101
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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: 0.5] [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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102
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Gonzalez-Castillo J, Ramot M, Momenan R. Editorial: Towards Expanded Utility of Real Time fMRI Neurofeedback in Clinical Applications. Front Hum Neurosci 2020; 14:606868. [PMID: 33281590 PMCID: PMC7689151 DOI: 10.3389/fnhum.2020.606868] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 10/12/2020] [Indexed: 11/13/2022] Open
Affiliation(s)
- Javier Gonzalez-Castillo
- Section on Functional Imaging Methods, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Michal Ramot
- Section on Cognitive Neuropsychology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States.,Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel
| | - Reza Momenan
- Clinical NeuroImaging Research Core, National Institute on Alcohol Abuse and Alcoholism (NIAAA), National Institute of Health (NIH), Bethesda, MD, United States
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103
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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: 33] [Impact Index Per Article: 6.6] [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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104
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Tsuchiyagaito A, Misaki M, Zoubi OA, Paulus M, Bodurka J. Prevent breaking bad: A proof of concept study of rebalancing the brain's rumination circuit with real-time fMRI functional connectivity neurofeedback. Hum Brain Mapp 2020; 42:922-940. [PMID: 33169903 PMCID: PMC7856643 DOI: 10.1002/hbm.25268] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 10/06/2020] [Accepted: 10/20/2020] [Indexed: 12/14/2022] Open
Abstract
Rumination, repetitively thinking about the causes, consequences, and one's negative affect, has been considered as an important factor of depression. The intrusion of ruminative thoughts is not easily controlled, and it may be useful to visualize one's neural activity related to rumination and to use that information to facilitate one's self‐control. Real‐time fMRI neurofeedback (rtfMRI‐nf) enables one to see and regulate the fMRI signal from their own brain. This proof‐of concept study utilized connectivity‐based rtfMRI‐nf (cnf) to normalize brain functional connectivity (FC) associated with rumination. Healthy participants were instructed to brake or decrease FC between the precuneus and the right temporoparietal junction (rTPJ), associated with high levels of rumination, while engaging in a self‐referential task. The cnf group (n = 14) showed a linear decrease in the precuneus‐rTPJ FC across neurofeedback training (trend [112] = −0.180, 95% confidence interval [CI] −0.330 to −0.031, while the sham group (n = 14) showed a linear increase in the target FC (trend [112] = 0.151, 95% CI 0.017 to 0.299). Although the cnf group showed a greater reduction in state‐rumination compared to the sham group after neurofeedback training (p < .05), decoupled precuneus‐rTPJ FC did not predict attenuated state‐rumination. We did not find any significant aversive effects of rtfMRI‐nf in all study participants. These results suggest that cnf has the capacity to influence FC among precuneus and rTPJ of a ruminative brain circuit. This approach can be applied to mood and anxiety patients to determine the clinical benefits of reduction in maladaptive rumination.
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Affiliation(s)
- Aki Tsuchiyagaito
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA.,Japan Society for the Promotion of Science, Tokyo, Japan
| | - Masaya Misaki
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Obada Al Zoubi
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA.,Department of Electrical and Computer Engineering, University of Oklahoma, Tulsa, Oklahoma, USA
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- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA.,Department of Community Medicine, Oxley Health Sciences, University of Tulsa, Tulsa, Oklahoma, USA
| | - Martin Paulus
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Jerzy Bodurka
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA.,Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, Oklahoma, USA
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105
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Mennen AC, Turk-Browne NB, Wallace G, Seok D, Jaganjac A, Stock J, deBettencourt MT, Cohen JD, Norman KA, Sheline YI. Cloud-Based Functional Magnetic Resonance Imaging Neurofeedback to Reduce the Negative Attentional Bias in Depression: A Proof-of-Concept Study. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2020; 6:490-497. [PMID: 33422469 DOI: 10.1016/j.bpsc.2020.10.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 10/15/2020] [Accepted: 10/18/2020] [Indexed: 11/29/2022]
Abstract
Individuals with depression show an attentional bias toward negatively valenced stimuli and thoughts. In this proof-of-concept study, we present a novel closed-loop neurofeedback procedure intended to remediate this bias. Internal attentional states were detected in real time by applying machine learning techniques to functional magnetic resonance imaging data on a cloud server; these attentional states were externalized using a visual stimulus that the participant could learn to control. We trained 15 participants with major depressive disorder and 12 healthy control participants over 3 functional magnetic resonance imaging sessions. Exploratory analysis showed that participants with major depressive disorder were initially more likely than healthy control participants to get stuck in negative attentional states, but this diminished with neurofeedback training relative to controls. Depression severity also decreased from pre- to posttraining. These results demonstrate that our method is sensitive to the negative attentional bias in major depressive disorder and showcase the potential of this novel technique as a treatment that can be evaluated in future clinical trials.
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Affiliation(s)
- Anne C Mennen
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey.
| | | | - Grant Wallace
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey
| | - Darsol Seok
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Adna Jaganjac
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Janet Stock
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | | | - Jonathan D Cohen
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey; Department of Psychology, Princeton University, Princeton, New Jersey
| | - Kenneth A Norman
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey; Department of Psychology, Princeton University, Princeton, New Jersey
| | - Yvette I Sheline
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
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106
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Zweerings J, Sarkheil P, Keller M, Dyck M, Klasen M, Becker B, Gaebler AJ, Ibrahim CN, Turetsky BI, Zvyagintsev M, Flatten G, Mathiak K. Rt-fMRI neurofeedback-guided cognitive reappraisal training modulates amygdala responsivity in posttraumatic stress disorder. NEUROIMAGE-CLINICAL 2020; 28:102483. [PMID: 33395974 PMCID: PMC7689411 DOI: 10.1016/j.nicl.2020.102483] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 10/15/2020] [Accepted: 10/21/2020] [Indexed: 12/14/2022]
Abstract
We found neurofeedback-specific attenuation of amygdala responses. Trauma symptoms and the affective state improved in patients at one-month follow-up. Reduced amygdala responses were associated with improved well-being at follow-up. 75% of individuals with PTSD used the learned strategies in daily life. Left lateral prefrontal cortex responses were reduced during neurofeedback training.
Background Traumatic experiences are associated with neurofunctional dysregulations in key regions of the emotion regulation circuits. In particular, amygdala responsivity to negative stimuli is exaggerated while engagement of prefrontal regulatory control regions is attenuated. Successful application of emotion regulation (ER) strategies may counteract this disbalance, however, application of learned strategies in daily life is hampered in individuals afflicted by posttraumatic stress disorder (PTSD). We hypothesized that a single session of real-time fMRI (rtfMRI) guided upregulation of prefrontal regions during an emotion regulation task enhances self-control during exposure to negative stimuli and facilitates transfer of the learned ER skills to daily life. Methods In a cross-over design, individuals with a PTSD diagnosis after a single traumatic event (n = 20) according to DSM-IV-TR criteria and individuals without a formal psychiatric diagnosis (n = 21) underwent a cognitive reappraisal training. In randomized order, all participants completed two rtfMRI neurofeedback (NF) runs targeting the left lateral prefrontal cortex (lPFC) and two control runs without NF (NoNF) while using cognitive reappraisal to reduce their emotional response to negative scenes. During the NoNF runs, two %%-signs were displayed instead of the two-digit feedback (FB) to achieve a comparable visual stimulation. The project aimed at defining the clinical potential of the training according to three success markers: (1) NF induced changes in left lateral prefrontal cortex and bilateral amygdala activity during the regulation of aversive scenes compared to cognitive reappraisal alone (primary registered outcome), (2) associated changes on the symptomatic and behavioral level such as indicated by PTSD symptom severity and affect ratings, (3) clinical utility such as indicated by perceived efficacy, acceptance, and transfer to daily life measured four weeks after the training. Results In comparison to the reappraisal without feedback, a neurofeedback-specific decrease in the left lateral PFC (d = 0.54) alongside an attenuation of amygdala responses (d = 0.33) emerged. Reduced amygdala responses during NF were associated with symptom improvement (r = −0.42) and less negative affect (r = −0.63) at follow-up. The difference in symptom scores exceeds requirements for a minimal clinically important difference and corresponds to a medium effect size (d = 0.64). Importantly, 75% of individuals with PTSD used the strategies in daily life during a one-month follow-up period and perceived the training as efficient. Conclusion Our findings suggest beneficial effects of the NF training indicated by reduced amygdala responses that were associated with improved symptom severity and affective state four weeks after the NF training as well as patient-centered perceived control during the training, helpfulness and application of strategies in daily life. However, reduced prefrontal involvement was unexpected. The study suggests good tolerability of the training protocol and potential for clinical use in the treatment of PTSD.
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Affiliation(s)
- Jana Zweerings
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Aachen, Germany; Institute of Neuroscience and Medicine, JARA-Institute Brain Structure Function Relationship (INM 10), Research Center Jülich, Jülich, Germany.
| | - Pegah Sarkheil
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Aachen, Germany; Institute of Neuroscience and Medicine, JARA-Institute Brain Structure Function Relationship (INM 10), Research Center Jülich, Jülich, Germany
| | - Micha Keller
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Aachen, Germany; Institute of Neuroscience and Medicine, JARA-Institute Brain Structure Function Relationship (INM 10), Research Center Jülich, Jülich, Germany
| | - Miriam Dyck
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Aachen, Germany; Novarea RPK, Aachen, Germany
| | - Martin Klasen
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Aachen, Germany; Institute of Neuroscience and Medicine, JARA-Institute Brain Structure Function Relationship (INM 10), Research Center Jülich, Jülich, Germany
| | - Benjamin Becker
- The Clinical Hospital of the Chengdu Brain Science Institute, School of Life Science and Technology, Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Arnim J Gaebler
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Aachen, Germany; Institute of Neuroscience and Medicine, JARA-Institute Brain Structure Function Relationship (INM 10), Research Center Jülich, Jülich, Germany
| | - Camellia N Ibrahim
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Aachen, Germany; Institute of Neuroscience and Medicine, JARA-Institute Brain Structure Function Relationship (INM 10), Research Center Jülich, Jülich, Germany
| | - Bruce I Turetsky
- Neuropsychiatry Section, Department of Psychiatry, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
| | - Mikhail Zvyagintsev
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Aachen, Germany; Brain Imaging Facility, Interdisciplinary Centre for Clinical Studies (IZKF), School of Medicine, RWTH Aachen University, Germany
| | - Guido Flatten
- Euregio-Institut für Psychosomatik und Psychotraumatologie, Aachen, Germany
| | - Klaus Mathiak
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Aachen, Germany; Institute of Neuroscience and Medicine, JARA-Institute Brain Structure Function Relationship (INM 10), Research Center Jülich, Jülich, Germany
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107
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Low Cost MR Compatible Haptic Stimulation with Application to fMRI Neurofeedback. Brain Sci 2020; 10:brainsci10110790. [PMID: 33126691 PMCID: PMC7692267 DOI: 10.3390/brainsci10110790] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 10/23/2020] [Accepted: 10/26/2020] [Indexed: 11/17/2022] Open
Abstract
The most common feedback displays in the fMRI environment are visual, e.g., in which participants try to increase or decrease the level of a thermometer. However, haptic feedback is increasingly valued in computer interaction tasks, particularly for real-time fMRI feedback. fMRI-neurofeedback is a clinical intervention that has not yet taken advantage of this trend. Here we describe a low-cost, user-friendly, MR-compatible system that can provide graded haptic vibrotactile stimulation in an initial application to fMRI neurofeedback. We also present a feasibility demonstration showing that we could successfully set up the system and obtain data in the context of a neurofeedback paradigm. We conclude that vibrotactile stimulation using this low-cost system is a viable method of feedback presentation, and encourage neurofeedback researchers to incorporate this type of feedback into their studies.
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108
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Peng X, Lau WKW, Wang C, Ning L, Zhang R. Impaired left amygdala resting state functional connectivity in subthreshold depression individuals. Sci Rep 2020; 10:17207. [PMID: 33057046 PMCID: PMC7560839 DOI: 10.1038/s41598-020-74166-x] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Accepted: 09/24/2020] [Indexed: 01/15/2023] Open
Abstract
Subthreshold depression (StD) affects people who experience clinically relevant depressive symptoms, which does not meet the diagnostic criteria for major depressive disorder (MDD). StD represents an ideal model for understanding the pathophysiological mechanisms of depression. Impaired emotion processing is a core feature of depression; careful investigation is required to better understand the neural correlates of emotion processing in depressed populations. In the current study, we explored whether the resting-state functional connectivity of the amygdala, a hub that taps a wide range of brain areas involved in emotion processing, is altered in individuals with StD when compared with healthy controls. Resting-state imaging data was collected from 59 individuals with StD and 59 age- and gender-matched controls. We found that the resting-state functional connectivity of the left amygdala with the cognitive control network and the left insula was significantly lower in people with StD than that in healthy controls. Such association was not observed in the right amygdala. Furthermore, functional connectivity strength between the left amygdala and the left precuneus was positively associated with depressive symptoms in individuals with StD. Our findings are in line with those reported in subjects with MDD, which may assist in further elucidating the pathophysiological mechanisms of depression, and contribute to the development of tailored treatments for individuals with StD who are at high risk of developing MDD.
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Affiliation(s)
- Xiaoling Peng
- Cognitive and Neuropsychology Laboratory, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, 510515, China.,Guangzhou Cana School, Guangzhou Rehabilitation and Research Center for Children With ASD, Guangzhou, 510540, China
| | - Way K W Lau
- Department of Special Education and Counselling, The Education University of Hong Kong, Hong Kong, China.,Integrated Centre for Wellbeing, The Education University of Hong Kong, Hong Kong, China.,Bioanalytical Laboratory for Educational Sciences, The Education University of Hong Kong, Hong Kong, China
| | - Chanyu Wang
- Cognitive and Neuropsychology Laboratory, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, 510515, China
| | - Lingfang Ning
- Cognitive and Neuropsychology Laboratory, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, 510515, China
| | - Ruibin Zhang
- Cognitive and Neuropsychology Laboratory, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, 510515, China. .,Department of Psychiatry, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China.
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109
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Haugg A, Sladky R, Skouras S, McDonald A, Craddock C, Kirschner M, Herdener M, Koush Y, Papoutsi M, Keynan JN, Hendler T, Cohen Kadosh K, Zich C, MacInnes J, Adcock RA, Dickerson K, Chen N, Young K, Bodurka J, Yao S, Becker B, Auer T, Schweizer R, Pamplona G, Emmert K, Haller S, Van De Ville D, Blefari M, Kim D, Lee J, Marins T, Fukuda M, Sorger B, Kamp T, Liew S, Veit R, Spetter M, Weiskopf N, Scharnowski F. Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity? Hum Brain Mapp 2020; 41:3839-3854. [PMID: 32729652 PMCID: PMC7469782 DOI: 10.1002/hbm.25089] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 05/18/2020] [Accepted: 05/26/2020] [Indexed: 12/31/2022] Open
Abstract
Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.
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Affiliation(s)
- Amelie Haugg
- Psychiatric University Hospital ZurichUniversity of ZurichZürichSwitzerland
- Faculty of PsychologyUniversity of ViennaViennaAustria
| | - Ronald Sladky
- Faculty of PsychologyUniversity of ViennaViennaAustria
| | - Stavros Skouras
- Department of Biological and Medical PsychologyUniversity of BergenBergenNorway
| | - Amalia McDonald
- Department of PsychologyUniversity of VirginiaCharlottesvilleVirginia
| | - Cameron Craddock
- Department of Diagnostic MedicineThe University of Texas at Austin Dell Medical SchoolAustinTexas
| | - Matthias Kirschner
- Psychiatric University Hospital ZurichUniversity of ZurichZürichSwitzerland
- McConnell Brain Imaging CentreMontréal Neurological Institute, McGill UniversityMontrealCanada
| | - Marcus Herdener
- Psychiatric University Hospital ZurichUniversity of ZurichZürichSwitzerland
| | - Yury Koush
- Magnetic Resonance Research Center, Department of Radiology & Biomedical ImagingYale UniversityNew HavenConnecticut
| | - Marina Papoutsi
- UCL Huntington's Disease CentreInstitute of Neurology, University College LondonLondonEngland
| | - Jackob N. Keynan
- Functional Brain CenterWohl Institute for Advanced Imaging, Tel‐Aviv Sourasky Medical Center, Tel‐Aviv UniversityTel AvivIsrael
| | - Talma Hendler
- Functional Brain CenterWohl Institute for Advanced Imaging, Tel‐Aviv Sourasky Medical Center, Tel‐Aviv UniversityTel AvivIsrael
| | | | - Catharina Zich
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordEngland
| | - Jeff MacInnes
- Institute for Learning and Brain SciencesUniversity of WashingtonSeattleWashington
| | - R. Alison Adcock
- Department of Psychiatry and Behavioral SciencesDuke UniversityDurhamNorth Carolina
| | - Kathryn Dickerson
- Department of Psychiatry and Behavioral SciencesDuke UniversityDurhamNorth Carolina
| | - Nan‐Kuei Chen
- Department of Biomedical EngineeringUniversity of ArizonaTucsonArizona
| | - Kymberly Young
- Department of Psychiatry, School of MedicineUniversity of PittsburghPittsburghPennsylvania
| | | | - Shuxia Yao
- Clinical Hospital of Chengdu the Brain Science Institute, MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Benjamin Becker
- Clinical Hospital of Chengdu the Brain Science Institute, MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Tibor Auer
- School of PsychologyUniversity of SurreyGuildfordEngland
| | - Renate Schweizer
- Functional Imaging LaboratoryGerman Primate CenterGöttingenGermany
| | - Gustavo Pamplona
- Hôpital and Ophtalmique Jules GoninUniversity of LausanneLausanneSwitzerland
| | - Kirsten Emmert
- Department of NeurologyUniversity Medical Center Schleswig‐Holstein, Kiel UniversityKielGermany
| | - Sven Haller
- Radiology‐Department of Surgical SciencesUppsala UniversityUppsalaSweden
| | - Dimitri Van De Ville
- Center for NeuroprostheticsEcole Polytechnique Féderale de LausanneLausanneSwitzerland
- Department of Radiology and Medical Informatics, Faculty of MedicineUniversity of GenevaGenevaSwitzerland
| | - Maria‐Laura Blefari
- Center for NeuroprostheticsEcole Polytechnique Féderale de LausanneLausanneSwitzerland
| | - Dong‐Youl Kim
- Department of Brain and Cognitive EngineeringKorea UniversitySeoulKorea
| | - Jong‐Hwan Lee
- Department of Brain and Cognitive EngineeringKorea UniversitySeoulKorea
| | - Theo Marins
- D'Or Institute for Research and Education (IDOR)Rio de JaneiroBrazil
| | - Megumi Fukuda
- School of Fundamental Science and EngineeringWaseda UniversityTokyoJapan
| | - Bettina Sorger
- Department Cognitive Neuroscience, Faculty of Psychology and NeuroscienceMaastricht UniversityMaastrichtThe Netherlands
| | - Tabea Kamp
- Department Cognitive Neuroscience, Faculty of Psychology and NeuroscienceMaastricht UniversityMaastrichtThe Netherlands
| | - Sook‐Lei Liew
- Division of Occupational Science and Occupational TherapyUniversity of Southern CaliforniaLos AngelesCalifornia
| | - Ralf Veit
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center MunichUniversity of TübingenTübingenGermany
| | - Maartje Spetter
- School of PsychologyUniversity of BirminghamBirminghamEngland
| | - Nikolaus Weiskopf
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Frank Scharnowski
- Psychiatric University Hospital ZurichUniversity of ZurichZürichSwitzerland
- Faculty of PsychologyUniversity of ViennaViennaAustria
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110
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MacInnes JJ, Adcock RA, Stocco A, Prat CS, Rao RPN, Dickerson KC. Pyneal: Open Source Real-Time fMRI Software. Front Neurosci 2020; 14:900. [PMID: 33041750 PMCID: PMC7522368 DOI: 10.3389/fnins.2020.00900] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 08/03/2020] [Indexed: 11/13/2022] Open
Abstract
Increasingly, neuroimaging researchers are exploring the use of real-time functional magnetic resonance imaging (rt-fMRI) as a way to access a participant's ongoing brain function throughout a scan. This approach presents novel and exciting experimental applications ranging from monitoring data quality in real time, to delivering neurofeedback from a region of interest, to dynamically controlling experimental flow, or interfacing with remote devices. Yet, for those interested in adopting this method, the existing software options are few and limited in application. This presents a barrier for new users, as well as hinders existing users from refining techniques and methods. Here we introduce a free, open-source rt-fMRI package, the Pyneal toolkit, designed to address this limitation. The Pyneal toolkit is python-based software that offers a flexible and user friendly framework for rt-fMRI, is compatible with all three major scanner manufacturers (GE, Siemens, Phillips), and, critically, allows fully customized analysis pipelines. In this article, we provide a detailed overview of the architecture, describe how to set up and run the Pyneal toolkit during an experimental session, offer tutorials with scan data that demonstrate how data flows through the Pyneal toolkit with example analyses, and highlight the advantages that the Pyneal toolkit offers to the neuroimaging community.
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Affiliation(s)
- Jeff J. MacInnes
- Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, United States
| | - R. Alison Adcock
- Department of Psychiatry and Behavioral Sciences, Center for Cognitive Neuroscience, Duke Institute for Brain Sciences, Duke University, Durham, NC, United States
| | - Andrea Stocco
- Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, United States
- Department of Psychology, University of Washington, Seattle, WA, United States
| | - Chantel S. Prat
- Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, United States
- Department of Psychology, University of Washington, Seattle, WA, United States
| | - Rajesh P. N. Rao
- Department of Computer Science and Engineering, Center for Neurotechnology, University of Washington, Seattle, WA, United States
| | - Kathryn C. Dickerson
- Department of Psychiatry and Behavioral Sciences, Center for Cognitive Neuroscience, Duke Institute for Brain Sciences, Duke University, Durham, NC, United States
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Bègue I, Kaiser S, Kirschner M. Pathophysiology of negative symptom dimensions of schizophrenia – Current developments and implications for treatment. Neurosci Biobehav Rev 2020; 116:74-88. [DOI: 10.1016/j.neubiorev.2020.06.004] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Revised: 04/13/2020] [Accepted: 06/02/2020] [Indexed: 02/06/2023]
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Paulus MP, Stewart JL. Neurobiology, Clinical Presentation, and Treatment of Methamphetamine Use Disorder: A Review. JAMA Psychiatry 2020; 77:959-966. [PMID: 32267484 PMCID: PMC8098650 DOI: 10.1001/jamapsychiatry.2020.0246] [Citation(s) in RCA: 168] [Impact Index Per Article: 33.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
IMPORTANCE The prevalence of and mortality associated with methamphetamine use has doubled during the past 10 years. There is evidence suggesting that methamphetamine use disorder could be the next substance use crisis in the United States and possibly worldwide. OBSERVATION The neurobiology of methamphetamine use disorder extends beyond the acute effect of the drug as a monoaminergic modulator and includes intracellular pathways focused on oxidative stress, neurotoxic and excitotoxic effects, and neuroinflammation. Similarly, the clinical picture extends beyond the acute psychostimulatory symptoms to include complex cardiovascular and cerebrovascular signs and symptoms that need to be identified by the clinician. Although there are no pharmacologic treatments for methamphetamine use disorder, cognitive behavioral therapy, behavioral activation, and contingency management show modest effectiveness. CONCLUSIONS AND RELEVANCE There is a need to better understand the complex neurobiology of methamphetamine use disorder and to develop interventions aimed at novel biological targets. Parsing the disorder into different processes (eg, craving or mood-associated alterations) and targeting the neural systems and biological pathways underlying these processes may lead to greater success in identifying disease-modifying interventions. Finally, mental health professionals need to be trained in recognizing early cardiovascular and cerebrovascular warning signs to mitigate the mortality associated with methamphetamine use disorder.
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Affiliation(s)
- Martin P. Paulus
- Scientific Director and President Laureate Institute for Brain Research 6655 S Yale Ave, Tulsa, OK 74136-3326,Department of Community Medicine, University of Tulsa, Tulsa OK 74104
| | - Jennifer L. Stewart
- Scientific Director and President Laureate Institute for Brain Research 6655 S Yale Ave, Tulsa, OK 74136-3326,Department of Community Medicine, University of Tulsa, Tulsa OK 74104
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113
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Young KD, Friedman ES, Collier A, Berman SR, Feldmiller J, Haggerty AE, Thase ME, Siegle GJ. Response to SSRI intervention and amygdala activity during self-referential processing in major depressive disorder. NEUROIMAGE-CLINICAL 2020; 28:102388. [PMID: 32871385 PMCID: PMC7476063 DOI: 10.1016/j.nicl.2020.102388] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 08/14/2020] [Accepted: 08/17/2020] [Indexed: 01/20/2023]
Abstract
Examined whether SSRIs normalize amygdala activity or dampen responsiveness. Responders and non-responders did not differ in amygdala activity prior to treatment. SSRI responders had increased amygdala activation to positive stimuli after treatment. SSRI responders also had decreased amygdala activation to negative stimuli after treatment.
There are conflicting reports on the impact of antidepressants on neural reactions for positive information. We thus hypothesized that there would be clinically important individual differences in neural reactivity to positive information during SSRI therapy. We further predicted that only those who responded to SSRIs would show increased amygdala reactivity to positive information following treatment to a level similar to that seen in healthy participants. Depressed individuals (n = 17) underwent fMRI during performance of a task involving rating the self-relevance of emotionally positive and negative cue words before and after receiving 12 weeks of SSRI therapy. At post-treatment, SSRI responders (n = 11) had increased amygdala activity in response to positive stimuli, and decreased activity in response to negative stimuli, compared to non-responders (n = 6). Results suggest that normalizing amygdala responses to salient information is a correlate of SSRI efficacy. Second line interventions that modulate amygdala activity, such as fMRI neurofeedback, may be beneficial in those who do not respond to SSRI medications.
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Affiliation(s)
- Kymberly D Young
- University of Pittsburgh School of Medicine, Pittsburgh, 15213 PA, USA.
| | - Edward S Friedman
- University of Pittsburgh School of Medicine, Pittsburgh, 15213 PA, USA
| | - Amanda Collier
- University of Pittsburgh Medical Center, Pittsburgh, 15213 PA, USA
| | | | | | - Agnes E Haggerty
- University of Miami Miller School of Medicine, Miami, 33136 FL, USA
| | - Michael E Thase
- University of Pennsylvania School of Medicine, Philadelphia, 19104 PA, USA
| | - Greg J Siegle
- University of Pittsburgh School of Medicine, Pittsburgh, 15213 PA, USA
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Scharnowski F, Nicholson AA, Pichon S, Rosa MJ, Rey G, Eickhoff SB, Van De Ville D, Vuilleumier P, Koush Y. The role of the subgenual anterior cingulate cortex in dorsomedial prefrontal-amygdala neural circuitry during positive-social emotion regulation. Hum Brain Mapp 2020; 41:3100-3118. [PMID: 32309893 PMCID: PMC7336138 DOI: 10.1002/hbm.25001] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Revised: 03/23/2020] [Accepted: 03/24/2020] [Indexed: 01/10/2023] Open
Abstract
Positive-social emotions mediate one's cognitive performance, mood, well-being, and social bonds, and represent a critical variable within therapeutic settings. It has been shown that the upregulation of positive emotions in social situations is associated with increased top-down signals that stem from the prefrontal cortices (PFC) which modulate bottom-up emotional responses in the amygdala. However, it remains unclear if positive-social emotion upregulation of the amygdala occurs directly through the dorsomedial PFC (dmPFC) or indirectly linking the bilateral amygdala with the dmPFC via the subgenual anterior cingulate cortex (sgACC), an area which typically serves as a gatekeeper between cognitive and emotion networks. We performed functional MRI (fMRI) experiments with and without effortful positive-social emotion upregulation to demonstrate the functional architecture of a network involving the amygdala, the dmPFC, and the sgACC. We found that effortful positive-social emotion upregulation was associated with an increase in top-down connectivity from the dmPFC on the amygdala via both direct and indirect connections with the sgACC. Conversely, we found that emotion processes without effortful regulation increased network modulation by the sgACC and amygdala. We also found that more anxious individuals with a greater tendency to suppress emotions and intrusive thoughts, were likely to display decreased amygdala, dmPFC, and sgACC activity and stronger connectivity strength from the sgACC onto the left amygdala during effortful emotion upregulation. Analyzed brain network suggests a more general role of the sgACC in cognitive control and sheds light on neurobiological informed treatment interventions.
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Affiliation(s)
- Frank Scharnowski
- Department of Cognition, Emotion and Methods in Psychology, Faculty of PsychologyUniversity of ViennaViennaAustria
- Department of Psychiatry, Psychotherapy and PsychosomaticsPsychiatric Hospital, University of ZürichZürichSwitzerland
- Neuroscience Center ZürichUniversity of Zürich and Swiss Federal Institute of TechnologyZürichSwitzerland
- Zürich Center for Integrative Human Physiology (ZIHP)University of ZürichZürichSwitzerland
| | - Andrew A. Nicholson
- Department of Cognition, Emotion and Methods in Psychology, Faculty of PsychologyUniversity of ViennaViennaAustria
| | - Swann Pichon
- Geneva Neuroscience Center, Department of NeuroscienceUniversity of GenevaGenevaSwitzerland
- NCCR Affective SciencesUniversity of GenevaGenevaSwitzerland
- Faculty of Psychology and Educational ScienceUniversity of GenevaGenevaSwitzerland
| | - Maria J. Rosa
- Department of Computer ScienceCentre for Computational Statistics and Machine Learning, University College LondonLondonUK
| | - Gwladys Rey
- Geneva Neuroscience Center, Department of NeuroscienceUniversity of GenevaGenevaSwitzerland
- Institute of BioengineeringEcole Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
| | - Simon B. Eickhoff
- Institute of Neuroscience and MedicineBrain & Behaviour (INM‐7), Research Center JülichJülichGermany
- Institute of Systems Neuroscience, Medical FacultyHeinrich Heine University DüsseldorfDüsseldorfGermany
| | - Dimitri Van De Ville
- Department of Radiology and Medical InformaticsUniversity of GenevaGenevaSwitzerland
- Institute of BioengineeringEcole Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
| | - Patrik Vuilleumier
- Geneva Neuroscience Center, Department of NeuroscienceUniversity of GenevaGenevaSwitzerland
- NCCR Affective SciencesUniversity of GenevaGenevaSwitzerland
| | - Yury Koush
- Department of Radiology and Biomedical ImagingYale UniversityNew HavenConnecticutUSA
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Althammer F, Ferreira-Neto HC, Rubaharan M, Roy RK, Patel AA, Murphy A, Cox DN, Stern JE. Three-dimensional morphometric analysis reveals time-dependent structural changes in microglia and astrocytes in the central amygdala and hypothalamic paraventricular nucleus of heart failure rats. J Neuroinflammation 2020; 17:221. [PMID: 32703230 PMCID: PMC7379770 DOI: 10.1186/s12974-020-01892-4] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 07/08/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Cardiovascular diseases, including heart failure, are the most common cause of death globally. Recent studies support a high degree of comorbidity between heart failure and cognitive and mood disorders resulting in memory loss, depression, and anxiety. While neuroinflammation in the hypothalamic paraventricular nucleus contributes to autonomic and cardiovascular dysregulation in heart failure, mechanisms underlying cognitive and mood disorders in this disease remain elusive. The goal of this study was to quantitatively assess markers of neuroinflammation (glial morphology, cytokines, and A1 astrocyte markers) in the central amygdala, a critical forebrain region involved in emotion and cognition, and to determine its time course and correlation to disease severity during the progression of heart failure. METHODS We developed and implemented a comprehensive microglial/astrocyte profiler for precise three-dimensional morphometric analysis of individual microglia and astrocytes in specific brain nuclei at different time points during the progression of heart failure. To this end, we used a well-established ischemic heart failure rat model. Morphometric studies were complemented with quantification of various pro-inflammatory cytokines and A1/A2 astrocyte markers via qPCR. RESULTS We report structural remodeling of central amygdala microglia and astrocytes during heart failure that affected cell volume, surface area, filament length, and glial branches, resulting overall in somatic swelling and deramification, indicative of a change in glial state. These changes occurred in a time-dependent manner, correlated with the severity of heart failure, and were delayed compared to changes in the hypothalamic paraventricular nucleus. Morphometric changes correlated with elevated mRNA levels of pro-inflammatory cytokines and markers of reactive A1-type astrocytes in the paraventricular nucleus and central amygdala during heart failure. CONCLUSION We provide evidence that in addition to the previously described hypothalamic neuroinflammation implicated in sympathohumoral activation during heart failure, microglia, and astrocytes within the central amygdala also undergo structural remodeling indicative of glial shifts towards pro-inflammatory phenotypes. Thus, our studies suggest that neuroinflammation in the amygdala stands as a novel pathophysiological mechanism and potential therapeutic target that could be associated with emotional and cognitive deficits commonly observed at later stages during the course of heart failure.
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Affiliation(s)
- Ferdinand Althammer
- Center for Neuroinflammation and Cardiometabolic Diseases, Georgia State University, Atlanta, USA
| | | | | | - Ranjan K Roy
- Center for Neuroinflammation and Cardiometabolic Diseases, Georgia State University, Atlanta, USA
| | - Atit A Patel
- Neuroscience Institute, Georgia State University, Atlanta, USA
| | - Anne Murphy
- Neuroscience Institute, Georgia State University, Atlanta, USA
| | - Daniel N Cox
- Neuroscience Institute, Georgia State University, Atlanta, USA
| | - Javier E Stern
- Center for Neuroinflammation and Cardiometabolic Diseases, Georgia State University, Atlanta, USA.
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116
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Quevedo K, Yuan Teoh J, Engstrom M, Wedan R, Santana-Gonzalez C, Zewde B, Porter D, Cohen Kadosh K. Amygdala Circuitry During Neurofeedback Training and Symptoms' Change in Adolescents With Varying Depression. Front Behav Neurosci 2020; 14:110. [PMID: 32774244 PMCID: PMC7388863 DOI: 10.3389/fnbeh.2020.00110] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Accepted: 06/04/2020] [Indexed: 12/28/2022] Open
Abstract
Typical adolescents have increased limbic engagement unchecked by regulatory medial prefrontal cortex (PFC) activity as well as heightened self-focus. The resulting emotion dysregulation and self-focused rumination make adolescents more susceptible to depression and suicide attempts. Heightened self-focus converges with mental illness among depressed adolescents, who deploy exaggerated attention to negative self-relevant stimuli and neglect positive ones as part of depression's phenomenology. This results in rigid negative self-representations during an identity formative period with potential lifetime repercussions. Current empirically supported treatments fail to allay recurrent depression. Evidence-based interventions for illnesses linked to suicide ideation and attempts (e.g., depression) underperform across the lifespan. This could be because current treatments are not successful in altering pervasive negative self-representations and affect dysregulation, which is known to be a risk factor of chronic depression. This study departs from the premise that increasing positive self-processing might be protective against chronic depression particularly during adolescence. The present research is a novel investigation of neurofeedback as a potential treatment alternative for adolescent depression. To enhance positive self-processing, we used the happy self-face as a cue to initiate neurofeedback from the bilateral amygdala and hippocampus and adolescents attempted to upregulate that limbic activity through the recall of positive autobiographical memories. We identified limbic functional circuitry engaged during neurofeedback and links to short-term symptoms' change in depression and rumination. We found that depressed youth showed greater right amygdala to right frontocortical connectivity and lower left amygdala to right frontocortical connectivity compared to healthy controls during neurofeedback vs. control conditions. Depressed youth also showed significant symptom reduction. Connectivity between the right amygdala and frontocortical regions was positively correlated with rumination and depression change, but connectivity between frontocortical regions and the left amygdala was negatively correlated with depression change. The results suggest that depressed youth might engage implicit emotion regulation circuitry while healthy youth recruit explicit emotion regulation circuits during neurofeedback. Our findings support a compensatory approach (i.e., target the right amygdala) during future neurofeedback interventions in depressed youth. Future work ought to include a placebo condition or group.
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Affiliation(s)
- Karina Quevedo
- Department of Psychiatry, Medical School, University of Minnesota, Minneapolis, MN, United States
| | - Jia Yuan Teoh
- Department of Psychiatry, Medical School, University of Minnesota, Minneapolis, MN, United States
| | - Maggie Engstrom
- Department of Psychiatry, Medical School, University of Minnesota, Minneapolis, MN, United States
| | - Riley Wedan
- Department of Psychiatry, Medical School, University of Minnesota, Minneapolis, MN, United States
| | - Carmen Santana-Gonzalez
- Department of Psychiatry, Medical School, University of Minnesota, Minneapolis, MN, United States
| | - Betanya Zewde
- Department of Psychiatry, Medical School, University of Minnesota, Minneapolis, MN, United States
| | - David Porter
- Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN, United States
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Martz ME, Hart T, Heitzeg MM, Peltier SJ. Neuromodulation of brain activation associated with addiction: A review of real-time fMRI neurofeedback studies. Neuroimage Clin 2020; 27:102350. [PMID: 32736324 PMCID: PMC7394772 DOI: 10.1016/j.nicl.2020.102350] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 07/07/2020] [Accepted: 07/13/2020] [Indexed: 02/07/2023]
Abstract
Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf) has emerged in recent years as an imaging modality used to examine volitional control over targeted brain activity. rtfMRI-nf has also been applied clinically as a way to train individuals to self-regulate areas of the brain, or circuitry, involved in various disorders. One such application of rtfMRI-nf has been in the domain of addictive behaviors, including substance use. Given the pervasiveness of substance use and the challenges of existing treatments to sustain abstinence, rtfMRI-nf has been identified as a promising treatment tool. rtfMRI-nf has also been used in basic science research in order to test the ability to modulate brain function involved in addiction. This review focuses first on providing an overview of recent rtfMRI-nf studies in substance-using populations, specifically nicotine, alcohol, and cocaine users, aimed at reducing craving-related brain activation. Next, rtfMRI-nf studies targeting reward responsivity and emotion regulation in healthy samples are reviewed in order to examine the extent to which areas of the brain involved in addiction can be self-regulated using neurofeedback. We propose that future rtfMRI-nf studies could be strengthened by improvements to study design, sample selection, and more robust strategies in the development and assessment of rtfMRI-nf as a clinical treatment. Recommendations for ways to accomplish these improvements are provided. rtfMRI-nf holds much promise as an imaging modality that can directly target key brain regions involved in addiction, however additional studies are needed in order to establish rtfMRI-nf as an effective, and practical, treatment for addiction.
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Affiliation(s)
- Meghan E Martz
- Addiction Center, Department of Psychiatry, University of Michigan, 4250 Plymouth Road, Ann Arbor, MI 48109, USA.
| | - Tabatha Hart
- Addiction Center, Department of Psychiatry, University of Michigan, 4250 Plymouth Road, Ann Arbor, MI 48109, USA
| | - Mary M Heitzeg
- Addiction Center, Department of Psychiatry, University of Michigan, 4250 Plymouth Road, Ann Arbor, MI 48109, USA
| | - Scott J Peltier
- Functional MRI Laboratory, USA; Department of Biomedical Engineering, Bonisteel Interdisciplinary Research Building, 2360 Bonisteel Blvd, Ann Arbor, MI 48109, USA
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118
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Zotev V, Mayeli A, Misaki M, Bodurka J. Emotion self-regulation training in major depressive disorder using simultaneous real-time fMRI and EEG neurofeedback. Neuroimage Clin 2020; 27:102331. [PMID: 32623140 PMCID: PMC7334611 DOI: 10.1016/j.nicl.2020.102331] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 06/22/2020] [Accepted: 06/23/2020] [Indexed: 12/11/2022]
Abstract
Simultaneous real-time fMRI and EEG neurofeedback (rtfMRI-EEG-nf) is an emerging neuromodulation approach, that enables simultaneous volitional regulation of both hemodynamic (BOLD fMRI) and electrophysiological (EEG) brain activities. Here we report the first application of rtfMRI-EEG-nf for emotion self-regulation training in patients with major depressive disorder (MDD). In this proof-of-concept study, MDD patients in the experimental group (n = 16) used rtfMRI-EEG-nf during a happy emotion induction task to simultaneously upregulate two fMRI and two EEG activity measures relevant to MDD. The target measures included BOLD activities of the left amygdala (LA) and left rostral anterior cingulate cortex (rACC), and frontal EEG asymmetries in the alpha band (FAA, [7.5-12.5] Hz) and high-beta band (FBA, [21-30] Hz). MDD patients in the control group (n = 8) were provided with sham feedback signals. An advanced procedure for improved real-time EEG-fMRI artifact correction was implemented. The experimental group participants demonstrated significant upregulation of the LA BOLD activity, FAA, and FBA during the rtfMRI-EEG-nf task, as well as significant enhancement in fMRI connectivity between the LA and left rACC. Average individual FAA changes during the rtfMRI-EEG-nf task positively correlated with depression and anhedonia severities, and negatively correlated with after-vs-before changes in depressed mood ratings. Temporal correlations between the FAA and FBA time courses and the LA BOLD activity were significantly enhanced during the rtfMRI-EEG-nf task. The experimental group participants reported significant mood improvements after the training. Our results suggest that the rtfMRI-EEG-nf may have potential for treatment of MDD.
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Affiliation(s)
- Vadim Zotev
- Laureate Institute for Brain Research, Tulsa, OK, USA.
| | - Ahmad Mayeli
- Laureate Institute for Brain Research, Tulsa, OK, USA; Electrical and Computer Engineering, University of Oklahoma, Tulsa, OK, USA
| | - Masaya Misaki
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Jerzy Bodurka
- Laureate Institute for Brain Research, Tulsa, OK, USA; Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, USA.
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Sukhodolsky DG, Walsh C, Koller WN, Eilbott J, Rance M, Fulbright RK, Zhao Z, Bloch MH, King R, Leckman JF, Scheinost D, Pittman B, Hampson M. Randomized, Sham-Controlled Trial of Real-Time Functional Magnetic Resonance Imaging Neurofeedback for Tics in Adolescents With Tourette Syndrome. Biol Psychiatry 2020; 87:1063-1070. [PMID: 31668476 PMCID: PMC7015800 DOI: 10.1016/j.biopsych.2019.07.035] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 07/26/2019] [Accepted: 07/31/2019] [Indexed: 12/15/2022]
Abstract
BACKGROUND Activity in the supplementary motor area (SMA) has been associated with tics in Tourette syndrome (TS). The aim of this study was to test a novel intervention-real-time functional magnetic resonance imaging neurofeedback from the SMA-for reduction of tics in adolescents with TS. METHODS Twenty-one adolescents with TS were enrolled in a double-blind, randomized, sham-controlled, crossover study involving two sessions of neurofeedback from their SMA. The primary outcome measure of tic severity was the Yale Global Tic Severity Scale administered by an independent evaluator before and after each arm. The secondary outcome was control over the SMA assessed in neuroimaging scans, in which subjects were cued to increase/decrease activity in SMA without receiving feedback. RESULTS All 21 subjects completed both arms of the study and all assessments. Participants had significantly greater reduction of tics on the Yale Global Tic Severity Scale after real neurofeedback as compared with the sham control (p < .05). Mean Yale Global Tic Severity Scale Total Tic score decreased from 25.2 ± 4.6 at baseline to 19.9 ± 5.7 at end point in the neurofeedback condition and from 24.8 ± 8.1 to 23.3 ± 8.5 in the sham control condition. The 3.8-point difference is clinically meaningful and corresponds to an effect size of 0.59. However, there were no differences in changes on the secondary measure of control over the SMA. CONCLUSIONS This first randomized controlled trial of real-time functional magnetic resonance imaging neurofeedback in adolescents with TS suggests that this neurofeedback intervention may be helpful for improving tic symptoms. However, no effects were found in terms of change in control over the SMA, the hypothesized mechanism of action.
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Affiliation(s)
| | - Christopher Walsh
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - William N Koller
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | | | - Mariela Rance
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Robert K Fulbright
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Zhiying Zhao
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Michael H Bloch
- Child Study Center, Yale School of Medicine, New Haven, Connecticut
| | - Robert King
- Child Study Center, Yale School of Medicine, New Haven, Connecticut
| | - James F Leckman
- Child Study Center, Yale School of Medicine, New Haven, Connecticut
| | - Dustin Scheinost
- Child Study Center, Yale School of Medicine, New Haven, Connecticut; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut; Department of Statistics and Data Science, Yale University, New Haven, Connecticut
| | - Brian Pittman
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | - Michelle Hampson
- Child Study Center, Yale School of Medicine, New Haven, Connecticut; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut; Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut.
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Takamura M, Okamoto Y, Shibasaki C, Yoshino A, Okada G, Ichikawa N, Yamawaki S. Antidepressive effect of left dorsolateral prefrontal cortex neurofeedback in patients with major depressive disorder: A preliminary report. J Affect Disord 2020; 271:224-227. [PMID: 32479320 DOI: 10.1016/j.jad.2020.03.080] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 01/22/2020] [Accepted: 03/24/2020] [Indexed: 12/16/2022]
Abstract
Background Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf) have recently attracted attention as a novel, individualized treatment method for major depressive disorder (MDD). In this study, the antidepressant effect of neurofeedback training for left dorsolateral prefrontal cortex (DLPFC) activity was examined. Methods Six patients with MDD completed 5 days of neurofeedback training sessions. In each session, the patients observed a BOLD signal within their left DLPFC as a line graph, and attempted to up-regulate the signal using the graphical cue. Primary outcome measures were clinical scales of severity of depression and rumination. Results After neurofeedback training, the clinical measures were improved significantly. In addition, patient proficiency for neurofeedback training was related significantly to the improvement of the rumination symptom. Limitations Study limitations include the lack of a control group or condition, the lack of transfer run, and the small number of participants. Conclusions This small sample study suggests the possible efficacy of DLPFC activity regulation training for the treatment of MDD. As a next step, a sham-controlled randomized clinical trial is needed to confirm the antidepressive effect of left DLPFC neurofeedback.
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Affiliation(s)
- Masahiro Takamura
- Brain, Mind and KANSEI Sciences Research Center, Hiroshima University, Hiroshima, Japan
| | - Yasumasa Okamoto
- Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Chiyo Shibasaki
- Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Atsuo Yoshino
- Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Go Okada
- Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Naho Ichikawa
- Brain, Mind and KANSEI Sciences Research Center, Hiroshima University, Hiroshima, Japan
| | - Shigeto Yamawaki
- Brain, Mind and KANSEI Sciences Research Center, Hiroshima University, Hiroshima, Japan; Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
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Ros T, Enriquez-Geppert S, Zotev V, Young KD, Wood G, Whitfield-Gabrieli S, Wan F, Vuilleumier P, Vialatte F, Van De Ville D, Todder D, Surmeli T, Sulzer JS, Strehl U, Sterman MB, Steiner NJ, Sorger B, Soekadar SR, Sitaram R, Sherlin LH, Schönenberg M, Scharnowski F, Schabus M, Rubia K, Rosa A, Reiner M, Pineda JA, Paret C, Ossadtchi A, Nicholson AA, Nan W, Minguez J, Micoulaud-Franchi JA, Mehler DMA, Lührs M, Lubar J, Lotte F, Linden DEJ, Lewis-Peacock JA, Lebedev MA, Lanius RA, Kübler A, Kranczioch C, Koush Y, Konicar L, Kohl SH, Kober SE, Klados MA, Jeunet C, Janssen TWP, Huster RJ, Hoedlmoser K, Hirshberg LM, Heunis S, Hendler T, Hampson M, Guggisberg AG, Guggenberger R, Gruzelier JH, Göbel RW, Gninenko N, Gharabaghi A, Frewen P, Fovet T, Fernández T, Escolano C, Ehlis AC, Drechsler R, Christopher deCharms R, Debener S, De Ridder D, Davelaar EJ, Congedo M, Cavazza M, Breteler MHM, Brandeis D, Bodurka J, Birbaumer N, Bazanova OM, Barth B, Bamidis PD, Auer T, Arns M, Thibault RT. Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist). Brain 2020; 143:1674-1685. [PMID: 32176800 PMCID: PMC7296848 DOI: 10.1093/brain/awaa009] [Citation(s) in RCA: 193] [Impact Index Per Article: 38.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Revised: 10/10/2019] [Accepted: 10/28/2020] [Indexed: 02/02/2023] Open
Abstract
Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.
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Affiliation(s)
- Tomas Ros
- Departments of Neuroscience and Psychiatry, University of Geneva; Campus Biotech, Geneva, Switzerland
| | - Stefanie Enriquez-Geppert
- Department of Clinical Neuropsychology, University of Groningen, Groningen, The Netherlands
- Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, Groningen, The Netherlands
| | - Vadim Zotev
- Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Kymberly D Young
- University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Guilherme Wood
- Institute of Psychology, University of Graz, Graz, Austria
| | - Susan Whitfield-Gabrieli
- Massachusetts Institute of Technology, Cambridge, MA, USA
- Northeastern University, Boston, MA, USA
| | - Feng Wan
- Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau, China
| | | | | | - Dimitri Van De Ville
- Institute of Bioengineering, Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne (EPFL); Campus Biotech, Geneva, Switzerland
| | - Doron Todder
- Faculty of Health, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- Beer-Sheva Mental Health Center, Israel Ministry of Health, Beer-Sheva, Israel
| | - Tanju Surmeli
- Living Health Center for Research and Education, Istanbul, Turkey
| | - James S Sulzer
- Department of Mechanical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Ute Strehl
- Institute for Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Maurice Barry Sterman
- Neurobiology and Biobehavioral Psychiatry, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Naomi J Steiner
- Boston University School of Medicine, Department of Pediatrics, Boston, MA, USA
| | - Bettina Sorger
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Surjo R Soekadar
- Clinical Neurotechnology Laboratory, Neuroscience Research Center (NWFZ), Department of Psychiatry and Psychotherapy (CCM), Charité - University Medicine Berlin, Berlin, Germany
| | - Ranganatha Sitaram
- Institute of Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Macul, Santiago, Chile
| | | | | | - Frank Scharnowski
- Department of Basic Psychological Research and Research Methods, Faculty of Psychology, University of Vienna, Vienna, Austria
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zürich, Zürich, Switzerland
| | - Manuel Schabus
- University of Salzburg, Centre for Cognitive Neuroscience and Department of Psychology, Salzburg, Austria
| | - Katya Rubia
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | | | - Miriam Reiner
- Technion, Israel Institute of Technology, Haifa, Israel
| | - Jaime A Pineda
- Cognitive Science Department, University of California, San Diego, CA, USA
| | - Christian Paret
- Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health Mannheim, Medical Faculty Mannheim/Heidelberg University, Germany
| | - Alexei Ossadtchi
- National Research University Higher School of Economics, Moscow, Russia
| | - Andrew A Nicholson
- Department of Basic Psychological Research and Research Methods, Faculty of Psychology, University of Vienna, Vienna, Austria
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zürich, Zürich, Switzerland
| | - Wenya Nan
- Department of Psychology, Shanghai Normal University, Shanghai, China
| | | | | | - David M A Mehler
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Michael Lührs
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Joel Lubar
- Department of Psychology, University of Tennessee, Knoxville, USA
| | - Fabien Lotte
- Inria Bordeaux Sud-Ouest/LaBRI University of Bordeaux - CNRS-Bordeaux INP, Bordeaux, France
| | - David E J Linden
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | | | - Mikhail A Lebedev
- Center for Bioelectric Interfaces of the Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
- Department of Information and Internet Technologies of Digital Health Institute; I.M. Sechenov First Moscow State Medical University, Moscow, Russia
- Duke Center for Neuroengineering, Duke University, Durham, NC, USA
| | - Ruth A Lanius
- Department of Psychiatry, Western University, London, Ontario, Canada
| | - Andrea Kübler
- Department of Psychology I, Psychological Intervention, Behavior Analysis and Regulation of Behavior, University of Würzburg
| | - Cornelia Kranczioch
- Neuropsychology Lab, Department of Psychology, University of Oldenburg, Oldenberg, Germany
| | - Yury Koush
- Magnetic Resonance Research Center (MRRC), Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Lilian Konicar
- Medical University of Vienna, Department of Child and Adolescent Psychiatry, Vienna, Austria
| | - Simon H Kohl
- JARA-Institute Molecular neuroscience and neuroimaging (INM-11), Jülich Research Centre, Jülich, Germany
| | | | - Manousos A Klados
- Department of Psychology, The University of Sheffield International Faculty, City College, Thessaloniki, Greece
| | - Camille Jeunet
- CLLE Lab, CNRS, Université Toulouse Jean Jaurès, Toulouse, France
| | - T W P Janssen
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Rene J Huster
- Multimodal imaging and Cognitive Control Lab, Department of Psychology, University of Olso, Norway
| | - Kerstin Hoedlmoser
- University of Salzburg, Centre for Cognitive Neuroscience and Department of Psychology, Salzburg, Austria
| | | | - Stephan Heunis
- Electrical Engineering Department, Eindhoven University of Technology, The Netherlands
| | - Talma Hendler
- Sagol Brain Institute, Wohl Institute for Advanced Imaging, Sourasky Medical Center, Tel Aviv, Israel
| | - Michelle Hampson
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Adrian G Guggisberg
- Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospital Geneva, Geneva, Switzerland
| | - Robert Guggenberger
- Division of Functional and Restorative Neurosurgery, University of Tübingen, Tübingen, Germany
| | - John H Gruzelier
- Department of Psychology, Goldsmiths, University of London, London, UK
| | - Rainer W Göbel
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Nicolas Gninenko
- Institute of Bioengineering, Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne (EPFL); Campus Biotech, Geneva, Switzerland
| | - Alireza Gharabaghi
- Division of Functional and Restorative Neurosurgery, University of Tübingen, Tübingen, Germany
| | - Paul Frewen
- Department of Psychiatry, Western University, London, Ontario, Canada
| | - Thomas Fovet
- Univ. Lille, INSERM U1172, CHU LILLE, Centre Lille Neuroscience & Cognition, Pôle de Psychiatrie, F-59000, Lille, France
| | - Thalía Fernández
- UNAM Institute of Neurobiology, National Autonomous University of Mexico, Juriquilla, Mexico
| | | | - Ann-Christine Ehlis
- Psychophysiology and Optical Imaging, Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Renate Drechsler
- Department of Child and Adolescent, Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zürich, Zürich, Switzerland
| | | | - Stefan Debener
- Neuropsychology Lab, Department of Psychology, University of Oldenburg, Oldenberg, Germany
| | - Dirk De Ridder
- Department of Surgery, Section of Neurosurgery, University of Otago, Dunedin, New Zealand
| | - Eddy J Davelaar
- Department of Psychological Sciences Birkbeck, University of London, Bloomsbury, London, UK
| | - Marco Congedo
- GIPSA-lab, CNRS, University Grenoble Alpes, Grenoble-INP, Grenoble, France
| | - Marc Cavazza
- School of Computing and Mathematical Sciences, University of Greenwich, London, UK
| | - Marinus H M Breteler
- Radboud University Nijmegen, Department of Clinical Psychology, Nijmegen, The Netherlands
| | - Daniel Brandeis
- Department of Child and Adolescent, Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zürich, Zürich, Switzerland
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Jerzy Bodurka
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Niels Birbaumer
- Institute for Medical Psychology and Behavioural Neurobiology, University of Tübingen, Tübingen, Germany
| | - Olga M Bazanova
- State Research Institute of Physiology and Basic Medicine, Novosibirsk, Russia
| | - Beatrix Barth
- Psychophysiology and Optical Imaging, Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | | | - Tibor Auer
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Martijn Arns
- Brainclinics Foundation, Research Institute Brainclinics, Nijmegen, The Netherlands
| | - Robert T Thibault
- School of Psychological Science, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
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Geissberger N, Tik M, Sladky R, Woletz M, Schuler AL, Willinger D, Windischberger C. Reproducibility of amygdala activation in facial emotion processing at 7T. Neuroimage 2020; 211:116585. [PMID: 31996330 DOI: 10.1016/j.neuroimage.2020.116585] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Revised: 11/24/2019] [Accepted: 01/23/2020] [Indexed: 01/10/2023] Open
Abstract
Despite its importance as the prime method for non-invasive assessment of human brain function, functional MRI (fMRI) was repeatedly challenged with regards to the validity of the fMRI-derived brain activation maps. Amygdala fMRI was particularly targeted, as the amygdala's anatomical position in the ventral brain combined with strong magnetic field inhomogeneities and proximity to large vessels pose considerable obstacles for robust activation mapping. In this high-resolution study performed at ultra-high field (7T) fMRI, we aimed at (1) investigating systematic replicability of amygdala group-level activation in response to an established emotion processing task by varying task instruction and acquisition parameters and (2) testing for intra- and intersession reliability. At group-level, our results show statistically significant activation in bilateral amygdala and fusiform gyrus for each of the runs acquired. In addition, while fusiform gyrus activations are consistent across runs and sessions, amygdala activation levels show habituation effects across runs. This amygdala habituation effect is replicated in a session repeated two weeks later. Varying task instruction between matching emotions and matching persons does not change amygdala activation strength. Also, comparing two acquisition protocols with repetition times of either 700 ms or 1400 ms did not result in statistically significant differences of activation levels. Regarding within-subject reliability of amygdala activation, despite considerable variance in individual habituation patterns, we report fair to good inter-session reliability for the first run and excellent reliability for averages over runs. We conclude that high-resolution fMRI at 7T allows for robust mapping of amygdala activation in a broad range of variations. Our results of amygdala 7T fMRI are suitable to inform methodology and may encourage future studies to continue using emotion discrimination paradigms in clinical and non-clinical applications.
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Affiliation(s)
- Nicole Geissberger
- MR Center of Excellence, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Austria
| | - Martin Tik
- MR Center of Excellence, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Austria
| | - Ronald Sladky
- MR Center of Excellence, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Austria
| | - Michael Woletz
- MR Center of Excellence, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Austria
| | - Anna-Lisa Schuler
- MR Center of Excellence, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Austria
| | - David Willinger
- MR Center of Excellence, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Austria
| | - Christian Windischberger
- MR Center of Excellence, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Austria.
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123
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Papoutsi M, Magerkurth J, Josephs O, Pépés SE, Ibitoye T, Reilmann R, Hunt N, Payne E, Weiskopf N, Langbehn D, Rees G, Tabrizi SJ. Activity or connectivity? A randomized controlled feasibility study evaluating neurofeedback training in Huntington's disease. Brain Commun 2020; 2:fcaa049. [PMID: 32954301 PMCID: PMC7425518 DOI: 10.1093/braincomms/fcaa049] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 02/11/2020] [Accepted: 03/27/2020] [Indexed: 12/20/2022] Open
Abstract
Non-invasive methods, such as neurofeedback training, could support cognitive symptom management in Huntington’s disease by targeting brain regions whose function is impaired. The aim of our single-blind, sham-controlled study was to collect rigorous evidence regarding the feasibility of neurofeedback training in Huntington’s disease by examining two different methods, activity and connectivity real-time functional MRI neurofeedback training. Thirty-two Huntington’s disease gene-carriers completed 16 runs of neurofeedback training, using an optimized real-time functional MRI protocol. Participants were randomized into four groups, two treatment groups, one receiving neurofeedback derived from the activity of the supplementary motor area, and another receiving neurofeedback based on the correlation of supplementary motor area and left striatum activity (connectivity neurofeedback training), and two sham control groups, matched to each of the treatment groups. We examined differences between the groups during neurofeedback training sessions and after training at follow-up sessions. Transfer of training was measured by measuring the participants’ ability to upregulate neurofeedback training target levels without feedback (near transfer), as well as by examining change in objective, a priori defined, behavioural measures of cognitive and psychomotor function (far transfer) before and at 2 months after training. We found that the treatment group had significantly higher neurofeedback training target levels during the training sessions compared to the control group. However, we did not find robust evidence of better transfer in the treatment group compared to controls, or a difference between the two neurofeedback training methods. We also did not find evidence in support of a relationship between change in cognitive and psychomotor function and learning success. We conclude that although there is evidence that neurofeedback training can be used to guide participants to regulate the activity and connectivity of specific regions in the brain, evidence regarding transfer of learning and clinical benefit was not robust.
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Affiliation(s)
- Marina Papoutsi
- UCL Huntington’s Disease Centre, Queen Square Institute of Neurology, University College London, London WC1B 5EH, UK
- Correspondence to: Marina Papoutsi, PhD UCL Huntington’s Disease Centre, Queen Square Institute of Neurology University College London, Russell Square House, 10–12 Russell Square London WC1B 5EH, UK E-mail:
| | - Joerg Magerkurth
- Birkbeck-UCL Centre for Neuroimaging, University College London, London WC1H 0AP, UK
| | - Oliver Josephs
- Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK
| | - Sophia E Pépés
- University of Oxford, Harris Manchester College, Oxford OX1 3TD, UK
| | - Temi Ibitoye
- UCL Huntington’s Disease Centre, Queen Square Institute of Neurology, University College London, London WC1B 5EH, UK
| | - Ralf Reilmann
- George Huntington Institute, 48149 Münster, Germany
- Department of Radiology, University of Muenster, 48149 Münster, Germany
- Section for Neurodegeneration and Hertie Institute for Clinical Brain Research, University of Tuebingen, 72076 Tübingen, Germany
| | - Nigel Hunt
- Eastman Dental Institute, University College London, London WC1X 8LD, UK
| | - Edwin Payne
- Eastman Dental Institute, University College London, London WC1X 8LD, UK
| | - Nikolaus Weiskopf
- Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK
- Max Planck Institute for Human Cognitive and Brain Sciences, D-04103 Leipzig, Germany
| | - Douglas Langbehn
- Carver College of Medicine, University of Iowa, Iowa City, IA 52242, USA
| | - Geraint Rees
- Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK
- Institute of Cognitive Neuroscience, University College London, London WC1N 3AZ, UK
| | - Sarah J Tabrizi
- UCL Huntington’s Disease Centre, Queen Square Institute of Neurology, University College London, London WC1B 5EH, UK
- UK Dementia Research Institute at University College London, London WC1E 6BT, UK
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Voon V, Grodin E, Mandali A, Morris L, Doñamayor N, Weidacker K, Kwako L, Goldman D, Koob GF, Momenan R. Addictions NeuroImaging Assessment (ANIA): Towards an integrative framework for alcohol use disorder. Neurosci Biobehav Rev 2020; 113:492-506. [PMID: 32298710 DOI: 10.1016/j.neubiorev.2020.04.004] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 03/30/2020] [Accepted: 04/05/2020] [Indexed: 02/08/2023]
Abstract
Alcohol misuse and addiction are major international public health issues. Addiction can be characterized as a disorder of aberrant neurocircuitry interacting with environmental, genetic and social factors. Neuroimaging in alcohol misuse can thus provide a critical window into underlying neural mechanisms, highlighting possible treatment targets and acting as clinical biomarkers for predicting risk and treatment outcomes. This neuroimaging review on alcohol misuse in humans follows the Addictions Neuroclinical Assessment (ANA) that proposes incorporating three functional neuroscience domains integral to the neurocircuitry of addiction: incentive salience and habits, negative emotional states, and executive function within the context of the addiction cycle. Here we review and integrate multiple imaging modalities focusing on underlying cognitive processes such as reward anticipation, negative emotionality, cue reactivity, impulsivity, compulsivity and executive function. We highlight limitations in the literature and propose a model forward in the use of neuroimaging as a tool to understanding underlying mechanisms and potential clinical applicability for phenotyping of heterogeneity and predicting risk and treatment outcomes.
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Affiliation(s)
- Valerie Voon
- Department of Psychiatry, University of Cambridge, Cambridge, UK; Behavioural and Clinical Neurosciences Institute, Cambridge, UK; Cambridgeshire and Peterborough NHS Trust, Cambridge, UK.
| | - Erica Grodin
- Clinical NeuroImaging Research Core, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, UK
| | - Alekhya Mandali
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Laurel Morris
- Behavioural and Clinical Neurosciences Institute, Cambridge, UK; Department of Psychology, University of Cambridge, Cambridge, UK
| | - Nuria Doñamayor
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | | | - Laura Kwako
- National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, UK
| | - David Goldman
- National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, UK
| | - George F Koob
- National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, UK
| | - Reza Momenan
- Clinical NeuroImaging Research Core, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, UK
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125
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Shiyam Sundar LK, Baajour S, Beyer T, Lanzenberger R, Traub-Weidinger T, Rausch I, Pataraia E, Hahn A, Rischka L, Hienert M, Klebermass EM, Muzik O. Fully Integrated PET/MR Imaging for the Assessment of the Relationship Between Functional Connectivity and Glucose Metabolic Rate. Front Neurosci 2020; 14:252. [PMID: 32269510 PMCID: PMC7111429 DOI: 10.3389/fnins.2020.00252] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Accepted: 03/06/2020] [Indexed: 01/06/2023] Open
Abstract
In the past, determination of absolute values of cerebral metabolic rate of glucose (CMRGlc) in clinical routine was rarely carried out due to the invasive nature of arterial sampling. With the advent of combined PET/MR imaging technology, CMRGlc values can be obtained non-invasively, thereby providing the opportunity to take advantage of fully quantitative data in clinical routine. However, CMRGlc values display high physiological variability, presumably due to fluctuations in the intrinsic activity of the brain at rest. To reduce CMRGlc variability associated with these fluctuations, the objective of this study was to determine whether functional connectivity measures derived from resting-state fMRI (rs-fMRI) could be used to correct for these fluctuations in intrinsic brain activity. METHODS We studied 10 healthy volunteers who underwent a test-retest dynamic [18F]FDG-PET study using a fully integrated PET/MR system (Siemens Biograph mMR). To validate the non-invasive derivation of an image-derived input function based on combined analysis of PET and MR data, arterial blood samples were obtained. Using the arterial input function (AIF), parametric images representing CMRGlc were determined using the Patlak graphical approach. Both directed functional connectivity (dFC) and undirected functional connectivity (uFC) were determined between nodes in six major networks (Default mode network, Salience, L/R Executive, Attention, and Sensory-motor network) using either a bivariate-correlation (R coefficient) or a Multi-Variate AutoRegressive (MVAR) model. In addition, the performance of a regional connectivity measure, the fractional amplitude of low frequency fluctuations (fALFF), was also investigated. RESULTS The average intrasubject variability for CMRGlc values between test and retest was determined as (14 ±8%) with an average inter-subject variability of 25% at test and 15% at retest. The average CMRGlc value (umol/100 g/min) across all networks was 39 ±10 at test and increased slightly to 43 ±6 at retest. The R, MVAR and fALFF coefficients showed relatively large test-retest variability in comparison to the inter-subjects variability, resulting in poor reliability (intraclass correlation in the range of 0.11-0.65). More importantly, no significant relationship was found between the R coefficients (for uFC), MVAR coefficients (for dFC) or fALFF and corresponding CMRGlc values for any of the six major networks. DISCUSSION Measurement of functional connectivity within established brain networks did not provide a means to decrease the inter- or intrasubject variability of CMRGlc values. As such, our results indicate that connectivity measured derived from rs-fMRI acquired contemporaneously with PET imaging are not suited for correction of CMRGlc variability associated with intrinsic fluctuations of resting-state brain activity. Thus, given the observed substantial inter- and intrasubject variability of CMRGlc values, the relevance of absolute quantification for clinical routine is presently uncertain.
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Affiliation(s)
- Lalith Kumar Shiyam Sundar
- QIMP Team, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Shahira Baajour
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Thomas Beyer
- QIMP Team, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Tatjana Traub-Weidinger
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Ivo Rausch
- QIMP Team, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | | | - Andreas Hahn
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Lucas Rischka
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Marius Hienert
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Eva-Maria Klebermass
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Otto Muzik
- Department of Pediatrics, Wayne State University School of Medicine, Detroit, MI, United States
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Misaki M, Tsuchiyagaito A, Al Zoubi O, Paulus M, Bodurka J. Connectome-wide search for functional connectivity locus associated with pathological rumination as a target for real-time fMRI neurofeedback intervention. Neuroimage Clin 2020; 26:102244. [PMID: 32193171 PMCID: PMC7082218 DOI: 10.1016/j.nicl.2020.102244] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Revised: 02/28/2020] [Accepted: 03/11/2020] [Indexed: 02/08/2023]
Abstract
Real-time fMRI neurofeedback (rtfMRI-nf) enables noninvasive targeted intervention in brain activation with high spatial specificity. To achieve this promise of rtfMRI-nf, we introduced and demonstrated a data-driven framework to design a rtfMRI-nf intervention through the discovery of precise target location associated with clinical symptoms and neurofeedback signal optimization. Specifically, we identified the functional connectivity locus associated with rumination symptoms, utilizing a connectome-wide search in resting-state fMRI data from a large cohort of mood and anxiety disorder individuals (N = 223) and healthy controls (N = 45). Then, we performed a rtfMRI simulation analysis to optimize the online functional connectivity neurofeedback signal for the identified functional connectivity. The connectome-wide search was performed in the medial prefrontal cortex and the posterior cingulate cortex/precuneus brain regions to identify the precise location of the functional connectivity associated with rumination severity as measured by the ruminative response style (RRS) scale. The analysis found that the functional connectivity between the loci in the precuneus (-6, -54, 48 mm in MNI) and the right temporo-parietal junction (RTPJ; 49, -49, 23 mm) was positively correlated with RRS scores (depressive, p < 0.001; brooding, p < 0.001; reflective, p = 0.002) in the mood and anxiety disorder group. We then performed a rtfMRI processing simulation to optimize the online computation of the precuneus-RTPJ connectivity. We determined that the two-point method without a control region was appropriate as a functional connectivity neurofeedback signal with less dependence on signal history and its accommodation of head motion. The present study offers a discovery framework for the precise location of functional connectivity targets for rtfMRI-nf intervention, which could help directly translate neuroimaging findings into clinical rtfMRI-nf interventions.
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Affiliation(s)
- Masaya Misaki
- Laureate Institute for Brain Research, 6655 South Yale Avenue, Tulsa, OK 74136, United States.
| | - Aki Tsuchiyagaito
- Laureate Institute for Brain Research, 6655 South Yale Avenue, Tulsa, OK 74136, United States; Japan Society for the Promotion of Science, Tokyo, Japan
| | - Obada Al Zoubi
- Laureate Institute for Brain Research, 6655 South Yale Avenue, Tulsa, OK 74136, United States; Department of Electrical and Computer Engineering, University of Oklahoma, Tulsa, Oklahoma, United States
| | - Martin Paulus
- Laureate Institute for Brain Research, 6655 South Yale Avenue, Tulsa, OK 74136, United States
| | - Jerzy Bodurka
- Laureate Institute for Brain Research, 6655 South Yale Avenue, Tulsa, OK 74136, United States; Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States.
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Bu J, Young KD, Hong W, Ma R, Song H, Wang Y, Zhang W, Hampson M, Hendler T, Zhang X. Effect of deactivation of activity patterns related to smoking cue reactivity on nicotine addiction. Brain 2020; 142:1827-1841. [PMID: 31135053 DOI: 10.1093/brain/awz114] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Revised: 01/24/2019] [Accepted: 02/24/2019] [Indexed: 02/04/2023] Open
Abstract
With approximately 75% of smokers resuming cigarette smoking after using the Gold Standard Programme for smoking cessation, investigation into novel therapeutic approaches is warranted. Typically, smoking cue reactivity is crucial for smoking behaviour. Here we developed a novel closed-loop, smoking cue reactivity patterns EEG-based neurofeedback protocol and evaluated its therapeutic efficacy on nicotine addiction. During an evoked smoking cue reactivity task participants' brain activity patterns corresponding to smoking cues were obtained with multivariate pattern analysis of all EEG channels data, then during neurofeedback the EEG activity patterns of smoking cue reactivity were continuously deactivated with adaptive closed-loop training. In a double-blind, placebo-controlled, randomized clinical trial, 60 nicotine-dependent participants were assigned to receive two neurofeedback training sessions (∼1 h/session) either from their own brain (n = 30, real-feedback group) or from the brain activity pattern of a matched participant (n = 30, yoked-feedback group). Cigarette craving and craving-related P300 were assessed at pre-neurofeedback and post-neurofeedback. The number of cigarettes smoked per day was assessed at baseline, 1 week, 1 month, and 4 months following the final neurofeedback visit. In the real-feedback group, participants successfully deactivated EEG activity patterns of smoking cue reactivity. The real-feedback group showed significant decrease in cigarette craving and craving-related P300 amplitudes compared with the yoked-feedback group. The rates of cigarettes smoked per day at 1 week, 1 month and 4 months follow-up decreased 30.6%, 38.2%, and 27.4% relative to baseline in the real-feedback group, compared to decreases of 14.0%, 13.7%, and 5.9% in the yoked-feedback group. The neurofeedback effects on craving change and smoking amount at the 4-month follow-up were further predicted by neural markers at pre-neurofeedback. This novel neurofeedback training approach produced significant short-term and long-term effects on cigarette craving and smoking behaviour, suggesting the neurofeedback protocol described herein is a promising brain-based tool for treating addiction.
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Affiliation(s)
- Junjie Bu
- Hefei National Laboratory for Physical Sciences at the Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, China
| | - Kymberly D Young
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, USA
| | - Wei Hong
- Hefei National Laboratory for Physical Sciences at the Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, China
| | - Ru Ma
- Hefei National Laboratory for Physical Sciences at the Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, China
| | - Hongwen Song
- School of Humanities and Social Science, University of Science and Technology of China, Hefei, China
| | - Ying Wang
- Hefei National Laboratory for Physical Sciences at the Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, China
| | - Wei Zhang
- Hefei National Laboratory for Physical Sciences at the Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, China
| | - Michelle Hampson
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Talma Hendler
- Functional Brain Center, Tel-Aviv University, Tel-Aviv, Israel
| | - Xiaochu Zhang
- Hefei National Laboratory for Physical Sciences at the Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, China.,School of Humanities and Social Science, University of Science and Technology of China, Hefei, China.,Hefei Medical Research Center on Alcohol Addiction, Anhui Mental Health Center, Hefei, China.,Academy of Psychology and Behaviour, Tianjin Normal University, Tianjin, China
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128
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Nicholson AA, Ros T, Jetly R, Lanius RA. Regulating posttraumatic stress disorder symptoms with neurofeedback: Regaining control of the mind. JOURNAL OF MILITARY, VETERAN AND FAMILY HEALTH 2020. [DOI: 10.3138/jmvfh.2019-0032] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Neurofeedback is emerging as a psychophysiological treatment where self-regulation is achieved through online feedback of neural states. Novel personalized medicine approaches are particularly important for the treatment of posttraumatic stress disorder (PTSD), as symptom presentation of the disorder, as well as responses to treatment, are highly heterogeneous. Learning to achieve control of specific neural substrates through neurofeedback has been shown to display therapeutic evidence in patients with a wide variety of psychiatric disorders, including PTSD. This article outlines the neural mechanisms underlying neurofeedback and examines converging evidence for the efficacy of neurofeedback as an adjunctive treatment for PTSD via both electroencephalography (EEG) and real-time functional magnetic resonance imaging (fMRI) modalities. Further, implications for the treatment of PTSD via neurofeedback in the military member and Veteran population is examined.
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Affiliation(s)
- Andrew A. Nicholson
- Department of Psychological Research and Research Methods, University of Vienna, Vienna, Austria
- Neurology and Imaging of Cognition Lab, University of Geneva, Geneva, Switzerland
- Canadian Forces Health Services Group, Department of National Defence, Government of Canada, Ottawa
- Department of Psychology, Western University, London, Ontario
| | - Tomas Ros
- Department of Psychological Research and Research Methods, University of Vienna, Vienna, Austria
- Neurology and Imaging of Cognition Lab, University of Geneva, Geneva, Switzerland
- Canadian Forces Health Services Group, Department of National Defence, Government of Canada, Ottawa
- Department of Psychology, Western University, London, Ontario
| | - Rakesh Jetly
- Department of Psychological Research and Research Methods, University of Vienna, Vienna, Austria
- Neurology and Imaging of Cognition Lab, University of Geneva, Geneva, Switzerland
- Canadian Forces Health Services Group, Department of National Defence, Government of Canada, Ottawa
- Department of Psychology, Western University, London, Ontario
| | - Ruth A. Lanius
- Department of Psychological Research and Research Methods, University of Vienna, Vienna, Austria
- Neurology and Imaging of Cognition Lab, University of Geneva, Geneva, Switzerland
- Canadian Forces Health Services Group, Department of National Defence, Government of Canada, Ottawa
- Department of Psychology, Western University, London, Ontario
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129
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Fede SJ, Dean SF, Manuweera T, Momenan R. A Guide to Literature Informed Decisions in the Design of Real Time fMRI Neurofeedback Studies: A Systematic Review. Front Hum Neurosci 2020; 14:60. [PMID: 32161529 PMCID: PMC7052377 DOI: 10.3389/fnhum.2020.00060] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 02/07/2020] [Indexed: 11/26/2022] Open
Abstract
Background: Although biofeedback using electrophysiology has been explored extensively, the approach of using neurofeedback corresponding to hemodynamic response is a relatively young field. Real time functional magnetic resonance imaging-based neurofeedback (rt-fMRI-NF) uses sensory feedback to operantly reinforce patterns of neural response. It can be used, for example, to alter visual perception, increase brain connectivity, and reduce depression symptoms. Within recent years, interest in rt-fMRI-NF in both research and clinical contexts has expanded considerably. As such, building a consensus regarding best practices is of great value. Objective: This systematic review is designed to describe and evaluate the variations in methodology used in previous rt-fMRI-NF studies to provide recommendations for rt-fMRI-NF study designs that are mostly likely to elicit reproducible and consistent effects of neurofeedback. Methods: We conducted a database search for fMRI neurofeedback papers published prior to September 26th, 2019. Of 558 studies identified, 146 met criteria for inclusion. The following information was collected from each study: sample size and type, task used, neurofeedback calculation, regulation procedure, feedback, whether feedback was explicitly related to changing brain activity, feedback timing, control group for active neurofeedback, how many runs and sessions of neurofeedback, if a follow-up was conducted, and the results of neurofeedback training. Results: rt-fMRI-NF is typically upregulation practice based on hemodynamic response from a specific region of the brain presented using a continually updating thermometer display. Most rt-fMRI-NF studies are conducted in healthy samples and half evaluate its effect on immediate changes in behavior or affect. The most popular control group method is to provide sham signal from another region; however, many studies do not compare use a comparison group. Conclusions: We make several suggestions for designs of future rt-fMRI-NF studies. Researchers should use feedback calculation methods that consider neural response across regions (i.e., SVM or connectivity), which should be conveyed as intermittent, auditory feedback. Participants should be given explicit instructions and should be assessed on individual differences. Future rt-fMRI-NF studies should use clinical samples; effectiveness of rt-fMRI-NF should be evaluated on clinical/behavioral outcomes at follow-up time points in comparison to both a sham and no feedback control group.
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Affiliation(s)
| | | | | | - Reza Momenan
- Clinical NeuroImaging Research Core, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, United States
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130
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Mayeli A, Misaki M, Zotev V, Tsuchiyagaito A, Al Zoubi O, Phillips R, Smith J, Stewart JL, Refai H, Paulus MP, Bodurka J. Self-regulation of ventromedial prefrontal cortex activation using real-time fMRI neurofeedback-Influence of default mode network. Hum Brain Mapp 2020; 41:342-352. [PMID: 31633257 PMCID: PMC7267960 DOI: 10.1002/hbm.24805] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Revised: 09/12/2019] [Accepted: 09/12/2019] [Indexed: 02/03/2023] Open
Abstract
The ventromedial prefrontal cortex (vmPFC) is involved in regulation of negative emotion and decision-making, emotional and behavioral control, and active resilient coping. This pilot study examined the feasibility of training healthy subjects (n = 27) to self-regulate the vmPFC activity using a real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf). Participants in the experimental group (EG, n = 18) were provided with an ongoing vmPFC hemodynamic activity (rtfMRI-nf signal represented as variable-height bar). Individuals were instructed to raise the bar by self-relevant value-based thinking. Participants in the control group (CG, n = 9) performed the same task; however, they were provided with computer-generated sham neurofeedback signal. Results demonstrate that (a) both the CG and the EG show a higher vmPFC fMRI signal at the baseline than during neurofeedback training; (b) no significant positive training effect was seen in the vmPFC across neurofeedback runs; however, the medial prefrontal cortex, middle temporal gyri, inferior frontal gyri, and precuneus showed significant decreasing trends across the training runs only for the EG; (c) the vmPFC rtfMRI-nf signal associated with the fMRI signal across the default mode network (DMN). These findings suggest that it may be difficult to modulate a single DMN region without affecting other DMN regions. Observed decreased vmPFC activity during the neurofeedback task could be due to interference from the fMRI signal within other DMN network regions, as well as interaction with task-positive networks. Even though participants in the EG did not show significant positive increase in the vmPFC activity among neurofeedback runs, they were able to learn to accommodate the demand of self-regulation task to maintain the vmPFC activity with the help of a neurofeedback signal.
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Affiliation(s)
- Ahmad Mayeli
- Laureate Institute for Brain ResearchTulsaOklahoma
- Electrical and Computer Engineering DepartmentUniversity of OklahomaTulsaOklahoma
| | | | - Vadim Zotev
- Laureate Institute for Brain ResearchTulsaOklahoma
| | - Aki Tsuchiyagaito
- Laureate Institute for Brain ResearchTulsaOklahoma
- Japan Society for the Promotion ScienceTokyoJapan
- Research Center for Child DevelopmentChiba UniversityChibaJapan
| | - Obada Al Zoubi
- Laureate Institute for Brain ResearchTulsaOklahoma
- Electrical and Computer Engineering DepartmentUniversity of OklahomaTulsaOklahoma
| | | | - Jared Smith
- Laureate Institute for Brain ResearchTulsaOklahoma
| | | | - Hazem Refai
- Electrical and Computer Engineering DepartmentUniversity of OklahomaTulsaOklahoma
| | | | - Jerzy Bodurka
- Laureate Institute for Brain ResearchTulsaOklahoma
- Stephenson School of Biomedical EngineeringUniversity of OklahomaTulsaOklahoma
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131
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Abstract
Brain-computer interfaces (BCIs) based on functional magnetic resonance imaging (fMRI) provide an important complement to other noninvasive BCIs. While fMRI has several disadvantages (being nonportable, methodologically challenging, costly, and noisy), it is the only method providing high spatial resolution whole-brain coverage of brain activation. These properties allow relating mental activities to specific brain regions and networks providing a transparent scheme for BCI users to encode information and for real-time fMRI BCI systems to decode the intents of the user. Various mental activities have been used successfully in fMRI BCIs so far that can be classified into the four categories: (a) higher-order cognitive tasks (e.g., mental calculation), (b) covert language-related tasks (e.g., mental speech and mental singing), (c) imagery tasks (motor, visual, auditory, tactile, and emotion imagery), and (d) selective attention tasks (visual, auditory, and tactile attention). While the ultimate spatial and temporal resolution of fMRI BCIs is limited by the physiologic properties of the hemodynamic response, technical and analytical advances will likely lead to substantially improved fMRI BCIs in the future using, for example, decoding of imagined letter shapes at 7T as the basis for more "natural" communication BCIs.
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Affiliation(s)
- Bettina Sorger
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands; Maastricht Brain Imaging Center (M-BIC), Maastricht, The Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands; Maastricht Brain Imaging Center (M-BIC), Maastricht, The Netherlands.
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132
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Affiliation(s)
- Michelle Hampson
- Department of Radiology and Biomedical Imaging, Department of Psychiatry, and the Child Study Center, Yale University School of Medicine, New Haven, CT, USA.
| | - Sergio Ruiz
- Department of Psychiatry, Medicine School, and Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile.
| | - Junichi Ushiba
- Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, Japan.
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133
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Scheele D, Zimbal S, Feinstein JS, Delis A, Neumann C, Mielacher C, Philipsen A, Hurlemann R. Treatment-Resistant Depression and Ketamine Response in a Patient With Bilateral Amygdala Damage. Am J Psychiatry 2019; 176:982-986. [PMID: 31787017 DOI: 10.1176/appi.ajp.2019.18101219] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Dirk Scheele
- Division of Medical Psychology (Scheele, Zimbal, Mielacher, Hurlemann), Department of Anesthesiology (Delis, Neumann), and Department of Psychiatry (Philipsen, Hurlemann), University Hospital, Bonn, Germany; Laureate Institute for Brain Research, Tulsa, Okla. (Feinstein); and Department of Psychiatry, University of Oldenburg Medical Campus, Bad Zwischenahn, Germany (Hurlemann)
| | - Sophia Zimbal
- Division of Medical Psychology (Scheele, Zimbal, Mielacher, Hurlemann), Department of Anesthesiology (Delis, Neumann), and Department of Psychiatry (Philipsen, Hurlemann), University Hospital, Bonn, Germany; Laureate Institute for Brain Research, Tulsa, Okla. (Feinstein); and Department of Psychiatry, University of Oldenburg Medical Campus, Bad Zwischenahn, Germany (Hurlemann)
| | - Justin S Feinstein
- Division of Medical Psychology (Scheele, Zimbal, Mielacher, Hurlemann), Department of Anesthesiology (Delis, Neumann), and Department of Psychiatry (Philipsen, Hurlemann), University Hospital, Bonn, Germany; Laureate Institute for Brain Research, Tulsa, Okla. (Feinstein); and Department of Psychiatry, University of Oldenburg Medical Campus, Bad Zwischenahn, Germany (Hurlemann)
| | - Achilles Delis
- Division of Medical Psychology (Scheele, Zimbal, Mielacher, Hurlemann), Department of Anesthesiology (Delis, Neumann), and Department of Psychiatry (Philipsen, Hurlemann), University Hospital, Bonn, Germany; Laureate Institute for Brain Research, Tulsa, Okla. (Feinstein); and Department of Psychiatry, University of Oldenburg Medical Campus, Bad Zwischenahn, Germany (Hurlemann)
| | - Claudia Neumann
- Division of Medical Psychology (Scheele, Zimbal, Mielacher, Hurlemann), Department of Anesthesiology (Delis, Neumann), and Department of Psychiatry (Philipsen, Hurlemann), University Hospital, Bonn, Germany; Laureate Institute for Brain Research, Tulsa, Okla. (Feinstein); and Department of Psychiatry, University of Oldenburg Medical Campus, Bad Zwischenahn, Germany (Hurlemann)
| | - Clemens Mielacher
- Division of Medical Psychology (Scheele, Zimbal, Mielacher, Hurlemann), Department of Anesthesiology (Delis, Neumann), and Department of Psychiatry (Philipsen, Hurlemann), University Hospital, Bonn, Germany; Laureate Institute for Brain Research, Tulsa, Okla. (Feinstein); and Department of Psychiatry, University of Oldenburg Medical Campus, Bad Zwischenahn, Germany (Hurlemann)
| | - Alexandra Philipsen
- Division of Medical Psychology (Scheele, Zimbal, Mielacher, Hurlemann), Department of Anesthesiology (Delis, Neumann), and Department of Psychiatry (Philipsen, Hurlemann), University Hospital, Bonn, Germany; Laureate Institute for Brain Research, Tulsa, Okla. (Feinstein); and Department of Psychiatry, University of Oldenburg Medical Campus, Bad Zwischenahn, Germany (Hurlemann)
| | - René Hurlemann
- Division of Medical Psychology (Scheele, Zimbal, Mielacher, Hurlemann), Department of Anesthesiology (Delis, Neumann), and Department of Psychiatry (Philipsen, Hurlemann), University Hospital, Bonn, Germany; Laureate Institute for Brain Research, Tulsa, Okla. (Feinstein); and Department of Psychiatry, University of Oldenburg Medical Campus, Bad Zwischenahn, Germany (Hurlemann)
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134
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Dai L, Zhou H, Xu X, Zuo Z. Brain structural and functional changes in patients with major depressive disorder: a literature review. PeerJ 2019; 7:e8170. [PMID: 31803543 PMCID: PMC6886485 DOI: 10.7717/peerj.8170] [Citation(s) in RCA: 63] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2019] [Accepted: 11/06/2019] [Indexed: 12/22/2022] Open
Abstract
Depression is a mental disorder characterized by low mood and anhedonia that involves abnormalities in multiple brain regions and networks. Epidemiological studies demonstrated that depression has become one of the most important diseases affecting human health and longevity. The pathogenesis of the disease has not been fully elucidated. The clinical effect of treatment is not satisfactory in many cases. Neuroimaging studies have provided rich and valuable evidence that psychological symptoms and behavioral deficits in patients with depression are closely related to structural and functional abnormalities in specific areas of the brain. There were morphological differences in several brain regions, including the frontal lobe, temporal lobe, and limbic system, in people with depression compared to healthy people. In addition, people with depression also had abnormal functional connectivity to the default mode network, the central executive network, and the salience network. These findings provide an opportunity to re-understand the biological mechanisms of depression. In the future, magnetic resonance imaging (MRI) may serve as an important auxiliary tool for psychiatrists in the process of early and accurate diagnosis of depression and finding the appropriate treatment target for each patient to optimize clinical response.
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Affiliation(s)
- Lisong Dai
- Department of Radiology, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongmei Zhou
- Department of Radiology, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiangyang Xu
- Department of Radiology, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhentao Zuo
- State Key Laboratory of Brain and Cognitive Science, Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.,Sino-Danish College, University of Chinese Academy of Sciences, Beijing, China.,Center for Excellence in Brain and Science and Intelligence Technology, Chinese Academy of Sciences, Beijing, China
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135
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Skottnik L, Linden DEJ. Mental Imagery and Brain Regulation-New Links Between Psychotherapy and Neuroscience. Front Psychiatry 2019; 10:779. [PMID: 31736799 PMCID: PMC6831624 DOI: 10.3389/fpsyt.2019.00779] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Accepted: 09/30/2019] [Indexed: 01/23/2023] Open
Abstract
Mental imagery is a promising tool and mechanism of psychological interventions, particularly for mood and anxiety disorders. In parallel developments, neuromodulation techniques have shown promise as add-on therapies in psychiatry, particularly non-invasive brain stimulation for depression. However, these techniques have not yet been combined in a systematic manner. One novel technology that may be able to achieve this is neurofeedback, which entails the self-regulation of activation in specific brain areas or networks (or the self-modulation of distributed activation patterns) by the patients themselves, through real-time feedback of brain activation (for example, from functional magnetic resonance imaging). One of the key mechanisms by which patients learn such self-regulation is mental imagery. Here, we will first review the main mental imagery approaches in psychotherapy and the implicated brain networks. We will then discuss how these networks can be targeted with neuromodulation (neurofeedback or non-invasive or invasive brain stimulation). We will review the clinical evidence for neurofeedback and discuss possible ways of enhancing it through systematic combination with psychological interventions, with a focus on depression, anxiety disorders, and addiction. The overarching aim of this perspective paper will be to open a debate on new ways of developing neuropsychotherapies.
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Affiliation(s)
| | - David E. J. Linden
- School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
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136
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Tan BL, Norhaizan ME. Effect of High-Fat Diets on Oxidative Stress, Cellular Inflammatory Response and Cognitive Function. Nutrients 2019; 11:nu11112579. [PMID: 31731503 PMCID: PMC6893649 DOI: 10.3390/nu11112579] [Citation(s) in RCA: 280] [Impact Index Per Article: 46.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2019] [Revised: 10/16/2019] [Accepted: 10/21/2019] [Indexed: 12/20/2022] Open
Abstract
Cognitive dysfunction is linked to chronic low-grade inflammatory stress that contributes to cell-mediated immunity in creating an oxidative environment. Food is a vitally important energy source; it affects brain function and provides direct energy. Several studies have indicated that high-fat consumption causes overproduction of circulating free fatty acids and systemic inflammation. Immune cells, free fatty acids, and circulating cytokines reach the hypothalamus and initiate local inflammation through processes such as microglial proliferation. Therefore, the role of high-fat diet (HFD) in promoting oxidative stress and neurodegeneration is worthy of further discussion. Of particular interest in this article, we highlight the associations and molecular mechanisms of HFD in the modulation of inflammation and cognitive deficits. Taken together, a better understanding of the role of oxidative stress in cognitive impairment following HFD consumption would provide a useful approach for the prevention of cognitive dysfunction.
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Affiliation(s)
- Bee Ling Tan
- Department of Nutrition and Dietetics, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia;
| | - Mohd Esa Norhaizan
- Department of Nutrition and Dietetics, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia;
- Research Centre of Excellent, Nutrition and Non-Communicable Diseases (NNCD), Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
- Laboratory of Molecular Biomedicine, Institute of Bioscience, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
- Correspondence: ; Tel.: +603-8947-2427
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137
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Liu Y, Admon R, Mellem MS, Belleau EL, Kaiser RH, Clegg R, Beltzer M, Goer F, Vitaliano G, Ahammad P, Pizzagalli DA. Machine Learning Identifies Large-Scale Reward-Related Activity Modulated by Dopaminergic Enhancement in Major Depression. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2019; 5:163-172. [PMID: 31784354 DOI: 10.1016/j.bpsc.2019.10.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Revised: 09/30/2019] [Accepted: 10/01/2019] [Indexed: 12/24/2022]
Abstract
BACKGROUND Theoretical models have emphasized systems-level abnormalities in major depressive disorder (MDD). For unbiased yet rigorous evaluations of pathophysiological mechanisms underlying MDD, it is critically important to develop data-driven approaches that harness whole-brain data to classify MDD and evaluate possible normalizing effects of targeted interventions. Here, using an experimental therapeutics approach coupled with machine learning, we investigated the effect of a pharmacological challenge aiming to enhance dopaminergic signaling on whole-brain response to reward-related stimuli in MDD. METHODS Using a double-blind, placebo-controlled design, we analyzed functional magnetic resonance imaging data from 31 unmedicated MDD participants receiving a single dose of 50 mg amisulpride (MDDAmisulpride), 26 MDD participants receiving placebo (MDDPlacebo), and 28 healthy control subjects receiving placebo (HCPlacebo) recruited through two independent studies. An importance-guided machine learning technique for model selection was used on whole-brain functional magnetic resonance imaging data probing reward anticipation and consumption to identify features linked to MDD (MDDPlacebo vs. HCPlacebo) and dopaminergic enhancement (MDDAmisulpride vs. MDDPlacebo). RESULTS Highly predictive classification models emerged that distinguished MDDPlacebo from HCPlacebo (area under the curve = 0.87) and MDDPlacebo from MDDAmisulpride (area under the curve = 0.89). Although reward-related striatal activation and connectivity were among the most predictive features, the best truncated models based on whole-brain features were significantly better relative to models trained using striatal features only. CONCLUSIONS Results indicate that in MDD, enhanced dopaminergic signaling restores abnormal activation and connectivity in a widespread network of regions. These findings provide new insights into the pathophysiology of MDD and pharmacological mechanism of antidepressants at the system level in addressing reward processing deficits among depressed individuals.
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Affiliation(s)
- Yuelu Liu
- BlackThorn Therapeutics, San Francisco, California
| | - Roee Admon
- Department of Psychology, University of Haifa, Haifa, Israel
| | | | - Emily L Belleau
- McLean Hospital, Belmont, Massachusetts; Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - Roselinde H Kaiser
- Department of Psychology and Neuroscience, University of Colorado, Boulder, Colorado
| | | | | | | | - Gordana Vitaliano
- McLean Hospital, Belmont, Massachusetts; Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | | | - Diego A Pizzagalli
- McLean Hospital, Belmont, Massachusetts; Department of Psychiatry, Harvard Medical School, Boston, Massachusetts.
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138
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Misaki M, Phillips R, Zotev V, Wong CK, Wurfel BE, Krueger F, Feldner M, Bodurka J. Brain activity mediators of PTSD symptom reduction during real-time fMRI amygdala neurofeedback emotional training. Neuroimage Clin 2019; 24:102047. [PMID: 31711031 PMCID: PMC6849428 DOI: 10.1016/j.nicl.2019.102047] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Revised: 10/08/2019] [Accepted: 10/21/2019] [Indexed: 11/20/2022]
Abstract
Self-regulation of brain activation with real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf) is emerging as a promising treatment for psychiatric disorders. The association between the regulation and symptom reduction, however, has not been consistent, and the mechanisms underlying the symptom reduction remain poorly understood. The present study investigated brain activity mediators of the amygdala rtfMRI-nf training effect on combat veterans' PTSD symptom reduction. The training was designed to increase a neurofeedback signal either from the left amygdala (experimental group; EG) or from a control region not implicated in emotion regulation (control group; CG) during positive autobiographical memory recall. We employed a structural equation model mapping analysis to identify brain regions that mediated the effects of the rtfMRI-nf training on PTSD symptoms. Symptom reduction was mediated by low activation in the dorsomedial prefrontal cortex (DMPFC) and the middle cingulate cortex. There was a trend toward less activation in these regions for the EG compared to the CG. Low activation in the precuneus, the right superior parietal, the right insula, and the right cerebellum also mediated symptom reduction while their effects were moderated by the neurofeedback signal; a higher signal was linked to less effect on symptom reduction. This moderation was not specific to the EG. MDD comorbidity was associated with high DMPFC activation, which resulted in less effective regulation of the feedback signal. These results indicated that symptom reduction due to the neurofeedback training was not specifically mediated by the neurofeedback target activity, but broad regions were involved in the process.
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Affiliation(s)
- Masaya Misaki
- Laureate Institute for Brain Research, Tulsa, OK, United States
| | - Raquel Phillips
- Laureate Psychiatric Clinic and Hospital, Tulsa, OK, United States
| | - Vadim Zotev
- Laureate Institute for Brain Research, Tulsa, OK, United States
| | - Chung-Ki Wong
- Laureate Institute for Brain Research, Tulsa, OK, United States
| | - Brent E Wurfel
- Laureate Institute for Brain Research, Tulsa, OK, United States; Laureate Psychiatric Clinic and Hospital, Tulsa, OK, United States
| | - Frank Krueger
- Neuroscience Department, George Mason University, Fairfax, VA, United States
| | - Matthew Feldner
- Department of Psychological Science, University of Arkansas, Fayetteville, AR, United States
| | - Jerzy Bodurka
- Laureate Institute for Brain Research, Tulsa, OK, United States; Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States.
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139
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Mennen AC, Norman KA, Turk-Browne NB. Attentional bias in depression: understanding mechanisms to improve training and treatment. Curr Opin Psychol 2019; 29:266-273. [PMID: 31521030 PMCID: PMC6980447 DOI: 10.1016/j.copsyc.2019.07.036] [Citation(s) in RCA: 63] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Revised: 07/18/2019] [Accepted: 07/23/2019] [Indexed: 12/31/2022]
Abstract
One of the most common symptoms of depression is the tendency to attend to negative stimuli in the world and negative thoughts in mind. This symptom is especially nefarious because it is also a cause - biasing processing to negatively valenced information, thus worsening mood, and exacerbating the condition. Here we attempt to systematize the diverse body of recent research on the negative attentional bias from across cognitive and clinical psychology in order to identify recurring themes and devise potential mechanistic explanations. We leverage theoretical progress in our understanding of healthy attention systems in terms of internal versus external components. With this lens, we review approaches to training attention that might reduce the negative attentional bias, including behavioral interventions and real-time neurofeedback. Although extant findings are somewhat mixed, these approaches provide hope and clues for the next generation of treatments.
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Affiliation(s)
- Anne C Mennen
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, United States.
| | - Kenneth A Norman
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, United States; Department of Psychology, Princeton University, Princeton, NJ 08540, United States
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140
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Shanechi MM. Brain–machine interfaces from motor to mood. Nat Neurosci 2019; 22:1554-1564. [DOI: 10.1038/s41593-019-0488-y] [Citation(s) in RCA: 82] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2019] [Accepted: 08/06/2019] [Indexed: 12/22/2022]
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141
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Neurofeedback and neuroplasticity of visual self-processing in depressed and healthy adolescents: A preliminary study. Dev Cogn Neurosci 2019; 40:100707. [PMID: 31733523 PMCID: PMC6974905 DOI: 10.1016/j.dcn.2019.100707] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Revised: 08/23/2019] [Accepted: 08/29/2019] [Indexed: 12/28/2022] Open
Abstract
Adolescence is a neuroplastic period for self-processing and emotion regulation transformations, that if derailed, are linked to persistent depression. Neural mechanisms of adolescent self-processing and emotion regulation ought to be targeted via new treatments, given moderate effectiveness of current interventions. Thus, we implemented a novel neurofeedback protocol in adolescents to test the engagement of circuits sub-serving self-processing and emotion regulation. Methods Depressed (n = 34) and healthy (n = 19) adolescents underwent neurofeedback training using a novel task. They saw their happy face as a cue to recall positive memories and increased displayed amygdala and hippocampus activity. The control condition was counting-backwards while viewing another happy face. A self vs. other face recognition task was administered before and after neurofeedback training. Results Adolescents showed higher frontotemporal activity during neurofeedback and higher amygdala and hippocampus and hippocampi activity in time series and region of interest analyses respectively. Before neurofeedback there was higher saliency network engagement for self-face recognition, but that network engagement was lower after neurofeedback. Depressed youth exhibited higher fusiform, inferior parietal lobule and cuneus activity during neurofeedback, but controls appeared to increase amygdala and hippocampus activity faster compared to depressed adolescents. Conclusions Neurofeedback recruited frontotemporal cortices that support social cognition and emotion regulation. Amygdala and hippocampus engagement via neurofeedback appears to change limbic-frontotemporal networks during self-face recognition. A placebo group or condition and contrasting amygdala and hippocampus, hippocampi or right amygdala versus frontal loci of neurofeedback, e.g. dorsal anterior cingulate cortex, with longer duration of neurofeedback training will elucidate dosage and loci of neurofeedback in adolescents.
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142
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Empathy to emotional voices and the use of real-time fMRI to enhance activation of the anterior insula. Neuroimage 2019; 198:53-62. [DOI: 10.1016/j.neuroimage.2019.05.021] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2018] [Revised: 05/08/2019] [Accepted: 05/08/2019] [Indexed: 11/20/2022] Open
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143
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Nguyen AJ, Hoyer E, Rajhans P, Strathearn L, Kim S. A tumultuous transition to motherhood: Altered brain and hormonal responses in mothers with postpartum depression. J Neuroendocrinol 2019; 31:e12794. [PMID: 31520440 DOI: 10.1111/jne.12794] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Revised: 08/26/2019] [Accepted: 09/08/2019] [Indexed: 12/19/2022]
Abstract
Postpartum depression (PPD) is a common but complex condition that is poorly understood and multifactorial in aetiology. It is a condition that can compromise the mother's care for her infant, which may pose challenges to the formation of the mother-infant bond and the infant's overall development. Past research has looked at abnormalities in the brain circuitry and hormonal profiles of mothers with PPD compared to non-depressed mothers. However, abnormalities in PPD that may specifically affect the mother's care of her infant have not been clearly assessed. Thus, the present review aims to synthesise studies of altered brain and hormonal responses in mothers with PPD in relation to their care of their infant. First, we review maternal brain responses and their relation to PPD symptomatology, focusing on the salience/fear network, reward/attachment network and default mode network. Next, we discuss oxytocin and hypothalamic-pituitary-adrenal axis hormones in the context of maternal behaviour and PPD. Finally, we synthesise these findings and propose how future studies may benefit from the combined study of both neural and hormonal activity to better understand the underlying neurobiology of maternal care in PPD.
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Affiliation(s)
- Amanda J Nguyen
- School of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Elisabeth Hoyer
- School of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Purva Rajhans
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
- Stead Family Department of Pediatrics, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - Lane Strathearn
- Stead Family Department of Pediatrics, University of Iowa Carver College of Medicine, Iowa City, IA, USA
- Center for Disabilities and Development, University of Iowa Stead Family Children's Hospital, Iowa City, IA, USA
| | - Sohye Kim
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
- Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX, USA
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
- Center for Reproductive Psychiatry, Pavilion for Women, Texas Children's Hospital, Houston, TX, USA
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144
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Kato T. Current understanding of bipolar disorder: Toward integration of biological basis and treatment strategies. Psychiatry Clin Neurosci 2019; 73:526-540. [PMID: 31021488 DOI: 10.1111/pcn.12852] [Citation(s) in RCA: 70] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Revised: 04/19/2019] [Accepted: 04/22/2019] [Indexed: 12/18/2022]
Abstract
Biological studies of bipolar disorder initially focused on the mechanism of action for antidepressants and antipsychotic drugs, and the roles of monoamines (e.g., serotonin, dopamine) have been extensively studied. Thereafter, based on the mechanism of action of lithium, intracellular signal transduction systems, including inositol metabolism and intracellular calcium signaling, have drawn attention. Involvement of intracellular calcium signaling has been supported by genetics and cellular studies. Elucidation of the neural circuits affected by calcium signaling abnormalities is critical, and our previous study suggested a role of the paraventricular thalamic nucleus. The genetic vulnerability of mitochondria causes calcium dysregulation and results in the hyperexcitability of serotonergic neurons, which are suggested to be susceptible to oxidative stress. Efficacy of anticonvulsants, animal studies of candidate genes, and studies using induced pluripotent stem cell-derived neurons have suggested a relation between bipolar disorder and the hyperexcitability of neurons. Recent genetic findings suggest the roles of polyunsaturated acids. At the systems level, social rhythm therapy targets circadian rhythm abnormalities, and cognitive behavioral therapy may target emotion/cognition (E/C) imbalance. In the future, pharmacological and psychosocial treatments may be combined and optimized based on the biological basis of each patient, which will realize individualized treatment.
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Affiliation(s)
- Tadafumi Kato
- Laboratory for Molecular Dynamics of Mental Disorders, RIKEN Center for Brain Science, Wako, Japan
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145
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Zahn R, Weingartner JH, Basilio R, Bado P, Mattos P, Sato JR, de Oliveira-Souza R, Fontenelle LF, Young AH, Moll J. Blame-rebalance fMRI neurofeedback in major depressive disorder: A randomised proof-of-concept trial. NEUROIMAGE-CLINICAL 2019; 24:101992. [PMID: 31505367 PMCID: PMC6737344 DOI: 10.1016/j.nicl.2019.101992] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Revised: 08/12/2019] [Accepted: 08/24/2019] [Indexed: 01/25/2023]
Abstract
Previously, using fMRI, we demonstrated lower connectivity between right anterior superior temporal (ATL) and anterior subgenual cingulate (SCC) regions while patients with major depressive disorder (MDD) experience guilt. This neural signature was detected despite symptomatic remission which suggested a putative role in vulnerability. This randomised controlled double-blind parallel group clinical trial investigated whether patients with MDD are able to voluntarily modulate this neural signature. To this end, we developed a fMRI neurofeedback software (FRIEND), which measures ATL-SCC coupling and displays its levels in real time. Twenty-eight patients with remitted MDD were randomised to two groups, each receiving one session of fMRI neurofeedback whilst retrieving guilt and indignation/anger-related autobiographical memories. They were instructed to feel the emotion whilst trying to increase the level of a thermometer-like display on a screen. Active intervention group: The thermometer levels increased with increasing levels of ATL-SCC correlations in the guilt condition. Control intervention group: The thermometer levels decreased when correlation levels deviated from the previous baseline level in the guilt condition, thus reinforcing stable correlations. Both groups also received feedback during the indignation condition reinforcing stable correlations. We confirmed our predictions that patients in the active intervention group were indeed able to increase levels of ATL-SCC correlations for guilt vs. indignation and their self-esteem after training compared to before training and that this differed significantly from the control intervention group. These data provide proof-of-concept for a novel treatment target for MDD patients and are in keeping with the hypothesis that ATL-SCC connectivity plays a key role in self-worth. https://clinicaltrials.gov/ct2/show/results/NCT01920490 Employs real-time fMRI of anterior temporal –subgenual cingulate connectivity Previously decreased for guilt in major depressive disorder (MDD) beyond remission This RCT shows MDD patients can increase connectivity in one neurofeedback session. Active neurofeedback group increase self-esteem vs control neurofeedback group Training-induced self-esteem increases correlate with connectivity increases
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Affiliation(s)
- Roland Zahn
- Centre for Affective Disorders, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom
| | - Julie H Weingartner
- Cognitive and Behavioral Neuroscience Unit, Neuroinformatics Workgroup, D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
| | - Rodrigo Basilio
- Cognitive and Behavioral Neuroscience Unit, Neuroinformatics Workgroup, D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
| | - Patricia Bado
- Cognitive and Behavioral Neuroscience Unit, Neuroinformatics Workgroup, D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil; Instituto de Ciências Biomédicas (ICB), Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Paulo Mattos
- Cognitive and Behavioral Neuroscience Unit, Neuroinformatics Workgroup, D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
| | - João R Sato
- Cognitive and Behavioral Neuroscience Unit, Neuroinformatics Workgroup, D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil; Center for Mathematics, Computation, and Cognition, Universidade Federal do ABC, Santo André, Brazil
| | - Ricardo de Oliveira-Souza
- Cognitive and Behavioral Neuroscience Unit, Neuroinformatics Workgroup, D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil; Gaffrée e Guinle University Hospital, Federal University of the State of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Leo F Fontenelle
- Cognitive and Behavioral Neuroscience Unit, Neuroinformatics Workgroup, D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
| | - Allan H Young
- Centre for Affective Disorders, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom
| | - Jorge Moll
- Cognitive and Behavioral Neuroscience Unit, Neuroinformatics Workgroup, D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil; Scients Institute, Palo Alto, USA.
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146
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Rouhani N, Niv Y. Depressive symptoms bias the prediction-error enhancement of memory towards negative events in reinforcement learning. Psychopharmacology (Berl) 2019; 236:2425-2435. [PMID: 31346654 PMCID: PMC6697578 DOI: 10.1007/s00213-019-05322-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 06/30/2019] [Indexed: 01/09/2023]
Abstract
RATIONALE Depression is a disorder characterized by sustained negative affect and blunted positive affect, suggesting potential abnormalities in reward learning and its interaction with episodic memory. OBJECTIVES This study investigated how reward prediction errors experienced during learning modulate memory for rewarding events in individuals with depressive and non-depressive symptoms. METHODS Across three experiments, participants learned the average values of two scene categories in two learning contexts. Each learning context had either high or low outcome variance, allowing us to test the effects of small and large prediction errors on learning and memory. Participants were later tested for their memory of trial-unique scenes that appeared alongside outcomes. We compared learning and memory performance of individuals with self-reported depressive symptoms (N = 101) to those without (N = 184). RESULTS Although there were no overall differences in reward learning between the depressive and non-depressive group, depression severity within the depressive group predicted greater error in estimating the values of the scene categories. Similarly, there were no overall differences in memory performance. However, in depressive participants, negative prediction errors enhanced episodic memory more so than did positive prediction errors, and vice versa for non-depressive participants who showed a larger effect of positive prediction errors on memory. These results reflected differences in memory both within group and across groups. CONCLUSIONS Individuals with self-reported depressive symptoms showed relatively intact reinforcement learning, but demonstrated a bias for encoding events that accompanied surprising negative outcomes versus surprising positive ones. We discuss a potential neural mechanism supporting these effects, which may underlie or contribute to the excessive negative affect observed in depression.
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Affiliation(s)
- Nina Rouhani
- Department of Psychology, Princeton University, Princeton, NJ, 08544, USA.
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, 08544, USA.
| | - Yael Niv
- Department of Psychology, Princeton University, Princeton, NJ, 08544, USA
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, 08544, USA
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147
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Chiba T, Kanazawa T, Koizumi A, Ide K, Taschereau-Dumouchel V, Boku S, Hishimoto A, Shirakawa M, Sora I, Lau H, Yoneda H, Kawato M. Current Status of Neurofeedback for Post-traumatic Stress Disorder: A Systematic Review and the Possibility of Decoded Neurofeedback. Front Hum Neurosci 2019; 13:233. [PMID: 31379538 PMCID: PMC6650780 DOI: 10.3389/fnhum.2019.00233] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Accepted: 06/25/2019] [Indexed: 11/13/2022] Open
Abstract
Background: Post-traumatic stress disorder (PTSD) is a neuropsychiatric affective disorder that can develop after traumatic life-events. Exposure-based therapy is currently one of the most effective treatments for PTSD. However, exposure to traumatic stimuli is so aversive that a significant number of patients drop-out of therapy during the course of treatment. Among various attempts to develop novel therapies that bypass such aversiveness, neurofeedback appears promising. With neurofeedback, patients can unconsciously self-regulate brain activity via real-time monitoring and feedback of the EEG or fMRI signals. With conventional neurofeedback methods, however, it is difficult to induce neural representation related to specific trauma because the feedback is based on the neural signals averaged within specific brain areas. To overcome this difficulty, novel neurofeedback approaches such as Decoded Neurofeedback (DecNef) might prove helpful. Instead of the average BOLD signals, DecNef allows patients to implicitly regulate multivariate voxel patterns of the BOLD signals related with feared stimuli. As such, DecNef effects are postulated to derive either from exposure or counter-conditioning, or some combination of both. Although the exact mechanism is not yet fully understood. DecNef has been successfully applied to reduce fear responses induced either by fear-conditioned or phobic stimuli among non-clinical participants. Methods: Follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic review was conducted to compare DecNef effect with those of conventional EEG/fMRI-based neurofeedback on PTSD amelioration. To elucidate the possible mechanisms of DecNef on fear reduction, we mathematically modeled the effects of exposure-based and counter conditioning separately and applied it to the data obtained from past DecNef studies. Finally, we conducted DecNef on four PTSD patients. Here, we review recent advances in application of neurofeedback to PTSD treatments, including the DecNef. This review is intended to be informative for neuroscientists in general as well as practitioners planning to use neurofeedback as a therapeutic strategy for PTSD. Results: Our mathematical model suggested that exposure is the key component for DecNef effects in the past studies. Following DecNef a significant reduction of PTSD severity was observed. This effect was comparable to those reported for conventional neurofeedback approach. Conclusions: Although a much larger number of participants will be needed in future, DecNef could be a promising therapy that bypasses the unpleasantness of conscious exposure associated with conventional therapies for fear related disorders, including PTSD.
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Affiliation(s)
- Toshinori Chiba
- Computational Neuroscience Laboratories, Department of Decoded Neurofeedback, Advanced Telecommunications Research Institute International, Kyoto, Japan.,Department of Psychiatry, Graduate School of Medicine, Kobe University, Kobe, Japan
| | - Tetsufumi Kanazawa
- Department of Neuropsychiatry, Osaka Medical College, Osaka, Japan.,The Florey Institute of Neuroscience and Mental Health, Melbourne, VIC, Australia
| | - Ai Koizumi
- Sony Computer Science Laboratories, Inc., Tokyo, Japan
| | - Kentarou Ide
- Computational Neuroscience Laboratories, Department of Decoded Neurofeedback, Advanced Telecommunications Research Institute International, Kyoto, Japan.,Flower of Light Clinic for Mind and Body, Tokyo, Japan
| | - Vincent Taschereau-Dumouchel
- Computational Neuroscience Laboratories, Department of Decoded Neurofeedback, Advanced Telecommunications Research Institute International, Kyoto, Japan.,Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Shuken Boku
- Department of Psychiatry, Graduate School of Medicine, Kobe University, Kobe, Japan
| | - Akitoyo Hishimoto
- Department of Psychiatry, Graduate School of Medicine, Kobe University, Kobe, Japan
| | | | - Ichiro Sora
- Department of Psychiatry, Graduate School of Medicine, Kobe University, Kobe, Japan
| | - Hakwan Lau
- Computational Neuroscience Laboratories, Department of Decoded Neurofeedback, Advanced Telecommunications Research Institute International, Kyoto, Japan.,Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Brain Research Institute, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Psychology, University of Hong Kong, Pokfulam, Hong Kong
| | - Hiroshi Yoneda
- Department of Neuropsychiatry, Osaka Medical College, Osaka, Japan
| | - Mitsuo Kawato
- Computational Neuroscience Laboratories, Department of Decoded Neurofeedback, Advanced Telecommunications Research Institute International, Kyoto, Japan.,RIKEN Center for Advanced Intelligence Project (AIP), Tokyo, Japan
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148
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Zhu Y, Gao H, Tong L, Li Z, Wang L, Zhang C, Yang Q, Yan B. Emotion Regulation of Hippocampus Using Real-Time fMRI Neurofeedback in Healthy Human. Front Hum Neurosci 2019; 13:242. [PMID: 31379539 PMCID: PMC6660260 DOI: 10.3389/fnhum.2019.00242] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Accepted: 06/28/2019] [Indexed: 01/12/2023] Open
Abstract
Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) is a prospective tool to enhance the emotion regulation capability of participants and to alleviate their emotional disorders. The hippocampus is a key brain region in the emotional brain network and plays a significant role in social cognition and emotion processing in the brain. However, few studies have focused on the emotion NF of the hippocampus. This study investigated the feasibility of NF training of healthy participants to self-regulate the activation of the hippocampus and assessed the effect of rtfMRI-NF on the hippocampus before and after training. Twenty-six right-handed healthy volunteers were randomly assigned to the experimental group receiving hippocampal rtfMRI-NF (n = 13) and the control group (CG) receiving rtfMRI-NF from the intraparietal sulcus rtfMRI-NF (n = 13) and completed a total of four NF runs. The hippocampus and the intraparietal sulcus were defined based on the Montreal Neurological Institute (MNI) standard template, and NF signal was measured as a percent signal change relative to the baseline obtained by averaging the fMRI signal for the preceding 20 s long rest block. NF signal (percent signal change) was updated every 2 s and was displayed on the screen. The amplitude of low-frequency fluctuation and regional homogeneity values was calculated to evaluate the effects of NF on spontaneous neural activity in resting-state fMRI. A standard general linear model (GLM) analysis was separately conducted for each fMRI NF run. Results showed that the activation of hippocampus increased after four NF training runs. The hippocampal activity of the experiment group participants was higher than that of the CG. They also showed elevated hippocampal activity and the greater amygdala–hippocampus connectivity. The anterior temporal lobe, parahippocampal gyrus, hippocampus, and amygdala of brain regions associated with emotional processing were activated during training. We presented a proof-of-concept study using rtfMRI-NF for hippocampus up-regulation in the recall of positive autobiographical memories. The current study may provide a new method to regulate our emotions and can potentially be applied to the clinical treatment of emotional disorders.
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Affiliation(s)
- Yashuo Zhu
- PLA Strategy Support Force Information Engineering University, Communication Engineering College, Zhengzhou, China
| | - Hui Gao
- PLA Strategy Support Force Information Engineering University, Communication Engineering College, Zhengzhou, China
| | - Li Tong
- PLA Strategy Support Force Information Engineering University, Communication Engineering College, Zhengzhou, China
| | - ZhongLin Li
- Department of Radiology, Zhengzhou University People's Hospital and Henan Provincial People's Hospital, Zhengzhou, China
| | - Linyuan Wang
- PLA Strategy Support Force Information Engineering University, Communication Engineering College, Zhengzhou, China
| | - Chi Zhang
- PLA Strategy Support Force Information Engineering University, Communication Engineering College, Zhengzhou, China
| | - Qiang Yang
- PLA Strategy Support Force Information Engineering University, Communication Engineering College, Zhengzhou, China
| | - Bin Yan
- PLA Strategy Support Force Information Engineering University, Communication Engineering College, Zhengzhou, China
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149
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Are the antidepressive effects of massage therapy mediated by restoration of impaired interoceptive functioning? A novel hypothetical mechanism. Med Hypotheses 2019; 128:28-32. [DOI: 10.1016/j.mehy.2019.05.004] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Revised: 04/11/2019] [Accepted: 05/10/2019] [Indexed: 12/20/2022]
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150
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Linhartová P, Látalová A, Kóša B, Kašpárek T, Schmahl C, Paret C. fMRI neurofeedback in emotion regulation: A literature review. Neuroimage 2019; 193:75-92. [DOI: 10.1016/j.neuroimage.2019.03.011] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2018] [Revised: 03/03/2019] [Accepted: 03/05/2019] [Indexed: 12/23/2022] Open
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