1
|
Yang X, Zeng Y, Jiao G, Gan X, Linden D, Hernaus D, Zhu C, Li K, Yao D, Yao S, Jiang Y, Becker B. A brief real-time fNIRS-informed neurofeedback training of the prefrontal cortex changes brain activity and connectivity during subsequent working memory challenge. Prog Neuropsychopharmacol Biol Psychiatry 2024; 132:110968. [PMID: 38354898 DOI: 10.1016/j.pnpbp.2024.110968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 11/06/2023] [Accepted: 02/11/2024] [Indexed: 02/16/2024]
Abstract
Working memory (WM) represents a building-block of higher cognitive functions and a wide range of mental disorders are associated with WM impairments. Initial studies have shown that several sessions of functional near-infrared spectroscopy (fNIRS) informed real-time neurofeedback (NF) allow healthy individuals to volitionally increase activity in the dorsolateral prefrontal cortex (DLPFC), a region critically involved in WM. For the translation to therapeutic or neuroenhancement applications, however, it is critical to assess whether fNIRS-NF success transfers into neural and behavioral WM enhancement in the absence of feedback. We therefore combined single-session fNIRS-NF of the left DLPFC with a randomized sham-controlled design (N = 62 participants) and a subsequent WM challenge with concomitant functional MRI. Over four runs of fNIRS-NF, the left DLPFC NF training group demonstrated enhanced neural activity in this region, reflecting successful acquisition of neural self-regulation. During the subsequent WM challenge, we observed no evidence for performance differences between the training and the sham group. Importantly, however, examination of the fMRI data revealed that - compared to the sham group - the training group exhibited significantly increased regional activity in the bilateral DLPFC and decreased left DLPFC - left anterior insula functional connectivity during the WM challenge. Exploratory analyses revealed a negative association between DLPFC activity and WM reaction times in the NF group. Together, these findings indicate that healthy individuals can learn to volitionally increase left DLPFC activity in a single training session and that the training success translates into WM-related neural activation and connectivity changes in the absence of feedback. This renders fNIRS-NF as a promising and scalable WM intervention approach that could be applied to various mental disorders.
Collapse
Affiliation(s)
- Xi Yang
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital; University of Electronic Science and Technology of China, Chengdu, China; MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands
| | - Yixu Zeng
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital; University of Electronic Science and Technology of China, Chengdu, China; MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Guojuan Jiao
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital; University of Electronic Science and Technology of China, Chengdu, China; MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xianyang Gan
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital; University of Electronic Science and Technology of China, Chengdu, China; MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - David Linden
- Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands
| | - Dennis Hernaus
- Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands
| | - Chaozhe Zhu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China
| | - Keshuang Li
- School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Dezhong Yao
- MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Shuxia Yao
- MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yihan Jiang
- Center for the Cognitive Science of Language, Beijing Language and Culture University, Beijing, China.
| | - Benjamin Becker
- The University of Hong Kong, State Key Laboratory of Brain and Cognitive Sciences, Hong Kong, China; The University of Hong Kong, Department of Psychology, Hong Kong, China.
| |
Collapse
|
2
|
Xia Z, Yang PY, Chen SL, Zhou HY, Yan C. Uncovering the power of neurofeedback: a meta-analysis of its effectiveness in treating major depressive disorders. Cereb Cortex 2024; 34:bhae252. [PMID: 38889442 DOI: 10.1093/cercor/bhae252] [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: 03/27/2024] [Revised: 05/25/2024] [Accepted: 06/04/2024] [Indexed: 06/20/2024] Open
Abstract
Neurofeedback, a non-invasive intervention, has been increasingly used as a potential treatment for major depressive disorders. However, the effectiveness of neurofeedback in alleviating depressive symptoms remains uncertain. To address this gap, we conducted a comprehensive meta-analysis to evaluate the efficacy of neurofeedback as a treatment for major depressive disorders. We conducted a comprehensive meta-analysis of 22 studies investigating the effects of neurofeedback interventions on depression symptoms, neurophysiological outcomes, and neuropsychological function. Our analysis included the calculation of Hedges' g effect sizes and explored various moderators like intervention settings, study designs, and demographics. Our findings revealed that neurofeedback intervention had a significant impact on depression symptoms (Hedges' g = -0.600) and neurophysiological outcomes (Hedges' g = -0.726). We also observed a moderate effect size for neurofeedback intervention on neuropsychological function (Hedges' g = -0.418). As expected, we observed that longer intervention length was associated with better outcomes for depressive symptoms (β = -4.36, P < 0.001) and neuropsychological function (β = -2.89, P = 0.003). Surprisingly, we found that shorter neurofeedback sessions were associated with improvements in neurophysiological outcomes (β = 3.34, P < 0.001). Our meta-analysis provides compelling evidence that neurofeedback holds promising potential as a non-pharmacological intervention option for effectively improving depressive symptoms, neurophysiological outcomes, and neuropsychological function in individuals with major depressive disorders.
Collapse
Affiliation(s)
- Zheng Xia
- Key Laboratory of Brain Functional Genomics (MOE&STCSM), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, 3663 North Zhongshan Road, Shanghai 200062, China
- Shanghai Changning Mental Health Center, 299 Xiehe Road, Shanghai 200335, China
| | - Peng-Yuan Yang
- Department of Methodology and Statistics, Faculty of Behavioral and Social Sciences, Tilburg University, Warandelaan 2, 5037 AB, Tilburg, The Netherlands
| | - Si-Lu Chen
- Shanghai Changning Mental Health Center, 299 Xiehe Road, Shanghai 200335, China
| | - Han-Yu Zhou
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, 3663 North Zhongshan Road, Shanghai 200062, China
| | - Chao Yan
- Key Laboratory of Brain Functional Genomics (MOE&STCSM), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, 3663 North Zhongshan Road, Shanghai 200062, China
- Shanghai Changning Mental Health Center, 299 Xiehe Road, Shanghai 200335, China
- Key Laboratory of Philosophy and Social Science of Anhui Province on Adolescent Mental Health and Crisis Intelligence Intervention, Hefei Normal University, 1688 Lianhua Road, Hefei 230601, China
| |
Collapse
|
3
|
Lucas JT, Abramson ZR, Epstein K, Morin CE, Jaju A, Lee JW, Lee CL, Sitaram R, Voss SD, Hudson MM, Constine LS, Hua CH. Imaging Assessment of Radiation Therapy-Related Normal Tissue Injury in Children: A PENTEC Visionary Statement. Int J Radiat Oncol Biol Phys 2024; 119:669-680. [PMID: 38760116 DOI: 10.1016/j.ijrobp.2024.03.006] [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: 03/08/2024] [Indexed: 05/19/2024]
Abstract
The Pediatric Normal Tissue Effects in the Clinic (PENTEC) consortium has made significant contributions to understanding and mitigating the adverse effects of childhood cancer therapy. This review addresses the role of diagnostic imaging in detecting, screening, and comprehending radiation therapy-related late effects in children, drawing insights from individual organ-specific PENTEC reports. We further explore how the development of imaging biomarkers for key organ systems, alongside technical advancements and translational imaging approaches, may enhance the systematic application of imaging evaluations in childhood cancer survivors. Moreover, the review critically examines knowledge gaps and identifies technical and practical limitations of existing imaging modalities in the pediatric population. Addressing these challenges may expand access to, minimize the risk of, and optimize the real-world application of, new imaging techniques. The PENTEC team envisions this document as a roadmap for the future development of imaging strategies in childhood cancer survivors, with the overarching goal of improving long-term health outcomes and quality of life for this vulnerable population.
Collapse
Affiliation(s)
| | - Zachary R Abramson
- Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Katherine Epstein
- Division of Radiology and Medical Imaging, UC Department of Radiology, Cincinnati, Ohio
| | - Cara E Morin
- Division of Radiology and Medical Imaging, UC Department of Radiology, Cincinnati, Ohio
| | - Alok Jaju
- Department of Medical Imaging, Ann and Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | | | - Chang-Lung Lee
- Department of Radiation Oncology and; Pathology, Duke University School of Medicine, Durham, North Carolina
| | - Ranganatha Sitaram
- Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Stephan D Voss
- Department of Radiology, Harvard Medical School, Boston, Massachusetts
| | - Melissa M Hudson
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Louis S Constine
- Department of Radiation Oncology, James P. Wilmot Cancer Institute, University of Rochester Medical Center, Rochester, New York
| | | |
Collapse
|
4
|
Wider W, Mutang JA, Chua BS, Pang NTP, Jiang L, Fauzi MA, Udang LN. Mapping the evolution of neurofeedback research: a bibliometric analysis of trends and future directions. Front Hum Neurosci 2024; 18:1339444. [PMID: 38799297 PMCID: PMC11116792 DOI: 10.3389/fnhum.2024.1339444] [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: 11/22/2023] [Accepted: 04/23/2024] [Indexed: 05/29/2024] Open
Abstract
Introduction This study conducts a bibliometric analysis on neurofeedback research to assess its current state and potential future developments. Methods It examined 3,626 journal articles from the Web of Science (WoS) using co-citation and co-word methods. Results The co-citation analysis identified three major clusters: "Real-Time fMRI Neurofeedback and Self-Regulation of Brain Activity," "EEG Neurofeedback and Cognitive Performance Enhancement," and "Treatment of ADHD Using Neurofeedback." The co-word analysis highlighted four key clusters: "Neurofeedback in Mental Health Research," "Brain-Computer Interfaces for Stroke Rehabilitation," "Neurofeedback for ADHD in Youth," and "Neural Mechanisms of Emotion and Self-Regulation with Advanced Neuroimaging. Discussion This in-depth bibliometric study significantly enhances our understanding of the dynamic field of neurofeedback, indicating its potential in treating ADHD and improving performance. It offers non-invasive, ethical alternatives to conventional psychopharmacology and aligns with the trend toward personalized medicine, suggesting specialized solutions for mental health and rehabilitation as a growing focus in medical practice.
Collapse
Affiliation(s)
- Walton Wider
- Faculty of Business and Communications, INTI International University, Nilai, Negeri Sembilan, Malaysia
| | - Jasmine Adela Mutang
- Faculty of Psychology and Education, Universiti Malaysia Sabah, Kota Kinabalu, Sabah, Malaysia
| | - Bee Seok Chua
- Faculty of Psychology and Education, Universiti Malaysia Sabah, Kota Kinabalu, Sabah, Malaysia
| | - Nicholas Tze Ping Pang
- Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Kota Kinabalu, Sabah, Malaysia
| | - Leilei Jiang
- Faculty of Education and Liberal Arts, INTI International University, Nilai, Negeri Sembilan, Malaysia
| | - Muhammad Ashraf Fauzi
- Faculty of Industrial Management, Universiti Malaysia Pahang Al-Sultan Abdullah, Pekan, Pahang, Malaysia
| | - Lester Naces Udang
- Faculty of Liberal Arts, Shinawatra University, Pathumthani, Thailand
- College of Education, University of the Philippines, Diliman, Philippines
| |
Collapse
|
5
|
Aupperle RL, Kuplicki R, Tsuchiyagaito A, Akeman E, Sturycz-Taylor CA, DeVille D, Lasswell T, Misaki M, Berg H, McDermott TJ, Touthang J, Ballard ED, Cha C, Schacter DL, Paulus MP. Ventromedial prefrontal cortex activation and neurofeedback modulation during episodic future thinking for individuals with suicidal thoughts and behaviors. Behav Res Ther 2024; 176:104522. [PMID: 38547724 PMCID: PMC11103812 DOI: 10.1016/j.brat.2024.104522] [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: 09/29/2023] [Revised: 01/30/2024] [Accepted: 03/14/2024] [Indexed: 04/08/2024]
Abstract
Individuals experiencing suicidal thoughts and behaviors (STBs) show less specificity and positivity during episodic future thinking (EFT). Here, we present findings from two studies aiming to (1) further our understanding of how STBs may relate to neural responsivity during EFT and (2) examine the feasibility of modulating EFT-related activation using real-time fMRI neurofeedback (rtfMRI-nf). Study 1 involved 30 individuals with major depressive disorder (MDD; half with STBs) who performed an EFT task during fMRI, for which they imagined personally-relevant future positive, negative, or neutral events. Positive EFT elicited greater ventromedial prefrontal cortex (vmPFC) activation compared to negative EFT. Importantly, the MDD + STB group exhibited reduced vmPFC activation across all EFT conditions compared to MDD-STB; although EFT fluency and subjective experience remained consistent across groups. Study 2 included rtfMRI-nf focused on vmPFC modulation during positive EFT for six participants with MDD + STBs. Results support the feasibility and acceptability of the rtfMRI-nf protocol and quantitative and qualitative observations are provided to help inform future, larger studies aiming to examine similar neurofeedback protocols. Results implicate vmPFC blunting as a promising treatment target for MDD + STBs and suggest rtfMRI-nf as one potential technique to explore for enhancing vmPFC engagement.
Collapse
Affiliation(s)
- R L Aupperle
- Laureate Institute for Brain Research, 6655 S. Yale Ave., Tulsa, OK, 74008, USA; School of Community Medicine, 1215 South Boulder Ave W., The University of Tulsa, Tulsa, OK, 74119, USA.
| | - R Kuplicki
- Laureate Institute for Brain Research, 6655 S. Yale Ave., Tulsa, OK, 74008, USA
| | - A Tsuchiyagaito
- Laureate Institute for Brain Research, 6655 S. Yale Ave., Tulsa, OK, 74008, USA
| | - E Akeman
- Laureate Institute for Brain Research, 6655 S. Yale Ave., Tulsa, OK, 74008, USA
| | - C A Sturycz-Taylor
- Laureate Institute for Brain Research, 6655 S. Yale Ave., Tulsa, OK, 74008, USA
| | - D DeVille
- Department of Psychiatry, University of California San Diego, 4510 Executive Drive, San Diego, CA, 92121, USA
| | - T Lasswell
- Laureate Institute for Brain Research, 6655 S. Yale Ave., Tulsa, OK, 74008, USA
| | - M Misaki
- Laureate Institute for Brain Research, 6655 S. Yale Ave., Tulsa, OK, 74008, USA
| | - H Berg
- Laureate Institute for Brain Research, 6655 S. Yale Ave., Tulsa, OK, 74008, USA
| | - T J McDermott
- Laureate Institute for Brain Research, 6655 S. Yale Ave., Tulsa, OK, 74008, USA
| | - J Touthang
- Laureate Institute for Brain Research, 6655 S. Yale Ave., Tulsa, OK, 74008, USA
| | - E D Ballard
- Experimental Therapeutics and Pathophysiological Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, MD, USA
| | - C Cha
- Department of Psychology, Columbia University, 428 Horace Mann, New York, NY, 10027, USA
| | - D L Schacter
- Department of Psychology, Harvard University, 33 Kirkland St., William James Hall, Cambridge, MA, 02138, USA
| | - M P Paulus
- Laureate Institute for Brain Research, 6655 S. Yale Ave., Tulsa, OK, 74008, USA; School of Community Medicine, 1215 South Boulder Ave W., The University of Tulsa, Tulsa, OK, 74119, USA
| |
Collapse
|
6
|
Kim K, Oblak E, Manella K, Sulzer J. Simulated operant reflex conditioning environment reveals effects of feedback parameters. PLoS One 2024; 19:e0300338. [PMID: 38512998 PMCID: PMC10956789 DOI: 10.1371/journal.pone.0300338] [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: 07/10/2023] [Accepted: 02/26/2024] [Indexed: 03/23/2024] Open
Abstract
Operant conditioning of neural activation has been researched for decades in humans and animals. Many theories suggest two parallel learning processes, implicit and explicit. The degree to which feedback affects these processes individually remains to be fully understood and may contribute to a large percentage of non-learners. Our goal is to determine the explicit decision-making processes in response to feedback representing an operant conditioning environment. We developed a simulated operant conditioning environment based on a feedback model of spinal reflex excitability, one of the simplest forms of neural operant conditioning. We isolated the perception of the feedback signal from self-regulation of an explicit unskilled visuomotor task, enabling us to quantitatively examine feedback strategy. Our hypothesis was that feedback type, biological variability, and reward threshold affect operant conditioning performance and operant strategy. Healthy individuals (N = 41) were instructed to play a web application game using keyboard inputs to rotate a virtual knob representative of an operant strategy. The goal was to align the knob with a hidden target. Participants were asked to "down-condition" the amplitude of the virtual feedback signal, which was achieved by placing the knob as close as possible to the hidden target. We varied feedback type (knowledge of performance, knowledge of results), biological variability (low, high), and reward threshold (easy, moderate, difficult) in a factorial design. Parameters were extracted from real operant conditioning data. Our main outcomes were the feedback signal amplitude (performance) and the mean change in dial position (operant strategy). We observed that performance was modulated by variability, while operant strategy was modulated by feedback type. These results show complex relations between fundamental feedback parameters and provide the principles for optimizing neural operant conditioning for non-responders.
Collapse
Affiliation(s)
- Kyoungsoon Kim
- University of Texas at Austin, Austin, Texas, United States of America
| | - Ethan Oblak
- RIKEN Center for Brain Science, Saitama, Japan
| | - Kathleen Manella
- Nova Southeastern University, Clearwater, Florida, United States of America
| | - James Sulzer
- MetroHealth Hospital and Case Western Reserve University, Cleveland, Ohio, United States of America
| |
Collapse
|
7
|
Voigt JD, Mosier M, Tendler A. Systematic review and meta-analysis of neurofeedback and its effect on posttraumatic stress disorder. Front Psychiatry 2024; 15:1323485. [PMID: 38577405 PMCID: PMC10993781 DOI: 10.3389/fpsyt.2024.1323485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 02/09/2024] [Indexed: 04/06/2024] Open
Abstract
Background To date, only one systematic review and meta-analysis of randomized controlled trials (RCTs) has evaluated the effect of neurofeedback in PTSD, which included only four studies and found an uncertainty of the effect of EEG-NF on PTSD symptoms. This meta-analysis is an update considering that numerous studies have since been published. Additionally, more recent studies have included fMRI-NF as well as fMRI-guided or -inspired EEG NF. Methods Systematic literature searches for RCTs were conducted in three online databases. Additional hand searches of each study identified and of systematic reviews and meta-analyses published were also undertaken. Outcomes evaluated the effect of neurofeedback vs. a control (active, sham, and waiting list) on their effects in reducing PTSD symptoms using various health instruments. Meta-analytical methods used were inverse variance random-effects models measuring both mean and standardized mean differences. Quality and certainty of the evidence were assessed using GRADE. Adverse events were also evaluated. Results A total of 17 studies were identified evaluating a total of 628 patients. There were 10 studies used in the meta-analysis. Results from all studies identified favored neurofeedback's effect on reducing PTSD symptoms including BDI pretest-posttest [mean difference (MD): 8.30 (95% CI: 3.09 to 13.52; P = 0.002; I 2 = 0%)]; BDI pretest-follow-up (MD: 8.75 (95% CI: 3.53 to 13.97; P < 0.00001; I 2 = 0%); CAPS-5 pretest-posttest [MD: 7.01 (95% CI: 1.36 to 12.66; P = 0.02; I 2 = 86%)]; CAPS-5 pretest-follow-up (MD: 10 (95% CI: 1.29 to 21.29; P = 0.006; I 2 = 77%); PCL-5 pretest-posttest (MD: 7.14 (95% CI: 3.08 to 11.2; P = 0.0006; I 2 = 0%); PCL-5 pretest-follow-up (MD: 14.95 (95% CI: 7.95 to 21.96; P < 0.0001; I 2 = 0%). Other studies reported improvements using various other instruments. GRADE assessments of CAPS, PCL, and BDI demonstrated a moderate/high level in the quality of the evidence that NF has a positive clinical effect. Conclusion Based on newer published studies and the outcomes measured, NF has demonstrated a clinically meaningful effect size, with an increased effect size at follow-up. This clinically meaningful effect appears to be driven by newer fMRI-guided NF and deeper brain derivates of it.
Collapse
Affiliation(s)
- Jeffrey D. Voigt
- Medical Device Consultants of Ridgewood, LLC, Waldwick, NJ, United States
| | - Michael Mosier
- EMB Statistical Solutions, LLC, Topeka, KS, United States
| | - Aron Tendler
- Department Life Sciences, Ben-Gurion University of the Negev, Be’er Sheva, Israel
| |
Collapse
|
8
|
Watve A, Haugg A, Frei N, Koush Y, Willinger D, Bruehl AB, Stämpfli P, Scharnowski F, Sladky R. Facing emotions: real-time fMRI-based neurofeedback using dynamic emotional faces to modulate amygdala activity. Front Neurosci 2024; 17:1286665. [PMID: 38274498 PMCID: PMC10808718 DOI: 10.3389/fnins.2023.1286665] [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: 08/31/2023] [Accepted: 12/18/2023] [Indexed: 01/27/2024] Open
Abstract
Introduction Maladaptive functioning of the amygdala has been associated with impaired emotion regulation in affective disorders. Recent advances in real-time fMRI neurofeedback have successfully demonstrated the modulation of amygdala activity in healthy and psychiatric populations. In contrast to an abstract feedback representation applied in standard neurofeedback designs, we proposed a novel neurofeedback paradigm using naturalistic stimuli like human emotional faces as the feedback display where change in the facial expression intensity (from neutral to happy or from fearful to neutral) was coupled with the participant's ongoing bilateral amygdala activity. Methods The feasibility of this experimental approach was tested on 64 healthy participants who completed a single training session with four neurofeedback runs. Participants were assigned to one of the four experimental groups (n = 16 per group), i.e., happy-up, happy-down, fear-up, fear-down. Depending on the group assignment, they were either instructed to "try to make the face happier" by upregulating (happy-up) or downregulating (happy-down) the amygdala or to "try to make the face less fearful" by upregulating (fear-up) or downregulating (fear-down) the amygdala feedback signal. Results Linear mixed effect analyses revealed significant amygdala activity changes in the fear condition, specifically in the fear-down group with significant amygdala downregulation in the last two neurofeedback runs as compared to the first run. The happy-up and happy-down groups did not show significant amygdala activity changes over four runs. We did not observe significant improvement in the questionnaire scores and subsequent behavior. Furthermore, task-dependent effective connectivity changes between the amygdala, fusiform face area (FFA), and the medial orbitofrontal cortex (mOFC) were examined using dynamic causal modeling. The effective connectivity between FFA and the amygdala was significantly increased in the happy-up group (facilitatory effect) and decreased in the fear-down group. Notably, the amygdala was downregulated through an inhibitory mechanism mediated by mOFC during the first training run. Discussion In this feasibility study, we intended to address key neurofeedback processes like naturalistic facial stimuli, participant engagement in the task, bidirectional regulation, task congruence, and their influence on learning success. It demonstrated that such a versatile emotional face feedback paradigm can be tailored to target biased emotion processing in affective disorders.
Collapse
Affiliation(s)
- Apurva Watve
- Department of Psychiatry, Psychotherapy, and Psychosomatics, Psychiatric University Hospital, University of Zürich, Zürich, Switzerland
| | - Amelie Haugg
- Department of Child and Adolescent Psychiatry, Psychiatric Hospital, University of Zürich, Zürich, Switzerland
| | - Nada Frei
- Department of Child and Adolescent Psychiatry, Psychiatric Hospital, University of Zürich, Zürich, Switzerland
| | - Yury Koush
- Magnetic Resonance Research Center (MRRC), Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, United States
| | - David Willinger
- Department of Child and Adolescent Psychiatry, Psychiatric Hospital, University of Zürich, Zürich, Switzerland
- Division of Psychodynamics, Department of Psychology and Psychodynamics, Karl Landsteiner University of Health Sciences, Krems an der Donau, Lower Austria, Austria
- Neuroscience Center Zürich, University of Zürich and Swiss Federal Institute of Technology, Zürich, Switzerland
| | - Annette Beatrix Bruehl
- Department of Psychiatry, Psychotherapy, and Psychosomatics, Psychiatric University Hospital, University of Zürich, Zürich, Switzerland
- Center for Affective, Stress and Sleep Disorders, Psychiatric University Hospital Basel, Basel, Switzerland
| | - Philipp Stämpfli
- Department of Psychiatry, Psychotherapy, and Psychosomatics, Psychiatric University Hospital, University of Zürich, Zürich, Switzerland
| | - Frank Scharnowski
- Department of Psychiatry, Psychotherapy, and Psychosomatics, Psychiatric University Hospital, University of Zürich, Zürich, Switzerland
- Neuroscience Center Zürich, University of Zürich and Swiss Federal Institute of Technology, Zürich, Switzerland
- Zurich Center for Integrative Human Physiology, Faculty of Medicine, University of Zürich, Zürich, Switzerland
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Ronald Sladky
- Department of Psychiatry, Psychotherapy, and Psychosomatics, Psychiatric University Hospital, University of Zürich, Zürich, Switzerland
- Social, Cognitive and Affective Neuroscience Unit, Department of Basic Psychological Research and Research Methods, Faculty of Psychology, University of Vienna, Vienna, Austria
| |
Collapse
|
9
|
Sparling T, Iyer L, Pasquina P, Petrus E. Cortical Reorganization after Limb Loss: Bridging the Gap between Basic Science and Clinical Recovery. J Neurosci 2024; 44:e1051232024. [PMID: 38171645 PMCID: PMC10851691 DOI: 10.1523/jneurosci.1051-23.2023] [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: 06/08/2023] [Revised: 08/28/2023] [Accepted: 09/29/2023] [Indexed: 01/05/2024] Open
Abstract
Despite the increasing incidence and prevalence of amputation across the globe, individuals with acquired limb loss continue to struggle with functional recovery and chronic pain. A more complete understanding of the motor and sensory remodeling of the peripheral and central nervous system that occurs postamputation may help advance clinical interventions to improve the quality of life for individuals with acquired limb loss. The purpose of this article is to first provide background clinical context on individuals with acquired limb loss and then to provide a comprehensive review of the known motor and sensory neural adaptations from both animal models and human clinical trials. Finally, the article bridges the gap between basic science researchers and clinicians that treat individuals with limb loss by explaining how current clinical treatments may restore function and modulate phantom limb pain using the underlying neural adaptations described above. This review should encourage the further development of novel treatments with known neurological targets to improve the recovery of individuals postamputation.Significance Statement In the United States, 1.6 million people live with limb loss; this number is expected to more than double by 2050. Improved surgical procedures enhance recovery, and new prosthetics and neural interfaces can replace missing limbs with those that communicate bidirectionally with the brain. These advances have been fairly successful, but still most patients experience persistent problems like phantom limb pain, and others discontinue prostheses instead of learning to use them daily. These problematic patient outcomes may be due in part to the lack of consensus among basic and clinical researchers regarding the plasticity mechanisms that occur in the brain after amputation injuries. Here we review results from clinical and animal model studies to bridge this clinical-basic science gap.
Collapse
Affiliation(s)
- Tawnee Sparling
- Department of Physical Medicine and Rehabilitation, Uniformed Services University of the Health Sciences, Bethesda, Maryland 20814
| | - Laxmi Iyer
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, Maryland 20817
| | - Paul Pasquina
- Department of Physical Medicine and Rehabilitation, Uniformed Services University of the Health Sciences, Bethesda, Maryland 20814
| | - Emily Petrus
- Department of Anatomy, Physiology and Genetics, Uniformed Services University, Bethesda, Maryland 20814
| |
Collapse
|
10
|
Zito GA, de Sousa Ribeiro R, Kamal E, Ledergerber D, Imbach L, Polania R. Self-modulation of the sense of agency via neurofeedback enhances sensory-guided behavioral control. Cereb Cortex 2023; 33:11447-11455. [PMID: 37750349 DOI: 10.1093/cercor/bhad360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 09/11/2023] [Accepted: 09/12/2023] [Indexed: 09/27/2023] Open
Abstract
The sense of agency is a fundamental aspect of human self-consciousness, whose neural correlates encompass widespread brain networks. Research has explored the neuromodulatory properties of the sense of agency with noninvasive brain stimulation, which induces exogenous manipulations of brain activity; however, it is unknown whether endogenous modulation of the sense of agency is also achievable. We investigated whether the sense of agency can be self-regulated with electroencephalography-based neurofeedback. We conducted 2 experiments in which healthy humans performed a motor task while their motor control was artificially disrupted, and gave agency statements on their perceived control. We first identified the electrophysiological response to agency processing, and then applied neurofeedback in a parallel, sham-controlled design, where participants learnt to self-modulate their sense of agency. We found that behavioral measures of agency and performance on the task decreased with the increasing disruption of control. This was negatively correlated with power spectral density in the theta band, and positively correlated in the alpha and beta bands, at central and parietal electrodes. After neurofeedback training of central theta rhythms, participants improved their actual control over the task, and this was associated with a significant decrease in the frequency band trained via neurofeedback. Thus, self-regulation of theta rhythms can improve sensory-guided behavior.
Collapse
Affiliation(s)
- Giuseppe A Zito
- Decision Neuroscience Lab, Department of Health Sciences and Technology, ETH Zurich, 8057 Zurich, CH, Switzerland
- Swiss Paraplegic Research, 6207 Nottwil, CH, Switzerland
| | - Ricardo de Sousa Ribeiro
- Decision Neuroscience Lab, Department of Health Sciences and Technology, ETH Zurich, 8057 Zurich, CH, Switzerland
| | - Eshita Kamal
- Decision Neuroscience Lab, Department of Health Sciences and Technology, ETH Zurich, 8057 Zurich, CH, Switzerland
| | | | - Lukas Imbach
- Swiss Epilepsy Center, Clinic Lengg, 8008 Zurich, CH, Switzerland
| | - Rafael Polania
- Decision Neuroscience Lab, Department of Health Sciences and Technology, ETH Zurich, 8057 Zurich, CH, Switzerland
| |
Collapse
|
11
|
Peng K, Wammes JD, Nguyen A, Cătălin Iordan M, Norman KA, Turk-Browne NB. INDUCING REPRESENTATIONAL CHANGE IN THE HIPPOCAMPUS THROUGH REAL-TIME NEUROFEEDBACK. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.01.569487. [PMID: 38106228 PMCID: PMC10723264 DOI: 10.1101/2023.12.01.569487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
When you perceive or remember one thing, other related things come to mind. This competition has consequences for how these items are later perceived, attended, or remembered. Such behavioral consequences result from changes in how much the neural representations of the items overlap, especially in the hippocampus. These changes can reflect increased (integration) or decreased (differentiation) overlap; previous studies have posited that the amount of coactivation between competing representations in cortex determines which will occur: high coactivation leads to hippocampal integration, medium coactivation leads to differentiation, and low coactivation is inert. However, those studies used indirect proxies for coactivation, by manipulating stimulus similarity or task demands. Here we induce coactivation of competing memories in visual cortex more directly using closed-loop neurofeedback from real-time fMRI. While viewing one object, participants were rewarded for implicitly activating the representation of another object as strongly as possible. Across multiple real-time fMRI training sessions, they succeeded in using the neurofeedback to induce coactivation. Compared with untrained objects, this coactivation led to behavioral and neural integration: The trained objects became harder for participants to discriminate in a categorical perception task and harder to decode from patterns of fMRI activity in the hippocampus.
Collapse
Affiliation(s)
- Kailong Peng
- Department of Psychology, Interdepartmental Neuroscience Program, Yale University
| | - Jeffrey D Wammes
- Department of Psychology, Centre for Neuroscience Studies, Queen's University
| | - Alex Nguyen
- Department of Psychology, Princeton Neuroscience Institute, Princeton University
| | - Marius Cătălin Iordan
- Department of Brain and Cognitive Sciences, Department of Neuroscience, University of Rochester
| | - Kenneth A Norman
- Department of Psychology, Princeton Neuroscience Institute, Princeton University
| | | |
Collapse
|
12
|
Koizumi K, Kunii N, Ueda K, Takabatake K, Nagata K, Fujitani S, Shimada S, Nakao M. Intracranial Neurofeedback Modulating Neural Activity in the Mesial Temporal Lobe During Memory Encoding: A Pilot Study. Appl Psychophysiol Biofeedback 2023; 48:439-451. [PMID: 37405548 PMCID: PMC10581957 DOI: 10.1007/s10484-023-09595-1] [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] [Accepted: 06/24/2023] [Indexed: 07/06/2023]
Abstract
Removal of the mesial temporal lobe (MTL) is an established surgical procedure that leads to seizure freedom in patients with intractable MTL epilepsy; however, it carries the potential risk of memory damage. Neurofeedback (NF), which regulates brain function by converting brain activity into perceptible information and providing feedback, has attracted considerable attention in recent years for its potential as a novel complementary treatment for many neurological disorders. However, no research has attempted to artificially reorganize memory functions by applying NF before resective surgery to preserve memory functions. Thus, this study aimed (1) to construct a memory NF system that used intracranial electrodes to feedback neural activity on the language-dominant side of the MTL during memory encoding and (2) to verify whether neural activity and memory function in the MTL change with NF training. Two intractable epilepsy patients with implanted intracranial electrodes underwent at least five sessions of memory NF training to increase the theta power in the MTL. There was an increase in theta power and a decrease in fast beta and gamma powers in one of the patients in the late stage of memory NF sessions. NF signals were not correlated with memory function. Despite its limitations as a pilot study, to our best knowledge, this study is the first to report that intracranial NF may modulate neural activity in the MTL, which is involved in memory encoding. The findings provide important insights into the future development of NF systems for the artificial reorganization of memory functions.
Collapse
Affiliation(s)
- Koji Koizumi
- Department of Mechanical Engineering, Graduate School of Engineering, The University of Tokyo, Tokyo, Japan.
| | - Naoto Kunii
- Department of Neurosurgery, The University of Tokyo, Tokyo, Japan
| | - Kazutaka Ueda
- Department of Mechanical Engineering, Graduate School of Engineering, The University of Tokyo, Tokyo, Japan
| | | | - Keisuke Nagata
- Department of Neurosurgery, The University of Tokyo, Tokyo, Japan
| | - Shigeta Fujitani
- Department of Neurosurgery, The University of Tokyo, Tokyo, Japan
| | - Seijiro Shimada
- Department of Neurosurgery, The University of Tokyo, Tokyo, Japan
| | - Masayuki Nakao
- Department of Mechanical Engineering, Graduate School of Engineering, The University of Tokyo, Tokyo, Japan
| |
Collapse
|
13
|
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.
Collapse
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
| |
Collapse
|
14
|
Zeng L, Wang C, Sun K, Pu Y, Gao Y, Wang H, Liu X, Wen Z. Upregulation of a Small-World Brain Network Improves Inhibitory Control: An fNIRS Neurofeedback Training Study. Brain Sci 2023; 13:1516. [PMID: 38002477 PMCID: PMC10670110 DOI: 10.3390/brainsci13111516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 10/22/2023] [Accepted: 10/24/2023] [Indexed: 11/26/2023] Open
Abstract
The aim of this study was to investigate the inner link between the small-world brain network and inhibitory control. Functional near-infrared spectroscopy (fNIRS) was used to construct a neurofeedback (NF) training system and regulate the frontal small-world brain network. The small-world network downregulation group (DOWN, n = 17) and the small-world network upregulation group (UP, n = 17) received five days of fNIRS-NF training and performed the color-word Stroop task before and after training. The behavioral and functional brain network topology results of both groups were analyzed by a repeated-measures analysis of variance (ANOVA), which showed that the upregulation training helped to improve inhibitory control. The upregulated small-world brain network exhibits an increase in the brain network regularization, links widely dispersed brain resources, and reduces the lateralization of brain functional networks between hemispheres. This suggests an inherent correlation between small-world functional brain networks and inhibitory control; moreover, dynamic optimization under cost efficiency trade-offs provides a neural basis for inhibitory control. Inhibitory control is not a simple function of a single brain region or connectivity but rather an emergent property of a broader network.
Collapse
Affiliation(s)
- Lingwei Zeng
- Department of Medical Psychology, Fourth Military Medical University, Xi’an 710032, China; (L.Z.); (K.S.); (Y.P.); (Y.G.); (H.W.)
| | - Chunchen Wang
- Department of Aerospace Medicine, Fourth Military Medical University, Xi’an 710032, China;
| | - Kewei Sun
- Department of Medical Psychology, Fourth Military Medical University, Xi’an 710032, China; (L.Z.); (K.S.); (Y.P.); (Y.G.); (H.W.)
| | - Yue Pu
- Department of Medical Psychology, Fourth Military Medical University, Xi’an 710032, China; (L.Z.); (K.S.); (Y.P.); (Y.G.); (H.W.)
| | - Yuntao Gao
- Department of Medical Psychology, Fourth Military Medical University, Xi’an 710032, China; (L.Z.); (K.S.); (Y.P.); (Y.G.); (H.W.)
| | - Hui Wang
- Department of Medical Psychology, Fourth Military Medical University, Xi’an 710032, China; (L.Z.); (K.S.); (Y.P.); (Y.G.); (H.W.)
| | - Xufeng Liu
- Department of Medical Psychology, Fourth Military Medical University, Xi’an 710032, China; (L.Z.); (K.S.); (Y.P.); (Y.G.); (H.W.)
| | - Zhihong Wen
- Department of Aerospace Medicine, Fourth Military Medical University, Xi’an 710032, China;
| |
Collapse
|
15
|
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).
Collapse
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
| |
Collapse
|
16
|
Pamplona GSP, Heldner J, Langner R, Koush Y, Michels L, Ionta S, Salmon CEG, Scharnowski F. Preliminary findings on long-term effects of fMRI neurofeedback training on functional networks involved in sustained attention. Brain Behav 2023; 13:e3217. [PMID: 37594145 PMCID: PMC10570501 DOI: 10.1002/brb3.3217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 07/25/2023] [Accepted: 07/29/2023] [Indexed: 08/19/2023] Open
Abstract
INTRODUCTION Neurofeedback based on functional magnetic resonance imaging allows for learning voluntary control over one's own brain activity, aiming to enhance cognition and clinical symptoms. We previously reported improved sustained attention temporarily by training healthy participants to up-regulate the differential activity of the sustained attention network minus the default mode network (DMN). However, the long-term brain and behavioral effects of this training have not yet been studied. In general, despite their relevance, long-term learning effects of neurofeedback training remain under-explored. METHODS Here, we complement our previously reported results by evaluating the neurofeedback training effects on functional networks involved in sustained attention and by assessing behavioral and brain measures before, after, and 2 months after training. The behavioral measures include task as well as questionnaire scores, and the brain measures include activity and connectivity during self-regulation runs without feedback (i.e., transfer runs) and during resting-state runs from 15 healthy individuals. RESULTS Neurally, we found that participants maintained their ability to control the differential activity during follow-up sessions. Further, exploratory analyses showed that the training increased the functional connectivity between the DMN and the occipital gyrus, which was maintained during follow-up transfer runs but not during follow-up resting-state runs. Behaviorally, we found that enhanced sustained attention right after training returned to baseline level during follow-up. CONCLUSION The discrepancy between lasting regulation-related brain changes but transient behavioral and resting-state effects raises the question of how neural changes induced by neurofeedback training translate to potential behavioral improvements. Since neurofeedback directly targets brain measures to indirectly improve behavior in the long term, a better understanding of the brain-behavior associations during and after neurofeedback training is needed to develop its full potential as a promising scientific and clinical tool.
Collapse
Affiliation(s)
- Gustavo Santo Pedro Pamplona
- Sensory‐Motor Laboratory (SeMoLa), Jules‐Gonin Eye Hospital/Fondation Asile des AveuglesDepartment of Ophthalmology/University of LausanneLausanneSwitzerland
- InBrain Lab, Department of PhysicsUniversity of Sao PauloRibeirao PretoBrazil
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric HospitalUniversity of ZurichZurichSwitzerland
- Rehabilitation Engineering Laboratory (RELab), Department of Health Sciences and TechnologyETH ZurichZurichSwitzerland
| | - Jennifer Heldner
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric HospitalUniversity of ZurichZurichSwitzerland
| | - Robert Langner
- Institute of Systems NeuroscienceHeinrich Heine University DusseldorfDusseldorfGermany
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM‐7)Research Centre JulichJulichGermany
| | - Yury Koush
- Department of Radiology and Biomedical Imaging, Yale School of MedicineYale UniversityNew HavenConnecticutUSA
| | - Lars Michels
- Department of NeuroradiologyUniversity Hospital ZurichZurichSwitzerland
- Neuroscience Center ZurichUniversity of Zurich and Swiss Federal Institute of TechnologyZurichSwitzerland
| | - Silvio Ionta
- Sensory‐Motor Laboratory (SeMoLa), Jules‐Gonin Eye Hospital/Fondation Asile des AveuglesDepartment of Ophthalmology/University of LausanneLausanneSwitzerland
| | | | - Frank Scharnowski
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric HospitalUniversity of ZurichZurichSwitzerland
- Neuroscience Center ZurichUniversity of Zurich and Swiss Federal Institute of TechnologyZurichSwitzerland
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of PsychologyUniversity of ViennaViennaAustria
| |
Collapse
|
17
|
Saxena A, Shovestul BJ, Dudek EM, Reda S, Venkataraman A, Lamberti JS, Dodell-Feder D. Training volitional control of the theory of mind network with real-time fMRI neurofeedback. Neuroimage 2023; 279:120334. [PMID: 37591479 DOI: 10.1016/j.neuroimage.2023.120334] [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: 03/17/2023] [Revised: 07/12/2023] [Accepted: 08/14/2023] [Indexed: 08/19/2023] Open
Abstract
Is there a way improve our ability to understand the minds of others? Towards addressing this question, here, we conducted a single-arm, proof-of-concept study to evaluate whether real-time fMRI neurofeedback (rtfMRI-NF) from the temporo-parietal junction (TPJ) leads to volitional control of the neural network subserving theory of mind (ToM; the process by which we attribute and reason about the mental states of others). As additional aims, we evaluated the strategies used to self-regulate the network and whether volitional control of the ToM network was moderated by participant characteristics and associated with improved performance on behavioral measures. Sixteen participants underwent fMRI while completing a task designed to individually-localize the TPJ, and then three separate rtfMRI-NF scans during which they completed multiple runs of a training task while receiving intermittent, activation-based feedback from the TPJ, and one run of a transfer task in which no neurofeedback was provided. Region-of-interest analyses demonstrated volitional control in most regions during the training tasks and during the transfer task, although the effects were smaller in magnitude and not observed in one of the neurofeedback targets for the transfer task. Text analysis demonstrated that volitional control was most strongly associated with thinking about prior social experiences when up-regulating the neural signal. Analysis of behavioral performance and brain-behavior associations largely did not reveal behavior changes except for a positive association between volitional control in RTPJ and changes in performance on one ToM task. Exploratory analysis suggested neurofeedback-related learning occurred, although some degree of volitional control appeared to be conferred with the initial self-regulation strategy provided to participants (i.e., without the neurofeedback signal). Critical study limitations include the lack of a control group and pre-rtfMRI transfer scan, which prevents a more direct assessment of neurofeedback-induced volitional control, and a small sample size, which may have led to an overestimate and/or unreliable estimate of study effects. Nonetheless, together, this study demonstrates the feasibility of training volitional control of a social cognitive brain network, which may have important clinical applications. Given the study's limitations, findings from this study should be replicated with more robust experimental designs.
Collapse
Affiliation(s)
- Abhishek Saxena
- Department of Psychology, University of Rochester, 500 Wilson Blvd Rochester, NY 14627 USA
| | - Bridget J Shovestul
- Department of Psychology, University of Rochester, 500 Wilson Blvd Rochester, NY 14627 USA
| | - Emily M Dudek
- Department of Psychology, University of Houston, 3695 Cullen Boulevard Houston, TX 77204 USA
| | - Stephanie Reda
- Department of Psychology, University of Rochester, 500 Wilson Blvd Rochester, NY 14627 USA
| | - Arun Venkataraman
- School of Medicine and Dentistry, University of Rochester Medical Center, 601 Elmwood Avenue, Rochester, NY 14642 USA
| | - J Steven Lamberti
- Department of Psychiatry, University of Rochester Medical Center, 601 Elmwood Avenue, Rochester, NY 14642 USA
| | - David Dodell-Feder
- Department of Psychology, University of Rochester, 500 Wilson Blvd Rochester, NY 14627 USA; Department of Neuroscience, University of Rochester Medical Center, 601 Elmwood Avenue, Rochester, NY 14642 USA.
| |
Collapse
|
18
|
Dehghani A, Soltanian-Zadeh H, Hossein-Zadeh GA. Neural modulation enhancement using connectivity-based EEG neurofeedback with simultaneous fMRI for emotion regulation. Neuroimage 2023; 279:120320. [PMID: 37586444 DOI: 10.1016/j.neuroimage.2023.120320] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 08/06/2023] [Accepted: 08/10/2023] [Indexed: 08/18/2023] Open
Abstract
Emotion regulation plays a key role in human behavior and overall well-being. Neurofeedback is a non-invasive self-brain training technique used for emotion regulation to enhance brain function and treatment of mental disorders through behavioral changes. Previous neurofeedback research often focused on using activity from a single brain region as measured by fMRI or power from one or two EEG electrodes. In a new study, we employed connectivity-based EEG neurofeedback through recalling positive autobiographical memories and simultaneous fMRI to upregulate positive emotion. In our novel approach, the feedback was determined by the coherence of EEG electrodes rather than the power of one or two electrodes. We compared the efficiency of this connectivity-based neurofeedback to traditional activity-based neurofeedback through multiple experiments. The results showed that connectivity-based neurofeedback effectively improved BOLD signal change and connectivity in key emotion regulation regions such as the amygdala, thalamus, and insula, and increased EEG frontal asymmetry, which is a biomarker for emotion regulation and treatment of mental disorders such as PTSD, anxiety, and depression and coherence among EEG channels. The psychometric evaluations conducted both before and after the neurofeedback experiments revealed that participants demonstrated improvements in enhancing positive emotions and reducing negative emotions when utilizing connectivity-based neurofeedback, as compared to traditional activity-based and sham neurofeedback approaches. These findings suggest that connectivity-based neurofeedback may be a superior method for regulating emotions and could be a useful alternative therapy for mental disorders, providing individuals with greater control over their brain and mental functions.
Collapse
Affiliation(s)
- Amin Dehghani
- School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran; Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA.
| | - Hamid Soltanian-Zadeh
- School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran; School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran; Departments of Radiology and Research Administration, Henry Ford Health System, Detroit, MI, USA
| | - Gholam-Ali Hossein-Zadeh
- School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran; School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| |
Collapse
|
19
|
Zotey V, Andhale A, Shegekar T, Juganavar A. Adaptive Neuroplasticity in Brain Injury Recovery: Strategies and Insights. Cureus 2023; 15:e45873. [PMID: 37885532 PMCID: PMC10598326 DOI: 10.7759/cureus.45873] [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: 09/07/2023] [Accepted: 09/24/2023] [Indexed: 10/28/2023] Open
Abstract
This review addresses the relationship between neuroplasticity and recovery from brain damage. Neuroplasticity's ability to adapt becomes crucial since brain injuries frequently result in severe impairments. We begin by describing the fundamentals of neuroplasticity and how it relates to rehabilitation. Examining different forms of brain injuries and their neurological effects highlights the complex difficulties in rehabilitation. By revealing cellular processes, we shed light on synaptic adaptability following damage. Our study of synaptic plasticity digs into axonal sprouting, dendritic remodeling, and the balance of long-term potentiation. These processes depict neural resilience amid change. Then, after damage, we investigate immediate and slow neuroplastic alterations, separating reorganizations that are adaptive from those that are maladaptive. As we go on to rehabilitation, we evaluate techniques that use neuroplasticity's potential. These methods take advantage of the brain's plasticity for healing, from virtual reality and brain-computer interfaces to constraint-induced movement therapy. Ethics and individualized neurorehabilitation are explored. We scrutinize the promise of combination therapy and the difficulties in putting new knowledge into clinical practice. In conclusion, this analysis highlights neuroplasticity's critical role in brain injury recovery, providing sophisticated approaches to improve life after damage.
Collapse
Affiliation(s)
- Vaishnavi Zotey
- Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Amol Andhale
- Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Tejas Shegekar
- Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Anup Juganavar
- Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| |
Collapse
|
20
|
Gao H, Zhang H, Wang L, Zhang C, Feng Z, Li Z, Tong L, Yan B, Hu G. Altered amygdala functional connectivity after real-time functional MRI emotion self-regulation training. Neuroreport 2023; 34:537-545. [PMID: 37384933 DOI: 10.1097/wnr.0000000000001921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/01/2023]
Abstract
Real-time functional MRI neurofeedback (rtfMRI-NF) is a noninvasive technique that extracts concurrent brain states and provides feedback to subjects in an online method. Our study aims to investigate the effect of rtfMRI-NF on amygdala-based emotion self-regulation by analyzing resting-state functional connectivity. We conducted a task experiment to train subjects in self-regulating amygdala activity in response to emotional stimuli. Twenty subjects were divided into two groups. The up-regulate group (URG) viewed positive stimulus, while the down-regulate group (DRG) viewed negative stimulus. The rtfMRI-NF experiment paradigm consisted of three conditions. The URG's percent amplitude fluctuation (PerAF) scores are significant, indicating that positive emotions may be a partial side effect, with increased activity in the left hemisphere. Resting-state functional connectivity was analyzed via a paired-sample t-test before and after neurofeedback training. Brain network properties and functional connectivity analysis showed a significant difference between the default mode network (DMN) and the brain region associated with the limbic system. These results reveal to some extent the mechanism of neurofeedback training to improve individuals' emotional regulate regulation ability. Our study has shown that rtfMRI-neurofeedback training can effectively enhance the ability to voluntarily control brain responses. Furthermore, the results of the functional analysis have revealed distinct changes in the amygdala functional connectivity circuits following rtfMRI-neurofeedback training. These findings may suggest the potential clinical applications of rtfMRI-neurofeedback as a new therapy for emotionally related mental disorders.
Collapse
Affiliation(s)
- Hui Gao
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou
| | - Huan Zhang
- Research Center for Human-Machine Augmented Intelligence, Research Institute of Artificial Intelligence, Zhejiang Lab, Hangzhou, Zhejiang
| | - Linyuan Wang
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou
| | - Chi Zhang
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou
| | - Zhiyuan Feng
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou
- No.988 Hospital of Joint Logistic Support Force
| | - Zhonglin Li
- Department of Radiology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, China
| | - Li Tong
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou
| | - Bin Yan
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou
| | - Guoen Hu
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou
| |
Collapse
|
21
|
Soleimani G, Nitsche MA, Bergmann TO, Towhidkhah F, Violante IR, Lorenz R, Kuplicki R, Tsuchiyagaito A, Mulyana B, Mayeli A, Ghobadi-Azbari P, Mosayebi-Samani M, Zilverstand A, Paulus MP, Bikson M, Ekhtiari H. Closing the loop between brain and electrical stimulation: towards precision neuromodulation treatments. Transl Psychiatry 2023; 13:279. [PMID: 37582922 PMCID: PMC10427701 DOI: 10.1038/s41398-023-02565-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 07/06/2023] [Accepted: 07/20/2023] [Indexed: 08/17/2023] Open
Abstract
One of the most critical challenges in using noninvasive brain stimulation (NIBS) techniques for the treatment of psychiatric and neurologic disorders is inter- and intra-individual variability in response to NIBS. Response variations in previous findings suggest that the one-size-fits-all approach does not seem the most appropriate option for enhancing stimulation outcomes. While there is a growing body of evidence for the feasibility and effectiveness of individualized NIBS approaches, the optimal way to achieve this is yet to be determined. Transcranial electrical stimulation (tES) is one of the NIBS techniques showing promising results in modulating treatment outcomes in several psychiatric and neurologic disorders, but it faces the same challenge for individual optimization. With new computational and methodological advances, tES can be integrated with real-time functional magnetic resonance imaging (rtfMRI) to establish closed-loop tES-fMRI for individually optimized neuromodulation. Closed-loop tES-fMRI systems aim to optimize stimulation parameters based on minimizing differences between the model of the current brain state and the desired value to maximize the expected clinical outcome. The methodological space to optimize closed-loop tES fMRI for clinical applications includes (1) stimulation vs. data acquisition timing, (2) fMRI context (task-based or resting-state), (3) inherent brain oscillations, (4) dose-response function, (5) brain target trait and state and (6) optimization algorithm. Closed-loop tES-fMRI technology has several advantages over non-individualized or open-loop systems to reshape the future of neuromodulation with objective optimization in a clinically relevant context such as drug cue reactivity for substance use disorder considering both inter and intra-individual variations. Using multi-level brain and behavior measures as input and desired outcomes to individualize stimulation parameters provides a framework for designing personalized tES protocols in precision psychiatry.
Collapse
Affiliation(s)
- Ghazaleh Soleimani
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
- Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Michael A Nitsche
- Department of Psychology and Neuroscience, Leibniz Research Center for Working Environment and Human Factors, Dortmund, Germany
- Bielefeld University, University Hospital OWL, Protestant Hospital of Bethel Foundation, University Clinic of Psychiatry and Psychotherapy, and University Clinic of Child and Adolescent Psychiatry and Psychotherapy, Bielefeld, Germany
| | - Til Ole Bergmann
- Neuroimaging Center, Focus Program Translational Neuroscience, Johannes Gutenberg University Medical Center Mainz, Mainz, Germany
- Leibniz Institute for Resilience Research, Mainz, Germany
| | - Farzad Towhidkhah
- Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Ines R Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guilford, UK
| | - Romy Lorenz
- Department of Psychology, Stanford University, Stanford, CA, USA
- MRC CBU, University of Cambridge, Cambridge, UK
- Department of Neurophysics, MPI, Leipzig, Germany
| | | | | | - Beni Mulyana
- Laureate Institute for Brain Research, Tulsa, OK, USA
- School of Electrical and Computer Engineering, University of Oklahoma, Tulsa, OK, USA
| | - Ahmad Mayeli
- University of Pittsburgh Medical Center, Pittsburg, PA, USA
| | - Peyman Ghobadi-Azbari
- Department of Biomedical Engineering, Shahed University, Tehran, Iran
- Iranian National Center for Addiction Studies, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohsen Mosayebi-Samani
- Department of Psychology and Neuroscience, Leibniz Research Center for Working Environment and Human Factors, Dortmund, Germany
| | - Anna Zilverstand
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | | | | | - Hamed Ekhtiari
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA.
- Laureate Institute for Brain Research, Tulsa, OK, USA.
| |
Collapse
|
22
|
Singer N, Poker G, Dunsky-Moran N, Nemni S, Reznik Balter S, Doron M, Baker T, Dagher A, Zatorre RJ, Hendler T. Development and validation of an fMRI-informed EEG model of reward-related ventral striatum activation. Neuroimage 2023; 276:120183. [PMID: 37225112 PMCID: PMC10300238 DOI: 10.1016/j.neuroimage.2023.120183] [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: 11/20/2022] [Revised: 04/06/2023] [Accepted: 05/22/2023] [Indexed: 05/26/2023] Open
Abstract
Reward processing is essential for our mental-health and well-being. In the current study, we developed and validated a scalable, fMRI-informed EEG model for monitoring reward processing related to activation in the ventral-striatum (VS), a significant node in the brain's reward system. To develop this EEG-based model of VS-related activation, we collected simultaneous EEG/fMRI data from 17 healthy individuals while listening to individually-tailored pleasurable music - a highly rewarding stimulus known to engage the VS. Using these cross-modal data, we constructed a generic regression model for predicting the concurrently acquired Blood-Oxygen-Level-Dependent (BOLD) signal from the VS using spectro-temporal features from the EEG signal (termed hereby VS-related-Electrical Finger Print; VS-EFP). The performance of the extracted model was examined using a series of tests that were applied on the original dataset and, importantly, an external validation dataset collected from a different group of 14 healthy individuals who underwent the same EEG/FMRI procedure. Our results showed that the VS-EFP model, as measured by simultaneous EEG, predicted BOLD activation in the VS and additional functionally relevant regions to a greater extent than an EFP model derived from a different anatomical region. The developed VS-EFP was also modulated by musical pleasure and predictive of the VS-BOLD during a monetary reward task, further indicating its functional relevance. These findings provide compelling evidence for the feasibility of using EEG alone to model neural activation related to the VS, paving the way for future use of this scalable neural probing approach in neural monitoring and self-guided neuromodulation.
Collapse
Affiliation(s)
- Neomi Singer
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montréal, QC H3A 2B4, Canada; Sagol Brain Institute, Tel-Aviv Sourasky Medical Center, 6 Weizman St. Tel Aviv, 64239, Israel; Sagol school of Neuroscience, Tel-Aviv University, PO Box 39040, Tel Aviv 6997801, Israel
| | - Gilad Poker
- Sagol Brain Institute, Tel-Aviv Sourasky Medical Center, 6 Weizman St. Tel Aviv, 64239, Israel
| | - Netta Dunsky-Moran
- Sagol Brain Institute, Tel-Aviv Sourasky Medical Center, 6 Weizman St. Tel Aviv, 64239, Israel; Sagol school of Neuroscience, Tel-Aviv University, PO Box 39040, Tel Aviv 6997801, Israel
| | - Shlomi Nemni
- Sagol school of Neuroscience, Tel-Aviv University, PO Box 39040, Tel Aviv 6997801, Israel; School of Psychological Sciences, Tel-Aviv University, PO Box 39040, Tel Aviv 6997801, Israel
| | - Shira Reznik Balter
- Sagol Brain Institute, Tel-Aviv Sourasky Medical Center, 6 Weizman St. Tel Aviv, 64239, Israel
| | - Maayan Doron
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montréal, QC H3A 2B4, Canada; Sackler School of Medicine, Tel-Aviv University, PO Box 39040, Tel Aviv 6997801, Israel
| | - Travis Baker
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montréal, QC H3A 2B4, Canada; Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, USA
| | - Alain Dagher
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montréal, QC H3A 2B4, Canada
| | - Robert J Zatorre
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montréal, QC H3A 2B4, Canada; International Laboratory for Brain, Music, and Sound Research (BRAMS), Canada
| | - Talma Hendler
- Sagol Brain Institute, Tel-Aviv Sourasky Medical Center, 6 Weizman St. Tel Aviv, 64239, Israel; Sagol school of Neuroscience, Tel-Aviv University, PO Box 39040, Tel Aviv 6997801, Israel; School of Psychological Sciences, Tel-Aviv University, PO Box 39040, Tel Aviv 6997801, Israel; Sackler School of Medicine, Tel-Aviv University, PO Box 39040, Tel Aviv 6997801, Israel.
| |
Collapse
|
23
|
Lee I, Kim D, Kim S, Kim HJ, Chung US, Lee JJ. Cognitive training based on functional near-infrared spectroscopy neurofeedback for the elderly with mild cognitive impairment: a preliminary study. Front Aging Neurosci 2023; 15:1168815. [PMID: 37564400 PMCID: PMC10410268 DOI: 10.3389/fnagi.2023.1168815] [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: 02/18/2023] [Accepted: 07/05/2023] [Indexed: 08/12/2023] Open
Abstract
Introduction Mild cognitive impairment (MCI) is often described as an intermediate stage of the normal cognitive decline associated with aging and dementia. There is a growing interest in various non-pharmacological interventions for MCI to delay the onset and inhibit the progressive deterioration of daily life functions. Previous studies suggest that cognitive training (CT) contributes to the restoration of working memory and that the brain-computer-interface technique can be applied to elicit a more effective treatment response. However, these techniques have certain limitations. Thus, in this preliminary study, we applied the neurofeedback paradigm during CT to increase the working memory function of patients with MCI. Methods Near-infrared spectroscopy (NIRS) was used to provide neurofeedback by measuring the changes in oxygenated hemoglobin in the prefrontal cortex. Thirteen elderly MCI patients who received CT-neurofeedback sessions four times on the left dorsolateral prefrontal cortex (dlPFC) once a week were recruited as participants. Results Compared with pre-intervention, the activity of the targeted brain region increased when the participants first engaged in the training; after 4 weeks of training, oxygen saturation was significantly decreased in the left dlPFC. The participants demonstrated significantly improved working memory compared with pre-intervention and decreased activity significantly correlated with improved cognitive performance. Conclusion Our results suggest that the applications for evaluating brain-computer interfaces can aid in elucidation of the subjective mental workload that may create additional or decreased task workloads due to CT.
Collapse
Affiliation(s)
- Ilju Lee
- Department of Psychology, College of Health Science, Dankook University, Cheonan, Republic of Korea
| | - Dohyun Kim
- Department of Psychiatry, Dankook University Hospital, Cheonan, Republic of Korea
- Department of Psychiatry, College of Medicine, Dankook University, Cheonan, Republic of Korea
| | - Sehwan Kim
- Department of Biomedical Engineering, College of Medicine, Dankook University, Cheonan, Republic of Korea
| | - Hee Jung Kim
- Department of Physiology, College of Medicine, Dankook University, Cheonan, Republic of Korea
| | - Un Sun Chung
- Department of Psychiatry, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Jung Jae Lee
- Department of Psychiatry, Dankook University Hospital, Cheonan, Republic of Korea
- Department of Psychiatry, College of Medicine, Dankook University, Cheonan, Republic of Korea
| |
Collapse
|
24
|
Babaskina L, Afanasyeva N, Semyonkina M, Myasnyankina O, Sushko N. Effectiveness of Neurofeedback Training for Patients with Personality Disorders: A Systematic Review. IRANIAN JOURNAL OF PSYCHIATRY 2023; 18:352-361. [PMID: 37575604 PMCID: PMC10422943 DOI: 10.18502/ijps.v18i3.13014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 02/15/2023] [Accepted: 02/22/2023] [Indexed: 08/15/2023]
Abstract
Objective: Personality disorders are serious psychiatric conditions, and some studies have examined neurofeedback training as a potential alternative treatment to improve cognitive and clinical symptoms in patients with such disorders. Here, we aimed to provide a first systematic review of such trials and present existing evidence regarding this treatment for individuals with personality disorders. Method : A systematic search of peer-reviewed English journal articles was conducted for this study to identify original studies on fMRI and EEG neurofeedback treatment protocols in patients with personality disorders up to January 2023. PubMed, Web of Science, ProQuest, Cochrane Library, and Google Scholar databases were queried through the keywords "neurofeedback," "biofeedback," and "personality disorder," as well as their related Mesh synonyms. Results: Totally, five studies were included in our systematic review. Two studies utilized EEG neurofeedback protocols, while three articles used real-time fMRI neurofeedback protocols. The types of studies were non-randomized, not-blinded case reports, case series, and single-arm trials with a high risk of bias. EEG neurofeedback protocols applied more training sessions and reported improvements in patients' neuropsychological and behavioral functions after treatment. Furthermore, fMRI-based neurofeedback studies reported neurophysiological changes, such as a shift in vmPFC-amygdala connectivity, towards healthy states following treatment. Moreover, behavioral symptoms of patients were reported to be improved after fMRI neurofeedback. Conclusion: Neurofeedback studies investigating this therapeutic technique for personality disorders are still very preliminary, and no strict conclusions can be drawn at this time. Therefore, further basic and clinical investigations are required to address several open methodological and technical questions and establish consensus and standardization, which will eventually lead to translational works.
Collapse
|
25
|
Haugg A, Frei N, Menghini M, Stutz F, Steinegger S, Röthlisberger M, Brem S. Self-regulation of visual word form area activation with real-time fMRI neurofeedback. Sci Rep 2023; 13:9195. [PMID: 37280217 DOI: 10.1038/s41598-023-35932-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 05/25/2023] [Indexed: 06/08/2023] Open
Abstract
The Visual Word Form Area (VWFA) is a key region of the brain's reading network and its activation has been shown to be strongly associated with reading skills. Here, for the first time, we investigated whether voluntary regulation of VWFA activation is feasible using real-time fMRI neurofeedback. 40 adults with typical reading skills were instructed to either upregulate (UP group, N = 20) or downregulate (DOWN group, N = 20) their own VWFA activation during six neurofeedback training runs. The VWFA target region was individually defined based on a functional localizer task. Before and after training, also regulation runs without feedback ("no-feedback runs") were performed. When comparing the two groups, we found stronger activation across the reading network for the UP than the DOWN group. Further, activation in the VWFA was significantly stronger in the UP group than the DOWN group. Crucially, we observed a significant interaction of group and time (pre, post) for the no-feedback runs: The two groups did not differ significantly in their VWFA activation before neurofeedback training, but the UP group showed significantly stronger activation than the DOWN group after neurofeedback training. Our results indicate that upregulation of VWFA activation is feasible and that, once learned, successful upregulation can even be performed in the absence of feedback. These results are a crucial first step toward the development of a potential therapeutic support to improve reading skills in individuals with reading impairments.
Collapse
Affiliation(s)
- Amelie Haugg
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland.
| | - Nada Frei
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Milena Menghini
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Felizia Stutz
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Sara Steinegger
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Martina Röthlisberger
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Silvia Brem
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
| |
Collapse
|
26
|
Kim K, Oblak E, Manella K, Sulzer J. OPERANT REFLEX CONDITIONING SIMULATION ENVIRONMENT REVEALS EFFECTS OF FEEDBACK PARAMETERS. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.26.542391. [PMID: 37293099 PMCID: PMC10245997 DOI: 10.1101/2023.05.26.542391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Operant conditioning of neural activation has been researched for decades in humans and animals. Many theories suggest two parallel learning processes, implicit and explicit. The degree to which feedback affects these processes individually remains to be fully understood and may contribute to a large percentage of non-learners. Our goal is to determine the explicit decision-making processes in response to feedback representing an operant conditioning environment. We developed a simulated operant conditioning environment based on a feedback model of spinal reflex excitability, one of the simplest forms of neural operant conditioning. We isolated the perception of the feedback signal from self-regulation of an explicit unskilled visuomotor task, enabling us to quantitatively examine feedback strategy. Our hypothesis was that feedback type, signal quality and success threshold affect operant conditioning performance and operant strategy. Healthy individuals (N = 41) were instructed to play a web application game using keyboard inputs to rotate a virtual knob representative of an operant strategy. The goal was to align the knob with a hidden target. Participants were asked to "down-condition" the amplitude of the virtual feedback signal, which was achieved by placing the knob as close as possible to the hidden target. We varied feedback type (knowledge of performance, knowledge of results), success threshold (easy, moderate, difficult), and biological variability (low, high) in a factorial design. Parameters were extracted from real operant conditioning data. Our main outcomes were the feedback signal amplitude (performance) and the mean change in dial position (operant strategy). We observed that performance was modulated by variability, while operant strategy was modulated by feedback type. These results show complex relations between fundamental feedback parameters and provide the principles for optimizing neural operant conditioning for non-responders.
Collapse
Affiliation(s)
| | - Ethan Oblak
- RIKEN Center for Brain Science, Saitama, Japan
| | | | - James Sulzer
- MetroHealth Hospital and Case Western Reserve University, Cleveland, OH, USA
| |
Collapse
|
27
|
Colenbier N, Sareen E, Del-Aguila Puntas T, Griffa A, Pellegrino G, Mantini D, Marinazzo D, Arcara G, Amico E. Task matters: Individual MEG signatures from naturalistic and neurophysiological brain states. Neuroimage 2023; 271:120021. [PMID: 36918139 DOI: 10.1016/j.neuroimage.2023.120021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 02/21/2023] [Accepted: 03/10/2023] [Indexed: 03/14/2023] Open
Abstract
The discovery that human brain connectivity data can be used as a "fingerprint" to identify a given individual from a population, has become a burgeoning research area in the neuroscience field. Recent studies have identified the possibility to extract these brain signatures from the temporal rich dynamics of resting-state magneto encephalography (MEG) recordings. Nevertheless, it is still uncertain to what extent MEG signatures can serve as an indicator of human identifiability during task-related conduct. Here, using MEG data from naturalistic and neurophysiological tasks, we show that identification improves in tasks relative to resting-state, providing compelling evidence for a task dependent axis of MEG signatures. Notably, improvements in identifiability were more prominent in strictly controlled tasks. Lastly, the brain regions contributing most towards individual identification were also modified when engaged in task activities. We hope that this investigation advances our understanding of the driving factors behind brain identification from MEG signals.
Collapse
Affiliation(s)
| | - Ekansh Sareen
- Medical Image Processing Laboratory, Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
| | - Tamara Del-Aguila Puntas
- Laboratorio de Psicobiologia, Departmento de Psicología Experimental, Facultad de Psicología, Universidad de Sevilla, Spain
| | - Alessandra Griffa
- Medical Image Processing Laboratory, Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland; Department of Radiology and Medical Informatics, University of Geneva, Switzerland; Leenaards Memory Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | | | - Dante Mantini
- Movement Control and Neuroplasticity Research Group, KU Leuven, Belgium
| | - Daniele Marinazzo
- Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent, Belgium
| | | | - Enrico Amico
- Medical Image Processing Laboratory, Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland; Department of Radiology and Medical Informatics, University of Geneva, Switzerland.
| |
Collapse
|
28
|
Di Pietro SV, Willinger D, Frei N, Lutz C, Coraj S, Schneider C, Stämpfli P, Brem S. Disentangling influences of dyslexia, development, and reading experience on effective brain connectivity in children. Neuroimage 2023; 268:119869. [PMID: 36639004 DOI: 10.1016/j.neuroimage.2023.119869] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 12/29/2022] [Accepted: 01/09/2023] [Indexed: 01/12/2023] Open
Abstract
Altered brain connectivity between regions of the reading network has been associated with reading difficulties. However, it remains unclear whether connectivity differences between children with dyslexia (DYS) and those with typical reading skills (TR) are specific to reading impairments or to reading experience. In this functional MRI study, 132 children (M = 10.06 y, SD = 1.46) performed a phonological lexical decision task. We aimed to disentangle (1) disorder-specific from (2) experience-related differences in effective connectivity and to (3) characterize the development of DYS and TR. We applied dynamic causal modeling to age-matched (ndys = 25, nTR = 35) and reading-level-matched (ndys = 25, nTR = 22) groups. Developmental effects were assessed in beginning and advanced readers (TR: nbeg = 48, nadv = 35, DYS: nbeg = 24, nadv = 25). We show that altered feedback connectivity between the inferior parietal lobule and the visual word form area (VWFA) during print processing can be specifically attributed to reading impairments, because these alterations were found in DYS compared to both the age-matched and reading-level-matched TR. In contrast, feedforward connectivity from the VWFA to parietal and frontal regions characterized experience in TR and increased with age and reading skill. These directed connectivity findings pinpoint disorder-specific and experience-dependent alterations in the brain's reading network.
Collapse
Affiliation(s)
- Sarah V Di Pietro
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Switzerland; URPP Adaptive Brain Circuits in Development and Learning (AdaBD), University of Zurich, Zurich, Switzerland
| | - David Willinger
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Switzerland; Department of Psychology and Psychodynamics, Karl Landsteiner University of Health Sciences, Krems an der Donau, Austria
| | - Nada Frei
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Switzerland
| | - Christina Lutz
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Switzerland
| | - Seline Coraj
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Switzerland
| | - Chiara Schneider
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Switzerland
| | - Philipp Stämpfli
- MR-Center of the Department of Psychiatry, Psychotherapy and Psychosomatics and the Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Silvia Brem
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Switzerland; URPP Adaptive Brain Circuits in Development and Learning (AdaBD), University of Zurich, Zurich, Switzerland; MR-Center of the Department of Psychiatry, Psychotherapy and Psychosomatics and the Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zurich, Switzerland.
| |
Collapse
|
29
|
Dehghani A, Soltanian-Zadeh H, Hossein-Zadeh GA. Probing fMRI brain connectivity and activity changes during emotion regulation by EEG neurofeedback. Front Hum Neurosci 2023; 16:988890. [PMID: 36684847 PMCID: PMC9853008 DOI: 10.3389/fnhum.2022.988890] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 12/13/2022] [Indexed: 01/09/2023] Open
Abstract
Despite the existence of several emotion regulation studies using neurofeedback, interactions among a small number of regions were evaluated, and therefore, further investigation is needed to understand the interactions of the brain regions involved in emotion regulation. We implemented electroencephalography (EEG) neurofeedback with simultaneous functional magnetic resonance imaging (fMRI) using a modified happiness-inducing task through autobiographical memories to upregulate positive emotion. Then, an explorative analysis of whole brain regions was done to understand the effect of neurofeedback on brain activity and the interaction of whole brain regions involved in emotion regulation. The participants in the control and experimental groups were asked to do emotion regulation while viewing positive images of autobiographical memories and getting sham or real (based on alpha asymmetry) EEG neurofeedback, respectively. The proposed multimodal approach quantified the effects of EEG neurofeedback in changing EEG alpha power, fMRI blood oxygenation level-dependent (BOLD) activity of prefrontal, occipital, parietal, and limbic regions (up to 1.9% increase), and functional connectivity in/between prefrontal, parietal, limbic system, and insula in the experimental group. New connectivity links were identified by comparing the brain functional connectivity between experimental conditions (Upregulation and View blocks) and also by comparing the brain connectivity of the experimental and control groups. Psychometric assessments confirmed significant changes in positive and negative mood states in the experimental group by neurofeedback. Based on the exploratory analysis of activity and connectivity among all brain regions involved in emotion regions, we found significant BOLD and functional connectivity increases due to EEG neurofeedback in the experimental group, but no learning effect was observed in the control group. The results reveal several new connections among brain regions as a result of EEG neurofeedback which can be justified according to emotion regulation models and the role of those regions in emotion regulation and recalling positive autobiographical memories.
Collapse
Affiliation(s)
- Amin Dehghani
- School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran,Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, United States,*Correspondence: Amin Dehghani, ,
| | - Hamid Soltanian-Zadeh
- School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran,Medical Image Analysis Lab, Department of Radiology and Research Administration, Henry Ford Health System, Detroit, MI, United States,School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Gholam-Ali Hossein-Zadeh
- School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran,School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| |
Collapse
|
30
|
Ciccarelli G, Federico G, Mele G, Di Cecca A, Migliaccio M, Ilardi CR, Alfano V, Salvatore M, Cavaliere C. Simultaneous real-time EEG-fMRI neurofeedback: A systematic review. Front Hum Neurosci 2023; 17:1123014. [PMID: 37063098 PMCID: PMC10102573 DOI: 10.3389/fnhum.2023.1123014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 03/15/2023] [Indexed: 04/18/2023] Open
Abstract
Neurofeedback (NF) is a biofeedback technique that teaches individuals self-control of brain functions by measuring brain activations and providing an online feedback signal to modify emotional, cognitive, and behavioral functions. NF approaches typically rely on a single modality, such as electroencephalography (EEG-NF) or a brain imaging technique, such as functional magnetic resonance imaging (fMRI-NF). The introduction of simultaneous EEG-fMRI tools has opened up the possibility of combining the high temporal resolution of EEG with the high spatial resolution of fMRI, thereby increasing the accuracy of NF. However, only a few studies have actively combined both techniques. In this study, we conducted a systematic review of EEG-fMRI-NF studies (N = 17) to identify the potential and effectiveness of this non-invasive treatment for neurological conditions. The systematic review revealed a lack of homogeneity among the studies, including sample sizes, acquisition methods in terms of simultaneity of the two procedures (unimodal EEG-NF and fMRI-NF), therapeutic targets field, and the number of sessions. Indeed, because most studies are based on a single session of NF, it is difficult to draw any conclusions regarding the therapeutic efficacy of NF. Therefore, further research is needed to fully understand non-clinical and clinical potential of EEG-fMRI-NF.
Collapse
|
31
|
Bibliometric analysis on Brain-computer interfaces in a 30-year period. APPL INTELL 2022. [DOI: 10.1007/s10489-022-04226-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
|
32
|
Lam SL, Criaud M, Lukito S, Westwood SJ, Agbedjro D, Kowalczyk OS, Curran S, Barret N, Abbott C, Liang H, Simonoff E, Barker GJ, Giampietro V, Rubia K. Double-Blind, Sham-Controlled Randomized Trial Testing the Efficacy of fMRI Neurofeedback on Clinical and Cognitive Measures in Children With ADHD. Am J Psychiatry 2022; 179:947-958. [PMID: 36349428 PMCID: PMC7614456 DOI: 10.1176/appi.ajp.21100999] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Functional MRI neurofeedback (fMRI-NF) could potentially be a novel, safe nonpharmacological treatment for attention deficit hyperactivity disorder (ADHD). A proof-of-concept randomized controlled trial of fMRI-NF of the right inferior frontal cortex (rIFC), compared to an active control condition, showed promising improvement of ADHD symptoms (albeit in both groups) and in brain function. However, comparison with a placebo condition in a larger trial is required to test efficacy. METHODS This double-blind, sham-controlled randomized controlled trial tested the effectiveness and efficacy of fMRI-NF of the rIFC on symptoms and executive functions in 88 boys with ADHD (44 each in the active and sham arms). To investigate treatment-related changes, groups were compared at the posttreatment and 6-month follow-up assessments, controlling for baseline scores, age, and medication status. The primary outcome measure was posttreatment score on the ADHD Rating Scale (ADHD-RS). RESULTS No significant group differences were found on the ADHD-RS. Both groups showed similar decreases in other clinical and cognitive measures, except for a significantly greater decrease in irritability and improvement in motor inhibition in sham relative to active fMRI-NF at the posttreatment assessment, covarying for baseline. There were no significant side effects or adverse events. The active relative to the sham fMRI-NF group showed enhanced activation in rIFC and other frontal and temporo-occipital-cerebellar self-regulation areas. However, there was no progressive rIFC upregulation, correlation with ADHD-RS scores, or transfer of learning. CONCLUSIONS Contrary to the hypothesis, the study findings do not suggest that fMRI-NF of the rIFC is effective in improving clinical symptoms or cognition in boys with ADHD.
Collapse
Affiliation(s)
- Sheut-Ling Lam
- Department of Child and Adolescent Psychiatry (Lam, Criaud, Lukito, Westwood, Simonoff, Rubia), Department of Neuroimaging (Kowalczyk, Barker, Giampietro), and Department of Biostatistics (Agbedjro), King's College London; Institute for Globally Distributed Open Research and Education (Criaud); Institute of Human Sciences, University of Wolverhampton, Wolverhampton, U.K. (Westwood); Department of Psychology, School of Social Science, University of Westminster, London (Westwood); Southwest London and St George's Mental Health NHS Trust, London (Curran); South London and Maudsley NHS Foundation Trust, London (Barret, Abbott); Great Ormond Street Hospital for Children NHS Foundation Trust, London (Liang); Department of Child and Adolescent Psychiatry, Technical University Dresden, Germany (Rubia)
| | - Marion Criaud
- Department of Child and Adolescent Psychiatry (Lam, Criaud, Lukito, Westwood, Simonoff, Rubia), Department of Neuroimaging (Kowalczyk, Barker, Giampietro), and Department of Biostatistics (Agbedjro), King's College London; Institute for Globally Distributed Open Research and Education (Criaud); Institute of Human Sciences, University of Wolverhampton, Wolverhampton, U.K. (Westwood); Department of Psychology, School of Social Science, University of Westminster, London (Westwood); Southwest London and St George's Mental Health NHS Trust, London (Curran); South London and Maudsley NHS Foundation Trust, London (Barret, Abbott); Great Ormond Street Hospital for Children NHS Foundation Trust, London (Liang); Department of Child and Adolescent Psychiatry, Technical University Dresden, Germany (Rubia)
| | - Steve Lukito
- Department of Child and Adolescent Psychiatry (Lam, Criaud, Lukito, Westwood, Simonoff, Rubia), Department of Neuroimaging (Kowalczyk, Barker, Giampietro), and Department of Biostatistics (Agbedjro), King's College London; Institute for Globally Distributed Open Research and Education (Criaud); Institute of Human Sciences, University of Wolverhampton, Wolverhampton, U.K. (Westwood); Department of Psychology, School of Social Science, University of Westminster, London (Westwood); Southwest London and St George's Mental Health NHS Trust, London (Curran); South London and Maudsley NHS Foundation Trust, London (Barret, Abbott); Great Ormond Street Hospital for Children NHS Foundation Trust, London (Liang); Department of Child and Adolescent Psychiatry, Technical University Dresden, Germany (Rubia)
| | - Samuel J Westwood
- Department of Child and Adolescent Psychiatry (Lam, Criaud, Lukito, Westwood, Simonoff, Rubia), Department of Neuroimaging (Kowalczyk, Barker, Giampietro), and Department of Biostatistics (Agbedjro), King's College London; Institute for Globally Distributed Open Research and Education (Criaud); Institute of Human Sciences, University of Wolverhampton, Wolverhampton, U.K. (Westwood); Department of Psychology, School of Social Science, University of Westminster, London (Westwood); Southwest London and St George's Mental Health NHS Trust, London (Curran); South London and Maudsley NHS Foundation Trust, London (Barret, Abbott); Great Ormond Street Hospital for Children NHS Foundation Trust, London (Liang); Department of Child and Adolescent Psychiatry, Technical University Dresden, Germany (Rubia)
| | - Deborah Agbedjro
- Department of Child and Adolescent Psychiatry (Lam, Criaud, Lukito, Westwood, Simonoff, Rubia), Department of Neuroimaging (Kowalczyk, Barker, Giampietro), and Department of Biostatistics (Agbedjro), King's College London; Institute for Globally Distributed Open Research and Education (Criaud); Institute of Human Sciences, University of Wolverhampton, Wolverhampton, U.K. (Westwood); Department of Psychology, School of Social Science, University of Westminster, London (Westwood); Southwest London and St George's Mental Health NHS Trust, London (Curran); South London and Maudsley NHS Foundation Trust, London (Barret, Abbott); Great Ormond Street Hospital for Children NHS Foundation Trust, London (Liang); Department of Child and Adolescent Psychiatry, Technical University Dresden, Germany (Rubia)
| | - Olivia S Kowalczyk
- Department of Child and Adolescent Psychiatry (Lam, Criaud, Lukito, Westwood, Simonoff, Rubia), Department of Neuroimaging (Kowalczyk, Barker, Giampietro), and Department of Biostatistics (Agbedjro), King's College London; Institute for Globally Distributed Open Research and Education (Criaud); Institute of Human Sciences, University of Wolverhampton, Wolverhampton, U.K. (Westwood); Department of Psychology, School of Social Science, University of Westminster, London (Westwood); Southwest London and St George's Mental Health NHS Trust, London (Curran); South London and Maudsley NHS Foundation Trust, London (Barret, Abbott); Great Ormond Street Hospital for Children NHS Foundation Trust, London (Liang); Department of Child and Adolescent Psychiatry, Technical University Dresden, Germany (Rubia)
| | - Sarah Curran
- Department of Child and Adolescent Psychiatry (Lam, Criaud, Lukito, Westwood, Simonoff, Rubia), Department of Neuroimaging (Kowalczyk, Barker, Giampietro), and Department of Biostatistics (Agbedjro), King's College London; Institute for Globally Distributed Open Research and Education (Criaud); Institute of Human Sciences, University of Wolverhampton, Wolverhampton, U.K. (Westwood); Department of Psychology, School of Social Science, University of Westminster, London (Westwood); Southwest London and St George's Mental Health NHS Trust, London (Curran); South London and Maudsley NHS Foundation Trust, London (Barret, Abbott); Great Ormond Street Hospital for Children NHS Foundation Trust, London (Liang); Department of Child and Adolescent Psychiatry, Technical University Dresden, Germany (Rubia)
| | - Nadia Barret
- Department of Child and Adolescent Psychiatry (Lam, Criaud, Lukito, Westwood, Simonoff, Rubia), Department of Neuroimaging (Kowalczyk, Barker, Giampietro), and Department of Biostatistics (Agbedjro), King's College London; Institute for Globally Distributed Open Research and Education (Criaud); Institute of Human Sciences, University of Wolverhampton, Wolverhampton, U.K. (Westwood); Department of Psychology, School of Social Science, University of Westminster, London (Westwood); Southwest London and St George's Mental Health NHS Trust, London (Curran); South London and Maudsley NHS Foundation Trust, London (Barret, Abbott); Great Ormond Street Hospital for Children NHS Foundation Trust, London (Liang); Department of Child and Adolescent Psychiatry, Technical University Dresden, Germany (Rubia)
| | - Chris Abbott
- Department of Child and Adolescent Psychiatry (Lam, Criaud, Lukito, Westwood, Simonoff, Rubia), Department of Neuroimaging (Kowalczyk, Barker, Giampietro), and Department of Biostatistics (Agbedjro), King's College London; Institute for Globally Distributed Open Research and Education (Criaud); Institute of Human Sciences, University of Wolverhampton, Wolverhampton, U.K. (Westwood); Department of Psychology, School of Social Science, University of Westminster, London (Westwood); Southwest London and St George's Mental Health NHS Trust, London (Curran); South London and Maudsley NHS Foundation Trust, London (Barret, Abbott); Great Ormond Street Hospital for Children NHS Foundation Trust, London (Liang); Department of Child and Adolescent Psychiatry, Technical University Dresden, Germany (Rubia)
| | - Holan Liang
- Department of Child and Adolescent Psychiatry (Lam, Criaud, Lukito, Westwood, Simonoff, Rubia), Department of Neuroimaging (Kowalczyk, Barker, Giampietro), and Department of Biostatistics (Agbedjro), King's College London; Institute for Globally Distributed Open Research and Education (Criaud); Institute of Human Sciences, University of Wolverhampton, Wolverhampton, U.K. (Westwood); Department of Psychology, School of Social Science, University of Westminster, London (Westwood); Southwest London and St George's Mental Health NHS Trust, London (Curran); South London and Maudsley NHS Foundation Trust, London (Barret, Abbott); Great Ormond Street Hospital for Children NHS Foundation Trust, London (Liang); Department of Child and Adolescent Psychiatry, Technical University Dresden, Germany (Rubia)
| | - Emily Simonoff
- Department of Child and Adolescent Psychiatry (Lam, Criaud, Lukito, Westwood, Simonoff, Rubia), Department of Neuroimaging (Kowalczyk, Barker, Giampietro), and Department of Biostatistics (Agbedjro), King's College London; Institute for Globally Distributed Open Research and Education (Criaud); Institute of Human Sciences, University of Wolverhampton, Wolverhampton, U.K. (Westwood); Department of Psychology, School of Social Science, University of Westminster, London (Westwood); Southwest London and St George's Mental Health NHS Trust, London (Curran); South London and Maudsley NHS Foundation Trust, London (Barret, Abbott); Great Ormond Street Hospital for Children NHS Foundation Trust, London (Liang); Department of Child and Adolescent Psychiatry, Technical University Dresden, Germany (Rubia)
| | - Gareth J Barker
- Department of Child and Adolescent Psychiatry (Lam, Criaud, Lukito, Westwood, Simonoff, Rubia), Department of Neuroimaging (Kowalczyk, Barker, Giampietro), and Department of Biostatistics (Agbedjro), King's College London; Institute for Globally Distributed Open Research and Education (Criaud); Institute of Human Sciences, University of Wolverhampton, Wolverhampton, U.K. (Westwood); Department of Psychology, School of Social Science, University of Westminster, London (Westwood); Southwest London and St George's Mental Health NHS Trust, London (Curran); South London and Maudsley NHS Foundation Trust, London (Barret, Abbott); Great Ormond Street Hospital for Children NHS Foundation Trust, London (Liang); Department of Child and Adolescent Psychiatry, Technical University Dresden, Germany (Rubia)
| | - Vincent Giampietro
- Department of Child and Adolescent Psychiatry (Lam, Criaud, Lukito, Westwood, Simonoff, Rubia), Department of Neuroimaging (Kowalczyk, Barker, Giampietro), and Department of Biostatistics (Agbedjro), King's College London; Institute for Globally Distributed Open Research and Education (Criaud); Institute of Human Sciences, University of Wolverhampton, Wolverhampton, U.K. (Westwood); Department of Psychology, School of Social Science, University of Westminster, London (Westwood); Southwest London and St George's Mental Health NHS Trust, London (Curran); South London and Maudsley NHS Foundation Trust, London (Barret, Abbott); Great Ormond Street Hospital for Children NHS Foundation Trust, London (Liang); Department of Child and Adolescent Psychiatry, Technical University Dresden, Germany (Rubia)
| | - Katya Rubia
- Department of Child and Adolescent Psychiatry (Lam, Criaud, Lukito, Westwood, Simonoff, Rubia), Department of Neuroimaging (Kowalczyk, Barker, Giampietro), and Department of Biostatistics (Agbedjro), King's College London; Institute for Globally Distributed Open Research and Education (Criaud); Institute of Human Sciences, University of Wolverhampton, Wolverhampton, U.K. (Westwood); Department of Psychology, School of Social Science, University of Westminster, London (Westwood); Southwest London and St George's Mental Health NHS Trust, London (Curran); South London and Maudsley NHS Foundation Trust, London (Barret, Abbott); Great Ormond Street Hospital for Children NHS Foundation Trust, London (Liang); Department of Child and Adolescent Psychiatry, Technical University Dresden, Germany (Rubia)
| |
Collapse
|
33
|
Perez TM, Glue P, Adhia DB, Navid MS, Zeng J, Dillingham P, Smith M, Niazi IK, Young CK, De Ridder D. Infraslow closed-loop brain training for anxiety and depression (ISAD): a protocol for a randomized, double-blind, sham-controlled pilot trial in adult females with internalizing disorders. Trials 2022; 23:949. [DOI: 10.1186/s13063-022-06863-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 10/22/2022] [Indexed: 11/18/2022] Open
Abstract
Abstract
Background
The core intrinsic connectivity networks (core-ICNs), encompassing the default-mode network (DMN), salience network (SN) and central executive network (CEN), have been shown to be dysfunctional in individuals with internalizing disorders (IDs, e.g. major depressive disorder, MDD; generalized anxiety disorder, GAD; social anxiety disorder, SOC). As such, source-localized, closed-loop brain training of electrophysiological signals, also known as standardized low-resolution electromagnetic tomography (sLORETA) neurofeedback (NFB), targeting key cortical nodes within these networks has the potential to reduce symptoms associated with IDs and restore normal core ICN function. We intend to conduct a randomized, double-blind (participant and assessor), sham-controlled, parallel-group (3-arm) trial of sLORETA infraslow (<0.1 Hz) fluctuation neurofeedback (sLORETA ISF-NFB) 3 times per week over 4 weeks in participants (n=60) with IDs. Our primary objectives will be to examine patient-reported outcomes (PROs) and neurophysiological measures to (1) compare the potential effects of sham ISF-NFB to either genuine 1-region ISF-NFB or genuine 2-region ISF-NFB, and (2) assess for potential associations between changes in PRO scores and modifications of electroencephalographic (EEG) activity/connectivity within/between the trained regions of interest (ROIs). As part of an exploratory analysis, we will investigate the effects of additional training sessions and the potential for the potentiation of the effects over time.
Methods
We will randomly assign participants who meet the criteria for MDD, GAD, and/or SOC per the MINI (Mini International Neuropsychiatric Interview for DSM-5) to one of three groups: (1) 12 sessions of posterior cingulate cortex (PCC) ISF-NFB up-training (n=15), (2) 12 sessions of concurrent PCC ISF up-training and dorsal anterior cingulate cortex (dACC) ISF-NFB down-training (n=15), or (3) 6 sessions of yoked-sham training followed by 6 sessions genuine ISF-NFB (n=30). Transdiagnostic PROs (Hospital Anxiety and Depression Scale, HADS; Inventory of Depression and Anxiety Symptoms – Second Version, IDAS-II; Multidimensional Emotional Disorder Inventory, MEDI; Intolerance of Uncertainty Scale – Short Form, IUS-12; Repetitive Thinking Questionnaire, RTQ-10) as well as resting-state neurophysiological measures (full-band EEG and ECG) will be collected from all subjects during two baseline sessions (approximately 1 week apart) then at post 6 sessions, post 12 sessions, and follow-up (1 month later). We will employ Bayesian methods in R and advanced source-localisation software (i.e. exact low-resolution brain electromagnetic tomography; eLORETA) in our analysis.
Discussion
This protocol will outline the rationale and research methodology for a clinical pilot trial of sLORETA ISF-NFB targeting key nodes within the core-ICNs in a female ID population with the primary aims being to assess its potential efficacy via transdiagnostic PROs and relevant neurophysiological measures.
Trial registration
Our study was prospectively registered with the Australia New Zealand Clinical Trials Registry (ANZCTR; Trial ID: ACTRN12619001428156). Registered on October 15, 2019.
Collapse
|
34
|
Patil AU, Madathil D, Fan YT, Tzeng OJL, Huang CM, Huang HW. Neurofeedback for the Education of Children with ADHD and Specific Learning Disorders: A Review. Brain Sci 2022; 12:brainsci12091238. [PMID: 36138974 PMCID: PMC9497239 DOI: 10.3390/brainsci12091238] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 09/03/2022] [Accepted: 09/07/2022] [Indexed: 12/02/2022] Open
Abstract
Neurofeedback (NF) is a type of biofeedback in which an individual’s brain activity is measured and presented to them to support self-regulation of ongoing brain oscillations and achieve specific behavioral and neurophysiological outcomes. NF training induces changes in neurophysiological circuits that are associated with behavioral changes. Recent evidence suggests that the NF technique can be used to train electrical brain activity and facilitate learning among children with learning disorders. Toward this aim, this review first presents a generalized model for NF systems, and then studies involving NF training for children with disorders such as dyslexia, attention-deficit/hyperactivity disorder (ADHD), and other specific learning disorders such as dyscalculia and dysgraphia are reviewed. The discussion elaborates on the potential for translational applications of NF in educational and learning settings with details. This review also addresses some issues concerning the role of NF in education, and it concludes with some solutions and future directions. In order to provide the best learning environment for children with ADHD and other learning disorders, it is critical to better understand the role of NF in educational settings. The review provides the potential challenges of the current systems to aid in highlighting the issues undermining the efficacy of current systems and identifying solutions to address them. The review focuses on the use of NF technology in education for the development of adaptive teaching methods and the best learning environment for children with learning disabilities.
Collapse
Affiliation(s)
- Abhishek Uday Patil
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan
| | - Deepa Madathil
- Jindal Institute of Behavioural Sciences, O.P. Jindal Global University, Haryana 131001, India
| | - Yang-Tang Fan
- Graduate Institute of Medicine, Yuan Ze University, Taoyuan 320315, Taiwan
| | - Ovid J. L. Tzeng
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan
- Centre for Intelligent Drug Systems and Smart Bio-Devices (IDSB), National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan
- College of Humanities and Social Sciences, Taipei Medical University, Taipei 106339, Taiwan
- Department of Educational Psychology and Counseling, National Taiwan Normal University, Taipei 106308, Taiwan
- Hong Kong Institute for Advanced Studies, City University of Hong Kong, Hong Kong
| | - Chih-Mao Huang
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan
- Centre for Intelligent Drug Systems and Smart Bio-Devices (IDSB), National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan
| | - Hsu-Wen Huang
- Department of Linguistics and Translation, City University of Hong Kong, Hong Kong
- Correspondence: ; Tel.: +852-3442-2579
| |
Collapse
|
35
|
Pereira JA, Ray A, Rana M, Silva C, Salinas C, Zamorano F, Irani M, Opazo P, Sitaram R, Ruiz S. A real-time fMRI neurofeedback system for the clinical alleviation of depression with a subject-independent classification of brain states: A proof of principle study. Front Hum Neurosci 2022; 16:933559. [PMID: 36092645 PMCID: PMC9452730 DOI: 10.3389/fnhum.2022.933559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Accepted: 07/25/2022] [Indexed: 11/13/2022] Open
Abstract
Most clinical neurofeedback studies based on functional magnetic resonance imaging use the patient's own neural activity as feedback. The objective of this study was to create a subject-independent brain state classifier as part of a real-time fMRI neurofeedback (rt-fMRI NF) system that can guide patients with depression in achieving a healthy brain state, and then to examine subsequent clinical changes. In a first step, a brain classifier based on a support vector machine (SVM) was trained from the neural information of happy autobiographical imagery and motor imagery blocks received from a healthy female participant during an MRI session. In the second step, 7 right-handed female patients with mild or moderate depressive symptoms were trained to match their own neural activity with the neural activity corresponding to the “happiness emotional brain state” of the healthy participant. The training (4 training sessions over 2 weeks) was carried out using the rt-fMRI NF system guided by the brain-state classifier we had created. Thus, the informative voxels previously obtained in the first step, using SVM classification and Effect Mapping, were used to classify the Blood-Oxygen-Level Dependent (BOLD) activity of the patients and converted into real-time visual feedback during the neurofeedback training runs. Improvements in the classifier accuracy toward the end of the training were observed in all the patients [Session 4–1 Median = 6.563%; Range = 4.10–27.34; Wilcoxon Test (0), 2-tailed p = 0.031]. Clinical improvement also was observed in a blind standardized clinical evaluation [HDRS CE2-1 Median = 7; Range 2 to 15; Wilcoxon Test (0), 2-tailed p = 0.016], and in self-report assessments [BDI-II CE2-1 Median = 8; Range 1–15; Wilcoxon Test (0), 2-tailed p = 0.031]. In addition, the clinical improvement was still present 10 days after the intervention [BDI-II CE3-2_Median = 0; Range −1 to 2; Wilcoxon Test (0), 2-tailed p = 0.50/ HDRS CE3-2 Median = 0; Range −1 to 2; Wilcoxon Test (0), 2-tailed p = 0.625]. Although the number of participants needs to be increased and a control group included to confirm these findings, the results suggest a novel option for neural modulation and clinical alleviation in depression using noninvasive stimulation technologies.
Collapse
Affiliation(s)
- Jaime A. Pereira
- Departamento de Psiquiatría, Facultad de Medicina, Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago, Chile
- Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Andreas Ray
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Mohit Rana
- Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Claudio Silva
- Unidad de Imágenes Cuantitativas Avanzadas, Departamento de Imágenes, Facultad de Medicina, Clínica Alemana- Universidad del Desarrollo, Santiago, Chile
| | - Cesar Salinas
- Unidad de Imágenes Cuantitativas Avanzadas, Departamento de Imágenes, Facultad de Medicina, Clínica Alemana- Universidad del Desarrollo, Santiago, Chile
| | - Francisco Zamorano
- Unidad de Imágenes Cuantitativas Avanzadas, Departamento de Imágenes, Facultad de Medicina, Clínica Alemana- Universidad del Desarrollo, Santiago, Chile
- Laboratorio de Neurociencia Social y Neuromodulación, Centro de Investigación en Complejidad Social (neuroCICS), Facultad de Gobierno, Universidad del Desarrollo, Santiago, Chile
| | - Martin Irani
- Departamento de Psiquiatría, Facultad de Medicina, Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Patricia Opazo
- Departamento de Psiquiatría, Facultad de Medicina, Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Ranganatha Sitaram
- Departamento de Psiquiatría, Facultad de Medicina, Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago, Chile
- Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, United States
- *Correspondence: Ranganatha Sitaram
| | - Sergio Ruiz
- Departamento de Psiquiatría, Facultad de Medicina, Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago, Chile
- Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile
- Sergio Ruiz
| |
Collapse
|
36
|
Orth L, Meeh J, Gur RC, Neuner I, Sarkheil P. Frontostriatal circuitry as a target for fMRI-based neurofeedback interventions: A systematic review. Front Hum Neurosci 2022; 16:933718. [PMID: 36092647 PMCID: PMC9449529 DOI: 10.3389/fnhum.2022.933718] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Accepted: 08/08/2022] [Indexed: 11/19/2022] Open
Abstract
Dysregulated frontostriatal circuitries are viewed as a common target for the treatment of aberrant behaviors in various psychiatric and neurological disorders. Accordingly, experimental neurofeedback paradigms have been applied to modify the frontostriatal circuitry. The human frontostriatal circuitry is topographically and functionally organized into the “limbic,” the “associative,” and the “motor” subsystems underlying a variety of affective, cognitive, and motor functions. We conducted a systematic review of the literature regarding functional magnetic resonance imaging-based neurofeedback studies that targeted brain activations within the frontostriatal circuitry. Seventy-nine published studies were included in our survey. We assessed the efficacy of these studies in terms of imaging findings of neurofeedback intervention as well as behavioral and clinical outcomes. Furthermore, we evaluated whether the neurofeedback targets of the studies could be assigned to the identifiable frontostriatal subsystems. The majority of studies that targeted frontostriatal circuitry functions focused on the anterior cingulate cortex, the dorsolateral prefrontal cortex, and the supplementary motor area. Only a few studies (n = 14) targeted the connectivity of the frontostriatal regions. However, post-hoc analyses of connectivity changes were reported in more cases (n = 32). Neurofeedback has been frequently used to modify brain activations within the frontostriatal circuitry. Given the regulatory mechanisms within the closed loop of the frontostriatal circuitry, the connectivity-based neurofeedback paradigms should be primarily considered for modifications of this system. The anatomical and functional organization of the frontostriatal system needs to be considered in decisions pertaining to the neurofeedback targets.
Collapse
Affiliation(s)
- Linda Orth
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany
- *Correspondence: Linda Orth
| | - Johanna Meeh
- Department of Psychiatry and Psychotherapy, University of Münster, Münster, Germany
| | - Ruben C. Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Irene Neuner
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany
- Institute of Neuroscience and Medicine 4, Forschungszentrum Jülich, Jülich, Germany
| | - Pegah Sarkheil
- Department of Psychiatry and Psychotherapy, University of Münster, Münster, Germany
| |
Collapse
|
37
|
Analysis of individual differences in neurofeedback training illuminates successful self-regulation of the dopaminergic midbrain. Commun Biol 2022; 5:845. [PMID: 35986202 PMCID: PMC9391365 DOI: 10.1038/s42003-022-03756-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 07/21/2022] [Indexed: 11/27/2022] Open
Abstract
The dopaminergic midbrain is associated with reinforcement learning, motivation and decision-making – functions often disturbed in neuropsychiatric disorders. Previous research has shown that dopaminergic midbrain activity can be endogenously modulated via neurofeedback. However, the robustness of endogenous modulation, a requirement for clinical translation, is unclear. Here, we examine whether the activation of particular brain regions associates with successful regulation transfer when feedback is no longer available. Moreover, to elucidate mechanisms underlying effective self-regulation, we study the relation of successful transfer with learning (temporal difference coding) outside the midbrain during neurofeedback training and with individual reward sensitivity in a monetary incentive delay (MID) task. Fifty-nine participants underwent neurofeedback training either in standard (Study 1 N = 15, Study 2 N = 28) or control feedback group (Study 1, N = 16). We find that successful self-regulation is associated with prefrontal reward sensitivity in the MID task (N = 25), with a decreasing relation between prefrontal activity and midbrain learning signals during neurofeedback training and with increased activity within cognitive control areas during transfer. The association between midbrain self-regulation and prefrontal temporal difference and reward sensitivity suggests that reinforcement learning contributes to successful self-regulation. Our findings provide insights in the control of midbrain activity and may facilitate individually tailoring neurofeedback training. Analysis of real-time fMRI data from 59 participants undergoing neurofeedback training suggests that reinforcement learning contributes to successful self-regulation in the dopaminergic midbrain.
Collapse
|
38
|
Kvamme TL, Sarmanlu M, Overgaard M. Doubting the double-blind: Introducing a questionnaire for awareness of experimental purposes in neurofeedback studies. Conscious Cogn 2022; 104:103381. [PMID: 35947940 DOI: 10.1016/j.concog.2022.103381] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 07/18/2022] [Accepted: 07/19/2022] [Indexed: 11/29/2022]
Abstract
Double-blinding subjects to the experiment's purpose is an important standard in neurofeedback studies. However, it is difficult to provide evidence that humans are entirely unaware of certain information. This study used insights from consciousness studies and neurophenomenology to develop a contingency awareness questionnaire for neurofeedback. We assessed whether participants had an awareness of experimental purposes to manipulate their attention and multisensory perception. A subset of subjects (5 out of 20) gained a degree of awareness of experimental purposes as evidenced by their correct guess about the purposes of the experiment to affect their attention and multisensory perceptions specific to their double-blinded group assignment. The results warrant replication before they are applied to clinical neurofeedback studies, given the considerable time taken to perform the questionnaire (∼25 min). We discuss the strengths and limitations of our contingency awareness questionnaire and the growing appeal of the double-blinded standard in clinical neurofeedback studies.
Collapse
Affiliation(s)
- Timo L Kvamme
- Cognitive Neuroscience Research Unit, CFIN/MINDLab, Aarhus University, Aarhus, Denmark; Centre for Alcohol and Drug Research, Aarhus University, Aarhus, Denmark.
| | - Mesud Sarmanlu
- Cognitive Neuroscience Research Unit, CFIN/MINDLab, Aarhus University, Aarhus, Denmark
| | - Morten Overgaard
- Cognitive Neuroscience Research Unit, CFIN/MINDLab, Aarhus University, Aarhus, Denmark
| |
Collapse
|
39
|
Real-time fMRI neurofeedback compared to cognitive behavioral therapy in a pilot study for the treatment of mild and moderate depression. Eur Arch Psychiatry Clin Neurosci 2022:10.1007/s00406-022-01462-0. [PMID: 35908116 PMCID: PMC10359372 DOI: 10.1007/s00406-022-01462-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 07/01/2022] [Indexed: 11/03/2022]
Abstract
Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback was found to reduce depressive symptoms. However, no direct comparison of drug-free patients with an active psychotherapy control group is available. The present study compared rt-fMRI neurofeedback with cognitive behavioral therapy, as the standard treatment in patients declining anti-depressants. Twenty adult, drug-free patients with mild or moderate depression were non-randomly assigned either to a course of eight half-hour sessions of neurofeedback targeting the left medial prefrontal cortex (N = 12) or to a 16-session course of cognitive behavioral therapy (N = 8). Montgomery-Asberg Depression Rating Scale was introduced at baseline, mid-treatment, and end-treatment points. In each group, 8 patients each remained in the study to a mid-treatment evaluation and 6 patients each to the study end-point. ANOVA revealed a depression reduction with a significant effect of Time (F(3,6) = 19.0, p < 0.001, η2 = 0.76). A trend to greater improvement in the cognitive behavioral therapy group compared to neurofeedback emerged (Group × Time; p = 0.078). Percent signal change in the region of interest between up- and down-regulation conditions was significantly correlated with session number (Pearson's r = 0.85, p < 0.001) indicating a learning effect. As limitations, small sample size could lead to insufficient power and non-random allocation to selection bias. Both neurofeedback and cognitive behavioral therapy improved mild and moderate depression. Neurofeedback was not superior to cognitive behavioral therapy. Noteworthy, the neurofeedback training course was associated with continuous improvement in the self-regulation skill, without plateau. This study delivers data to plan clinical trials comparing neurofeedback with cognitive behavioral interventions.
Collapse
|
40
|
Goldway N, Jalon I, Keynan JN, Hellrung L, Horstmann A, Paret C, Hendler T. Feasibility and utility of amygdala neurofeedback. Neurosci Biobehav Rev 2022; 138:104694. [PMID: 35623447 DOI: 10.1016/j.neubiorev.2022.104694] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Revised: 04/12/2022] [Accepted: 05/11/2022] [Indexed: 10/18/2022]
Abstract
Amygdala NeuroFeedback (NF) have the potential of being a valuable non-invasive intervention tool in many psychiatric disporders. However, the feasibility and best practices of this method have not been systematically examined. The current article presents a review of amygdala-NF studies, an analytic summary of study design parameters, and examination of brain mechanisms related to successful amygdala-NF performance. A meta-analysis of 33 publications showed that real amygdala-NF facilitates learned modulation compared to control conditions. In addition, while variability in study dsign parameters is high, these design choices are implicitly organized by the targeted valence domain (positive or negative). However, in most cases the neuro-behavioral effects of targeting such domains were not directly assessed. Lastly, re-analyzing six data sets of amygdala-fMRI-NF revealed that successful amygdala down-modulation is coupled with deactivation of the posterior insula and nodes in the Default-Mode-Network. Our findings suggest that amygdala self-modulation can be acquired using NF. Yet, additional controlled studies, relevant behavioral tasks before and after NF intervention, and neural 'target engagement' measures are critically needed to establish efficacy and specificity. In addition, the fMRI analysis presented here suggest that common accounts regarding the brain network involved in amygdala NF might reflect unsuccessful modulation attempts rather than successful modulation.
Collapse
Affiliation(s)
- Noam Goldway
- Sagol Brain Institute, Wohl Institute for Advanced Imaging, Tel-Aviv Sourasky Medical Centre, Tel-Aviv, Israel; Sagol School of Neuroscience, Tel Aviv University, Tel-Aviv, Israel; Department of Psychology, New York University, New York, USA
| | - Itamar Jalon
- Sagol Brain Institute, Wohl Institute for Advanced Imaging, Tel-Aviv Sourasky Medical Centre, Tel-Aviv, Israel; School of Psychological Sciences, Tel Aviv University, Tel-Aviv, Israel
| | - Jackob N Keynan
- Sagol Brain Institute, Wohl Institute for Advanced Imaging, Tel-Aviv Sourasky Medical Centre, Tel-Aviv, Israel; Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Lydia Hellrung
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Laboratory for Social and Neural Systems Research, Department of Economics, University of Zurich, Zurich, Switzerland
| | - Annette Horstmann
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Faculty of Medicine, University of Leipzig, Leipzig, Germany; Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Christian Paret
- Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health Mannheim, Medical Faculty Mannheim/Heidelberg University, Germany
| | - Talma Hendler
- Sagol Brain Institute, Wohl Institute for Advanced Imaging, Tel-Aviv Sourasky Medical Centre, Tel-Aviv, Israel; Sagol School of Neuroscience, Tel Aviv University, Tel-Aviv, Israel; School of Psychological Sciences, Tel Aviv University, Tel-Aviv, Israel; Sackler School of Medicine, Tel Aviv University, Tel-Aviv, Israel.
| |
Collapse
|
41
|
Kvamme TL, Ros T, Overgaard M. Can neurofeedback provide evidence of direct brain-behavior causality? Neuroimage 2022; 258:119400. [PMID: 35728786 DOI: 10.1016/j.neuroimage.2022.119400] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 06/13/2022] [Accepted: 06/17/2022] [Indexed: 01/01/2023] Open
Abstract
Neurofeedback is a procedure that measures brain activity in real-time and presents it as feedback to an individual, thus allowing them to self-regulate brain activity with effects on cognitive processes inferred from behavior. One common argument is that neurofeedback studies can reveal how the measured brain activity causes a particular cognitive process. The causal claim is often made regarding the measured brain activity being manipulated as an independent variable, similar to brain stimulation studies. However, this causal inference is vulnerable to the argument that other upstream brain activities change concurrently and cause changes in the brain activity from which feedback is derived. In this paper, we outline the inference that neurofeedback may causally affect cognition by indirect means. We further argue that researchers should remain open to the idea that the trained brain activity could be part of a "causal network" that collectively affects cognition rather than being necessarily causally primary. This particular inference may provide a better translation of evidence from neurofeedback studies to the rest of neuroscience. We argue that the recent advent of multivariate pattern analysis, when combined with implicit neurofeedback, currently comprises the strongest case for causality. Our perspective is that although the burden of inferring direct causality is difficult, it may be triangulated using a collection of various methods in neuroscience. Finally, we argue that the neurofeedback methodology provides unique advantages compared to other methods for revealing changes in the brain and cognitive processes but that researchers should remain mindful of indirect causal effects.
Collapse
Affiliation(s)
- Timo L Kvamme
- Cognitive Neuroscience Research Unit, CFIN/MINDLab, Aarhus University, Universitetsbyen 3, Aarhus, Denmark; Centre for Alcohol and Drug Research (CRF), Aarhus University, Aarhus, Denmark.
| | - Tomas Ros
- Departments of Neuroscience and Psychiatry, University of Geneva, Campus Biotech, Geneva, Switzerland
| | - Morten Overgaard
- Cognitive Neuroscience Research Unit, CFIN/MINDLab, Aarhus University, Universitetsbyen 3, Aarhus, Denmark
| |
Collapse
|
42
|
Wöstmann M, Störmer VS, Obleser J, Addleman DA, Andersen SK, Gaspelin N, Geng JJ, Luck SJ, Noonan MP, Slagter HA, Theeuwes J. Ten simple rules to study distractor suppression. Prog Neurobiol 2022. [PMID: 35427732 DOI: 10.1016/j.pneurobio.2022.102269] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Distractor suppression refers to the ability to filter out distracting and task-irrelevant information. Distractor suppression is essential for survival and considered a key aspect of selective attention. Despite the recent and rapidly evolving literature on distractor suppression, we still know little about how the brain suppresses distracting information. What limits progress is that we lack mutually agreed upon principles of how to study the neural basis of distractor suppression and its manifestation in behavior. Here, we offer ten simple rules that we believe are fundamental when investigating distractor suppression. We provide guidelines on how to design conclusive experiments on distractor suppression (Rules 1-3), discuss different types of distractor suppression that need to be distinguished (Rules 4-6), and provide an overview of models of distractor suppression and considerations of how to evaluate distractor suppression statistically (Rules 7-10). Together, these rules provide a concise and comprehensive synopsis of promising advances in the field of distractor suppression. Following these rules will propel research on distractor suppression in important ways, not only by highlighting prominent issues to both new and more advanced researchers in the field, but also by facilitating communication between sub-disciplines.
Collapse
Affiliation(s)
- Malte Wöstmann
- Department of Psychology, University of Lübeck, Lübeck, Germany; Center of Brain, Behavior and Metabolism (CBBM), University of Lübeck, Lübeck, Germany.
| | - Viola S Störmer
- Department of Psychological and Brain Sciences, Dartmouth College, USA.
| | - Jonas Obleser
- Department of Psychology, University of Lübeck, Lübeck, Germany; Center of Brain, Behavior and Metabolism (CBBM), University of Lübeck, Lübeck, Germany
| | | | - Søren K Andersen
- School of Psychology, University of Aberdeen, UK; Department of Psychology, University of Southern Denmark, Denmark
| | - Nicholas Gaspelin
- Department of Psychology and Department of Integrative Neuroscience, Binghamton University, State University of New York, USA
| | - Joy J Geng
- Center for Mind and Brain and Department of Psychology, University of California, Davis, USA
| | - Steven J Luck
- Center for Mind and Brain and Department of Psychology, University of California, Davis, USA
| | | | - Heleen A Slagter
- Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Institute for Brain and Behavior, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Jan Theeuwes
- Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Institute for Brain and Behavior, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| |
Collapse
|
43
|
Lubianiker N, Paret C, Dayan P, Hendler T. Neurofeedback through the lens of reinforcement learning. Trends Neurosci 2022; 45:579-593. [PMID: 35550813 DOI: 10.1016/j.tins.2022.03.008] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 02/11/2022] [Accepted: 03/24/2022] [Indexed: 11/29/2022]
Abstract
Despite decades of experimental and clinical practice, the neuropsychological mechanisms underlying neurofeedback (NF) training remain obscure. NF is a unique form of reinforcement learning (RL) task, during which participants are provided with rewarding feedback regarding desired changes in neural patterns. However, key RL considerations - including choices during practice, prediction errors, credit-assignment problems, or the exploration-exploitation tradeoff - have infrequently been considered in the context of NF. We offer an RL-based framework for NF, describing different internal states, actions, and rewards in common NF protocols, thus fashioning new proposals for characterizing, predicting, and hastening the course of learning. In this way we hope to advance current understanding of neural regulation via NF, and ultimately to promote its effectiveness, personalization, and clinical utility.
Collapse
Affiliation(s)
- Nitzan Lubianiker
- School of Psychological Sciences, Gershon H. Gordon Faculty of Social Sciences, Tel Aviv University, Tel Aviv, Israel; Sagol Brain Institute, Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
| | - Christian Paret
- School of Psychological Sciences, Gershon H. Gordon Faculty of Social Sciences, Tel Aviv University, Tel Aviv, Israel; Sagol Brain Institute, Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel; Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health Mannheim, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Peter Dayan
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany; University of Tübingen, Tübingen, Germany
| | - Talma Hendler
- School of Psychological Sciences, Gershon H. Gordon Faculty of Social Sciences, Tel Aviv University, Tel Aviv, Israel; Sagol Brain Institute, Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel; Sagol school of Neuroscience, Tel Aviv University, Tel Aviv, Israel; Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
| |
Collapse
|
44
|
Marins T, Tovar-Moll F. Using neurofeedback to induce and explore brain plasticity. Trends Neurosci 2022; 45:415-416. [DOI: 10.1016/j.tins.2022.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 03/27/2022] [Indexed: 10/18/2022]
|
45
|
Wöstmann M, Störmer VS, Obleser J, Addleman DA, Andersen SK, Gaspelin N, Geng JJ, Luck SJ, Noonan MP, Slagter HA, Theeuwes J. Ten simple rules to study distractor suppression. Prog Neurobiol 2022; 213:102269. [PMID: 35427732 PMCID: PMC9069241 DOI: 10.1016/j.pneurobio.2022.102269] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 03/28/2022] [Accepted: 04/04/2022] [Indexed: 01/23/2023]
Abstract
Distractor suppression refers to the ability to filter out distracting and task-irrelevant information. Distractor suppression is essential for survival and considered a key aspect of selective attention. Despite the recent and rapidly evolving literature on distractor suppression, we still know little about how the brain suppresses distracting information. What limits progress is that we lack mutually agreed upon principles of how to study the neural basis of distractor suppression and its manifestation in behavior. Here, we offer ten simple rules that we believe are fundamental when investigating distractor suppression. We provide guidelines on how to design conclusive experiments on distractor suppression (Rules 1–3), discuss different types of distractor suppression that need to be distinguished (Rules 4–6), and provide an overview of models of distractor suppression and considerations of how to evaluate distractor suppression statistically (Rules 7–10). Together, these rules provide a concise and comprehensive synopsis of promising advances in the field of distractor suppression. Following these rules will propel research on distractor suppression in important ways, not only by highlighting prominent issues to both new and more advanced researchers in the field, but also by facilitating communication between sub-disciplines. Distractor suppression is the ability to filter out irrelevant information. At present, we know little about how the brain suppresses distraction. We offer ten rules that are fundamental when investigating distractor suppression. Following the rules will propel research and foster interaction between disciplines.
Collapse
Affiliation(s)
- Malte Wöstmann
- Department of Psychology, University of Lübeck, Lübeck, Germany; Center of Brain, Behavior and Metabolism (CBBM), University of Lübeck, Lübeck, Germany.
| | - Viola S Störmer
- Department of Psychological and Brain Sciences, Dartmouth College, USA.
| | - Jonas Obleser
- Department of Psychology, University of Lübeck, Lübeck, Germany; Center of Brain, Behavior and Metabolism (CBBM), University of Lübeck, Lübeck, Germany
| | | | - Søren K Andersen
- School of Psychology, University of Aberdeen, UK; Department of Psychology, University of Southern Denmark, Denmark
| | - Nicholas Gaspelin
- Department of Psychology and Department of Integrative Neuroscience, Binghamton University, State University of New York, USA
| | - Joy J Geng
- Center for Mind and Brain and Department of Psychology, University of California, Davis, USA
| | - Steven J Luck
- Center for Mind and Brain and Department of Psychology, University of California, Davis, USA
| | | | - Heleen A Slagter
- Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Institute for Brain and Behavior, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Jan Theeuwes
- Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Institute for Brain and Behavior, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| |
Collapse
|
46
|
Cohen AL. Using causal methods to map symptoms to brain circuits in neurodevelopment disorders: moving from identifying correlates to developing treatments. J Neurodev Disord 2022; 14:19. [PMID: 35279095 PMCID: PMC8918299 DOI: 10.1186/s11689-022-09433-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 03/03/2022] [Indexed: 11/20/2022] Open
Abstract
A wide variety of model systems and experimental techniques can provide insight into the structure and function of the human brain in typical development and in neurodevelopmental disorders. Unfortunately, this work, whether based on manipulation of animal models or observational and correlational methods in humans, has a high attrition rate in translating scientific discovery into practicable treatments and therapies for neurodevelopmental disorders.With new computational and neuromodulatory approaches to interrogating brain networks, opportunities exist for "bedside-to bedside-translation" with a potentially shorter path to therapeutic options. Specifically, methods like lesion network mapping can identify brain networks involved in the generation of complex symptomatology, both from acute onset lesion-related symptoms and from focal developmental anomalies. Traditional neuroimaging can examine the generalizability of these findings to idiopathic populations, while non-invasive neuromodulation techniques such as transcranial magnetic stimulation provide the ability to do targeted activation or inhibition of these specific brain regions and networks. In parallel, real-time functional MRI neurofeedback also allow for endogenous neuromodulation of specific targets that may be out of reach for transcranial exogenous methods.Discovery of novel neuroanatomical circuits for transdiagnostic symptoms and neuroimaging-based endophenotypes may now be feasible for neurodevelopmental disorders using data from cohorts with focal brain anomalies. These novel circuits, after validation in large-scale highly characterized research cohorts and tested prospectively using noninvasive neuromodulation and neurofeedback techniques, may represent a new pathway for symptom-based targeted therapy.
Collapse
Affiliation(s)
- Alexander Li Cohen
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA. .,Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA. .,Laboratory for Brain Network Imaging and Modulation, Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
47
|
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] [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
Collapse
|
48
|
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).
Collapse
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.
| |
Collapse
|
49
|
Kumar M, Anderson MJ, Antony JW, Baldassano C, Brooks PP, Cai MB, Chen PHC, Ellis CT, Henselman-Petrusek G, Huberdeau D, Hutchinson JB, Li YP, Lu Q, Manning JR, Mennen AC, Nastase SA, Richard H, Schapiro AC, Schuck NW, Shvartsman M, Sundaram N, Suo D, Turek JS, Turner D, Vo VA, Wallace G, Wang Y, Williams JA, Zhang H, Zhu X, Capota˘ M, Cohen JD, Hasson U, Li K, Ramadge PJ, Turk-Browne NB, Willke TL, Norman KA. BrainIAK: The Brain Imaging Analysis Kit. APERTURE NEURO 2022; 1. [PMID: 35939268 PMCID: PMC9351935 DOI: 10.52294/31bb5b68-2184-411b-8c00-a1dacb61e1da] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
Functional magnetic resonance imaging (fMRI) offers a rich source of data for studying the neural basis of cognition. Here, we describe the Brain Imaging Analysis Kit (BrainIAK), an open-source, free Python package that provides computationally optimized solutions to key problems in advanced fMRI analysis. A variety of techniques are presently included in BrainIAK: intersubject correlation (ISC) and intersubject functional connectivity (ISFC), functional alignment via the shared response model (SRM), full correlation matrix analysis (FCMA), a Bayesian version of representational similarity analysis (BRSA), event segmentation using hidden Markov models, topographic factor analysis (TFA), inverted encoding models (IEMs), an fMRI data simulator that uses noise characteristics from real data (fmrisim), and some emerging methods. These techniques have been optimized to leverage the efficiencies of high-performance compute (HPC) clusters, and the same code can be seamlessly transferred from a laptop to a cluster. For each of the aforementioned techniques, we describe the data analysis problem that the technique is meant to solve and how it solves that problem; we also include an example Jupyter notebook for each technique and an annotated bibliography of papers that have used and/or described that technique. In addition to the sections describing various analysis techniques in BrainIAK, we have included sections describing the future applications of BrainIAK to real-time fMRI, tutorials that we have developed and shared online to facilitate learning the techniques in BrainIAK, computational innovations in BrainIAK, and how to contribute to BrainIAK. We hope that this manuscript helps readers to understand how BrainIAK might be useful in their research.
Collapse
Affiliation(s)
- Manoj Kumar
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ
| | - Michael J. Anderson
- Work done while at Parallel Computing Lab, Intel Corporation, Santa Clara, CA
| | - James W. Antony
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ
| | | | - Paula P. Brooks
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ
| | - Ming Bo Cai
- International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Japan
| | - Po-Hsuan Cameron Chen
- Work done while at Princeton Neuroscience Institute, Princeton University, Princeton, NJ
| | | | | | | | | | - Y. Peeta Li
- Department of Psychology, University of Oregon, Eugene, OR
| | - Qihong Lu
- Department of Psychology, Princeton University, Princeton, NJ
| | - Jeremy R. Manning
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH
| | - Anne C. Mennen
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ
| | - Samuel A. Nastase
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ
| | - Hugo Richard
- Parietal Team, Inria, Neurospin, CEA, Université Paris-Saclay, France
| | - Anna C. Schapiro
- Department of Psychology, University of Pennsylvania, Philadelphia, PA
| | - Nicolas W. Schuck
- Max Planck Research Group NeuroCode, Max Planck Institute for Human Development, Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
| | - Michael Shvartsman
- Work done while at Princeton Neuroscience Institute, Princeton University, Princeton, NJ
| | - Narayanan Sundaram
- Work done while at Parallel Computing Lab, Intel Corporation, Santa Clara, CA
| | - Daniel Suo
- epartment of Computer Science, Princeton University, Princeton, NJ
| | - Javier S. Turek
- Brain-Inspired Computing Lab, Intel Corporation, Hillsboro, OR
| | - David Turner
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ
| | - Vy A. Vo
- Brain-Inspired Computing Lab, Intel Corporation, Hillsboro, OR
| | - Grant Wallace
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ
| | - Yida Wang
- Work done while at Parallel Computing Lab, Intel Corporation, Santa Clara, CA
| | - Jamal A. Williams
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ; Department of Psychology, Princeton University, Princeton, NJ
| | - Hejia Zhang
- Work done while at Princeton Neuroscience Institute, Princeton University, Princeton, NJ
| | - Xia Zhu
- Brain-Inspired Computing Lab, Intel Corporation, Hillsboro, OR
| | - Mihai Capota˘
- Brain-Inspired Computing Lab, Intel Corporation, Hillsboro, OR
| | - Jonathan D. Cohen
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ; Department of Psychology, Princeton University, Princeton, NJ
| | - Uri Hasson
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ; Department of Psychology, Princeton University, Princeton, NJ
| | - Kai Li
- Department of Computer Science, Princeton University, Princeton, NJ
| | - Peter J. Ramadge
- Department of Electrical Engineering, and the Center for Statistics and Machine Learning, Princeton University, Princeton, NJ
| | | | | | - Kenneth A. Norman
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ; Department of Psychology, Princeton University, Princeton, NJ
| |
Collapse
|
50
|
Poststroke Cognitive Impairment Research Progress on Application of Brain-Computer Interface. BIOMED RESEARCH INTERNATIONAL 2022; 2022:9935192. [PMID: 35252458 PMCID: PMC8896931 DOI: 10.1155/2022/9935192] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 12/20/2021] [Accepted: 12/23/2021] [Indexed: 12/19/2022]
Abstract
Brain-computer interfaces (BCIs), a new type of rehabilitation technology, pick up nerve cell signals, identify and classify their activities, and convert them into computer-recognized instructions. This technique has been widely used in the rehabilitation of stroke patients in recent years and appears to promote motor function recovery after stroke. At present, the application of BCI in poststroke cognitive impairment is increasing, which is a common complication that also affects the rehabilitation process. This paper reviews the promise and potential drawbacks of using BCI to treat poststroke cognitive impairment, providing a solid theoretical basis for the application of BCI in this area.
Collapse
|