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Rojczyk P, Seitz-Holland J, Heller C, Marcolini S, Marshall AD, Sydnor VJ, Kaufmann E, Jung LB, Bonke EM, Berger L, Umminger LF, Wiegand TLT, Cho KIK, Rathi Y, Bouix S, Pasternak O, Hinds SR, Fortier CB, Salat D, Milberg WP, Shenton ME, Koerte IK. Posttraumatic survivor guilt is associated with white matter microstructure alterations. J Affect Disord 2024; 361:768-777. [PMID: 38897303 DOI: 10.1016/j.jad.2024.06.047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 05/31/2024] [Accepted: 06/15/2024] [Indexed: 06/21/2024]
Abstract
BACKGROUND Military veterans with posttraumatic stress disorder (PTSD) commonly experience posttraumatic guilt. Guilt over commission or omission evolves when responsibility is assumed for an unfortunate outcome (e.g., the death of a fellow combatant). Survivor guilt is a state of intense emotional distress experienced by the weight of knowing that one survived while others did not. METHODS This study of the Translational Research Center for TBI and Stress Disorders (TRACTS) analyzed structural and diffusion-weighted magnetic resonance imaging data from 132 male Iraq/Afghanistan veterans with PTSD. The Clinician-Administered PTSD Scale for DSM-IV (CAPS-IV) was employed to classify guilt. Thirty (22.7 %) veterans experienced guilt over acts of commission or omission, 34 (25.8 %) experienced survivor guilt, and 68 (51.5 %) had no posttraumatic guilt. White matter microstructure (fractional anisotropy, FA), cortical thickness, and cortical volume were compared between veterans with guilt over acts of commission or omission, veterans with survivor guilt, and veterans without guilt. RESULTS Veterans with survivor guilt had significantly lower white matter FA compared to veterans who did not experience guilt (p < .001), affecting several regions of major white matter fiber bundles. There were no significant differences in white matter FA, cortical thickness, or volumes between veterans with guilt over acts of commission or omission and veterans without guilt (p > .050). LIMITATIONS This cross-sectional study with exclusively male veterans precludes inferences of causality between the studied variables and generalizability to the larger veteran population that includes women. CONCLUSION Survivor guilt may be a particularly impactful form of posttraumatic guilt that requires specific treatment efforts targeting brain health.
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Affiliation(s)
- Philine Rojczyk
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-University, Munich, Germany
| | - Johanna Seitz-Holland
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Carina Heller
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany; Department of Clinical Psychology, Friedrich Schiller University Jena, Jena, Germany; German Center for Mental Health (DZPG), Partner Site Jena-Magdeburg-Halle, Jena, Germany; Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Partner Site Jena-Magdeburg-Halle, Jena, Germany
| | - Sofia Marcolini
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Neurology, Alzheimer Center Groningen, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Amy D Marshall
- Department of Psychology, The Pennsylvania State University, PA, USA
| | - Valerie J Sydnor
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Elisabeth Kaufmann
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Neurology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Leonard B Jung
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-University, Munich, Germany
| | - Elena M Bonke
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-University, Munich, Germany
| | - Luisa Berger
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-University, Munich, Germany
| | - Lisa F Umminger
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-University, Munich, Germany
| | - Tim L T Wiegand
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-University, Munich, Germany
| | - Kang Ik K Cho
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Yogesh Rathi
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sylvain Bouix
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Software Engineering and Information Technology, École de technologie supérieure, Université du Québec, Montréal, QC, Canada
| | - Ofer Pasternak
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sidney R Hinds
- Department of Neurology, Uniformed Services University, Bethesda, MD, USA
| | - Catherine B Fortier
- Translational Research Center for TBI and Stress Disorders (TRACTS) and Geriatric Research, Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - David Salat
- Translational Research Center for TBI and Stress Disorders (TRACTS) and Geriatric Research, Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA, USA; Neuroimaging Research for Veterans (NeRVe) Center, VA Boston Healthcare System, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital Department of Radiology, Boston, MA, USA
| | - William P Milberg
- Translational Research Center for TBI and Stress Disorders (TRACTS) and Geriatric Research, Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA; Neuroimaging Research for Veterans (NeRVe) Center, VA Boston Healthcare System, Boston, MA, USA
| | - Martha E Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Psychiatry, VA Boston Healthcare System, Brockton, MA, USA
| | - Inga K Koerte
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-University, Munich, Germany; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Psychiatry, VA Boston Healthcare System, Brockton, MA, USA; Graduate School of Systemic Neurosciences, Ludwig-Maximilians-University, Munich, Germany.
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Marin-Marin L, Renau-Lagranja J, Ávila C, Costumero V. Depression and Agitation Factors Are Related to Regional Brain Atrophy and Faster Longitudinal Cognitive Decline in Mild Cognitive Impairment. J Alzheimers Dis 2024; 97:1341-1351. [PMID: 38217601 DOI: 10.3233/jad-230929] [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] [Indexed: 01/15/2024]
Abstract
BACKGROUND Neuropsychiatric symptoms (NPS) are a common aspect of Alzheimer's disease (AD). Multiple studies have investigated its brain correlates, but it still remains unclear how they relate with brain atrophy in mild cognitive impairment (MCI). OBJECTIVE Our objective was to investigate brain volume in MCI patients as a function of NPS. METHODS We measured grey matter volume, neuropsychological status and NPS (Neuropsychiatric Inventory, NPI), in a sample of 81 MCI patients (43 females). Participants were divided in groups depending on presence (NPS+) or absence (NPS-) of NPS and on type of NPS. RESULTS We found lower volume of left temporal pole in patients with depression compared to NPS- (p = 0.012), and in patients with agitation compared to NPS- in the right middle occipital gyrus (p = 0.003). We also found a significant correlation between volume of left temporal pole and MMSE (r (78) = 0.232, p = 0.019). Finally, NPS+ presented lower cross-sectional cognitive level than NPS- (t (79) = 1.79, p = 0.038), and faster cognitive decline (t (48) = -1.74, p = 0.044). CONCLUSIONS Our results support the colocalization of structural damage as a possible mechanism underlying the relationship between MCI and depression and provide novel evidence regarding agitation. Moreover, our longitudinal evidence highlights the relevance of an adequate identification of NPS in MCI patients to identify those at risk of faster cognitive decline.
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Affiliation(s)
- Lidón Marin-Marin
- Department of Psychology, The University of York, York, UK
- York Neuroimaging Centre, York, UK
| | - Julia Renau-Lagranja
- Hospital General Universitari de Castelló, Castelló, Spain
- Department of Basic Psychology, Neuropsychology and Functional Neuroimaging Group, Clinical Psychology and Psychobiology, University Jaume I, Castelló, Spain
| | - César Ávila
- Department of Basic Psychology, Neuropsychology and Functional Neuroimaging Group, Clinical Psychology and Psychobiology, University Jaume I, Castelló, Spain
| | - Víctor Costumero
- Department of Basic Psychology, Neuropsychology and Functional Neuroimaging Group, Clinical Psychology and Psychobiology, University Jaume I, Castelló, Spain
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González-García I, Visser M. A Semantic Cognition Contribution to Mood and Anxiety Disorder Pathophysiology. Healthcare (Basel) 2023; 11:healthcare11060821. [PMID: 36981478 PMCID: PMC10047953 DOI: 10.3390/healthcare11060821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/17/2023] [Accepted: 03/02/2023] [Indexed: 03/14/2023] Open
Abstract
Over the last two decades, the functional role of the bilateral anterior temporal lobes (bATLs) has been receiving more attention. They have been associated with semantics and social concept processing, and are regarded as a core region for depression. In the past, the role of the ATL has often been overlooked in semantic models based on functional magnetic resonance imaging (fMRI) due to geometric distortions in the BOLD signal. However, previous work has unequivocally associated the bATLs with these higher-order cognitive functions following advances in neuroimaging techniques to overcome the geometric distortions. At the same time, the importance of the neural basis of conceptual knowledge in understanding mood disorders became apparent. Theoretical models of the neural basis of mood and anxiety disorders have been classically studied from the emotion perspective, without concentrating on conceptual processing. However, recent work suggests that the ATL, a brain region underlying conceptual knowledge, plays an essential role in mood and anxiety disorders. Patients with anxiety and depression often cope with self-blaming biases and guilt. The theory is that in order to experience guilt, the brain needs to access the related conceptual information via the ATL. This narrative review describes how aberrant interactions of the ATL with the fronto–limbic emotional system could underlie mood and anxiety disorders.
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Pindi P, Houenou J, Piguet C, Favre P. Real-time fMRI neurofeedback as a new treatment for psychiatric disorders: A meta-analysis. Prog Neuropsychopharmacol Biol Psychiatry 2022; 119:110605. [PMID: 35843369 DOI: 10.1016/j.pnpbp.2022.110605] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 06/12/2022] [Accepted: 07/11/2022] [Indexed: 10/17/2022]
Abstract
Neurofeedback using real-time functional MRI (RT-fMRI-NF) is an innovative technique that allows to voluntarily modulate a targeted brain response and its associated behavior. Despite promising results in the current literature, its effectiveness on symptoms management in psychiatric disorders is not yet clearly demonstrated. Here, we provide 1) a state-of-art qualitative review of RT-fMRI-NF studies aiming at alleviating clinical symptoms in a psychiatric population; 2) a quantitative evaluation (meta-analysis) of RT-fMRI-NF effectiveness on various psychiatric disorders and 3) methodological suggestions for future studies. Thirty-one clinical trials focusing on psychiatric disorders were included and categorized according to standard diagnostic categories. Among the 31 identified studies, 22 consisted of controlled trials, of which only eight showed significant clinical improvement in the experimental vs. control group after the training. Nine studies found an effect at follow-up on ADHD symptoms, emotion dysregulation, facial emotion processing, depressive symptoms, hallucinations, psychotic symptoms, and specific phobia. Within-group meta-analysis revealed large effects of the NF training on depressive symptoms right after the training (g = 0.81, p < 0.01) and at follow-up (g = 1.19, p < 0.01), as well as medium effects on anxiety (g = 0.44, p = 0.01) and emotion regulation (g = 0.48, p < 0.01). Between-group meta-analysis showed a medium effect on depressive symptoms (g = 0.49, p < 0.01) and a large effect on anxiety (g = 0.77, p = 0.01). However, the between-studies heterogeneity is very high. The use of RT-fMRI-NF as a treatment for psychiatric symptoms is promising, however, further double-blind, multicentric, randomized-controlled trials are warranted.
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Affiliation(s)
- Pamela Pindi
- Paris Est Créteil University (UPEC), INSERM U955, IMRB, Translational Neuro-psychiatry Team, AP-HP, DMU IMPACT, Mondor University Hospitals, FondaMental Foundation, F-94010 Créteil, France; Paris-Saclay University, Neurospin, CEA, UNIACT Lab, PsyBrain Team, F-91191 Gif-sur-Yvette, France
| | - Josselin Houenou
- Paris Est Créteil University (UPEC), INSERM U955, IMRB, Translational Neuro-psychiatry Team, AP-HP, DMU IMPACT, Mondor University Hospitals, FondaMental Foundation, F-94010 Créteil, France; Paris-Saclay University, Neurospin, CEA, UNIACT Lab, PsyBrain Team, F-91191 Gif-sur-Yvette, France.
| | - Camille Piguet
- Department of Psychiatry, Faculty of Medicine, University of Geneva, Campus Biotech, Geneva, Switzerland
| | - Pauline Favre
- Paris Est Créteil University (UPEC), INSERM U955, IMRB, Translational Neuro-psychiatry Team, AP-HP, DMU IMPACT, Mondor University Hospitals, FondaMental Foundation, F-94010 Créteil, France; Paris-Saclay University, Neurospin, CEA, UNIACT Lab, PsyBrain Team, F-91191 Gif-sur-Yvette, France
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5
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González Méndez PP, Rodino Climent J, Stanley JA, Sitaram R. Real-Time fMRI Neurofeedback Training as a Neurorehabilitation Approach on Depressive Disorders: A Systematic Review of Randomized Control Trials. J Clin Med 2022; 11:jcm11236909. [PMID: 36498484 PMCID: PMC9737316 DOI: 10.3390/jcm11236909] [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: 10/17/2022] [Revised: 11/02/2022] [Accepted: 11/10/2022] [Indexed: 11/25/2022] Open
Abstract
Real-time functional magnetic resonance imaging neurofeedback (rt-fMRI-nf) training is an emerging intervention for neurorehabilitation. However, its translation into clinical use on participants with clinical depression is unclear, the effect estimates from randomized control trials and the certainty of the supporting evidence on the effect estimates are unknown. As the number of studies on neurofeedback increases every year, and better quality evidence becomes available, we evaluate the evidence of all randomized control trials available on the clinical application of rt-fMRI-nf training on participants with clinical depression. We performed electronic searches in Pubmed, Embase, CENTRAL, rtFIN database, Epistemonikos, trial registers, reference lists, other systematic reviews, conference abstracts, and cross-citation in Google Scholar. Reviewers independently selected studies, extracted data and evaluated the risk of bias. The certainty of the evidence was judged using the GRADE framework. This review complies with PRISMA guidelines and was submitted to PROSPERO registration. We found 435 results. After the selection process, we included 11 reports corresponding to four RCTs. The effect of rt-fMRI-nf on improving the severity of clinical depression scores demonstrated a tendency to favor the intervention; however, the general effect was not significant. At end of treatment, SMD (standardized mean difference): -0.32 (95% CI -0.73 to 0.10). At follow-up, SMD: -0.33 (95% CI -0.91, 1.25). All the studies showed changes in BOLD fMRI activation after training; however, only one study confirmed regulation success during a transfer run. Whole-brain analyses suggests that rt-fMRI nf may alter activity patterns in brain networks. More studies are needed to evaluate quality of life, acceptability, adverse effects, cognitive tasks, and physiology measures. We conclude that the current evidence on the effect of rt-fMRI-nf training for decision-making outcomes in patients with clinical depression is still based on low certainty of the evidence.
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Affiliation(s)
- Pamela P. González Méndez
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago 8331150, Chile
- Correspondence: (P.P.G.M.); (R.S.)
| | - Julio Rodino Climent
- Brain Dynamics Laboratory, School of Biomedical Engineering, Universidad de Valparaíso, Valparaíso 2362905, Chile
| | - Jeffrey A. Stanley
- Department of Psychiatry and Behavioral Neurosciences, School of Medicine, Wayne State University, Detroit, MI 48202, USA
| | - Ranganatha Sitaram
- Diagnostic Imaging Department, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Correspondence: (P.P.G.M.); (R.S.)
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Pereira JA, Ray A, Rana M, Silva C, Salinas C, Zamorano F, Irani M, Opazo P, Sitaram R, Ruiz S. A real-time fMRI neurofeedback system for the clinical alleviation of depression with a subject-independent classification of brain states: A proof of principle study. Front Hum Neurosci 2022; 16:933559. [PMID: 36092645 PMCID: PMC9452730 DOI: 10.3389/fnhum.2022.933559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Accepted: 07/25/2022] [Indexed: 11/13/2022] Open
Abstract
Most clinical neurofeedback studies based on functional magnetic resonance imaging use the patient's own neural activity as feedback. The objective of this study was to create a subject-independent brain state classifier as part of a real-time fMRI neurofeedback (rt-fMRI NF) system that can guide patients with depression in achieving a healthy brain state, and then to examine subsequent clinical changes. In a first step, a brain classifier based on a support vector machine (SVM) was trained from the neural information of happy autobiographical imagery and motor imagery blocks received from a healthy female participant during an MRI session. In the second step, 7 right-handed female patients with mild or moderate depressive symptoms were trained to match their own neural activity with the neural activity corresponding to the “happiness emotional brain state” of the healthy participant. The training (4 training sessions over 2 weeks) was carried out using the rt-fMRI NF system guided by the brain-state classifier we had created. Thus, the informative voxels previously obtained in the first step, using SVM classification and Effect Mapping, were used to classify the Blood-Oxygen-Level Dependent (BOLD) activity of the patients and converted into real-time visual feedback during the neurofeedback training runs. Improvements in the classifier accuracy toward the end of the training were observed in all the patients [Session 4–1 Median = 6.563%; Range = 4.10–27.34; Wilcoxon Test (0), 2-tailed p = 0.031]. Clinical improvement also was observed in a blind standardized clinical evaluation [HDRS CE2-1 Median = 7; Range 2 to 15; Wilcoxon Test (0), 2-tailed p = 0.016], and in self-report assessments [BDI-II CE2-1 Median = 8; Range 1–15; Wilcoxon Test (0), 2-tailed p = 0.031]. In addition, the clinical improvement was still present 10 days after the intervention [BDI-II CE3-2_Median = 0; Range −1 to 2; Wilcoxon Test (0), 2-tailed p = 0.50/ HDRS CE3-2 Median = 0; Range −1 to 2; Wilcoxon Test (0), 2-tailed p = 0.625]. Although the number of participants needs to be increased and a control group included to confirm these findings, the results suggest a novel option for neural modulation and clinical alleviation in depression using noninvasive stimulation technologies.
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Affiliation(s)
- Jaime A. Pereira
- Departamento de Psiquiatría, Facultad de Medicina, Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago, Chile
- Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Andreas Ray
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Mohit Rana
- Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Claudio Silva
- Unidad de Imágenes Cuantitativas Avanzadas, Departamento de Imágenes, Facultad de Medicina, Clínica Alemana- Universidad del Desarrollo, Santiago, Chile
| | - Cesar Salinas
- Unidad de Imágenes Cuantitativas Avanzadas, Departamento de Imágenes, Facultad de Medicina, Clínica Alemana- Universidad del Desarrollo, Santiago, Chile
| | - Francisco Zamorano
- Unidad de Imágenes Cuantitativas Avanzadas, Departamento de Imágenes, Facultad de Medicina, Clínica Alemana- Universidad del Desarrollo, Santiago, Chile
- Laboratorio de Neurociencia Social y Neuromodulación, Centro de Investigación en Complejidad Social (neuroCICS), Facultad de Gobierno, Universidad del Desarrollo, Santiago, Chile
| | - Martin Irani
- Departamento de Psiquiatría, Facultad de Medicina, Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Patricia Opazo
- Departamento de Psiquiatría, Facultad de Medicina, Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Ranganatha Sitaram
- Departamento de Psiquiatría, Facultad de Medicina, Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago, Chile
- Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, United States
- *Correspondence: Ranganatha Sitaram
| | - Sergio Ruiz
- Departamento de Psiquiatría, Facultad de Medicina, Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago, Chile
- Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile
- Sergio Ruiz
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Orth L, Meeh J, Gur RC, Neuner I, Sarkheil P. Frontostriatal circuitry as a target for fMRI-based neurofeedback interventions: A systematic review. Front Hum Neurosci 2022; 16:933718. [PMID: 36092647 PMCID: PMC9449529 DOI: 10.3389/fnhum.2022.933718] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Accepted: 08/08/2022] [Indexed: 11/19/2022] Open
Abstract
Dysregulated frontostriatal circuitries are viewed as a common target for the treatment of aberrant behaviors in various psychiatric and neurological disorders. Accordingly, experimental neurofeedback paradigms have been applied to modify the frontostriatal circuitry. The human frontostriatal circuitry is topographically and functionally organized into the “limbic,” the “associative,” and the “motor” subsystems underlying a variety of affective, cognitive, and motor functions. We conducted a systematic review of the literature regarding functional magnetic resonance imaging-based neurofeedback studies that targeted brain activations within the frontostriatal circuitry. Seventy-nine published studies were included in our survey. We assessed the efficacy of these studies in terms of imaging findings of neurofeedback intervention as well as behavioral and clinical outcomes. Furthermore, we evaluated whether the neurofeedback targets of the studies could be assigned to the identifiable frontostriatal subsystems. The majority of studies that targeted frontostriatal circuitry functions focused on the anterior cingulate cortex, the dorsolateral prefrontal cortex, and the supplementary motor area. Only a few studies (n = 14) targeted the connectivity of the frontostriatal regions. However, post-hoc analyses of connectivity changes were reported in more cases (n = 32). Neurofeedback has been frequently used to modify brain activations within the frontostriatal circuitry. Given the regulatory mechanisms within the closed loop of the frontostriatal circuitry, the connectivity-based neurofeedback paradigms should be primarily considered for modifications of this system. The anatomical and functional organization of the frontostriatal system needs to be considered in decisions pertaining to the neurofeedback targets.
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Affiliation(s)
- Linda Orth
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany
- *Correspondence: Linda Orth
| | - Johanna Meeh
- Department of Psychiatry and Psychotherapy, University of Münster, Münster, Germany
| | - Ruben C. Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Irene Neuner
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany
- Institute of Neuroscience and Medicine 4, Forschungszentrum Jülich, Jülich, Germany
| | - Pegah Sarkheil
- Department of Psychiatry and Psychotherapy, University of Münster, Münster, Germany
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Dudek E, Dodell-Feder D. The efficacy of real-time functional magnetic resonance imaging neurofeedback for psychiatric illness: A meta-analysis of brain and behavioral outcomes. Neurosci Biobehav Rev 2021; 121:291-306. [PMID: 33370575 PMCID: PMC7856210 DOI: 10.1016/j.neubiorev.2020.12.020] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 12/01/2020] [Accepted: 12/18/2020] [Indexed: 12/13/2022]
Abstract
Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) has gained popularity as an experimental treatment for a variety of psychiatric illnesses. However, there has yet to be a quantitative review regarding its efficacy. Here, we present the first meta-analysis of rtfMRI-NF for psychiatric disorders, evaluating its impact on brain and behavioral outcomes. Our literature review identified 17 studies and 105 effect sizes across brain and behavioral outcomes. We find that rtfMRI-NF produces a medium-sized effect on neural activity during training (g = .59, 95 % CI [.44, .75], p < .0001), a large-sized effect after training when no neurofeedback is provided (g = .84, 95 % CI [.37, 1.31], p = .005), and small-sized effects for behavioral outcomes (symptoms g = .37, 95 % CI [.16, .58], p = .002; cognition g = .23, 95 % CI [-.33, .78], p = .288). Mixed-effects analyses revealed few moderators. Together, these data suggest a positive impact of rtfMRI-NF on brain and behavioral outcomes, although more research is needed to determine how rtfMRI-NF works, for whom, and under what circumstances.
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Affiliation(s)
- Emily Dudek
- Department of Psychology, University of Rochester, United States
| | - David Dodell-Feder
- Department of Psychology, University of Rochester, United States; Department of Neuroscience, University of Rochester Medical Center, United States.
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Mathiak K, Keller M. Clinical Application of Real-Time fMRI-Based Neurofeedback for Depression. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1305:275-293. [PMID: 33834405 DOI: 10.1007/978-981-33-6044-0_15] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/09/2022]
Abstract
Real-time functional magnetic resonance imaging-based neurofeedback (rt-fMRI NF) is a recent technique used to train self-regulation of circumscribed brain areas or networks. For clinical applications in depression, NF training targets brain areas with disturbed activation patterns, such as heightened reactivity of amygdala in response to negative stimuli, in order to normalize the neurophysiology and their behavioral correlates. Recent studies have targeted emotion processing areas such as the amygdala, the salience network, and top-down control areas such as the lateral prefrontal cortex. Different methods of rt-fMRI-based NF in depression, their potential for clinical improvement, and most recent advancements of this technology are discussed considering their role for future clinical applications. Initial findings of randomized controlled trials show promising results. However, for lasting treatment effects, clinical efficiency and optimal target regions, tasks, control conditions, and duration of training need to be established.
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Affiliation(s)
- Klaus Mathiak
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen, Germany.
| | - Micha Keller
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen, Germany
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Tursic A, Eck J, Lührs M, Linden DEJ, Goebel R. A systematic review of fMRI neurofeedback reporting and effects in clinical populations. Neuroimage Clin 2020; 28:102496. [PMID: 33395987 PMCID: PMC7724376 DOI: 10.1016/j.nicl.2020.102496] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 10/29/2020] [Accepted: 11/02/2020] [Indexed: 12/22/2022]
Abstract
Real-time fMRI-based neurofeedback is a relatively young field with a potential to impact the currently available treatments of various disorders. In order to evaluate the evidence of clinical benefits and investigate how consistently studies report their methods and results, an exhaustive search of fMRI neurofeedback studies in clinical populations was performed. Reporting was evaluated using a limited number of Consensus on the reporting and experimental design of clinical and cognitive-behavioral neurofeedback studies (CRED-NF checklist) items, which was, together with a statistical power and sensitivity calculation, used to also evaluate the existing evidence of the neurofeedback benefits on clinical measures. The 62 found studies investigated regulation abilities and/or clinical benefits in a wide range of disorders, but with small sample sizes and were therefore unable to detect small effects. Most points from the CRED-NF checklist were adequately reported by the majority of the studies, but some improvements are suggested for the reporting of group comparisons and relations between regulation success and clinical benefits. To establish fMRI neurofeedback as a clinical tool, more emphasis should be placed in the future on using larger sample sizes determined through a priori power calculations and standardization of procedures and reporting.
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Affiliation(s)
- Anita Tursic
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands; Brain Innovation B.V, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands.
| | - Judith Eck
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands; Brain Innovation B.V, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands.
| | - Michael Lührs
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands; Brain Innovation B.V, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands.
| | - David E J Linden
- School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Universiteitssingel 40, 6229 ER Maastricht, The Netherlands.
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands; Brain Innovation B.V, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands; Department of Neuroimaging and Neuromodeling, Netherlands Institute for Neuroscience, Meibergdreef 47, 1105 BA Amsterdam, the Netherlands.
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Klöbl M, Michenthaler P, Godbersen GM, Robinson S, Hahn A, Lanzenberger R. Reinforcement and Punishment Shape the Learning Dynamics in fMRI Neurofeedback. Front Hum Neurosci 2020; 14:304. [PMID: 32792929 PMCID: PMC7393482 DOI: 10.3389/fnhum.2020.00304] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 07/08/2020] [Indexed: 12/22/2022] Open
Abstract
Introduction Neurofeedback (NF) using real-time functional magnetic resonance imaging (fMRI) has proven to be a valuable neuroscientific tool for probing cognition and promising therapeutic approach for several psychiatric disorders. Even though learning constitutes an elementary aspect of NF, the question whether certain training schemes might positively influence its dynamics has largely been neglected. Methods To address this issue, participants were trained to exert control on their subgenual anterior cingulate cortex (sgACC) blood-oxygenation-level-dependent signal, receiving either exclusively positive reinforcement (PR, “positive feedback”) or also positive punishment (PP, “negative feedback”). The temporal dynamics of the learning process were investigated by individually modeling the feedback periods and trends, offering the possibility to assess activation changes within and across blocks, runs and sessions. Results The results show faster initial learning of the PR + PP group by significantly lower deactivations of the sgACC in the first session and stronger regulation trends during the first runs. Independent of the group, significant control over the sgACC could further be shown with but not without feedback. Conclusion The beneficial effect of PP is supported by previous findings of multiple research domains suggesting that error avoidance represents an important motivational factor of learning, which complements the reward spectrum. This hypothesis warrants further investigation with respect to NF, as it could offer a way to generally facilitate the process of gaining volitional control over brain activity.
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Affiliation(s)
- Manfred Klöbl
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Paul Michenthaler
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | | | - Simon Robinson
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.,Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia.,Department of Neurology, Medical University of Graz, Graz, Austria
| | - Andreas Hahn
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
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