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Dhanis H, Gninenko N, Morgenroth E, Potheegadoo J, Rognini G, Faivre N, Blanke O, Van De Ville D. Real-time fMRI neurofeedback modulates induced hallucinations and underlying brain mechanisms. Commun Biol 2024; 7:1120. [PMID: 39261559 PMCID: PMC11391061 DOI: 10.1038/s42003-024-06842-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Accepted: 09/04/2024] [Indexed: 09/13/2024] Open
Abstract
Hallucinations can occur in the healthy population, are clinically relevant and frequent symptoms in many neuropsychiatric conditions, and have been shown to mark disease progression in patients with neurodegenerative disorders where antipsychotic treatment remains challenging. Here, we combine MR-robotics capable of inducing a clinically-relevant hallucination, with real-time fMRI neurofeedback (fMRI-NF) to train healthy individuals to up-regulate a fronto-parietal brain network associated with the robotically-induced hallucination. Over three days, participants learned to modulate occurrences of and transition probabilities to this network, leading to heightened sensitivity to induced hallucinations after training. Moreover, participants who became sensitive and succeeded in fMRI-NF training, showed sustained and specific neural changes after training, characterized by increased hallucination network occurrences during induction and decreased hallucination network occurrences during a matched control condition. These data demonstrate that fMRI-NF modulates specific hallucination network dynamics and highlights the potential of fMRI-NF as a novel antipsychotic treatment in neurodegenerative disorders and schizophrenia.
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Affiliation(s)
- Herberto Dhanis
- Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Nicolas Gninenko
- Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
- Department of Neurology, Inselspital, University Hospital of Bern, Bern, Switzerland
| | - Elenor Morgenroth
- Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| | - Jevita Potheegadoo
- Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Giulio Rognini
- Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Nathan Faivre
- Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LPNC, Grenoble, France
| | - Olaf Blanke
- Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland.
- Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
- Department of Clinical Neurosciences, University Hospital of Geneva, Geneva, Switzerland.
| | - Dimitri Van De Ville
- Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland.
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland.
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2
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Misaki M, Tsuchiyagaito A, Guinjoan SM, Rohan ML, Paulus MP. Whole-brain mechanism of neurofeedback therapy: predictive modeling of neurofeedback outcomes on repetitive negative thinking in depression. Transl Psychiatry 2024; 14:354. [PMID: 39227376 PMCID: PMC11371824 DOI: 10.1038/s41398-024-03066-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 08/20/2024] [Accepted: 08/23/2024] [Indexed: 09/05/2024] Open
Abstract
Real-time fMRI neurofeedback (rtfMRI-NF) has emerged as a promising intervention for psychiatric disorders, yet its clinical efficacy remains underexplored due to an incomplete mechanistic understanding. This study aimed to delineate the whole-brain mechanisms underpinning the effects of rtfMRI-NF on repetitive negative thinking in depression. In a double-blind randomized controlled trial, forty-three depressed individuals underwent NF training targeting the functional connectivity (FC) between the posterior cingulate cortex and the right temporoparietal junction, linked to rumination severity. Participants were randomly assigned to active or sham groups, with the sham group receiving synthesized feedback mimicking real NF signal patterns. The active group demonstrated a significant reduction in brooding rumination scores (d = -1.52, p < 0.001), whereas the sham group did not (d = -0.23, p = 0.503). While the target FC did not show discernible training effects or group differences, connectome-based predictive modeling (CPM) analysis revealed that the interaction between brain activity during regulation and brain response to the feedback signal was the critical factor in explaining treatment outcomes. The model incorporating this interaction successfully predicted rumination changes across both groups. The FCs significantly contributing to the prediction were distributed across brain regions, notably the frontal control, salience network, and subcortical reward processing areas. These results underscore the importance of considering the interplay between brain regulation activities and brain response to the feedback signal in understanding the therapeutic mechanisms of rtfMRI-NF. The study affirms rtfMRI-NF's potential as a therapeutic intervention for repetitive negative thinking and highlights the need for a nuanced understanding of the whole-brain mechanisms contributing to its efficacy.
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Affiliation(s)
- Masaya Misaki
- Laureate Institute for Brain Research, Tulsa, OK, USA.
- Oxley College of Health & Natural Sciences, The University of Tulsa, Tulsa, OK, USA.
| | - Aki Tsuchiyagaito
- Laureate Institute for Brain Research, Tulsa, OK, USA
- Oxley College of Health & Natural Sciences, The University of Tulsa, Tulsa, OK, USA
| | - Salvador M Guinjoan
- Laureate Institute for Brain Research, Tulsa, OK, USA
- Department of Psychiatry, Oklahoma University Health Sciences Center at Tulsa, Tulsa, OK, USA
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3
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Trambaiolli L, Maffei C, Dann E, Biazoli C, Bezgin G, Yendiki A, Haber S. Translation of monosynaptic circuits underlying amygdala fMRI neurofeedback training. Neuropsychopharmacology 2024:10.1038/s41386-024-01944-w. [PMID: 39103495 DOI: 10.1038/s41386-024-01944-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Revised: 07/16/2024] [Accepted: 07/23/2024] [Indexed: 08/07/2024]
Abstract
fMRI neurofeedback using autobiographical memory recall to upregulate the amygdala is associated with resting-state functional connectivity (rsFC) changes between the amygdala and the salience and default mode networks (SN and DMN, respectively). We hypothesize the existence of anatomical circuits underlying these rsFC changes. Using a cross-species brain parcellation, we identified in non-human primates locations homologous to the regions of interest (ROIs) from studies showing pre-to-post-neurofeedback changes in rsFC with the left amygdala. We injected bidirectional tracers in the basolateral, lateral, and central amygdala nuclei of adult macaques and used bright- and dark-field microscopy to identify cells and axon terminals in each ROI (SN: anterior cingulate, ventrolateral, and insular cortices; DMN: temporal pole, middle frontal gyrus, angular gyrus, precuneus, posterior cingulate cortex, parahippocampal gyrus, hippocampus, and thalamus). We also performed additional injections in specific ROIs to validate the results following amygdala injections and delineate potential disynaptic pathways. Finally, we used high-resolution diffusion MRI data from four post-mortem macaque brains and one in vivo human brain to translate our findings to the neuroimaging domain. Different amygdala nuclei had significant monosynaptic connections with all the SN and DMN ipsilateral ROIs. Amygdala connections with the DMN contralateral ROIs are disynaptic through the hippocampus and parahippocampal gyrus. Diffusion MRI in both species benefitted from using the ground-truth tracer data to validate its findings, as we identified false-negative ipsilateral and false-positive contralateral connectivity results. This study provides the foundation for future causal investigations of amygdala neurofeedback modulation of the SN and DMN through these anatomic connections.
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Affiliation(s)
- Lucas Trambaiolli
- McLean Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Pharmacology and Physiology, University of Rochester, Rochester, NY, USA.
| | - Chiara Maffei
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Evan Dann
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Claudinei Biazoli
- Center for Mathematics Computation and Cognition, Federal University of ABC, Santo André, Brazil
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - Gleb Bezgin
- Neuroinformatics for Personalized Medicine lab, Montreal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Suzanne Haber
- McLean Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Pharmacology and Physiology, University of Rochester, Rochester, NY, USA.
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Morrissey G, Tsuchiyagaito A, Takahashi T, McMillin J, Aupperle RL, Misaki M, Khalsa SS. Could neurofeedback improve therapist-patient communication? Considering the potential for neuroscience informed examinations of the psychotherapeutic relationship. Neurosci Biobehav Rev 2024; 161:105680. [PMID: 38641091 DOI: 10.1016/j.neubiorev.2024.105680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 03/22/2024] [Accepted: 04/16/2024] [Indexed: 04/21/2024]
Abstract
Empathic communication between a patient and therapist is an essential component of psychotherapy. However, finding objective neural markers of the quality of the psychotherapeutic relationship have been elusive. Here we conceptualize how a neuroscience-informed approach involving real-time neurofeedback, facilitated via existing functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) technologies, could provide objective information for facilitating therapeutic rapport. We propose several neurofeedback-assisted psychotherapy (NF-AP) approaches that could be studied as a way to optimize the experience of the individual patient and therapist across the spectrum of psychotherapeutic treatment. Finally, we consider how the possible strengths of these approaches are balanced by their current limitations and discuss the future prospects of NF-AP.
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Affiliation(s)
| | - Aki Tsuchiyagaito
- Laureate Institute for Brain Research, Tulsa, OK, USA; Oxley College of Health and Natural Sciences, University of Tulsa, Tulsa, OK, USA
| | - Toru Takahashi
- Laureate Institute for Brain Research, Tulsa, OK, USA; Japan Society for the Promotion of Science, Chiyoda-ku, Tokyo, Japan
| | - John McMillin
- Advocate Medical Group, Downers Grove, IL, USA; Department of Psychiatry, University of Oklahoma-Tulsa, Tulsa, OK, USA
| | - Robin L Aupperle
- Laureate Institute for Brain Research, Tulsa, OK, USA; Oxley College of Health and Natural Sciences, University of Tulsa, Tulsa, OK, USA
| | - Masaya Misaki
- Laureate Institute for Brain Research, Tulsa, OK, USA; Oxley College of Health and Natural Sciences, University of Tulsa, Tulsa, OK, USA
| | - Sahib S Khalsa
- Laureate Institute for Brain Research, Tulsa, OK, USA; Oxley College of Health and Natural Sciences, University of Tulsa, Tulsa, OK, USA.
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5
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Bressler RA, Raible S, Lührs M, Tier R, Goebel R, Linden DE. No threat: Emotion regulation neurofeedback for police special forces recruits. Neuropsychologia 2023; 190:108699. [PMID: 37816480 DOI: 10.1016/j.neuropsychologia.2023.108699] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 08/15/2023] [Accepted: 10/06/2023] [Indexed: 10/12/2023]
Abstract
Police officers of the Special Forces are confronted with highly demanding situations in terms of stress, high tension and threats to their lives. Their tasks are specifically high-risk operations, such as arrests of armed suspects and anti-terror interventions. Improving the emotion regulation skills of police officers might be a vital investment, supporting them to stay calm and focused. A promising approach is training emotion regulation by using real-time (rt-) fMRI neurofeedback. Specifically, downregulating activity in key areas of the fronto-limbic emotion regulation network in the presence of threatening stimuli. Thirteen recruits of the Dutch police special forces underwent six weekly rt-fMRI sessions, receiving neurofeedback from individualized regions of their emotion regulation network. Their task was to reduce the image size of threatening images, wherein the image size represented their brain activity. A reduction in image size represented successful downregulation. Participants were free to use their preferred regulation strategy. A control group of fifteen recruits received no neurofeedback. Both groups completed behavioural tests (image rating on evoked valence and arousal, questionnaire) before and after the neurofeedback training. We hypothesized that the neurofeedback group would improve in downregulation and would score better than the control group on the behavioural tests after the neurofeedback training. Neurofeedback training resulted in a significant decrease in image size (t(12) = 2.82, p = .015) and a trend towards decreased activation in the target regions (t(10) = 1.82, p = .099) from the first to the last session. Notably, subjects achieved downregulation below the pre-stimulus baseline in the last two sessions. No relevant differences between groups were found in the behavioural tasks. Through the training of rt-fMRI neurofeedback, participants learned to downregulate the activity in individualized areas of the emotion regulation network, by using their own preferred strategies. The lack of behavioural between-group differences may be explained by floor effects. Tasks that are close to real-life situations may be needed to uncover behavioural correlates of this emotion regulation training.
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Affiliation(s)
- Ruben Andreas Bressler
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Universiteitssingel 40, 6229 ER, Maastricht, the Netherlands.
| | - Sophie Raible
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Universiteitssingel 40, 6229 ER, Maastricht, the Netherlands
| | - Michael Lührs
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Universiteitssingel 40, 6229 ER, Maastricht, the Netherlands; Brain Innovation, Maastricht, The Netherlands, Oxfordlaan 55, 6229 EV, Maastricht, the Netherlands
| | - Ralph Tier
- Landelijke Eenheid, Dienst Speciale Interventies, Hoofdstraat 54, 3972 LB, Postbus 100, 3970 AC, Driebergen, the Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Universiteitssingel 40, 6229 ER, Maastricht, the Netherlands; Brain Innovation, Maastricht, The Netherlands, Oxfordlaan 55, 6229 EV, Maastricht, the Netherlands
| | - David E Linden
- School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Universiteitssingel 40, 6229 ER, Maastricht, the Netherlands
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6
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Bloom PA, Pagliaccio D, Zhang J, Bauer CCC, Kyler M, Greene KD, Treves I, Morfini F, Durham K, Cherner R, Bajwa Z, Wool E, Olafsson V, Lee RF, Bidmead F, Cardona J, Kirshenbaum JS, Ghosh S, Hinds O, Wighton P, Galfalvy H, Simpson HB, Whitfield-Gabrieli S, Auerbach RP. Mindfulness-based real-time fMRI neurofeedback: a randomized controlled trial to optimize dosing for depressed adolescents. BMC Psychiatry 2023; 23:757. [PMID: 37848857 PMCID: PMC10580563 DOI: 10.1186/s12888-023-05223-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Accepted: 09/26/2023] [Indexed: 10/19/2023] Open
Abstract
BACKGROUND Adolescence is characterized by a heightened vulnerability for Major Depressive Disorder (MDD) onset, and currently, treatments are only effective for roughly half of adolescents with MDD. Accordingly, novel interventions are urgently needed. This study aims to establish mindfulness-based real-time fMRI neurofeedback (mbNF) as a non-invasive approach to downregulate the default mode network (DMN) in order to decrease ruminatory processes and depressive symptoms. METHODS Adolescents (N = 90) with a current diagnosis of MDD ages 13-18-years-old will be randomized in a parallel group, two-arm, superiority trial to receive either 15 or 30 min of mbNF with a 1:1 allocation ratio. Real-time neurofeedback based on activation of the frontoparietal network (FPN) relative to the DMN will be displayed to participants via the movement of a ball on a computer screen while participants practice mindfulness in the scanner. We hypothesize that within-DMN (medial prefrontal cortex [mPFC] with posterior cingulate cortex [PCC]) functional connectivity will be reduced following mbNF (Aim 1: Target Engagement). Additionally, we hypothesize that participants in the 30-min mbNF condition will show greater reductions in within-DMN functional connectivity (Aim 2: Dosing Impact on Target Engagement). Aim 1 will analyze data from all participants as a single-group, and Aim 2 will leverage the randomized assignment to analyze data as a parallel-group trial. Secondary analyses will probe changes in depressive symptoms and rumination. DISCUSSION Results of this study will determine whether mbNF reduces functional connectivity within the DMN among adolescents with MDD, and critically, will identify the optimal dosing with respect to DMN modulation as well as reduction in depressive symptoms and rumination. TRIAL REGISTRATION This study has been registered with clinicaltrials.gov, most recently updated on July 6, 2023 (trial identifier: NCT05617495).
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Affiliation(s)
- Paul A Bloom
- Department of Psychiatry, Columbia University, New York, NY, USA.
| | - David Pagliaccio
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Jiahe Zhang
- Department of Psychology, Northeastern University, Boston, MA, USA
| | - Clemens C C Bauer
- Department of Psychology, Northeastern University, Boston, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Mia Kyler
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Keara D Greene
- Department of Psychology, Northeastern University, Boston, MA, USA
| | - Isaac Treves
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - Katherine Durham
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Rachel Cherner
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Zia Bajwa
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Emma Wool
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Valur Olafsson
- Northeastern University Biomedical Imaging Center, Boston, MA, USA
| | - Ray F Lee
- Zuckerman Mind Brain and Behavior Institute, Columbia University, New York, NY, USA
| | - Fred Bidmead
- Northeastern University Biomedical Imaging Center, Boston, MA, USA
| | - Jonathan Cardona
- Zuckerman Mind Brain and Behavior Institute, Columbia University, New York, NY, USA
| | | | | | | | - Paul Wighton
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Hanga Galfalvy
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - H Blair Simpson
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Susan Whitfield-Gabrieli
- Department of Psychology, Northeastern University, Boston, MA, USA
- Northeastern University Biomedical Imaging Center, Boston, MA, USA
| | - Randy P Auerbach
- Department of Psychiatry, Columbia University, New York, NY, USA
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7
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Farb NAS, Zuo Z, Price CJ. Interoceptive Awareness of the Breath Preserves Attention and Language Networks amidst Widespread Cortical Deactivation: A Within-Participant Neuroimaging Study. eNeuro 2023; 10:ENEURO.0088-23.2023. [PMID: 37316296 PMCID: PMC10295813 DOI: 10.1523/eneuro.0088-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 05/26/2023] [Accepted: 06/06/2023] [Indexed: 06/16/2023] Open
Abstract
Interoception, the representation of the body's internal state, serves as a foundation for emotion, motivation, and wellbeing. Yet despite its centrality in human experience, the neural mechanisms of interoceptive attention are poorly understood. The Interoceptive/Exteroceptive Attention Task (IEAT) is a novel neuroimaging paradigm that compares behavioral tracking of the respiratory cycle (Active Interoception) to tracking of a visual stimulus (Active Exteroception). Twenty-two healthy participants completed the IEAT during two separate scanning sessions (N = 44) as part of a randomized control trial of mindful awareness in body-oriented therapy (MABT). Compared with Active Exteroception, Active Interoception deactivated somatomotor and prefrontal regions. Greater self-reported interoceptive sensibility (MAIA scale) predicted sparing from deactivation within the anterior cingulate cortex (ACC) and left-lateralized language regions. The right insula, typically described as a primary interoceptive cortex, was only specifically implicated by its deactivation during an exogenously paced respiration condition (Active Matching) relative to self-paced Active Interoception. Psychophysiological interaction (PPI) analysis characterized Active Interoception as promoting greater ACC connectivity with lateral prefrontal and parietal regions commonly referred to as the dorsal attention network (DAN). In contrast to evidence relating accurate detection of liminal interoceptive signals such as the heartbeat to anterior insula activity, interoceptive attention toward salient signals such as the respiratory cycle may involve reduced cortical activity but greater ACC-DAN connectivity, with greater sensibility linked to reduced deactivation within the ACC and language-processing regions.
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Affiliation(s)
- Norman A S Farb
- Department of Psychology, University of Toronto Mississauga, Mississauga, Ontario L5L 1C6, Canada
- Department of Psychological Clinical Sciences, University of Toronto Scarborough, Scarborough, Ontario M1C 1A4, Canada
| | - Zoey Zuo
- Department of Psychological Clinical Sciences, University of Toronto Scarborough, Scarborough, Ontario M1C 1A4, Canada
| | - Cynthia J Price
- Department of Biobehavioral Nursing and Health Informatics, University of Washington, Seattle, WA 98195
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8
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Kahnt T. Computationally Informed Interventions for Targeting Compulsive Behaviors. Biol Psychiatry 2023; 93:729-738. [PMID: 36464521 PMCID: PMC9989040 DOI: 10.1016/j.biopsych.2022.08.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 08/04/2022] [Accepted: 08/30/2022] [Indexed: 11/02/2022]
Abstract
Compulsive behaviors are central to addiction and obsessive-compulsive disorder and can be understood as a failure of adaptive decision making. Particularly, they can be conceptualized as an imbalance in behavioral control, such that behavior is guided predominantly by learned rather than inferred outcome expectations. Inference is a computational process required for adaptive behavior, and recent work across species has identified the neural circuitry that supports inference-based decision making. This includes the orbitofrontal cortex, which has long been implicated in disorders of compulsive behavior. Inspired by evidence that modulating orbitofrontal cortex activity can alter inference-based behaviors, here we discuss noninvasive approaches to target these circuits in humans. Specifically, we discuss the potential of network-targeted transcranial magnetic stimulation and real-time neurofeedback to modulate the neural underpinnings of inference. Both interventions leverage recent advances in our understanding of the neurocomputational mechanisms of inference-based behavior and may be used to complement current treatment approaches for behavioral disorders.
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Affiliation(s)
- Thorsten Kahnt
- National Institute on Drug Abuse Intramural Research Program, Baltimore, Maryland.
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9
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Pereira DJ, Sayal A, Pereira J, Morais S, Macedo A, Direito B, Castelo-Branco M. Neurofeedback-dependent influence of the ventral striatum using a working memory paradigm targeting the dorsolateral prefrontal cortex. Front Behav Neurosci 2023; 17:1014223. [PMID: 36844653 PMCID: PMC9947361 DOI: 10.3389/fnbeh.2023.1014223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 01/18/2023] [Indexed: 02/11/2023] Open
Abstract
Executive functions and motivation have been established as key aspects for neurofeedback success. However, task-specific influence of cognitive strategies is scarcely explored. In this study, we test the ability to modulate the dorsolateral prefrontal cortex, a strong candidate for clinical application of neurofeedback in several disorders with dysexecutive syndrome, and investigate how feedback contributes to better performance in a single session. Participants of both neurofeedback (n = 17) and sham-control (n = 10) groups were able to modulate DLPFC in most runs (with or without feedback) while performing a working memory imagery task. However, activity in the target area was higher and more sustained in the active group when receiving feedback. Furthermore, we found increased activity in the nucleus accumbens in the active group, compared with a predominantly negative response along the block in participants receiving sham feedback. Moreover, they acknowledged the non-contingency between imagery and feedback, reflecting the impact on motivation. This study reinforces DLPFC as a robust target for neurofeedback clinical implementations and enhances the critical influence of the ventral striatum, both poised to achieve success in the self-regulation of brain activity.
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Affiliation(s)
- Daniela Jardim Pereira
- Neurorradiology Functional Area, Imaging Department, Coimbra Hospital and University Center, Coimbra, Portugal,Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal,Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Alexandre Sayal
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal,Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal,Siemens Healthineers Portugal, Lisboa, Portugal
| | - João Pereira
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal,Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
| | - Sofia Morais
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal,Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal,Psychiatry Department, Coimbra Hospital and University Center, Coimbra, Portugal
| | - António Macedo
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal,Psychiatry Department, Coimbra Hospital and University Center, Coimbra, Portugal
| | - Bruno Direito
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal,Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal,IATV—Instituto do Ambiente, Tecnologia e Vida (IATV), Coimbra, Portugal
| | - Miguel Castelo-Branco
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal,Faculty of Medicine, University of Coimbra, Coimbra, Portugal,Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal,*Correspondence: Miguel Castelo-Branco
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10
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Mulyana B, Tsuchiyagaito A, Misaki M, Kuplicki R, Smith J, Soleimani G, Rashedi A, Shereen D, Bergman TO, Cheng S, Paulus MP, Bodurka J, Ekhtiari H. Online closed-loop real-time tES-fMRI for brain modulation: A technical report. Brain Behav 2022; 12:e2667. [PMID: 36134450 PMCID: PMC9575607 DOI: 10.1002/brb3.2667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 04/29/2022] [Accepted: 05/22/2022] [Indexed: 11/17/2022] Open
Abstract
Recent studies suggest that transcranial electrical stimulation (tES) can be performed during functional magnetic resonance imaging (fMRI). The novel approach of using concurrent tES-fMRI to modulate and measure targeted brain activity/connectivity may provide unique insights into the causal interactions between the brain neural responses and psychiatric/neurologic signs and symptoms, and importantly, guide the development of new treatments. However, tES stimulation parameters to optimally influence the underlying brain activity may vary with respect to phase difference, frequency, intensity, and electrode's montage among individuals. Here, we propose a protocol for closed-loop tES-fMRI to optimize the frequency and phase difference of alternating current stimulation (tACS) for two nodes (frontal and parietal regions) in individual participants. We carefully considered the challenges in an online optimization of tES parameters with concurrent fMRI, specifically in its safety, artifact in fMRI image quality, online evaluation of the tES effect, and parameter optimization method, and we designed the protocol to run an effective study to enhance frontoparietal connectivity and working memory performance with the optimized tACS using closed-loop tES-fMRI. We provide technical details of the protocol, including electrode types, electrolytes, electrode montages, concurrent tES-fMRI hardware, online fMRI processing pipelines, and the optimization algorithm. We confirmed the implementation of this protocol worked successfully with a pilot experiment.
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Affiliation(s)
- Beni Mulyana
- Laureate Institute for Brain ResearchTulsaOklahomaUSA
- Electrical and Computer EngineeringUniversity of OklahomaTulsaOklahomaUSA
| | | | - Masaya Misaki
- Laureate Institute for Brain ResearchTulsaOklahomaUSA
| | | | - Jared Smith
- Laureate Institute for Brain ResearchTulsaOklahomaUSA
| | - Ghazaleh Soleimani
- Department of Biomedical EngineeringAmirkabir University of Technology, Tehran, Iran
- Iranian National Center for Addiction StudiesTehran University of Medical SciencesTehranIran
| | | | - Duke Shereen
- The Graduate Center of the City University of New YorkNew YorkNew YorkUSA
| | - Til Ole Bergman
- Neuroimaging Center (NIC)University Medical Center of the Johannes Gutenberg University MainzGermany
- Leibniz Institute for Resilience Research (LIR)MainzGermany
| | - Samuel Cheng
- Electrical and Computer EngineeringUniversity of OklahomaTulsaOklahomaUSA
| | | | - Jerzy Bodurka
- Laureate Institute for Brain ResearchTulsaOklahomaUSA
- Stephenson School of Biomedical EngineeringUniversity of OklahomaNormanOklahomaUSA
| | - Hamed Ekhtiari
- Laureate Institute for Brain ResearchTulsaOklahomaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of MinnesotaMinneapolisMinnesotaUSA
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11
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Hu L, Hu L, Xu J, Zhang Z, Wu J, Xiang Y, He Q, Zhang T, Li J. Efficacy of Respiratory Training in Relieving Postoperative Pain in Patients with Spinal Nerve Root Entrapment Syndrome. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:7703835. [PMID: 35912158 PMCID: PMC9337933 DOI: 10.1155/2022/7703835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 06/10/2022] [Accepted: 06/14/2022] [Indexed: 11/23/2022]
Abstract
Background Breathing exercise can help patients with dyspnea to change the wrong breathing pattern, improve the degree of freedom of respiratory muscles, increase alveolar ventilation, promote breathing, and relieve the symptoms of dyspnea patients. Therefore, this study is aimed at investigating the role of breathing training in alleviating postoperative pain in patients with spinal nerve root entrapment syndrome. Objective To explore the effect of respiratory training in relieving postoperative pain in patients with spinal nerve root entrapment syndrome. Methods Fifty-eight patients with spinal nerve root entrapment syndrome treated in our hospital from May 2020 to May 2021 were analyzed retrospectively. The patients were randomly divided into a control group (n = 29) and an observation group (n = 29). The control group was given routine postoperative pain nursing, and the observation group was given respiratory training on the basis of the control group. The scores of visual analogue scale (VAS), self-rating anxiety scale (SAS), Oswestry dysfunction index questionnaire (ODI), the dosage of postoperative analgesics, and the time of first out-of-bed activity were recorded before pain nursing intervention and 3 days and 7 days after intervention. Results The VAS, SAS, and ODI scores of the observation group after 3 d and 7 d of intervention were lower than those of the control group. Compared with the same group, the scores of VAS, SAS, and ODI after 3 d and 7 d of intervention were lower than those before intervention, and those after 7 d of intervention were lower than those after 3 d of intervention (P < 0.05). The dosage of postoperative analgesics and the time of first out-of-bed activity in the observation group were lower than those in the control group (P < 0.05). Conclusion Respiratory training can effectively relieve postoperative pain, reduce anxiety, and improve spinal function in patients with spinal nerve root entrapment syndrome, which is beneficial to the prognosis of patients and is worthy of promotion.
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Affiliation(s)
- Ling Hu
- Department of Neurosurgery, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan City, Hubei Province 430014, China
| | - Liqiong Hu
- Department of Neurosurgery, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan City, Hubei Province 430014, China
| | - Jinglin Xu
- Department of Neurosurgery, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan City, Hubei Province 430014, China
| | - Zhang Zhang
- Department of Neurosurgery, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan City, Hubei Province 430014, China
| | - Jun Wu
- Department of Neurosurgery, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan City, Hubei Province 430014, China
| | - Yun Xiang
- Department of Neurosurgery, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan City, Hubei Province 430014, China
| | - Qianqian He
- Department of Neurosurgery, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan City, Hubei Province 430014, China
| | - Ting Zhang
- Department of Neurosurgery, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan City, Hubei Province 430014, China
| | - Jun Li
- Department of Neurosurgery, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan City, Hubei Province 430014, China
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12
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Karch S, Krause D, Lehnert K, Konrad J, Haller D, Rauchmann BS, Maywald M, Engelbregt H, Adorjan K, Koller G, Reidler P, Karali T, Tschentscher N, Ertl-Wagner B, Pogarell O, Paolini M, Keeser D. Functional and clinical outcomes of FMRI-based neurofeedback training in patients with alcohol dependence: a pilot study. Eur Arch Psychiatry Clin Neurosci 2022; 272:557-569. [PMID: 34622344 PMCID: PMC9095551 DOI: 10.1007/s00406-021-01336-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2020] [Accepted: 09/22/2021] [Indexed: 01/20/2023]
Abstract
Identifying treatment options for patients with alcohol dependence is challenging. This study investigates the application of real-time functional MRI (rtfMRI) neurofeedback (NF) to foster resistance towards craving-related neural activation in alcohol dependence. We report a double-blind, placebo-controlled rtfMRI study with three NF sessions using alcohol-associated cues as an add-on therapy to the standard treatment. Fifty-two patients (45 male; 7 female) diagnosed with alcohol dependence were recruited in Munich, Germany. RtfMRI data were acquired in three sessions and clinical abstinence was evaluated 3 months after the last NF session. Before the NF training, BOLD responses and clinical data did not differ between groups, apart from anger and impulsiveness. During NF training, BOLD responses of the active group were decreased in medial frontal areas/caudate nucleus, and increased, e.g. in the cuneus/precuneus and occipital cortex. Within the active group, the down-regulation of neuronal responses was more pronounced in patients who remained abstinent for at least 3 months after the intervention compared to patients with a relapse. As BOLD responses were comparable between groups before the NF training, functional variations during NF cannot be attributed to preexisting distinctions. We could not demonstrate that rtfMRI as an add-on treatment in patients with alcohol dependence leads to clinically superior abstinence for the active NF group after 3 months. However, the study provides evidence for a targeted modulation of addiction-associated brain responses in alcohol dependence using rtfMRI.
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Affiliation(s)
- Susanne Karch
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Nußbaumstr. 7, 80336, Munich, Germany
| | - Daniela Krause
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Nußbaumstr. 7, 80336, Munich, Germany.
| | - Kevin Lehnert
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Nußbaumstr. 7, 80336, Munich, Germany
| | - Julia Konrad
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Nußbaumstr. 7, 80336, Munich, Germany
| | - Dinah Haller
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Nußbaumstr. 7, 80336, Munich, Germany
| | - Boris-Stephan Rauchmann
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Nußbaumstr. 7, 80336, Munich, Germany
- Department of Radiology, University Hospital LMU, Munich, Germany
| | - Maximilian Maywald
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Nußbaumstr. 7, 80336, Munich, Germany
| | - Hessel Engelbregt
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Nußbaumstr. 7, 80336, Munich, Germany
- Hersencentrum Mental Health Institute, Amsterdam, The Netherlands
| | - Kristina Adorjan
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Nußbaumstr. 7, 80336, Munich, Germany
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU, Munich, Germany
| | - Gabriele Koller
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Nußbaumstr. 7, 80336, Munich, Germany
| | - Paul Reidler
- Department of Radiology, University Hospital LMU, Munich, Germany
| | - Temmuz Karali
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Nußbaumstr. 7, 80336, Munich, Germany
- Department of Radiology, University Hospital LMU, Munich, Germany
| | - Nadja Tschentscher
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Nußbaumstr. 7, 80336, Munich, Germany
| | - Birgit Ertl-Wagner
- Department of Radiology, University Hospital LMU, Munich, Germany
- Division of Neuroradiology, Department of Medical Imaging, The Hospital for Sick Children, University of Toronto, Toronto, Canada
| | - Oliver Pogarell
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Nußbaumstr. 7, 80336, Munich, Germany
| | - Marco Paolini
- Department of Radiology, University Hospital LMU, Munich, Germany
| | - Daniel Keeser
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Nußbaumstr. 7, 80336, Munich, Germany
- Department of Radiology, University Hospital LMU, Munich, Germany
- Munich Center for Neurosciences (MCN), LMU, Munich, Germany
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13
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Misaki M, Bodurka J, Paulus MP. A Library for fMRI Real-Time Processing Systems in Python (RTPSpy) With Comprehensive Online Noise Reduction, Fast and Accurate Anatomical Image Processing, and Online Processing Simulation. Front Neurosci 2022; 16:834827. [PMID: 35360171 PMCID: PMC8963181 DOI: 10.3389/fnins.2022.834827] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 02/14/2022] [Indexed: 01/18/2023] Open
Abstract
Real-time fMRI (rtfMRI) has enormous potential for both mechanistic brain imaging studies or treatment-oriented neuromodulation. However, the adaption of rtfMRI has been limited due to technical difficulties in implementing an efficient computational framework. Here, we introduce a python library for real-time fMRI (rtfMRI) data processing systems, Real-Time Processing System in python (RTPSpy), to provide building blocks for a custom rtfMRI application with extensive and advanced functionalities. RTPSpy is a library package including (1) a fast, comprehensive, and flexible online fMRI image processing modules comparable to offline denoising, (2) utilities for fast and accurate anatomical image processing to define an anatomical target region, (3) a simulation system of online fMRI processing to optimize a pipeline and target signal calculation, (4) simple interface to an external application for feedback presentation, and (5) a boilerplate graphical user interface (GUI) integrating operations with RTPSpy library. The fast and accurate anatomical image processing utility wraps external tools, including FastSurfer, ANTs, and AFNI, to make tissue segmentation and region of interest masks. We confirmed that the quality of the output masks was comparable with FreeSurfer, and the anatomical image processing could complete in a few minutes. The modular nature of RTPSpy provides the ability to use it for a simulation analysis to optimize a processing pipeline and target signal calculation. We present a sample script for building a real-time processing pipeline and running a simulation using RTPSpy. The library also offers a simple signal exchange mechanism with an external application using a TCP/IP socket. While the main components of the RTPSpy are the library modules, we also provide a GUI class for easy access to the RTPSpy functions. The boilerplate GUI application provided with the package allows users to develop a customized rtfMRI application with minimum scripting labor. The limitations of the package as it relates to environment-specific implementations are discussed. These library components can be customized and can be used in parts. Taken together, RTPSpy is an efficient and adaptable option for developing rtfMRI applications. Code available at: https://github.com/mamisaki/RTPSpy.
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Affiliation(s)
- Masaya Misaki
- Laureate Institute for Brain Research, Tulsa, OK, United States
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14
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Taylor JE, Yamada T, Kawashima T, Kobayashi Y, Yoshihara Y, Miyata J, Murai T, Kawato M, Motegi T. Depressive symptoms reduce when dorsolateral prefrontal cortex-precuneus connectivity normalizes after functional connectivity neurofeedback. Sci Rep 2022; 12:2581. [PMID: 35173179 PMCID: PMC8850610 DOI: 10.1038/s41598-022-05860-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 01/18/2022] [Indexed: 11/09/2022] Open
Abstract
Depressive disorders contribute heavily to global disease burden; This is possibly because patients are often treated homogeneously, despite having heterogeneous symptoms with differing underlying neural mechanisms. A novel treatment that can directly influence the neural circuit relevant to an individual patient's subset of symptoms might more precisely and thus effectively aid in the alleviation of their specific symptoms. We tested this hypothesis in a proof-of-concept study using fMRI functional connectivity neurofeedback. We targeted connectivity between the left dorsolateral prefrontal cortex/middle frontal gyrus and the left precuneus/posterior cingulate cortex, because this connection has been well-established as relating to a specific subset of depressive symptoms. Specifically, this connectivity has been shown in a data-driven manner to be less anticorrelated in patients with melancholic depression than in healthy controls. Furthermore, a posterior cingulate dominant state-which results in a loss of this anticorrelation-is expected to specifically relate to an increase in rumination symptoms such as brooding. In line with predictions, we found that, with neurofeedback training, the more a participant normalized this connectivity (restored the anticorrelation), the more related (depressive and brooding symptoms), but not unrelated (trait anxiety), symptoms were reduced. Because these results look promising, this paradigm next needs to be examined with a greater sample size and with better controls. Nonetheless, here we provide preliminary evidence for a correlation between the normalization of a neural network and a reduction in related symptoms. Showing their reproducibility, these results were found in two experiments that took place several years apart by different experimenters. Indicative of its potential clinical utility, effects of this treatment remained one-two months later.Clinical trial registration: Both experiments reported here were registered clinical trials (UMIN000015249, jRCTs052180169).
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Affiliation(s)
- Jessica Elizabeth Taylor
- Department of Decoded Neurofeedback (DecNef), Computational Neuroscience Laboratories, Advanced Telecommunications Research Institute International (ATR), Hikaridai 2-2-2. Seika-cho, Soraku, Kyoto, 619-0237, Japan
| | - Takashi Yamada
- Department of Decoded Neurofeedback (DecNef), Computational Neuroscience Laboratories, Advanced Telecommunications Research Institute International (ATR), Hikaridai 2-2-2. Seika-cho, Soraku, Kyoto, 619-0237, Japan.,Department of Cognitive, Linguistic and Psychological Sciences, Brown University, Providence, USA.,Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
| | - Takahiko Kawashima
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yuko Kobayashi
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yujiro Yoshihara
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Jun Miyata
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Toshiya Murai
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Mitsuo Kawato
- Department of Decoded Neurofeedback (DecNef), Computational Neuroscience Laboratories, Advanced Telecommunications Research Institute International (ATR), Hikaridai 2-2-2. Seika-cho, Soraku, Kyoto, 619-0237, Japan
| | - Tomokazu Motegi
- Department of Decoded Neurofeedback (DecNef), Computational Neuroscience Laboratories, Advanced Telecommunications Research Institute International (ATR), Hikaridai 2-2-2. Seika-cho, Soraku, Kyoto, 619-0237, Japan. .,Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Gunma, Japan.
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15
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Weiss F, Zhang J, Aslan A, Kirsch P, Gerchen MF. Feasibility of training the dorsolateral prefrontal-striatal network by real-time fMRI neurofeedback. Sci Rep 2022; 12:1669. [PMID: 35102203 PMCID: PMC8803939 DOI: 10.1038/s41598-022-05675-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 01/17/2022] [Indexed: 12/17/2022] Open
Abstract
Real-time fMRI neurofeedback (rt-fMRI NF) is a promising non-invasive technique that enables volitional control of usually covert brain processes. While most rt-fMRI NF studies so far have demonstrated the ability of the method to evoke changes in brain activity and improve symptoms of mental disorders, a recently evolving field is network-based functional connectivity (FC) rt-fMRI NF. However, FC rt-fMRI NF has methodological challenges such as respirational artefacts that could potentially bias the training if not controlled. In this randomized, double-blind, yoke-controlled, pre-registered FC rt-fMRI NF study with healthy participants (N = 40) studied over three training days, we tested the feasibility of an FC rt-fMRI NF approach with online global signal regression (GSR) to control for physiological artefacts for up-regulation of connectivity in the dorsolateral prefrontal-striatal network. While our pre-registered null hypothesis significance tests failed to reach criterion, we estimated the FC training effect at a medium effect size at the end of the third training day after rigorous control of physiological artefacts in the offline data. This hints at the potential of FC rt-fMRI NF for the development of innovative transdiagnostic circuit-specific interventional approaches for mental disorders and the effect should now be confirmed in a well-powered study.
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Affiliation(s)
- Franziska Weiss
- Department of Clinical Psychology, Central Institute of Mental Health (ZI), Heidelberg University/Medical Faculty Mannheim, J5, 68159, Mannheim, Germany
| | - Jingying Zhang
- Department of Clinical Psychology, Central Institute of Mental Health (ZI), Heidelberg University/Medical Faculty Mannheim, J5, 68159, Mannheim, Germany
| | - Acelya Aslan
- Department of Addiction Behavior and Addiction Medicine, Central Institute of Mental Health, Heidelberg University/Medical Faculty Mannheim, Mannheim, Germany
| | - Peter Kirsch
- Department of Clinical Psychology, Central Institute of Mental Health (ZI), Heidelberg University/Medical Faculty Mannheim, J5, 68159, Mannheim, Germany.,Bernstein Center for Computational Neuroscience Heidelberg/Mannheim, Mannheim, Germany.,Department of Psychology, Heidelberg University, Heidelberg, Germany
| | - Martin Fungisai Gerchen
- Department of Clinical Psychology, Central Institute of Mental Health (ZI), Heidelberg University/Medical Faculty Mannheim, J5, 68159, Mannheim, Germany. .,Bernstein Center for Computational Neuroscience Heidelberg/Mannheim, Mannheim, Germany. .,Department of Psychology, Heidelberg University, Heidelberg, Germany.
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16
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Taschereau-Dumouchel V, Cushing C, Lau H. Real-Time Functional MRI in the Treatment of Mental Health Disorders. Annu Rev Clin Psychol 2022; 18:125-154. [DOI: 10.1146/annurev-clinpsy-072220-014550] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Multiple mental disorders have been associated with dysregulation of precise brain processes. However, few therapeutic approaches can correct such specific patterns of brain activity. Since the late 1960s and early 1970s, many researchers have hoped that this feat could be achieved by closed-loop brain imaging approaches, such as neurofeedback, that aim to modulate brain activity directly. However, neurofeedback never gained mainstream acceptance in mental health, in part due to methodological considerations. In this review, we argue that, when contemporary methodological guidelines are followed, neurofeedback is one of the few intervention methods in psychology that can be assessed in double-blind placebo-controlled trials. Furthermore, using new advances in machine learning and statistics, it is now possible to target very precise patterns of brain activity for therapeutic purposes. We review the recent literature in functional magnetic resonance imaging neurofeedback and discuss current and future applications to mental health. Expected final online publication date for the Annual Review of Clinical Psychology, Volume 18 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Vincent Taschereau-Dumouchel
- Department of Psychiatry and Addictology, Université de Montréal, Montréal, Québec, Canada
- Centre de Recherche de l'Institut Universitaire en Santé Mentale de Montréal, Montréal, Québec, Canada
| | - Cody Cushing
- Department of Psychology, University of California, Los Angeles, California, USA
| | - Hakwan Lau
- RIKEN Center for Brain Science, Wakoshi, Saitama, Japan
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17
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Krause F, Kogias N, Krentz M, Lührs M, Goebel R, Hermans EJ. Self-regulation of stress-related large-scale brain network balance using real-time fMRI neurofeedback. Neuroimage 2021; 243:118527. [PMID: 34469815 DOI: 10.1016/j.neuroimage.2021.118527] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 08/23/2021] [Accepted: 08/25/2021] [Indexed: 10/20/2022] Open
Abstract
It has recently been shown that acute stress affects the allocation of neural resources between large-scale brain networks, and the balance between the executive control network and the salience network in particular. Maladaptation of this dynamic resource reallocation process is thought to play a major role in stress-related psychopathology, suggesting that stress resilience may be determined by the retained ability to adaptively reallocate neural resources between these two networks. Actively training this ability could hence be a potentially promising way to increase resilience in individuals at risk for developing stress-related symptomatology. Using real-time functional Magnetic Resonance Imaging, the current study investigated whether individuals can learn to self-regulate stress-related large-scale network balance. Participants were engaged in a bidirectional and implicit real-time fMRI neurofeedback paradigm in which they were intermittently provided with a visual representation of the difference signal between the average activation of the salience and executive control networks, and tasked with attempting to self-regulate this signal. Our results show that, given feedback about their performance over three training sessions, participants were able to (1) learn strategies to differentially control the balance between SN and ECN activation on demand, as well as (2) successfully transfer this newly learned skill to a situation where they (a) did not receive any feedback anymore, and (b) were exposed to an acute stressor in form of the prospect of a mild electric stimulation. The current study hence constitutes an important first successful demonstration of neurofeedback training based on stress-related large-scale network balance - a novel approach that has the potential to train control over the central response to stressors in real-life and could build the foundation for future clinical interventions that aim at increasing resilience.
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Affiliation(s)
- Florian Krause
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.
| | - Nikos Kogias
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Martin Krentz
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Michael Lührs
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Research and Development, Brain Innovation B.V., Maastricht, the Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Research and Development, Brain Innovation B.V., Maastricht, the Netherlands
| | - Erno J Hermans
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
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18
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Misaki M, Bodurka J. The impact of real-time fMRI denoising on online evaluation of brain activity and functional connectivity. J Neural Eng 2021; 18. [PMID: 34126595 DOI: 10.1088/1741-2552/ac0b33] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 06/14/2021] [Indexed: 11/11/2022]
Abstract
Objective. Comprehensive denoising is imperative in functional magnetic resonance imaging (fMRI) analysis to reliably evaluate neural activity from the blood oxygenation level dependent signal. In real-time fMRI, however, only a minimal denoising process has been applied and the impact of insufficient denoising on online brain activity estimation has not been assessed comprehensively. This study evaluated the noise reduction performance of online fMRI processes in a real-time estimation of regional brain activity and functional connectivity.Approach.We performed a series of real-time processing simulations of online fMRI processing, including slice-timing correction, motion correction, spatial smoothing, signal scaling, and noise regression with high-pass filtering, motion parameters, motion derivatives, global signal, white matter/ventricle average signals, and physiological noise models with image-based retrospective correction of physiological motion effects (RETROICOR) and respiration volume per time (RVT).Main results.All the processing was completed in less than 400 ms for whole-brain voxels. Most processing had a benefit for noise reduction except for RVT that did not work due to the limitation of the online peak detection. The global signal regression, white matter/ventricle signal regression, and RETROICOR had a distinctive noise reduction effect, depending on the target signal, and could not substitute for each other. Global signal regression could eliminate the noise-associated bias in the mean dynamic functional connectivity across time.Significance.The results indicate that extensive real-time denoising is possible and highly recommended for real-time fMRI applications.
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Affiliation(s)
- Masaya Misaki
- Laureate Institute for Brain Research, 6655 South Yale Avenue, Tulsa, OK 74136, United States of America
| | - Jerzy Bodurka
- Laureate Institute for Brain Research, 6655 South Yale Avenue, Tulsa, OK 74136, United States of America.,Stephenson School of Biomedical Engineering, University of Oklahoma, 173 Felgar St., Norman, OK 73019, United States of America
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19
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Zhou G, Olofsson JK, Koubeissi MZ, Menelaou G, Rosenow J, Schuele SU, Xu P, Voss JL, Lane G, Zelano C. Human hippocampal connectivity is stronger in olfaction than other sensory systems. Prog Neurobiol 2021; 201:102027. [PMID: 33640412 DOI: 10.1016/j.pneurobio.2021.102027] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 01/20/2021] [Accepted: 02/21/2021] [Indexed: 12/17/2022]
Abstract
During mammalian evolution, primate neocortex expanded, shifting hippocampal functional networks away from primary sensory cortices, towards association cortices. Reflecting this rerouting, human resting hippocampal functional networks preferentially include higher association cortices, while those in rodents retained primary sensory cortices. Research on human visual, auditory and somatosensory systems shows evidence of this rerouting. Olfaction, however, is unique among sensory systems in its relative structural conservation throughout mammalian evolution, and it is unknown whether human primary olfactory cortex was subject to the same rerouting. We combined functional neuroimaging and intracranial electrophysiology to directly compare hippocampal functional networks across human sensory systems. We show that human primary olfactory cortex-including the anterior olfactory nucleus, olfactory tubercle and piriform cortex-has stronger functional connectivity with hippocampal networks at rest, compared to other sensory systems. This suggests that unlike other sensory systems, olfactory-hippocampal connectivity may have been retained in mammalian evolution. We further show that olfactory-hippocampal connectivity oscillates with nasal breathing. Our findings suggest olfaction might provide insight into how memory and cognition depend on hippocampal interactions.
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Affiliation(s)
- Guangyu Zhou
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
| | - Jonas K Olofsson
- Department of Psychology, Stockholm University, Stockholm, Sweden; Emotional Brain Institute, Nathan S. Kline Institute, Orangeburg, NY, USA; Department of Child and Adolescent Psychiatry, New York University School of Medicine, New York, NY, USA
| | | | | | - Joshua Rosenow
- Department of Neurosurgery, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Stephan U Schuele
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Pengfei Xu
- Beijing Key Laboratory of Applied Experimental Psychology, Faculty of Psychology, Beijing Normal University, Beijing, China; Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, China; Guangdong-Hong Kong-Macao Greater Bay Area Research Institute for Neuroscience and Neurotechnologies, Kwun Tong, Hong Kong, China
| | - Joel L Voss
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Gregory Lane
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Christina Zelano
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
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20
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Trambaiolli LR, Kohl SH, Linden DEJ, Mehler DMA. Neurofeedback training in major depressive disorder: A systematic review of clinical efficacy, study quality and reporting practices. Neurosci Biobehav Rev 2021; 125:33-56. [PMID: 33587957 DOI: 10.1016/j.neubiorev.2021.02.015] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 02/05/2021] [Accepted: 02/06/2021] [Indexed: 12/28/2022]
Abstract
Major depressive disorder (MDD) is the leading cause of disability worldwide. Neurofeedback training has been suggested as a potential additional treatment option for MDD patients not reaching remission from standard care (i.e., psychopharmacology and psychotherapy). Here we systematically reviewed neurofeedback studies employing electroencephalography, or functional magnetic resonance-based protocols in depressive patients. Of 585 initially screened studies, 24 were included in our final sample (N = 480 patients in experimental and N = 194 in the control groups completing the primary endpoint). We evaluated the clinical efficacy across studies and attempted to group studies according to the control condition categories currently used in the field that affect clinical outcomes in group comparisons. In most studies, MDD patients showed symptom improvement superior to the control group(s). However, most articles did not comply with the most stringent study quality and reporting practices. We conclude with recommendations on best practices for experimental designs and reporting standards for neurofeedback training.
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Affiliation(s)
- Lucas R Trambaiolli
- Division of Basic Neuroscience, McLean Hospital, Harvard Medical School, Boston, USA.
| | - Simon H Kohl
- JARA Institute Molecular Neuroscience and Neuroimaging (INM-11), Jülich Research Centre, Germany; Department of Child and Adolescent Psychiatry, Medical Faculty, RWTH Aachen University, Germany
| | - David E J Linden
- School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, the Netherlands
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21
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Dudek E, Dodell-Feder D. The efficacy of real-time functional magnetic resonance imaging neurofeedback for psychiatric illness: A meta-analysis of brain and behavioral outcomes. Neurosci Biobehav Rev 2021; 121:291-306. [PMID: 33370575 PMCID: PMC7856210 DOI: 10.1016/j.neubiorev.2020.12.020] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 12/01/2020] [Accepted: 12/18/2020] [Indexed: 12/13/2022]
Abstract
Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) has gained popularity as an experimental treatment for a variety of psychiatric illnesses. However, there has yet to be a quantitative review regarding its efficacy. Here, we present the first meta-analysis of rtfMRI-NF for psychiatric disorders, evaluating its impact on brain and behavioral outcomes. Our literature review identified 17 studies and 105 effect sizes across brain and behavioral outcomes. We find that rtfMRI-NF produces a medium-sized effect on neural activity during training (g = .59, 95 % CI [.44, .75], p < .0001), a large-sized effect after training when no neurofeedback is provided (g = .84, 95 % CI [.37, 1.31], p = .005), and small-sized effects for behavioral outcomes (symptoms g = .37, 95 % CI [.16, .58], p = .002; cognition g = .23, 95 % CI [-.33, .78], p = .288). Mixed-effects analyses revealed few moderators. Together, these data suggest a positive impact of rtfMRI-NF on brain and behavioral outcomes, although more research is needed to determine how rtfMRI-NF works, for whom, and under what circumstances.
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Affiliation(s)
- Emily Dudek
- Department of Psychology, University of Rochester, United States
| | - David Dodell-Feder
- Department of Psychology, University of Rochester, United States; Department of Neuroscience, University of Rochester Medical Center, United States.
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22
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Mathiak K, Keller M. Clinical Application of Real-Time fMRI-Based Neurofeedback for Depression. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1305:275-293. [PMID: 33834405 DOI: 10.1007/978-981-33-6044-0_15] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/09/2022]
Abstract
Real-time functional magnetic resonance imaging-based neurofeedback (rt-fMRI NF) is a recent technique used to train self-regulation of circumscribed brain areas or networks. For clinical applications in depression, NF training targets brain areas with disturbed activation patterns, such as heightened reactivity of amygdala in response to negative stimuli, in order to normalize the neurophysiology and their behavioral correlates. Recent studies have targeted emotion processing areas such as the amygdala, the salience network, and top-down control areas such as the lateral prefrontal cortex. Different methods of rt-fMRI-based NF in depression, their potential for clinical improvement, and most recent advancements of this technology are discussed considering their role for future clinical applications. Initial findings of randomized controlled trials show promising results. However, for lasting treatment effects, clinical efficiency and optimal target regions, tasks, control conditions, and duration of training need to be established.
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Affiliation(s)
- Klaus Mathiak
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen, Germany.
| | - Micha Keller
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen, Germany
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23
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Rosenbaum D, Int-Veen I, Kroczek A, Hilsendegen P, Velten-Schurian K, Bihlmaier I, Fallgatter AJ, Ehlis AC. Amplitude of low frequency fluctuations (ALFF) of spontaneous and induced rumination in major depression: An fNIRS study. Sci Rep 2020; 10:21520. [PMID: 33299001 PMCID: PMC7725822 DOI: 10.1038/s41598-020-78317-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Accepted: 11/24/2020] [Indexed: 12/24/2022] Open
Abstract
In the current study, we investigated the amplitude of low frequency fluctuations (ALFF) at rest and during a rumination induction. Specifically, we explored the differences of cortical blood oxygenation using fNIRS in subjects with Major Depressive Disorder (MDD) and healthy controls (HC). Rumination was assessed as state and trait measure, as well as with a qualitative semi-structured interview. Qualitative and quantitative measures of rumination indicated that the MDD group showed elevated rumination regarding state and trait measures. Furthermore, rumination differed qualitatively between the groups. The MDD group showed higher levels of general rumination and increased rumination during the rumination induction. However, the MDD group did not show a carry-over effect of elevated rumination after the induction paradigm to the following resting-state measurement. On a neuronal level, we observed a general hypoactivity in the MDD group compared to the HC group. Moreover, both groups showed increased ALFF during the rumination induction compared to the rest phase, especially in temporo-parietal areas. However, no interaction effect of MDD status and rumination induction was found. The current findings are discussed with respect to the literature of paradigms used in the investigation of rumination and suggestions on general improvements in rumination research are given.
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Affiliation(s)
- David Rosenbaum
- Department of Psychiatry and Psychotherapy, University Hospital of Tuebingen, Calwerstraße 14, 72076, Tübingen, Germany.
| | - Isabell Int-Veen
- Department of Psychiatry and Psychotherapy, University Hospital of Tuebingen, Calwerstraße 14, 72076, Tübingen, Germany
| | - Agnes Kroczek
- Department of Psychiatry and Psychotherapy, University Hospital of Tuebingen, Calwerstraße 14, 72076, Tübingen, Germany
| | - Paula Hilsendegen
- Department of Psychiatry and Psychotherapy, University Hospital of Tuebingen, Calwerstraße 14, 72076, Tübingen, Germany
| | - Kerstin Velten-Schurian
- Department of Psychiatry and Psychotherapy, University Hospital of Tuebingen, Calwerstraße 14, 72076, Tübingen, Germany
| | - Isabel Bihlmaier
- Department of Psychiatry and Psychotherapy, University Hospital of Tuebingen, Calwerstraße 14, 72076, Tübingen, Germany
| | - Andreas J Fallgatter
- Department of Psychiatry and Psychotherapy, University Hospital of Tuebingen, Calwerstraße 14, 72076, Tübingen, Germany.,LEAD Graduate School and Research Network, University of Tübingen, Tübingen, Germany.,German Center for Neurodegenerative Disorders, Tübingen, Germany
| | - Ann-Christine Ehlis
- Department of Psychiatry and Psychotherapy, University Hospital of Tuebingen, Calwerstraße 14, 72076, Tübingen, Germany.,LEAD Graduate School and Research Network, University of Tübingen, Tübingen, Germany
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24
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Task-related activity in human visual cortex. PLoS Biol 2020; 18:e3000921. [PMID: 33156829 PMCID: PMC7673548 DOI: 10.1371/journal.pbio.3000921] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 11/18/2020] [Accepted: 09/21/2020] [Indexed: 01/27/2023] Open
Abstract
The brain exhibits widespread endogenous responses in the absence of visual stimuli, even at the earliest stages of visual cortical processing. Such responses have been studied in monkeys using optical imaging with a limited field of view over visual cortex. Here, we used functional MRI (fMRI) in human participants to study the link between arousal and endogenous responses in visual cortex. The response that we observed was tightly entrained to task timing, was spatially extensive, and was independent of visual stimulation. We found that this response follows dynamics similar to that of pupil size and heart rate, suggesting that task-related activity is related to arousal. Finally, we found that higher reward increased response amplitude while decreasing its trial-to-trial variability (i.e., the noise). Computational simulations suggest that increased temporal precision underlies both of these observations. Our findings are consistent with optical imaging studies in monkeys and support the notion that arousal increases precision of neural activity. The brain exhibits widespread endogenous responses in the absence of visual stimuli, even at the earliest stages of visual cortical processing. This fMRI study characterizes a widespread hemodynamic response in early visual cortex that is not related to visual input but instead reflects a participant’s engagement in a task, is modulated by expected monetary reward, and may reflect neural quenching.
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25
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Simões M, Abreu R, Direito B, Sayal A, Castelhano J, Carvalho P, Castelo-Branco M. How much of the BOLD-fMRI signal can be approximated from simultaneous EEG data: relevance for the transfer and dissemination of neurofeedback interventions. J Neural Eng 2020; 17:046007. [DOI: 10.1088/1741-2552/ab9a98] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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26
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Weiss F, Aslan A, Zhang J, Gerchen MF, Kiefer F, Kirsch P. Using mind control to modify cue-reactivity in AUD: the impact of mindfulness-based relapse prevention on real-time fMRI neurofeedback to modify cue-reactivity in alcohol use disorder: a randomized controlled trial. BMC Psychiatry 2020; 20:309. [PMID: 32546139 PMCID: PMC7298966 DOI: 10.1186/s12888-020-02717-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 06/04/2020] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Alcohol Use Disorder is a severe mental disorder affecting the individuals concerned, their family and friends and society as a whole. Despite its high prevalence, novel treatment options remain rather limited. Two innovative interventions used for treating severe disorders are the use of real-time functional magnetic resonance imaging neurofeedback that targets brain regions related to the disorder, and mindfulness-based treatments. In the context of the TRR SFB 265 C04 "Mindfulness-based relapse prevention as an addition to rtfMRI NFB intervention for patients with Alcohol Use Disorder (MiND)" study, both interventions will be combined to a state-of-the art intervention that will use mindfulness-based relapse prevention to improve the efficacy of a real-time neurofeedback intervention targeting the ventral striatum, which is a brain region centrally involved in cue-reactivity to alcohol-related stimuli. METHODS/DESIGN After inclusion, N = 88 patients will be randomly assigned to one of four groups. Two of those groups will receive mindfulness-based relapse prevention. All groups will receive two fMRI sessions and three real-time neurofeedback sessions in a double-blind manner and will regulate either the ventral striatum or the auditory cortex as a control region. Two groups will additionally receive five sessions of mindfulness-based relapse prevention prior to the neurofeedback intervention. After the last fMRI session, the participants will be followed-up monthly for a period of 3 months for an assessment of the relapse rate and clinical effects of the intervention. DISCUSSION The results of this study will give further insights into the efficacy of real-time functional magnetic resonance imaging neurofeedback interventions for the treatment of Alcohol Use Disorder. Additionally, the study will provide further insight on neurobiological changes in the brain caused by the neurofeedback intervention as well as by the mindfulness-based relapse prevention. The outcome might be useful to develop new treatment approaches targeting mechanisms of Alcohol Use Disorder with the goal to reduce relapse rates after discharge from the hospital. TRIAL REGISTRATION This trial is pre-registered at clinicaltrials.gov (trial identifier: NCT04366505; WHO Universal Trial Number (UTN): U1111-1250-2964). Registered 30 March 2020, published 29 April 2020.
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Affiliation(s)
- Franziska Weiss
- Department of Clinical Psychology, Central Institute of Mental Health (ZI), Heidelberg University/Medical Faculty Mannheim, 68159, Mannheim, Germany.
| | - Acelya Aslan
- grid.7700.00000 0001 2190 4373Department of Addiction Behavior and Addiction Medicine, Central Institute of Mental Health, Heidelberg University/Medical Faculty Mannheim, Mannheim, Germany
| | - Jingying Zhang
- grid.7700.00000 0001 2190 4373Department of Clinical Psychology, Central Institute of Mental Health (ZI), Heidelberg University/Medical Faculty Mannheim, 68159 Mannheim, Germany
| | - Martin Fungisai Gerchen
- grid.7700.00000 0001 2190 4373Department of Clinical Psychology, Central Institute of Mental Health (ZI), Heidelberg University/Medical Faculty Mannheim, 68159 Mannheim, Germany ,grid.7700.00000 0001 2190 4373Department of Psychology, Heidelberg University, Heidelberg, Germany ,grid.455092.fBernstein Center for Computational Neuroscience Heidelberg/Mannheim, Mannheim, Germany
| | - Falk Kiefer
- grid.7700.00000 0001 2190 4373Department of Addiction Behavior and Addiction Medicine, Central Institute of Mental Health, Heidelberg University/Medical Faculty Mannheim, Mannheim, Germany
| | - Peter Kirsch
- grid.7700.00000 0001 2190 4373Department of Clinical Psychology, Central Institute of Mental Health (ZI), Heidelberg University/Medical Faculty Mannheim, 68159 Mannheim, Germany ,grid.7700.00000 0001 2190 4373Department of Psychology, Heidelberg University, Heidelberg, Germany ,grid.455092.fBernstein Center for Computational Neuroscience Heidelberg/Mannheim, Mannheim, Germany
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27
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The Contribution of Functional Magnetic Resonance Imaging to the Understanding of the Effects of Acute Physical Exercise on Cognition. Brain Sci 2020; 10:brainsci10030175. [PMID: 32197357 PMCID: PMC7139910 DOI: 10.3390/brainsci10030175] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 03/04/2020] [Accepted: 03/13/2020] [Indexed: 02/06/2023] Open
Abstract
The fact that a single bout of acute physical exercise has a positive impact on cognition is well-established in the literature, but the neural correlates that underlie these cognitive improvements are not well understood. Here, the use of neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), offers great potential, which is just starting to be recognized. This review aims at providing an overview of those studies that used fMRI to investigate the effects of acute physical exercises on cerebral hemodynamics and cognition. To this end, a systematic literature survey was conducted by two independent reviewers across five electronic databases. The search returned 668 studies, of which 14 studies met the inclusion criteria and were analyzed in this systematic review. Although the findings of the reviewed studies suggest that acute physical exercise (e.g., cycling) leads to profound changes in functional brain activation, the small number of available studies and the great variability in the study protocols limits the conclusions that can be drawn with certainty. In order to overcome these limitations, new, more well-designed trials are needed that (i) use a more rigorous study design, (ii) apply more sophisticated filter methods in fMRI data analysis, (iii) describe the applied processing steps of fMRI data analysis in more detail, and (iv) provide a more precise exercise prescription.
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28
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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: 18] [Impact Index Per Article: 4.5] [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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29
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Scheinost D, Hsu TW, Avery EW, Hampson M, Constable RT, Chun MM, Rosenberg MD. Connectome-based neurofeedback: A pilot study to improve sustained attention. Neuroimage 2020; 212:116684. [PMID: 32114151 DOI: 10.1016/j.neuroimage.2020.116684] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 02/23/2020] [Accepted: 02/24/2020] [Indexed: 12/27/2022] Open
Abstract
Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback is a non-invasive, non-pharmacological therapeutic tool that may be useful for training behavior and alleviating clinical symptoms. Although previous work has used rt-fMRI to target brain activity in or functional connectivity between a small number of brain regions, there is growing evidence that symptoms and behavior emerge from interactions between a number of distinct brain areas. Here, we propose a new method for rt-fMRI, connectome-based neurofeedback, in which intermittent feedback is based on the strength of complex functional networks spanning hundreds of regions and thousands of functional connections. We first demonstrate the technical feasibility of calculating whole-brain functional connectivity in real-time and provide resources for implementing connectome-based neurofeedback. We next show that this approach can be used to provide accurate feedback about the strength of a previously defined connectome-based model of sustained attention, the saCPM, during task performance. Although, in our initial pilot sample, neurofeedback based on saCPM strength did not improve performance on out-of-scanner attention tasks, future work characterizing effects of network target, training duration, and amount of feedback on the efficacy of rt-fMRI can inform experimental or clinical trial designs.
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Affiliation(s)
- Dustin Scheinost
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA; Child Study Center, Yale School of Medicine, New Haven, CT, USA; Department of Statistics and Data Science, Yale University, New Haven, CT, USA; Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA.
| | - Tiffany W Hsu
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Emily W Avery
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Michelle Hampson
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA; Child Study Center, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - R Todd Constable
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA; Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA; Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Marvin M Chun
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA; Department of Psychology, Yale University, New Haven, CT, USA; Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Monica D Rosenberg
- Department of Psychology, Yale University, New Haven, CT, USA; Department of Psychology, University of Chicago, Chicago, IL, USA.
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