and nature of functional risks, especially for language functions. These presurgical risk assessments, in turn, help to predict the resectability of tumours, select or deselect patients for awake surgery, indicate the need for neurophysiological monitoring and guide the optimal use of intra-operative stimulation mapping. A further emerging application of fMRI is in measuring functional adaptation of functional networks after (partial) surgery, of potential use in the timing of further surgery. CONCLUSIONS In appropriately selected patients with a clearly defined surgical question, fMRI offers a valuable complementary tool in the pre-surgical evaluation of brain tumours. However, there is a great need for standards in the administration and analysis of fMRI as much as in the techniques that it is commonly evaluated against. Surprisingly little data exists that evaluates the accuracy of fMRI not just against complementary methods, but in terms of its ultimate clinical aim of minimising post-surgical morbidity.
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Affiliation(s)
- Natalie L Voets
- Department of Neurosurgery, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- GenesisCare Ltd, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Andreas J Bartsch
- Department of Neuroradiology, University of Heidelberg, Heidelberg, Germany
| | - Puneet Plaha
- Department of Neurosurgery, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Nuffield Department of Neurosurgery, University of Oxford, Oxford, UK
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5
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Linguiti S, Vogel JW, Sydnor VJ, Pines A, Wellman N, Basbaum A, Eickhoff CR, Eickhoff SB, Edwards RR, Larsen B, McKinstry-Wu A, Scott JC, Roalf DR, Sharma V, Strain EC, Corder G, Dworkin RH, Satterthwaite TD. Functional imaging studies of acute administration of classic psychedelics, ketamine, and MDMA: Methodological limitations and convergent results. Neurosci Biobehav Rev 2023; 154:105421. [PMID: 37802267 DOI: 10.1016/j.neubiorev.2023.105421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/13/2023] [Accepted: 10/02/2023] [Indexed: 10/08/2023]
Abstract
Functional magnetic resonance imaging (fMRI) is increasingly used to non-invasively study the acute impact of psychedelics on the human brain. While fMRI is a promising tool for measuring brain function in response to psychedelics, it also has known methodological challenges. We conducted a systematic review of fMRI studies examining acute responses to experimentally administered psychedelics in order to identify convergent findings and characterize heterogeneity in the literature. We reviewed 91 full-text papers; these studies were notable for substantial heterogeneity in design, task, dosage, drug timing, and statistical approach. Data recycling was common, with 51 unique samples across 91 studies. Fifty-seven studies (54%) did not meet contemporary standards for Type I error correction or control of motion artifact. Psilocybin and LSD were consistently reported to moderate the connectivity architecture of the sensorimotor-association cortical axis. Studies also consistently reported that ketamine administration increased activation in the dorsomedial prefrontal cortex. Moving forward, use of best practices such as pre-registration, standardized image processing and statistical testing, and data sharing will be important in this rapidly developing field.
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Affiliation(s)
- Sophia Linguiti
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Philadelphia, PA, United States; Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Jacob W Vogel
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Philadelphia, PA, United States; Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States; Department of Clinical Sciences, Malmö, SciLifeLab, Lund University, Lund, Sweden
| | - Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Philadelphia, PA, United States; Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Adam Pines
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Philadelphia, PA, United States; Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States; Department of Psychiatry, Stanford University, Stanford, CA, United States
| | - Nick Wellman
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Philadelphia, PA, United States; Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Allan Basbaum
- Department of Anatomy, University of California, San Francisco, United States
| | - Claudia R Eickhoff
- Institute of Neuroscience and Medicine, (INM-1, INM-7), Research Centre Jülich, Jülich, Germany; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, (INM-1, INM-7), Research Centre Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
| | - Robert R Edwards
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Philadelphia, PA, United States; Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Andrew McKinstry-Wu
- Department of Anesthesiology and Critical Care, Neuroscience of Unconsciousness and Reanimation Research Alliance (NEURRAL), University of Pennsylvania, Philadelphia, United States
| | - J Cobb Scott
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States; VISN4 Mental Illness Research, Education, and Clinical Center at the Corporal Michael J. Crescenz VA (Veterans Affairs) Medical Center, Philadelphia, PA, United States
| | - David R Roalf
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Vaishnavi Sharma
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Philadelphia, PA, United States; Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Eric C Strain
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University School of Medicine, 5510 Nathan Shock Drive, Baltimore, MD, United States
| | - Gregory Corder
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Robert H Dworkin
- Department of Anesthesiology and Perioperative Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY, United States
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Philadelphia, PA, United States; Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States.
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Soleimani G, Nitsche MA, Bergmann TO, Towhidkhah F, Violante IR, Lorenz R, Kuplicki R, Tsuchiyagaito A, Mulyana B, Mayeli A, Ghobadi-Azbari P, Mosayebi-Samani M, Zilverstand A, Paulus MP, Bikson M, Ekhtiari H. Closing the loop between brain and electrical stimulation: towards precision neuromodulation treatments. Transl Psychiatry 2023; 13:279. [PMID: 37582922 PMCID: PMC10427701 DOI: 10.1038/s41398-023-02565-5] [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: 07/08/2022] [Revised: 07/06/2023] [Accepted: 07/20/2023] [Indexed: 08/17/2023] Open
Abstract
One of the most critical challenges in using noninvasive brain stimulation (NIBS) techniques for the treatment of psychiatric and neurologic disorders is inter- and intra-individual variability in response to NIBS. Response variations in previous findings suggest that the one-size-fits-all approach does not seem the most appropriate option for enhancing stimulation outcomes. While there is a growing body of evidence for the feasibility and effectiveness of individualized NIBS approaches, the optimal way to achieve this is yet to be determined. Transcranial electrical stimulation (tES) is one of the NIBS techniques showing promising results in modulating treatment outcomes in several psychiatric and neurologic disorders, but it faces the same challenge for individual optimization. With new computational and methodological advances, tES can be integrated with real-time functional magnetic resonance imaging (rtfMRI) to establish closed-loop tES-fMRI for individually optimized neuromodulation. Closed-loop tES-fMRI systems aim to optimize stimulation parameters based on minimizing differences between the model of the current brain state and the desired value to maximize the expected clinical outcome. The methodological space to optimize closed-loop tES fMRI for clinical applications includes (1) stimulation vs. data acquisition timing, (2) fMRI context (task-based or resting-state), (3) inherent brain oscillations, (4) dose-response function, (5) brain target trait and state and (6) optimization algorithm. Closed-loop tES-fMRI technology has several advantages over non-individualized or open-loop systems to reshape the future of neuromodulation with objective optimization in a clinically relevant context such as drug cue reactivity for substance use disorder considering both inter and intra-individual variations. Using multi-level brain and behavior measures as input and desired outcomes to individualize stimulation parameters provides a framework for designing personalized tES protocols in precision psychiatry.
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Affiliation(s)
- Ghazaleh Soleimani
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
- Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Michael A Nitsche
- Department of Psychology and Neuroscience, Leibniz Research Center for Working Environment and Human Factors, Dortmund, Germany
- Bielefeld University, University Hospital OWL, Protestant Hospital of Bethel Foundation, University Clinic of Psychiatry and Psychotherapy, and University Clinic of Child and Adolescent Psychiatry and Psychotherapy, Bielefeld, Germany
| | - Til Ole Bergmann
- Neuroimaging Center, Focus Program Translational Neuroscience, Johannes Gutenberg University Medical Center Mainz, Mainz, Germany
- Leibniz Institute for Resilience Research, Mainz, Germany
| | - Farzad Towhidkhah
- Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Ines R Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guilford, UK
| | - Romy Lorenz
- Department of Psychology, Stanford University, Stanford, CA, USA
- MRC CBU, University of Cambridge, Cambridge, UK
- Department of Neurophysics, MPI, Leipzig, Germany
| | | | | | - Beni Mulyana
- Laureate Institute for Brain Research, Tulsa, OK, USA
- School of Electrical and Computer Engineering, University of Oklahoma, Tulsa, OK, USA
| | - Ahmad Mayeli
- University of Pittsburgh Medical Center, Pittsburg, PA, USA
| | - Peyman Ghobadi-Azbari
- Department of Biomedical Engineering, Shahed University, Tehran, Iran
- Iranian National Center for Addiction Studies, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohsen Mosayebi-Samani
- Department of Psychology and Neuroscience, Leibniz Research Center for Working Environment and Human Factors, Dortmund, Germany
| | - Anna Zilverstand
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | | | | | - Hamed Ekhtiari
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA.
- Laureate Institute for Brain Research, Tulsa, OK, USA.
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7
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Obrecht M, Zurbruegg S, Accart N, Lambert C, Doelemeyer A, Ledermann B, Beckmann N. Magnetic resonance imaging and ultrasound elastography in the context of preclinical pharmacological research: significance for the 3R principles. Front Pharmacol 2023; 14:1177421. [PMID: 37448960 PMCID: PMC10337591 DOI: 10.3389/fphar.2023.1177421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 06/16/2023] [Indexed: 07/18/2023] Open
Abstract
The 3Rs principles-reduction, refinement, replacement-are at the core of preclinical research within drug discovery, which still relies to a great extent on the availability of models of disease in animals. Minimizing their distress, reducing their number as well as searching for means to replace them in experimental studies are constant objectives in this area. Due to its non-invasive character in vivo imaging supports these efforts by enabling repeated longitudinal assessments in each animal which serves as its own control, thereby enabling to reduce considerably the animal utilization in the experiments. The repetitive monitoring of pathology progression and the effects of therapy becomes feasible by assessment of quantitative biomarkers. Moreover, imaging has translational prospects by facilitating the comparison of studies performed in small rodents and humans. Also, learnings from the clinic may be potentially back-translated to preclinical settings and therefore contribute to refining animal investigations. By concentrating on activities around the application of magnetic resonance imaging (MRI) and ultrasound elastography to small rodent models of disease, we aim to illustrate how in vivo imaging contributes primarily to reduction and refinement in the context of pharmacological research.
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Affiliation(s)
- Michael Obrecht
- Diseases of Aging and Regenerative Medicines, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Stefan Zurbruegg
- Neurosciences Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Nathalie Accart
- Diseases of Aging and Regenerative Medicines, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Christian Lambert
- Diseases of Aging and Regenerative Medicines, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Arno Doelemeyer
- Diseases of Aging and Regenerative Medicines, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Birgit Ledermann
- 3Rs Leader, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Nicolau Beckmann
- Diseases of Aging and Regenerative Medicines, Novartis Institutes for BioMedical Research, Basel, Switzerland
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8
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Kotoula V, Evans JW, Punturieri CE, Zarate CA. Review: The use of functional magnetic resonance imaging (fMRI) in clinical trials and experimental research studies for depression. FRONTIERS IN NEUROIMAGING 2023; 2:1110258. [PMID: 37554642 PMCID: PMC10406217 DOI: 10.3389/fnimg.2023.1110258] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 06/12/2023] [Indexed: 08/10/2023]
Abstract
Functional magnetic resonance imaging (fMRI) is a non-invasive technique that can be used to examine neural responses with and without the use of a functional task. Indeed, fMRI has been used in clinical trials and pharmacological research studies. In mental health, it has been used to identify brain areas linked to specific symptoms but also has the potential to help identify possible treatment targets. Despite fMRI's many advantages, such findings are rarely the primary outcome measure in clinical trials or research studies. This article reviews fMRI studies in depression that sought to assess the efficacy and mechanism of action of compounds with antidepressant effects. Our search results focused on selective serotonin reuptake inhibitors (SSRIs), the most commonly prescribed treatments for depression and ketamine, a fast-acting antidepressant treatment. Normalization of amygdala hyperactivity in response to negative emotional stimuli was found to underlie successful treatment response to SSRIs as well as ketamine, indicating a potential common pathway for both conventional and fast-acting antidepressants. Ketamine's rapid antidepressant effects make it a particularly useful compound for studying depression with fMRI; its effects on brain activity and connectivity trended toward normalizing the increases and decreases in brain activity and connectivity associated with depression. These findings highlight the considerable promise of fMRI as a tool for identifying treatment targets in depression. However, additional studies with improved methodology and study design are needed before fMRI findings can be translated into meaningful clinical trial outcomes.
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9
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El Ahdab J, Khachan MJ, Richa S, Raad G. A comprehensive review on the role of testosterone on the neurobehavioral systems implicated in the reinforcement sensitivity theory of personality. L'ENCEPHALE 2023; 49:174-184. [PMID: 36411119 DOI: 10.1016/j.encep.2022.08.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 08/19/2022] [Accepted: 08/25/2022] [Indexed: 11/19/2022]
Abstract
OBJECTIVES The Reinforcement Sensitivity Theory (RST) is a neuropsychological theory of personality emphasizing approach and avoidance as the two core behavioral aspects. Approach is represented by the behavioral approach system (BAS). Avoidance is represented by the behavioral inhibition system (BIS) and the fight-flight-freeze system (FFFS). Although the influence of testosterone on human behavior has been demonstrated, few studies have investigated the relation between testosterone and the RST. The aim of this narrative review was to decipher the possible role of testosterone on the biological systems involved in the RST in humans. METHODS Google scholar, PubMed, PsycARTICLES, PsycINFO, Scopus and Cochrane library databases were interrogated using keywords such as testosterone, BIS, BAS, FFFS, personality, reinforcement sensitivity theory. RESULTS Seven original articles, published between 2009 and 2022, assessing the relation between testosterone and the systems implicated in the RST, were included. The results of these studies suggested the presence of a possible positive relation between testosterone and the BAS. However, the impact of testosterone on the BIS and/or FFFS seems to be less clear. DISCUSSION The consistency in the results supporting the presence of a positive relation between testosterone and the BAS might lead to the consideration of testosterone as a potential correlate in the clinical assessment of several psychopathologies. The inconsistency in the conclusions regarding the impact of testosterone on the BIS and/or the FFFS might be attributed to the different questionnaires used as measurement tools. Additional research remains needed.
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Affiliation(s)
- J El Ahdab
- Faculty of Medicine and Medical Sciences, Holy Spirit University of Kaslik (USEK), Jounieh, Lebanon
| | - M-J Khachan
- Faculty of Medicine and Medical Sciences, Holy Spirit University of Kaslik (USEK), Jounieh, Lebanon
| | - S Richa
- Psychiatry Department, University Hospital, Hôtel Dieu de France, Beirut, Lebanon; Faculty of Medicine, Saint-Joseph University, Beirut, Lebanon
| | - G Raad
- Faculty of Medicine and Medical Sciences, Holy Spirit University of Kaslik (USEK), Jounieh, Lebanon; Al-Hadi laboratory and medical center, Beirut, Lebanon.
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10
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Zhu H, Zhu H, Liu X, Wei F, Li H, Guo Z. The Characteristics of Entorhinal Cortex Functional Connectivity in Alzheimer's Disease Patients with Depression. Curr Alzheimer Res 2023; 19:CAR-EPUB-129980. [PMID: 36872356 DOI: 10.2174/1567205020666230303093112] [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: 12/07/2022] [Revised: 02/24/2023] [Accepted: 02/26/2023] [Indexed: 03/07/2023]
Abstract
BACKGROUND Depression is one of the most common neuropsychiatric symptoms of Alzheimer's disease (AD) which decreases the life quality of both patients and caregivers. There are currently no effective drugs. It is therefore important to explore the pathogenesis of depression in AD patients. OBJECTIVE The present study aimed to investigate the characteristics of the entorhinal cortex (EC) functional connectivity (FC) in the whole brain neural network of AD patients with depression (D-AD). METHODS Twenty-four D-AD patients, 14 AD patients without depression (nD-AD), and 20 healthy controls underwent resting-state functional magnetic resonance imaging. We set the EC as the seed and used FC analysis. One-way analysis of variance was used to examine FC differences among the three groups. RESULTS Using the left EC as the seed point, there were FC differences among the three groups in the left EC-inferior occipital gyrus. Using the right EC as the seed point, there were FC differences among the three groups in the right EC-middle frontal gyrus, -superior parietal gyrus, -superior medial frontal gyrus, and -precentral gyrus. Compared with the nD-AD group, the D-AD group had increased FC between the right EC and right postcentral gyrus. CONCLUSION Asymmetry of FC in the EC and increased FC between the EC and right postcentral gyrus may be important in the pathogenesis of depression in AD.
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Affiliation(s)
- Haokai Zhu
- The Second Clinical Medical College, Zhejiang Chinese Medical University, Zhejiang 310000, China
| | - Hong Zhu
- Tongde Hospital of Zhejiang Province, Zhejiang Mental Health Center, Hangzhou, Zhejiang 310012, China
| | - Xiaozheng Liu
- Department of Radiology of the Second Affiliated Hospital, China-USA Neuroimaging Research Institute, Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
| | - Fuquan Wei
- Tongde Hospital of Zhejiang Province, Zhejiang Mental Health Center, Hangzhou, Zhejiang 310012, China
| | - Huichao Li
- Tongde Hospital of Zhejiang Province, Zhejiang Mental Health Center, Hangzhou, Zhejiang 310012, China
| | - Zhongwei Guo
- Tongde Hospital of Zhejiang Province, Zhejiang Mental Health Center, Hangzhou, Zhejiang 310012, China
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11
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English BA, Ereshefsky L. Experimental Medicine Approaches in Early-Phase CNS Drug Development. ADVANCES IN NEUROBIOLOGY 2023; 30:417-455. [PMID: 36928860 DOI: 10.1007/978-3-031-21054-9_17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/17/2023]
Abstract
Traditionally, Phase 1 clinical trials were largely conducted in healthy normal volunteers and focused on collection of safety, tolerability, and pharmacokinetic data. However, in the CNS therapeutic area, with more drugs failing in later phase development, Phase 1 trials have undergone an evolution that includes incorporation of novel approaches involving novel study designs, inclusion of biomarkers, and early inclusion of patients to improve the pharmacologic understanding of novel CNS-active compounds early in clinical development with the hope of improving success in later phase pivotal trials. In this chapter, the authors will discuss the changing landscape of Phase 1 clinical trials in CNS, including novel trial methodology, inclusion of pharmacodynamic biomarkers, and experimental medicine approaches to inform early decision-making in clinical development.
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12
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Carmichael O. The Role of fMRI in Drug Development: An Update. ADVANCES IN NEUROBIOLOGY 2023; 30:299-333. [PMID: 36928856 DOI: 10.1007/978-3-031-21054-9_13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
Functional magnetic resonance imaging (fMRI) of the brain is a technology that holds great potential for increasing the efficiency of drug development for the central nervous system (CNS). In preclinical studies and both early- and late-phase human trials, fMRI has the potential to improve cross-species translation of drug effects, help to de-risk compounds early in development, and contribute to the portfolio of evidence for a compound's efficacy and mechanism of action. However, to date, the utilization of fMRI in the CNS drug development process has been limited. The purpose of this chapter is to explore this mismatch between potential and utilization. This chapter provides introductory material related to fMRI and drug development, describes what is required of fMRI measurements for them to be useful in a drug development setting, lists current capabilities of fMRI in this setting and challenges faced in its utilization, and ends with directions for future development of capabilities in this arena. This chapter is the 5-year update of material from a previously published workshop summary (Carmichael et al., Drug DiscovToday 23(2):333-348, 2018).
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Affiliation(s)
- Owen Carmichael
- Pennington Biomedical Research Center, Baton Rouge, LA, USA.
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13
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McCulloch DEW, Knudsen GM, Barrett FS, Doss MK, Carhart-Harris RL, Rosas FE, Deco G, Kringelbach ML, Preller KH, Ramaekers JG, Mason NL, Müller F, Fisher PM. Psychedelic resting-state neuroimaging: A review and perspective on balancing replication and novel analyses. Neurosci Biobehav Rev 2022; 138:104689. [PMID: 35588933 DOI: 10.1016/j.neubiorev.2022.104689] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 05/05/2022] [Accepted: 05/05/2022] [Indexed: 12/20/2022]
Abstract
Clinical research into serotonergic psychedelics is expanding rapidly, showing promising efficacy across myriad disorders. Resting-state functional magnetic resonance imaging (rs-fMRI) is a commonly used strategy to identify psychedelic-induced changes in neural pathways in clinical and healthy populations. Here we, a large group of psychedelic imaging researchers, review the 42 research articles published to date, based on the 17 unique studies evaluating psychedelic effects on rs-fMRI, focusing on methodological variation. Prominently, we observe that nearly all studies vary in data processing and analysis methodology, two datasets are the foundation of over half of the published literature, and there is lexical ambiguity in common outcome metric terminology. We offer guidelines for future studies that encourage coherence in the field. Psychedelic rs-fMRI will benefit from the development of novel methods that expand our understanding of the brain mechanisms mediating its intriguing effects; yet, this field is at a crossroads where we must also consider the critical importance of consistency and replicability to effectively converge on stable representations of the neural effects of psychedelics.
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Affiliation(s)
| | - Gitte Moos Knudsen
- Neurobiology Research Unit and NeuroPharm, Rigshospitalet, Copenhagen, Denmark; Institute of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Frederick Streeter Barrett
- Department of Psychiatry and Behavioral Sciences, Center for Psychedelic and Consciousness Research, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neuroscience and Department of Psychological and Brain Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Manoj K Doss
- Department of Psychiatry and Behavioral Sciences, Center for Psychedelic and Consciousness Research, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Robin Lester Carhart-Harris
- Neuroscape, Weill Institute for Neurosciences, University of California San Francisco, CA, USA; Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London, UK
| | - Fernando E Rosas
- Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London, UK; Data Science Institute, Imperial College London, London, UK; Centre for Complexity Science, Imperial College London, London, UK
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain; Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain; Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona, Spain; Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; School of Psychological Sciences, Monash University, Melbourne, Australia
| | - Morten L Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, UK; Department of Psychiatry, University of Oxford, Oxford, UK; Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Denmark
| | - Katrin H Preller
- Pharmaco-Neuroimaging and Cognitive-Emotional Processing, Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital, University of Zurich, Zurich, Switzerland
| | | | - Natasha L Mason
- Faculty of Psychology and Neuroscience, Maastricht University, The Netherlands
| | - Felix Müller
- University of Basel, Department of Psychiatry (UPK), Basel, Switzerland
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14
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Ekhtiari H, Zare-Bidoky M, Sangchooli A, Janes AC, Kaufman MJ, Oliver JA, Prisciandaro JJ, Wüstenberg T, Anton RF, Bach P, Baldacchino A, Beck A, Bjork JM, Brewer J, Childress AR, Claus ED, Courtney KE, Ebrahimi M, Filbey FM, Ghahremani DG, Azbari PG, Goldstein RZ, Goudriaan AE, Grodin EN, Hamilton JP, Hanlon CA, Hassani-Abharian P, Heinz A, Joseph JE, Kiefer F, Zonoozi AK, Kober H, Kuplicki R, Li Q, London ED, McClernon J, Noori HR, Owens MM, Paulus MP, Perini I, Potenza M, Potvin S, Ray L, Schacht JP, Seo D, Sinha R, Smolka MN, Spanagel R, Steele VR, Stein EA, Steins-Loeber S, Tapert SF, Verdejo-Garcia A, Vollstädt-Klein S, Wetherill RR, Wilson SJ, Witkiewitz K, Yuan K, Zhang X, Zilverstand A. A methodological checklist for fMRI drug cue reactivity studies: development and expert consensus. Nat Protoc 2022; 17:567-595. [PMID: 35121856 PMCID: PMC9063851 DOI: 10.1038/s41596-021-00649-4] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 10/21/2021] [Indexed: 12/23/2022]
Abstract
Cue reactivity is one of the most frequently used paradigms in functional magnetic resonance imaging (fMRI) studies of substance use disorders (SUDs). Although there have been promising results elucidating the neurocognitive mechanisms of SUDs and SUD treatments, the interpretability and reproducibility of these studies is limited by incomplete reporting of participants' characteristics, task design, craving assessment, scanning preparation and analysis decisions in fMRI drug cue reactivity (FDCR) experiments. This hampers clinical translation, not least because systematic review and meta-analysis of published work are difficult. This consensus paper and Delphi study aims to outline the important methodological aspects of FDCR research, present structured recommendations for more comprehensive methods reporting and review the FDCR literature to assess the reporting of items that are deemed important. Forty-five FDCR scientists from around the world participated in this study. First, an initial checklist of items deemed important in FDCR studies was developed by several members of the Enhanced NeuroImaging Genetics through Meta-Analyses (ENIGMA) Addiction working group on the basis of a systematic review. Using a modified Delphi consensus method, all experts were asked to comment on, revise or add items to the initial checklist, and then to rate the importance of each item in subsequent rounds. The reporting status of the items in the final checklist was investigated in 108 recently published FDCR studies identified through a systematic review. By the final round, 38 items reached the consensus threshold and were classified under seven major categories: 'Participants' Characteristics', 'General fMRI Information', 'General Task Information', 'Cue Information', 'Craving Assessment Inside Scanner', 'Craving Assessment Outside Scanner' and 'Pre- and Post-Scanning Considerations'. The review of the 108 FDCR papers revealed significant gaps in the reporting of the items considered important by the experts. For instance, whereas items in the 'General fMRI Information' category were reported in 90.5% of the reviewed papers, items in the 'Pre- and Post-Scanning Considerations' category were reported by only 44.7% of reviewed FDCR studies. Considering the notable and sometimes unexpected gaps in the reporting of items deemed to be important by experts in any FDCR study, the protocols could benefit from the adoption of reporting standards. This checklist, a living document to be updated as the field and its methods advance, can help improve experimental design, reporting and the widespread understanding of the FDCR protocols. This checklist can also provide a sample for developing consensus statements for protocols in other areas of task-based fMRI.
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Affiliation(s)
- Hamed Ekhtiari
- Laureate Institute for Brain Research, Tulsa, OK, USA.
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA.
| | - Mehran Zare-Bidoky
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
- Shahid-Sadoughi University of Medical Sciences, Yazd, Iran
| | - Arshiya Sangchooli
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | - Amy C Janes
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | - Marc J Kaufman
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | - Jason A Oliver
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
- TSET Health Promotion Research Center, Stephenson Cancer Center, Oklahoma City, OK, USA
- Department of Psychiatry & Behavioral Sciences, Oklahoma State University Center for Health Sciences, Tulsa, OK, USA
| | - James J Prisciandaro
- Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Torsten Wüstenberg
- Department of Psychiatry and Neurosciences, Charité Campus Mitte, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Raymond F Anton
- Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Patrick Bach
- Department of Addictive Behaviour and Addiction Medicine, Central Institute of Mental Health (CIMH), Heidelberg University, Mannheim, Germany
| | - Alex Baldacchino
- Division of Population Studies and Behavioural Sciences, St Andrews University Medical School, University of St Andrews, Scotland, UK
| | - Anne Beck
- Department of Psychiatry and Neurosciences, Charité Campus Mitte, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Faculty of Health, Health and Medical University, Campus Potsdam, Potsdam, Germany
| | - James M Bjork
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Judson Brewer
- Department of Behavioral and Social Sciences, Brown University School of Public Health, Providence, RI, USA
| | - Anna Rose Childress
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Eric D Claus
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA, USA
| | - Kelly E Courtney
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Mohsen Ebrahimi
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | - Francesca M Filbey
- Center for BrainHealth, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, USA
| | - Dara G Ghahremani
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, USA
| | - Peyman Ghobadi Azbari
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
- Department of Biomedical Engineering, Shahed University, Tehran, Iran
| | - Rita Z Goldstein
- Departments of Psychiatry & Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Anna E Goudriaan
- Department of Psychiatry, Amsterdam University Medical Center, University of Amsterdam and Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Erica N Grodin
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, USA
| | - J Paul Hamilton
- Center for Social and Affective Neuroscience, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Colleen A Hanlon
- Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | | | - Andreas Heinz
- Department of Psychiatry and Neurosciences, Charité Campus Mitte, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Jane E Joseph
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
| | - Falk Kiefer
- Department of Addictive Behaviour and Addiction Medicine, Central Institute of Mental Health (CIMH), Heidelberg University, Mannheim, Germany
| | - Arash Khojasteh Zonoozi
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
- Mashhad University of Medical Sciences, Mashhad, Iran
| | - Hedy Kober
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | | | - Qiang Li
- Department of Radiology, Tangdu Hospital, Fourth Military Medical University, Xi'an, China
| | - Edythe D London
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, USA
| | - Joseph McClernon
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Hamid R Noori
- International Center for Primate Brain Research, Center for Excellence in Brain Science and Intelligence Technology (CEBSIT)/Institute of Neuroscience (ION), Chinese Academy of Sciences, Shanghai, China
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Max M Owens
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | | | - Irene Perini
- Center for Social and Affective Neuroscience, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Marc Potenza
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Connecticut Mental Health Center, New Haven, CT, USA
- Connecticut Council on Problem Gambling, Wethersfield, CT, USA
- Department of Neuroscience, Child Study Center and Wu Tsai Institute, Yale School of Medicine, New Haven, CT, USA
| | - Stéphane Potvin
- Centre de recherche de l'Institut Universitaire en Santé Mentale de Montréal, University of Montreal, Montreal, Canada
| | - Lara Ray
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Dongju Seo
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Rajita Sinha
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Michael N Smolka
- Department of Psychiatry, Technische Universität Dresden, Dresden, Germany
| | - Rainer Spanagel
- Institute of Psychopharmacology, Central Institute of Mental Health, Mannheim, Germany
| | - Vaughn R Steele
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Elliot A Stein
- Intramural Research Program, National Institute on Drug Abuse, Baltimore, MD, USA
| | - Sabine Steins-Loeber
- Department of Clinical Psychology and Psychotherapy, Otto-Friedrich-University of Bamberg, Bamberg, Germany
| | - Susan F Tapert
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | | | - Sabine Vollstädt-Klein
- Department of Addictive Behaviour and Addiction Medicine, Central Institute of Mental Health (CIMH), Heidelberg University, Mannheim, Germany
| | - Reagan R Wetherill
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Stephen J Wilson
- Department of Psychology, The Pennsylvania State University, University Park, PA, USA
| | - Katie Witkiewitz
- Department of Psychology, University of New Mexico, Albuquerque, NM, USA
| | - Kai Yuan
- School of Life Science and Technology, Xidian University, Xi'an, China
| | - Xiaochu Zhang
- Department of Psychology, School of Humanities and Social Science, University of Science and Technology of China, Anhui, China
- Department of Radiology, First Affiliated Hospital of USTC, Hefei National Laboratory for Physical Science at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science and Technology of China, Anhui, China
| | - Anna Zilverstand
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
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15
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Hotta N, Miyamoto M, Suzuki K. Lamotrigine and retigabine increase motor threshold in transcranial magnetic stimulation at the dose required to produce an antiepileptic effect against maximal electroshock-induced seizure in rats. Neurosci Lett 2022; 771:136460. [PMID: 35051437 DOI: 10.1016/j.neulet.2022.136460] [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: 09/21/2021] [Revised: 01/07/2022] [Accepted: 01/11/2022] [Indexed: 10/19/2022]
Abstract
Transcranial magnetic stimulation (TMS) is a neurophysiological technique that enables noninvasive evaluation of neuronal excitability in the brain. In the past, a large number of antiepileptic drugs were shown to increase the motor threshold (MT) in clinical TMS studies, suggesting the inhibition of excessive neuronal excitability. To facilitate drug development, the confirmation of similar changes in neurophysiological biomarkers in both preclinical and clinical studies is crucial; however, until now, there have been no data showing the drug efficacies on neuronal excitabilities as measured using TMS in rodents. In this study, we found that the antiepileptic drugs, lamotrigine (10 mg/kg) and retigabine (5 mg/kg), significantly increased the MT in rats using TMS, which is similar to clinical study findings. In addition, we demonstrated that these drugs could inhibit maximal electroshock (MES)-induced seizures in rats when given at the same dose required to be effective in the TMS experiment. These findings suggest that the effects of antiepileptic drugs in our rat TMS system have a similar sensitivity to that of the antiepileptic effects in rats with MES-induced seizures. The measurement of MT in a TMS study may be a noninvasive translational approach for predicting antiepileptic efficacy in drug development.
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Affiliation(s)
- Natsu Hotta
- Neuroscience Drug Discovery Unit, Research, Takeda Pharmaceutical Company Limited
| | - Maki Miyamoto
- Drug Metabolism and Pharmacokinetics Research Laboratories, Research, Takeda Pharmaceutical Company Limited
| | - Kazunori Suzuki
- Neuroscience Drug Discovery Unit, Research, Takeda Pharmaceutical Company Limited.
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Effects of Ketamine and Midazolam on Simultaneous EEG/fMRI Data During Working Memory Processes. Brain Topogr 2021; 34:863-880. [PMID: 34642836 DOI: 10.1007/s10548-021-00876-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Accepted: 06/20/2021] [Indexed: 10/20/2022]
Abstract
Reliable measures of cognitive brain activity from functional neuroimaging techniques may provide early indications of efficacy in clinical trials. Functional magnetic resonance imaging and electroencephalography provide complementary spatiotemporal information and simultaneous recording of these two modalities can remove inter-session drug response and environment variability. We sought to assess the effects of ketamine and midazolam on simultaneous electrophysiological and hemodynamic recordings during working memory (WM) processes. Thirty participants were included in a placebo-controlled, three-way crossover design with ketamine and midazolam. Compared to placebo, ketamine administration attenuated theta power increases and alpha power decreases and midazolam attenuated low beta band decreases to increasing WM load. Additionally, ketamine caused larger blood-oxygen-dependent (BOLD) signal increases in the supplementary motor area and angular gyrus, and weaker deactivations of the default mode network (DMN), whereas no difference was found between midazolam and placebo. Ketamine administration caused positive temporal correlations between frontal-midline theta (fm-theta) power and the BOLD signal to disappear and attenuated negative correlations. However, the relationship between fm-theta and the BOLD signal from DMN areas was maintained in some participants during ketamine administration, as increasing theta strength was associated with stronger BOLD signal reductions in these areas. The presence of, and ability to manipulate, both positive and negative associations between the BOLD signal and fm-theta suggest the presence of multiple fm-theta components involved in WM processes, with ketamine administration disrupting one or more of these theta-linked WM strategies.
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Kashyap K, Siddiqi MI. Recent trends in artificial intelligence-driven identification and development of anti-neurodegenerative therapeutic agents. Mol Divers 2021; 25:1517-1539. [PMID: 34282519 DOI: 10.1007/s11030-021-10274-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Accepted: 07/05/2021] [Indexed: 12/12/2022]
Abstract
Neurological disorders affect various aspects of life. Finding drugs for the central nervous system is a very challenging and complex task due to the involvement of the blood-brain barrier, P-glycoprotein, and the drug's high attrition rates. The availability of big data present in online databases and resources has enabled the emergence of artificial intelligence techniques including machine learning to analyze, process the data, and predict the unknown data with high efficiency. The use of these modern techniques has revolutionized the whole drug development paradigm, with an unprecedented acceleration in the central nervous system drug discovery programs. Also, the new deep learning architectures proposed in many recent works have given a better understanding of how artificial intelligence can tackle big complex problems that arose due to central nervous system disorders. Therefore, the present review provides comprehensive and up-to-date information on machine learning/artificial intelligence-triggered effort in the brain care domain. In addition, a brief overview is presented on machine learning algorithms and their uses in structure-based drug design, ligand-based drug design, ADMET prediction, de novo drug design, and drug repurposing. Lastly, we conclude by discussing the major challenges and limitations posed and how they can be tackled in the future by using these modern machine learning/artificial intelligence approaches.
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Affiliation(s)
- Kushagra Kashyap
- Academy of Scientific and Innovative Research (AcSIR), CSIR-Central Drug Research Institute (CSIR-CDRI) Campus, Lucknow, India.,Molecular and Structural Biology Division, CSIR-Central Drug Research Institute (CSIR-CDRI), Sector 10, Jankipuram Extension, Sitapur Road, Lucknow, 226031, India
| | - Mohammad Imran Siddiqi
- Academy of Scientific and Innovative Research (AcSIR), CSIR-Central Drug Research Institute (CSIR-CDRI) Campus, Lucknow, India. .,Molecular and Structural Biology Division, CSIR-Central Drug Research Institute (CSIR-CDRI), Sector 10, Jankipuram Extension, Sitapur Road, Lucknow, 226031, India.
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Tsuji K, Satsuka A, Kanda Y. [Current challenges and future perspectives of pharmacological testing using new approach methodologies]. Nihon Yakurigaku Zasshi 2021; 156:208-213. [PMID: 34193697 DOI: 10.1254/fpj.21020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
The mission of regulatory science is to promote human longevity by providing safer and more effective drugs and ensuring human health. At present, various in vitro and in vivo evaluation methods are used for drug development, and no major problems have been observed. However, there is still room for improvement in terms of risk prediction in humans. Thus, new approaches and methodologies (NAMs) have recently been developed to predict adverse events in humans more accurately. Based on the animal alternative methods and the current COVID-19 pandemic, in vitro methods, such as human iPS cells, and computational approach are accelerated to improve the efficiency of drug development, ensure the patients' safety and speed up the review process. In this review, we would like to summarize the current status and future perspectives of pharmacological assay system using NAM in drug development.
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Affiliation(s)
- Kayoko Tsuji
- Division of Pharmacology, National Institute of Health Sciences (NIHS)
| | - Ayano Satsuka
- Division of Pharmacology, National Institute of Health Sciences (NIHS)
| | - Yasunari Kanda
- Division of Pharmacology, National Institute of Health Sciences (NIHS)
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One-pot synthesis of carboxymethyl-dextran coated iron oxide nanoparticles (CION) for preclinical fMRI and MRA applications. Neuroimage 2021; 238:118213. [PMID: 34116153 PMCID: PMC8418149 DOI: 10.1016/j.neuroimage.2021.118213] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 05/15/2021] [Accepted: 05/25/2021] [Indexed: 11/21/2022] Open
Abstract
Superparamagnetic iron-oxide nanoparticles are robust contrast agents for magnetic resonance imaging (MRI) used for sensitive structural and functional mapping of the cerebral blood volume (CBV) when administered intravenously. To date, many CBV-MRI studies are conducted with Feraheme, manufactured for the clinical treatment of iron-deficiency. Unfortunately, Feraheme is currently not available outside the United States due to commercial and regulatory constraints, making CBV-MRI methods either inaccessible or very costly to achieve. To address this barrier, we developed a simple, one-pot recipe to synthesize Carboxymethyl-dextran coated Iron Oxide Nanoparticles, namely, “CION”, suitable for preclinical CBV-MRI applications. Here we disseminate a step-by-step instruction of our one-pot synthesis protocol, which allows CION to be produced in laboratories with minimal cost. We also characterized different CION-conjugations by manipulating polymer to metal stoichiometric ratio in terms of their size, surface chemistry, and chemical composition, and shifts in MR relaxivity and pharmacokinetics. We performed several proof-of-concept experiments in vivo, demonstrating the utility of CION for functional and structural MRI applications, including hypercapnic CO2 challenge, visual stimulation, targeted optogenetic stimulation, and microangiography. We also present evidence that CION can serve as a cross-modality research platform by showing concurrent in vivo optical and MRI measurement of CBV using fluorescent-labeled CION. The simplicity and cost-effectiveness of our one-pot synthesis method should allow researchers to reproduce CION and tailor the relaxivity and pharmacokinetics according to their imaging needs. It is our hope that this work makes CBV-MRI more openly available and affordable for a variety of research applications.
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Sadraee A, Paulus M, Ekhtiari H. fMRI as an outcome measure in clinical trials: A systematic review in clinicaltrials.gov. Brain Behav 2021; 11:e02089. [PMID: 33662169 PMCID: PMC8119793 DOI: 10.1002/brb3.2089] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 12/29/2020] [Accepted: 01/02/2021] [Indexed: 12/13/2022] Open
Abstract
INTRODUCTION More than one-thousand trials with functional magnetic resonance imaging (fMRI) as an outcome measure were registered in clinicaltrials.gov at the time of writing this article. However, 93% of these registered trials are still not completed with published results and there is no picture available about methodological dimensions of these ongoing trials with fMRI as an outcome measure. METHODS We collected trials that use fMRI as an outcome measure in the ClinicalTrials.gov registry on 13 October 2018 and reviewed each trial's record entry. Eligible trials' characteristics were extracted and summarized. RESULTS In total, 1,386 clinical trials were identified that reported fMRI in their outcome measures with fMRI as the only primary outcome in 33% of them. 82% of fMRI trials were started after 2011. The most frequent intervention was drug (pharmacological intervention) (29%). 57% of trials had parallel assignment design and 20% were designed for cross-over assignment. For task-based fMRI, cognitive systems (46%) based on Research Domain Criteria (RDoC) was the most frequent domain of tasks. Less than one-third of trials (28%) registered at least one region of interest for their analysis. Food cue reactivity task, pain perception task, n-back task, and monetary incentive delay task were recruited in more than 25 registered trials. CONCLUSION The number of fMRI trials (fMRI as an outcome measure) with both task and rest protocols is growing rapidly. Our study suggests a growing need for harmonization and standardized checklists on both methods and analysis for preregistration of fMRI-based outcomes in clinical trials.
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Affiliation(s)
- Alaleh Sadraee
- Institute for Cognitive Science StudiesTehranIran
- Iranian National Center for Addiction StudiesTehran University of Medical SciencesTehranIran
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Vatansever S, Schlessinger A, Wacker D, Kaniskan HÜ, Jin J, Zhou M, Zhang B. Artificial intelligence and machine learning-aided drug discovery in central nervous system diseases: State-of-the-arts and future directions. Med Res Rev 2021; 41:1427-1473. [PMID: 33295676 PMCID: PMC8043990 DOI: 10.1002/med.21764] [Citation(s) in RCA: 102] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 10/30/2020] [Accepted: 11/20/2020] [Indexed: 01/11/2023]
Abstract
Neurological disorders significantly outnumber diseases in other therapeutic areas. However, developing drugs for central nervous system (CNS) disorders remains the most challenging area in drug discovery, accompanied with the long timelines and high attrition rates. With the rapid growth of biomedical data enabled by advanced experimental technologies, artificial intelligence (AI) and machine learning (ML) have emerged as an indispensable tool to draw meaningful insights and improve decision making in drug discovery. Thanks to the advancements in AI and ML algorithms, now the AI/ML-driven solutions have an unprecedented potential to accelerate the process of CNS drug discovery with better success rate. In this review, we comprehensively summarize AI/ML-powered pharmaceutical discovery efforts and their implementations in the CNS area. After introducing the AI/ML models as well as the conceptualization and data preparation, we outline the applications of AI/ML technologies to several key procedures in drug discovery, including target identification, compound screening, hit/lead generation and optimization, drug response and synergy prediction, de novo drug design, and drug repurposing. We review the current state-of-the-art of AI/ML-guided CNS drug discovery, focusing on blood-brain barrier permeability prediction and implementation into therapeutic discovery for neurological diseases. Finally, we discuss the major challenges and limitations of current approaches and possible future directions that may provide resolutions to these difficulties.
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Affiliation(s)
- Sezen Vatansever
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Mount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Icahn Institute for Data Science and Genomic TechnologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Avner Schlessinger
- Department of Pharmacological SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Mount Sinai Center for Therapeutics DiscoveryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Daniel Wacker
- Department of Pharmacological SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Mount Sinai Center for Therapeutics DiscoveryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of NeuroscienceIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - H. Ümit Kaniskan
- Department of Pharmacological SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Mount Sinai Center for Therapeutics DiscoveryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of Oncological Sciences, Tisch Cancer InstituteIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Jian Jin
- Department of Pharmacological SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Mount Sinai Center for Therapeutics DiscoveryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of Oncological Sciences, Tisch Cancer InstituteIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Ming‐Ming Zhou
- Department of Pharmacological SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of Oncological Sciences, Tisch Cancer InstituteIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Bin Zhang
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Mount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Icahn Institute for Data Science and Genomic TechnologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of Pharmacological SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
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Nathan PJ, Bakker G. Lessons learned from using fMRI in the early clinical development of a mu-opioid receptor antagonist for disorders of compulsive consumption. Psychopharmacology (Berl) 2021; 238:1255-1263. [PMID: 31900526 DOI: 10.1007/s00213-019-05427-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Accepted: 12/06/2019] [Indexed: 01/23/2023]
Abstract
Functional magnetic resonance imaging (fMRI) has been widely used to gain a greater understanding of brain circuitry abnormalities in CNS disorders. fMRI has also been used to examine pharmacological modulation of brain circuity and is increasingly being used in early clinical drug development as functional pharmacodynamic index of target engagement, and to provide early indication of clinical efficacy. In this short review, we summarize data from experimental medicine and early clinical development studies of a mu-opioid receptor antagonist, GSK1521498 developed for disorders of compulsive consumption including binge eating in obesity. We demonstrate how fMRI can be used to answer important questions of early clinical drug development relating to; (1) target engagement, (2) dose response relationships, (3) differential efficacy and (4) prediction of behavioural and clinically relevant outcomes. We also highlight important methodological factors that need to be considered when conducting fMRI studies in drug development given the challenges faced with small sample sizes in Phase 1 and early proof of mechanism studies. While these data highlight the value of fMRI as a biomarker in drug development, its use for making Go/No-go decisions is still faced with challenges given the variability of responses, interpretation of brain activation changes and the limited data linking drug induced changes in brain activity to clinical or behavioural outcome. These challenges need to be addressed to fulfil the promise of fMRI as a tool in clinical drug development.
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Affiliation(s)
- Pradeep J Nathan
- Experimental Medicine (Neuroscience), Sosei Heptares, Cambridge, UK
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
- The Monash School of Psychological Sciences, Monash University, Melbourne, Australia
| | - Geor Bakker
- Experimental Medicine (Neuroscience), Sosei Heptares, Cambridge, UK.
- Department of Psychiatry and Psychology, Maastricht University, Maastricht, Netherlands.
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.
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23
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Tsunemoto K, Yamada S, Kanda Y. [Current challenges and future perspectives of iPSC-based neurotoxicity testing]. Nihon Yakurigaku Zasshi 2021; 156:107-113. [PMID: 33642528 DOI: 10.1254/fpj.20097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Predicting drug-induced side effects in central nervous system is important because they can lead to the discontinuation of new drugs/candidates or the withdrawal of marketed drugs. Although many efforts are made, evaluation system using animals have not been highly predictive in humans. In addition, animal experiments are time-consuming and costly. To address these issues, in vitro evaluation methods, such as the use of New Approach Methodologies (NAM) have been explored. Human iPS cell technology has already been applied to assess drug-induced cardiotoxicity. In addition, the use of human iPS cell technology and in silico has been promoted for neurotoxicity assessment during the developmental neurotoxicity in terms of chemical safety issues. Organization for Economic Cooperation and Development (OECD) guidance regarding developmental neurotoxicity is under preparation. In this review, we will review the current trends in safety assessment methods for the central nervous system in light of these international trends.
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Affiliation(s)
| | - Shigeru Yamada
- Division of Pharmacology, National Institute of Health Sciences (NIHS)
| | - Yasunari Kanda
- Division of Pharmacology, National Institute of Health Sciences (NIHS)
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24
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Molecular and Functional Imaging in Central Nervous System Drug Development. Mol Imaging 2021. [DOI: 10.1016/b978-0-12-816386-3.00084-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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Pharmaco-fUS: Quantification of pharmacologically-induced dynamic changes in brain perfusion and connectivity by functional ultrasound imaging in awake mice. Neuroimage 2020; 222:117231. [DOI: 10.1016/j.neuroimage.2020.117231] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Revised: 07/24/2020] [Accepted: 07/31/2020] [Indexed: 11/20/2022] Open
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Tinnermann A, Büchel C, Cohen-Adad J. Cortico-spinal imaging to study pain. Neuroimage 2020; 224:117439. [PMID: 33039624 DOI: 10.1016/j.neuroimage.2020.117439] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 09/21/2020] [Accepted: 10/01/2020] [Indexed: 12/15/2022] Open
Abstract
Functional magnetic resonance imaging of the brain has helped to reveal mechanisms of pain perception in health and disease. Recently, imaging approaches have been developed that allow recording neural activity simultaneously in the brain and in the spinal cord. These approaches offer the possibility to examine pain perception in the entire central pain system and in addition, to investigate cortico-spinal interactions during pain processing. Although cortico-spinal imaging is a promising technique, it bears challenges concerning data acquisition and data analysis strategies. In this review, we discuss studies that applied simultaneous imaging of the brain and spinal cord to explore central pain processing. Furthermore, we describe different MR-related acquisition techniques, summarize advantages and disadvantages of approaches that have been implemented so far and present software that has been specifically developed for the analysis of spinal fMRI data to address challenges of spinal data analysis.
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Affiliation(s)
- Alexandra Tinnermann
- Department for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Max Planck School of Cognition, Leipzig, Germany.
| | - Christian Büchel
- Department for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Max Planck School of Cognition, Leipzig, Germany
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada; Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, Quebec, Canada.
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Gonen OM, Kwan P, O'Brien TJ, Lui E, Desmond PM. Resting-state functional MRI of the default mode network in epilepsy. Epilepsy Behav 2020; 111:107308. [PMID: 32698105 DOI: 10.1016/j.yebeh.2020.107308] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Revised: 06/28/2020] [Accepted: 06/28/2020] [Indexed: 02/09/2023]
Abstract
The default mode network (DMN) is a major neuronal network that deactivates during goal-directed tasks. Recent advances in neuroimaging have shed light on its structure and function. Alterations in the DMN are increasingly recognized in a range of neurological and psychiatric conditions including epilepsy. This review first describes the current understanding of the DMN in health, normal aging, and disease as it is acquired via resting-state functional magnetic resonance imaging (MRI), before focusing on how it is affected in various types of focal and generalized epilepsy. These findings support the potential use of DMN parameters as future biomarkers in epilepsy research, diagnosis, and management.
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Affiliation(s)
- Ofer M Gonen
- The Royal Melbourne Hospital, VIC, Australia; The University of Melbourne, VIC, Australia; The Alfred Hospital, VIC, Australia.
| | - Patrick Kwan
- The Royal Melbourne Hospital, VIC, Australia; The University of Melbourne, VIC, Australia; The Alfred Hospital, VIC, Australia; Monash University, VIC, Australia
| | - Terence J O'Brien
- The Royal Melbourne Hospital, VIC, Australia; The University of Melbourne, VIC, Australia; The Alfred Hospital, VIC, Australia; Monash University, VIC, Australia
| | - Elaine Lui
- The Royal Melbourne Hospital, VIC, Australia; The University of Melbourne, VIC, Australia
| | - Patricia M Desmond
- The Royal Melbourne Hospital, VIC, Australia; The University of Melbourne, VIC, Australia
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Masaki Y, Kashiwagi Y, Rokugawa T, Ito M, Iimori H, Abe K. Pharmacological MRI responses of raclopride in rats: The relationship with D2 receptor occupancy and cataleptic behavior. Synapse 2020; 74:e22180. [PMID: 32644234 DOI: 10.1002/syn.22180] [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: 03/31/2020] [Revised: 06/26/2020] [Accepted: 07/02/2020] [Indexed: 11/08/2022]
Abstract
Pharmacological magnetic resonance imaging (phMRI) allows the visualization of brain pharmacological effects of drugs using functional MRI (fMRI). phMRI can help us facilitate central nervous system (CNS) drug development. However, there have been few studies demonstrating the dose relationship of the fMRI response induced by CNS drugs to underlying target engagement or behavioral efficacy. To clarify these relationships, we examined receptor occupancy measurements using positron emission tomography (PET) (n = 3~5), fMRI (n = 5~8) and a cataleptic behavior (n = 6) with raclopride, a dopamine D2 receptor antagonist (8, 20, and 200 μg/kg) on Wistar rats. Dopamine D2 receptor occupancy was increased dose dependently by raclopride (41.8 ± 2.7%, 8 μg/kg; 64.9 ± 2.8%, 20 μg/kg; 83.1 ± 3.0%, 200 μg/kg). phMRI study revealed significant positive responses to raclopride at 200 μg/kg specifically in the striatum and nucleus accumbens, related to dopaminergic system. Slight fMRI responses were observed at 20 μg/kg in some areas corresponding to the striatum and nucleus accumbens. There were no noticeable fMRI responses at 8 μg/kg raclopride administration. Raclopride at 200 μg/kg significantly increased the cataleptic score, although, at 8 and 20 μg/kg, raclopride had no significant effects. These findings showed that raclopride-induced fMRI responses were observed at doses inducing cataleptic behavior and high D2 receptor occupancy, suggesting that phMRI can be useful for dose selection in clinical trial as an evaluation method of brain activity, which reflects behavioral responses induced by target engagements.
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Affiliation(s)
- Yukiko Masaki
- Imaging Biomarker, Biomarker R&D Department, Shionogi & Co., Ltd., Osaka, Japan
| | - Yuto Kashiwagi
- Imaging Biomarker, Biomarker R&D Department, Shionogi & Co., Ltd., Osaka, Japan
| | - Takemi Rokugawa
- Imaging Biomarker, Biomarker R&D Department, Shionogi & Co., Ltd., Osaka, Japan
| | - Miwa Ito
- Imaging Biomarker, Biomarker R&D Department, Shionogi & Co., Ltd., Osaka, Japan
| | - Hitoshi Iimori
- Research Laboratory for Development, Shionogi & Co., Ltd., Osaka, Japan
| | - Kohji Abe
- Imaging Biomarker, Biomarker R&D Department, Shionogi & Co., Ltd., Osaka, Japan
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McKinney WS, Bartolotti J, Khemani P, Wang JY, Hagerman RJ, Mosconi MW. Cerebellar-cortical function and connectivity during sensorimotor behavior in aging FMR1 gene premutation carriers. NEUROIMAGE-CLINICAL 2020; 27:102332. [PMID: 32711390 PMCID: PMC7381687 DOI: 10.1016/j.nicl.2020.102332] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 06/23/2020] [Accepted: 06/24/2020] [Indexed: 12/13/2022]
Abstract
FMR1 premutation carriers show increased variability in motor control. Premutation carriers show reduced extrastriate activation during motor behavior. Premutation carriers show reduced extrastriate-cerebellar functional connectivity. Reduced extrastriate-cerebellar functional connectivity is related to motor issues.
Introduction Premutation carriers of the FMR1 gene are at risk of developing fragile X-associated tremor/ataxia syndrome (FXTAS), a neurodegenerative disease characterized by motor, cognitive, and psychiatric decline as well as cerebellar and cerebral white matter pathology. Several studies have documented preclinical sensorimotor issues in aging premutation carriers, but the extent to which sensorimotor brain systems are affected and may represent early indicators of atypical neurodegeneration has not been determined. Materials and methods Eighteen healthy controls and 16 FMR1 premutation carriers (including five with possible, probable, or definite FXTAS) group-matched on age, sex, and handedness completed a visually guided precision gripping task with their right hand during fMRI. During the test, they used a modified pinch grip to press at 60% of their maximum force against a custom fiber-optic transducer. Participants viewed a horizontal white force bar that moved upward with increased force and downward with decreased force and a static target bar that was red during rest and turned green to cue the participant to begin pressing at the beginning of each trial. Participants were instructed to press so that the white force bar stayed as steady as possible at the level of the green target bar. Trials were 2-sec in duration and alternated with 2-sec rest periods. Five 24-sec blocks consisting of six trials were presented. Participants’ reaction time, the accuracy of their force relative to the target force, and the variability of their force accuracy across trials were examined. BOLD signal change and task-based functional connectivity (FC) were examined during force vs. rest. Results Relative to healthy controls, premutation carriers showed increased trial-to-trial variability of force output, though this was specific to younger premutation carriers in our sample. Relative to healthy controls, premutation carriers also showed reduced extrastriate activation during force relative to rest. FC between ipsilateral cerebellar Crus I and extrastriate cortex was reduced in premutation carriers compared to controls. Reduced Crus I-extrastriate FC was related to increased force accuracy variability in premutation carriers. Increased reaction time was associated with more severe clinically rated neurological abnormalities. Conclusions Findings of reduced activation in extrastriate cortex and reduced Crus I-extrastriate FC implicate deficient visual feedback processing and reduced cerebellar modulation of corrective motor commands. Our results are consistent with documented cerebellar pathology and visual-spatial processing in FXTAS and pre-symptomatic premutation carriers, and suggest FC alterations of cerebellar-cortical networks during sensorimotor behavior may represent a “prodromal” feature associated with FXTAS degeneration.
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Affiliation(s)
- Walker S McKinney
- Life Span Institute and Kansas Center for Autism Research and Training (K-CART), Clinical Child Psychology Program, University of Kansas, 1000 Sunnyside Avenue, Lawrence, KS 66045, USA.
| | - James Bartolotti
- Life Span Institute and Kansas Center for Autism Research and Training (K-CART), Clinical Child Psychology Program, University of Kansas, 1000 Sunnyside Avenue, Lawrence, KS 66045, USA.
| | - Pravin Khemani
- Department of Neurology, Swedish Neuroscience Institute, 550 17th Avenue, Suite 400, Seattle, WA 98122, USA.
| | - Jun Yi Wang
- Center for Mind and Brain, University of California, Davis, 267 Cousteau Place, Davis, CA 95618, USA.
| | - Randi J Hagerman
- MIND Institute and Department of Pediatrics, University of California, Davis School of Medicine, 2825 50th St., Sacramento, CA 95817, USA.
| | - Matthew W Mosconi
- Life Span Institute and Kansas Center for Autism Research and Training (K-CART), Clinical Child Psychology Program, University of Kansas, 1000 Sunnyside Avenue, Lawrence, KS 66045, USA.
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An FDA/CDER perspective on nonclinical testing strategies: Classical toxicology approaches and new approach methodologies (NAMs). Regul Toxicol Pharmacol 2020; 114:104662. [DOI: 10.1016/j.yrtph.2020.104662] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 04/03/2020] [Accepted: 04/15/2020] [Indexed: 02/08/2023]
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Rolle CE, Fonzo GA, Wu W, Toll R, Jha MK, Cooper C, Chin-Fatt C, Pizzagalli DA, Trombello JM, Deckersbach T, Fava M, Weissman MM, Trivedi MH, Etkin A. Cortical Connectivity Moderators of Antidepressant vs Placebo Treatment Response in Major Depressive Disorder: Secondary Analysis of a Randomized Clinical Trial. JAMA Psychiatry 2020; 77:397-408. [PMID: 31895437 PMCID: PMC6990859 DOI: 10.1001/jamapsychiatry.2019.3867] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
IMPORTANCE Despite the widespread awareness of functional magnetic resonance imaging findings suggesting a role for cortical connectivity networks in treatment selection for major depressive disorder, its clinical utility remains limited. Recent methodological advances have revealed functional magnetic resonance imaging-like connectivity networks using electroencephalography (EEG), a tool more easily implemented in clinical practice. OBJECTIVE To determine whether EEG connectivity could reveal neural moderators of antidepressant treatment. DESIGN, SETTING, AND PARTICIPANTS In this nonprespecified secondary analysis, data were analyzed from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinic Care study, a placebo-controlled, double-blinded randomized clinical trial. Recruitment began July 29, 2011, and was completed December 15, 2015. A random sample of 221 outpatients with depression aged 18 to 65 years who were not taking medication for depression was recruited and assessed at 4 clinical sites. Analysis was performed on an intent-to-treat basis. Statistical analysis was performed from November 16, 2018, to May 23, 2019. INTERVENTIONS Patients received either the selective serotonin reuptake inhibitor sertraline hydrochloride or placebo for 8 weeks. MAIN OUTCOMES AND MEASURES Electroencephalographic orthogonalized power envelope connectivity analyses were applied to resting-state EEG data. Intent-to-treat prediction linear mixed models were used to determine which pretreatment connectivity patterns were associated with response to sertraline vs placebo. The primary clinical outcome was the total score on the 17-item Hamilton Rating Scale for Depression, administered at each study visit. RESULTS Of the participants recruited, 9 withdrew after first dose owing to reported adverse effects, and 221 participants (150 women; mean [SD] age, 37.8 [12.7] years) underwent EEG recordings and had high-quality pretreatment EEG data. After correction for multiple comparisons, connectome-wide analyses revealed moderation by connections within and between widespread cortical regions-most prominently parietal-for both the antidepressant and placebo groups. Greater alpha-band and lower gamma-band connectivity predicted better placebo outcomes and worse antidepressant outcomes. Lower connectivity levels in these moderating connections were associated with higher levels of anhedonia. Connectivity features that moderate treatment response differentially by treatment group were distinct from connectivity features that change from baseline to 1 week into treatment. The group mean (SD) score on the 17-item Hamilton Rating Scale for Depression was 18.35 (4.58) at baseline and 26.14 (30.37) across all time points. CONCLUSIONS AND RELEVANCE These findings establish the utility of EEG-based network functional connectivity analyses for differentiating between responses to an antidepressant vs placebo. A role emerged for parietal cortical regions in predicting placebo outcome. From a treatment perspective, capitalizing on the therapeutic components leading to placebo response differentially from antidepressant response should provide an alternative direction toward establishing a placebo signature in clinical trials, thereby enhancing the signal detection in randomized clinical trials. TRIAL REGISTRATION ClinicalTrials.gov identifier: NCT01407094.
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Affiliation(s)
- Camarin E. Rolle
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California,Wu Tsai Neuroscience Institute, Stanford University, Stanford, California,Veterans Affairs Palo Alto Healthcare System, Palo Alto, California,Sierra Pacific Mental Illness, Research, Education, and Clinical Center, Palo Alto, California
| | - Gregory A. Fonzo
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California,Wu Tsai Neuroscience Institute, Stanford University, Stanford, California,Veterans Affairs Palo Alto Healthcare System, Palo Alto, California,Sierra Pacific Mental Illness, Research, Education, and Clinical Center, Palo Alto, California,Department of Psychiatry, Dell Medical School, The University of Texas at Austin
| | - Wei Wu
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California,Wu Tsai Neuroscience Institute, Stanford University, Stanford, California,Veterans Affairs Palo Alto Healthcare System, Palo Alto, California,School of Automation Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China
| | - Russ Toll
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California,Wu Tsai Neuroscience Institute, Stanford University, Stanford, California,Veterans Affairs Palo Alto Healthcare System, Palo Alto, California
| | - Manish K. Jha
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas
| | - Crystal Cooper
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas
| | - Cherise Chin-Fatt
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas
| | | | - Joseph M. Trombello
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas
| | - Thilo Deckersbach
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - Maurizio Fava
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - Myrna M. Weissman
- New York State Psychiatric Institute, Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York
| | - Madhukar H. Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas
| | - Amit Etkin
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California,Wu Tsai Neuroscience Institute, Stanford University, Stanford, California,Veterans Affairs Palo Alto Healthcare System, Palo Alto, California,Sierra Pacific Mental Illness, Research, Education, and Clinical Center, Palo Alto, California,now at Alto Neuroscience Inc, Los Altos, California
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32
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Borsook D, Upadhyay J, Hargreaves R, Wager T. Enhancing Choice and Outcomes for Therapeutic Trials in Chronic Pain: N-of-1 + Imaging (+ i). Trends Pharmacol Sci 2020; 41:85-98. [DOI: 10.1016/j.tips.2019.12.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Revised: 11/27/2019] [Accepted: 12/04/2019] [Indexed: 10/25/2022]
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Specht K. Current Challenges in Translational and Clinical fMRI and Future Directions. Front Psychiatry 2020; 10:924. [PMID: 31969840 PMCID: PMC6960120 DOI: 10.3389/fpsyt.2019.00924] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Accepted: 11/20/2019] [Indexed: 12/15/2022] Open
Abstract
Translational neuroscience is an important field that brings together clinical praxis with neuroscience methods. In this review article, the focus will be on functional neuroimaging (fMRI) and its applicability in clinical fMRI studies. In the light of the "replication crisis," three aspects will be critically discussed: First, the fMRI signal itself, second, current fMRI praxis, and, third, the next generation of analysis strategies. Current attempts such as resting-state fMRI, meta-analyses, and machine learning will be discussed with their advantages and potential pitfalls and disadvantages. One major concern is that the fMRI signal shows substantial within- and between-subject variability, which affects the reliability of both task-related, but in particularly resting-state fMRI studies. Furthermore, the lack of standardized acquisition and analysis methods hinders the further development of clinical relevant approaches. However, meta-analyses and machine-learning approaches may help to overcome current shortcomings in the methods by identifying new, and yet hidden relationships, and may help to build new models on disorder mechanisms. Furthermore, better control of parameters that may have an influence on the fMRI signal and that can easily be controlled for, like blood pressure, heart rate, diet, time of day, might improve reliability substantially.
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Affiliation(s)
- Karsten Specht
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
- Mohn Medical Imaging and Visualization Centre, Haukeland University Hospital, Bergen, Norway
- Department of Education, UiT/The Arctic University of Norway, Tromsø, Norway
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34
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Ewen JB, Sweeney JA, Potter WZ. Conceptual, Regulatory and Strategic Imperatives in the Early Days of EEG-Based Biomarker Validation for Neurodevelopmental Disabilities. Front Integr Neurosci 2019; 13:45. [PMID: 31496945 PMCID: PMC6712089 DOI: 10.3389/fnint.2019.00045] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Accepted: 08/06/2019] [Indexed: 12/14/2022] Open
Abstract
Biological treatment development for syndromal neuropsychiatric conditions such as autism has seen slow progress for decades. Speeding drug discovery may result from the judicious development and application of biomarker measures of brain function to select patients for clinical trials, to confirm target engagement and to optimize drug dose. For neurodevelopmental disorders, electrophysiology (EEG) offers considerable promise because of its ability to monitor brain activity with high temporal resolution and its more ready application for pediatric populations relative to MRI. Here, we discuss conceptual/definitional issues related to biomarker development, discuss practical implementation issues, and suggest preliminary guidelines for validating EEG approaches as biomarkers with a context of use in neurodevelopmental disorder drug development.
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Affiliation(s)
- Joshua B. Ewen
- Department of Neurology and Developmental Medicine, Kennedy Krieger Institute, Baltimore, MD, United States
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, United States
| | - John A. Sweeney
- Department of Psychiatry, University of Cincinnati, Cincinnati, OH, United States
| | - William Z. Potter
- National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
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Abstract
Measuring brain activity in infants provides an objective surrogate approach with which to infer pain perception following noxious events. Here we discuss different approaches which can be used to measure noxious-evoked brain activity, and discuss how these measures can be used to assess the analgesic efficacy of pharmacological and non-pharmacological interventions. We review factors that can modulate noxious-evoked brain activity, which may impact infant pain experience, including gestational age, sex, prior pain, stress, and illness.
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Affiliation(s)
- Deniz Gursul
- Department of Paediatrics, University of Oxford, John Radcliffe Hospital, Headington, Oxford, OX3 9DU, United Kingdom
| | - Caroline Hartley
- Department of Paediatrics, University of Oxford, John Radcliffe Hospital, Headington, Oxford, OX3 9DU, United Kingdom
| | - Rebeccah Slater
- Department of Paediatrics, University of Oxford, John Radcliffe Hospital, Headington, Oxford, OX3 9DU, United Kingdom.
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36
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Zetterberg H, Winblad B, Bernick C, Yaffe K, Majdan M, Johansson G, Newcombe V, Nyberg L, Sharp D, Tenovuo O, Blennow K. Head trauma in sports - clinical characteristics, epidemiology and biomarkers. J Intern Med 2019; 285:624-634. [PMID: 30481401 DOI: 10.1111/joim.12863] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Traumatic brain injury (TBI) is clinically divided into a spectrum of severities, with mild TBI being the least severe form and a frequent occurrence in contact sports, such as ice hockey, American football, rugby, horse riding and boxing. Mild TBI is caused by blunt nonpenetrating head trauma that causes movement of the brain and stretching and tearing of axons, with diffuse axonal injury being a central pathogenic mechanism. Mild TBI is in principle synonymous with concussion; both have similar criteria in which the most important elements are acute alteration or loss of consciousness and/or post-traumatic amnesia following head trauma and no apparent brain changes on standard neuroimaging. Symptoms in mild TBI are highly variable and there are no validated imaging or fluid biomarkers to determine whether or not a patient with a normal computerized tomography scan of the brain has neuronal damage. Mild TBI typically resolves within a few weeks but 10-15% of concussion patients develop postconcussive syndrome. Repetitive mild TBI, which is frequent in contact sports, is a risk factor for a complicated recovery process. This overview paper discusses the relationships between repetitive head impacts in contact sports, mild TBI and chronic neurological symptoms. What are these conditions, how common are they, how are they linked and can they be objectified using imaging or fluid-based biomarkers? It gives an update on the current state of research on these questions with a specific focus on clinical characteristics, epidemiology and biomarkers.
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Affiliation(s)
- H Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,UK Dementia Research Institute at UCL, London, UK.,Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
| | - B Winblad
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Neurogeriatrics, Karolinska Institutet, Huddinge, Sweden.,Department of Geriatric Medicine, Karolinska University Hospital, Huddinge, Sweden
| | - C Bernick
- Neurological Institute, Cleveland Clinic, Las Vegas, NV, USA
| | - K Yaffe
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA.,San Francisco Veterans Affairs Health Care System, San Francisco, CA, USA.,Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.,Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - M Majdan
- Department of Public Health, Faculty of Health Sciences and Social Work, Trnava University, Trnava, Slovakia
| | - G Johansson
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Neurogeriatrics, Karolinska Institutet, Huddinge, Sweden.,Department of Geriatric Medicine, Karolinska University Hospital, Huddinge, Sweden
| | - V Newcombe
- Division of Anaesthesia, University of Cambridge, Addenbrookes Hospital, Cambridge, Cambs, UK
| | - L Nyberg
- Centre for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - D Sharp
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | - O Tenovuo
- Turku Brain Injury Centre, Turku University Hospital, Turku, Finland.,Department of Neurology, University of Turku, Turku, Finland
| | - K Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
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Forsyth A, McMillan R, Campbell D, Malpas G, Maxwell E, Sleigh J, Dukart J, Hipp JF, Muthukumaraswamy SD. Comparison of local spectral modulation, and temporal correlation, of simultaneously recorded EEG/fMRI signals during ketamine and midazolam sedation. Psychopharmacology (Berl) 2018; 235:3479-3493. [PMID: 30426183 DOI: 10.1007/s00213-018-5064-8] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Accepted: 10/03/2018] [Indexed: 10/27/2022]
Abstract
RATIONALE AND OBJECTIVES The identification of biomarkers of drug action can be supported by non-invasive brain imaging techniques, such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), with simultaneous collection plausibly overcoming the limitations of either modality alone. Despite this, few studies have assessed the feasibility and utility of recording simultaneous EEG/fMRI in a drug study. METHODS We used simultaneous EEG/fMRI to assess the modulation of neural activity by ketamine and midazolam, in a placebo-controlled, single-blind, three-way cross-over design. Specifically, we analysed the sensitivity and direction of the spectral effects of each modality and the temporal correlations between the modulations of power of the common EEG bands and the blood-oxygen-level-dependent (BOLD) signal. RESULTS AND CONCLUSIONS Demonstrating feasibility, local spectral effects were similar to those found in previous non-simultaneous EEG and fMRI studies. Ketamine administration resulted in a widespread reduction of BOLD fractional amplitude of low frequency fluctuations (fALFF) and a diverse pattern of effects in the different EEG bands. Midazolam increased fALFF in occipital, parietal, and temporal areas, and frontal delta and beta EEG power. While EEG spectra were more sensitive to pharmacological modulations than the fALFF bands, there was no clear spatial relationship between the two modalities. Additionally, ketamine modulated the temporal correlation strengths between the theta EEG band and the BOLD signal, whereas midazolam altered temporal correlations with the alpha and beta bands. Taken together, these results demonstrate the utility of simultaneous recording: each modality provides unique insights, and combinatorial analyses elicit more information than separate recordings.
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Affiliation(s)
- Anna Forsyth
- School of Pharmacy, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag, Auckland, 92019, New Zealand
| | - Rebecca McMillan
- School of Pharmacy, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag, Auckland, 92019, New Zealand
| | - Doug Campbell
- Department of Anaesthesiology, Auckland District Health Board, Auckland, New Zealand
| | - Gemma Malpas
- Department of Anaesthesiology, Auckland District Health Board, Auckland, New Zealand
| | - Elizabeth Maxwell
- Department of Anaesthesiology, Auckland District Health Board, Auckland, New Zealand
| | - Jamie Sleigh
- Department of Anaesthesiology, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
| | - Juergen Dukart
- Roche Pharma Research and Early Development, Neuroscience, Ophthalmology and Rare Diseases, Roche Innovation Center, F Hoffman La Roche, Basel, Switzerland
| | - Joerg F Hipp
- Roche Pharma Research and Early Development, Neuroscience, Ophthalmology and Rare Diseases, Roche Innovation Center, F Hoffman La Roche, Basel, Switzerland
| | - Suresh D Muthukumaraswamy
- School of Pharmacy, Faculty of Medical and Health Sciences, The University of Auckland, Private Bag, Auckland, 92019, New Zealand.
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Harvey JL, Demetriou L, McGonigle J, Wall MB. A short, robust brain activation control task optimised for pharmacological fMRI studies. PeerJ 2018; 6:e5540. [PMID: 30221091 PMCID: PMC6138041 DOI: 10.7717/peerj.5540] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 08/07/2018] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Functional magnetic resonance imaging (fMRI) is a popular method for examining pharmacological effects on the brain; however, the BOLD response is dependent on intact neurovascular coupling, and potentially modulated by a number of physiological factors. Pharmacological fMRI is therefore vulnerable to confounding effects of pharmacological probes on general physiology or neurovascular coupling. Controlling for such non-specific effects in pharmacological fMRI studies is therefore an important consideration, and there is an additional need for well-validated fMRI task paradigms that could be used to control for such effects, or for general testing purposes. METHODS We have developed two variants of a standardized control task that are short (5 minutes duration) simple (for both the subject and experimenter), widely applicable, and yield a number of readouts in a spatially diverse set of brain networks. The tasks consist of four functionally discrete three-second trial types (plus additional null trials) and contain visual, auditory, motor and cognitive (eye-movements, and working memory tasks in the two task variants) stimuli. Performance of the tasks was assessed in a group of 15 subjects scanned on two separate occasions, with test-retest reliability explicitly assessed using intra-class correlation coefficients. RESULTS Both tasks produced robust patterns of brain activation in the expected brain regions, and region of interest-derived reliability coefficients for the tasks were generally high, with four out of eight task conditions rated as 'excellent' or 'good', and only one out of eight rated as 'poor'. Median values in the voxel-wise reliability measures were also >0.7 for all task conditions, and therefore classed as 'excellent' or 'good'. The spatial concordance between the most highly activated voxels and those with the highest reliability coefficients was greater for the sensory (auditory, visual) conditions than the other (motor, cognitive) conditions. DISCUSSION Either of the two task variants would be suitable for use as a control task in future pharmacological fMRI studies or for any other investigation where a short, reliable, basic task paradigm is required. Stimulus code is available online for re-use by the scientific community.
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Affiliation(s)
- Jessica-Lily Harvey
- School of Psychology and Neuroscience, University of St. Andrews, St Andrews, United Kingdom
- Division of Brain Sciences, Imperial College London, London, United Kingdom
| | - Lysia Demetriou
- Invicro Ltd., London, United Kingdom
- Department of Medicine, Imperial College London, London, United Kingdom
| | - John McGonigle
- Division of Brain Sciences, Imperial College London, London, United Kingdom
- Perspectum Diagnostics, Oxford, United Kingdom
| | - Matthew B. Wall
- Division of Brain Sciences, Imperial College London, London, United Kingdom
- Invicro Ltd., London, United Kingdom
- Clinical Psychopharmacology Unit, University College London, University of London, London, United Kingdom
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