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Fagerland SM, Berntsen HR, Fredriksen M, Endestad T, Skouras S, Rootwelt-Revheim ME, Undseth RM. Exploring protocol development: Implementing systematic contextual memory to enhance real-time fMRI neurofeedback. JOURNAL OF ELECTRICAL BIOIMPEDANCE 2024; 15:41-62. [PMID: 38827812 PMCID: PMC11141335 DOI: 10.2478/joeb-2024-0006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/10/2024] [Indexed: 06/05/2024]
Abstract
Objective The goal of this study was to explore the development and implementation of a protocol for real-time fMRI neurofeedback (rtfMRI-nf) and to assess the potential for enhancing the selective brain activation using stimuli from Virtual Reality (VR). In this study we focused on two specific brain regions, supplementary motor area (SMA) and right inferior frontal gyrus (rIFG). Publications by other study groups have suggested impaired function in these specific brain regions in patients with the diagnoses Attention Deficit Hyperactivity Disorder (ADHD) and Tourette's Syndrome (TS). This study explored the development of a protocol to investigate if attention and contextual memory may be used to systematically strengthen the procedure of rtfMRI-nf. Methods We used open-science software and platforms for rtfMRI-nf and for developing a simulated repetition of the rtfMRI-nf brain training in VR. We conducted seven exploratory tests in which we updated the protocol at each step. During rtfMRI-nf, MRI images are analyzed live while a person is undergoing an MRI scan, and the results are simultaneously shown to the person in the MRI-scanner. By focusing the analysis on specific regions of the brain, this procedure can be used to help the person strengthen conscious control of these regions. The VR simulation of the same experience involved a walk through the hospital toward the MRI scanner where the training sessions were conducted, as well as a subsequent simulated repetition of the MRI training. The VR simulation was a 2D projection of the experience.The seven exploratory tests involved 19 volunteers. Through this exploration, methods for aiming within the brain (e.g. masks/algorithms for coordinate-system control) and calculations for the analyses (e.g. calculations based on connectivity versus activity) were updated by the project team throughout the project. The final procedure involved three initial rounds of rtfMRI-nf for learning brain strategies. Then, the volunteers were provided with VR headsets and given instructions for one week of use. Afterward, a new session with three rounds of rtfMRI-nf was conducted. Results Through our exploration of the indirect effect parameters - brain region activity (directed oxygenated blood flow), connectivity (degree of correlated activity in different regions), and neurofeedback score - the volunteers tended to increase activity in the reinforced brain regions through our seven tests. Updates of procedures and analyses were always conducted between pilots, and never within. The VR simulated repetition was tested in pilot 7, but the role of the VR contribution in this setting is unclear due to underpowered testing. Conclusion This proof-of-concept protocol implies how rtfMRI-nf may be used to selectively train two brain regions (SMA and rIFG). The method may likely be adapted to train any given region in the brain, but readers are advised to update and adapt the procedure to experimental needs.
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Affiliation(s)
- Steffen Maude Fagerland
- The Intervention Centre, Division of Technology and Innovation, Oslo University Hospital, Oslo, Norway
- Department of Cognitive and Neuropsychology, Department of Psychology, University of Oslo, Oslo, Norway
- RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, Department of Psychology, University of Oslo, Norway
| | - Henrik Røsholm Berntsen
- The Intervention Centre, Division of Technology and Innovation, Oslo University Hospital, Oslo, Norway
| | - Mats Fredriksen
- Neuropsychatric Outpatient Clinic, Vestfold Hospital Trust, Tønsberg, Norway
| | - Tor Endestad
- RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, Department of Psychology, University of Oslo, Norway
- Department of Neuropsychology, Helgeland Hospital, Norway
| | - Stavros Skouras
- Department of Fundamental Neurosciences, Faculty of Medicine, University of Geneva, Geneva, CH-1202, Switzerland
- Department of Biological and Medical Psychology, University of Bergen, Bergen, NO-5020, Norway
- Department of Neurology, Inselspital University Hospital Bern, Bern, CH-3010, Switzerland
| | - Mona Elisabeth Rootwelt-Revheim
- The Intervention Centre, Division of Technology and Innovation, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Ragnhild Marie Undseth
- The Intervention Centre, Division of Technology and Innovation, Oslo University Hospital, Oslo, Norway
- Department of Cognitive and Neuropsychology, Department of Psychology, University of Oslo, Oslo, Norway
- Division of Radiology Research, The Intervention Centre, Oslo University Hospital, Oslo, Norway
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Sawai S, Fujikawa S, Ohsumi C, Ushio R, Tamura K, Yamamoto R, Kai Y, Murata S, Shima K, Nakano H. Effects of neurofeedback on standing postural control task with combined imagined and executed movements. Front Neurosci 2023; 17:1199398. [PMID: 37483338 PMCID: PMC10360181 DOI: 10.3389/fnins.2023.1199398] [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: 04/03/2023] [Accepted: 06/16/2023] [Indexed: 07/25/2023] Open
Abstract
Introduction Motor imagery (MI) is a method of imagining movement without actual movement, and its use in combination with motor execution (ME) enhances the effects of motor learning. Neurofeedback (NFB) is another method that promotes the effects of MI. This study aimed to investigate the effects of NFB on combined MI and ME (MIME) training in a standing postural control task. Methods Sixteen participants were randomly divided into MIME and MIME + NFB groups and performed 10 trials of a postural control task on an unstable board, with nine trials of MI in between. Electroencephalogram was assessed during MI, and the MIME + NFB group received neurofeedback on the degree of MI via auditory stimulation. A postural control task using an unstable board was performed before and after the MIME task, during which postural instability was evaluated. Results Postural instability was reduced after the MIME task in both groups. In addition, the root mean square, which indicates the sway of the unstable board, was significantly reduced in the MIME + NFB group compared to that in the MIME group. Conclusion Our results indicate that MIME training is effective for motor learning of standing postural control. Furthermore, when MI and ME are combined, the feedback on the degree of MI enhances the learning effect.
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Affiliation(s)
- Shun Sawai
- Graduate School of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
- Department of Rehabilitation, Kyoto Kuno Hospital, Kyoto, Japan
| | - Shoya Fujikawa
- Department of Physical Therapy, Faculty of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
| | - Chihiro Ohsumi
- Department of Physical Therapy, Faculty of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
| | - Ryu Ushio
- Department of Physical Therapy, Faculty of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
| | - Kosuke Tamura
- Department of Physical Therapy, Faculty of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
| | - Ryosuke Yamamoto
- Department of Rehabilitation, Tesseikai Neurosurgical Hospital, Shijonawate, Japan
| | - Yoshihiro Kai
- Graduate School of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
- Department of Physical Therapy, Faculty of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
| | - Shin Murata
- Graduate School of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
- Department of Physical Therapy, Faculty of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
| | - Keisuke Shima
- Graduate School of Environment and Information Sciences, Yokohama National University, Yokohama, Japan
| | - Hideki Nakano
- Graduate School of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
- Department of Physical Therapy, Faculty of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
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Onagawa R, Muraoka Y, Hagura N, Takemi M. An investigation of the effectiveness of neurofeedback training on motor performance in healthy adults: A systematic review and meta-analysis. Neuroimage 2023; 270:120000. [PMID: 36870431 DOI: 10.1016/j.neuroimage.2023.120000] [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: 11/17/2022] [Revised: 02/26/2023] [Accepted: 02/28/2023] [Indexed: 03/06/2023] Open
Abstract
Neurofeedback training (NFT) refers to a training where the participants voluntarily aim to manipulate their own brain activity using the sensory feedback abstracted from their brain activity. NFT has attracted attention in the field of motor learning due to its potential as an alternative or additional training method for general physical training. In this study, a systematic review of NFT studies for motor performance improvements in healthy adults and a meta-analysis on the effectiveness of NFT were conducted. A computerized search was performed using the databases Web of Science, Scopus, PubMed, JDreamIII, and Ichushi-Web to identify relevant studies published between January 1st, 1990, and August 3rd, 2021. Thirty-three studies were identified for the qualitative synthesis and 16 randomized controlled trials (374 subjects) for the meta-analysis. The meta-analysis, including all trials found in the search, revealed significant effects of NFT for motor performance improvement examined at the timing after the last NFT session (standardized mean difference = 0.85, 95% CI [0.18-1.51]), but with the existence of publication biases and substantial heterogeneity among the trials. Subsequent meta-regression analysis demonstrated the dose-response gradient between NFTs and motor performance improvements; more than 125 min of cumulative training time may benefit for the subsequent motor performance. For each motor performance measure (e.g., speed, accuracy, and hand dexterity), the effectiveness of NFT remains inconclusive, mainly due to its small sample sizes. More empirical NFT studies for motor performance improvement may be needed to show beneficial effects on motor performance and to safely incorporate NFT into real-world scenarios.
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Affiliation(s)
- Ryoji Onagawa
- Faculty of Science and Engineering, Waseda University, Tokyo, Japan.
| | - Yoshihito Muraoka
- Graduate School of Science and Technology, Keio University, Kanagawa, Japan
| | - Nobuhiro Hagura
- Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology, Osaka, Japan; Graduate School of Frontiers Biosciences, Osaka University, Osaka, Japan
| | - Mitsuaki Takemi
- Graduate School of Science and Technology, Keio University, Kanagawa, Japan.
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Sawai S, Murata S, Fujikawa S, Yamamoto R, Shima K, Nakano H. Effects of neurofeedback training combined with transcranial direct current stimulation on motor imagery: A randomized controlled trial. Front Neurosci 2023; 17:1148336. [PMID: 36937688 PMCID: PMC10017549 DOI: 10.3389/fnins.2023.1148336] [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: 01/20/2023] [Accepted: 02/16/2023] [Indexed: 03/06/2023] Open
Abstract
Introduction Neurofeedback (NFB) training and transcranial direct current stimulation (tDCS) have been shown to individually improve motor imagery (MI) abilities. However, the effect of combining both of them with MI has not been verified. Therefore, the aim of this study was to examine the effect of applying tDCS directly before MI with NFB. Methods Participants were divided into an NFB group (n = 10) that performed MI with NFB and an NFB + tDCS group (n = 10) that received tDCS for 10 min before MI with NFB. Both groups performed 60 MI trials with NFB. The MI task was performed 20 times without NFB before and after training, and μ-event-related desynchronization (ERD) and vividness MI were evaluated. Results μ-ERD increased significantly in the NFB + tDCS group compared to the NFB group. MI vividness significantly increased before and after training. Discussion Transcranial direct current stimulation and NFB modulate different processes with respect to MI ability improvement; hence, their combination might further improve MI performance. The results of this study indicate that the combination of NFB and tDCS for MI is more effective in improving MI abilities than applying them individually.
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Affiliation(s)
- Shun Sawai
- Graduate School of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
- Department of Rehabilitation, Kyoto Kuno Hospital, Kyoto, Japan
| | - Shin Murata
- Graduate School of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
- Department of Physical Therapy, Faculty of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
| | - Shoya Fujikawa
- Department of Physical Therapy, Faculty of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
| | - Ryosuke Yamamoto
- Department of Rehabilitation, Tesseikai Neurosurgical Hospital, Shijonawate, Japan
| | - Keisuke Shima
- Graduate School of Environment and Information Sciences, Yokohama National University, Yokohama, Japan
| | - Hideki Nakano
- Graduate School of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
- Department of Physical Therapy, Faculty of Health Sciences, Kyoto Tachibana University, Kyoto, Japan
- *Correspondence: Hideki Nakano,
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Using Real-Time fMRI Neurofeedback to Modulate M1-Cerebellum Connectivity. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2022; 2022:8744982. [PMID: 36082347 PMCID: PMC9448559 DOI: 10.1155/2022/8744982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 07/16/2022] [Accepted: 07/25/2022] [Indexed: 11/18/2022]
Abstract
Objective The potential of neurofeedback to alter the M1-cerebellum connectivity was explored using motor imagery-based rt-fMRI. These regions were chosen due to their importance in motor performance and motor rehabilitation. Methods Four right-handed individuals were recruited to examine the potential to change the M1-cerebellum neurofeedback link. The University of Glasgow Cognitive Neuroimaging Centre used a 3T MRI scanner from January 2019 to January 2020 to conduct this prospective study. Everyone participated in each fMRI session, which included six NF training runs. Participants were instructed to imagine complicated hand motions during the NF training to raise a thermometer bar's height. To contrast the correlation coefficients between the initial and last NF runs, a t-test was performed post hoc. Results The neurofeedback connection between M1 and the cerebellum was strengthened in each participant. Motor imagery strategy was a significant task in training M1-cerebellum connectivity as participants used it successfully to enhance the activation level between these regions during M1-cerebellum modulation using real-time fMRI. The t-test and linear regression, on the other hand, showed this increase to be insignificant. Conclusion A novel technique to manipulate M1-cerebellum connectivity was discovered using real-time fMRI NF. This study showed that each participant's neurofeedback connectivity between M1 and cerebellum was enhanced. This increase, on the other hand, was insignificant statistically. The results showed that the connectivity between both areas increased positively. Through the integration of fMRI and neurofeedback, M1-cerebellum connectivity can be positively affected.
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Orth L, Meeh J, Gur RC, Neuner I, Sarkheil P. Frontostriatal circuitry as a target for fMRI-based neurofeedback interventions: A systematic review. Front Hum Neurosci 2022; 16:933718. [PMID: 36092647 PMCID: PMC9449529 DOI: 10.3389/fnhum.2022.933718] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Accepted: 08/08/2022] [Indexed: 11/19/2022] Open
Abstract
Dysregulated frontostriatal circuitries are viewed as a common target for the treatment of aberrant behaviors in various psychiatric and neurological disorders. Accordingly, experimental neurofeedback paradigms have been applied to modify the frontostriatal circuitry. The human frontostriatal circuitry is topographically and functionally organized into the “limbic,” the “associative,” and the “motor” subsystems underlying a variety of affective, cognitive, and motor functions. We conducted a systematic review of the literature regarding functional magnetic resonance imaging-based neurofeedback studies that targeted brain activations within the frontostriatal circuitry. Seventy-nine published studies were included in our survey. We assessed the efficacy of these studies in terms of imaging findings of neurofeedback intervention as well as behavioral and clinical outcomes. Furthermore, we evaluated whether the neurofeedback targets of the studies could be assigned to the identifiable frontostriatal subsystems. The majority of studies that targeted frontostriatal circuitry functions focused on the anterior cingulate cortex, the dorsolateral prefrontal cortex, and the supplementary motor area. Only a few studies (n = 14) targeted the connectivity of the frontostriatal regions. However, post-hoc analyses of connectivity changes were reported in more cases (n = 32). Neurofeedback has been frequently used to modify brain activations within the frontostriatal circuitry. Given the regulatory mechanisms within the closed loop of the frontostriatal circuitry, the connectivity-based neurofeedback paradigms should be primarily considered for modifications of this system. The anatomical and functional organization of the frontostriatal system needs to be considered in decisions pertaining to the neurofeedback targets.
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Affiliation(s)
- Linda Orth
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany
- *Correspondence: Linda Orth
| | - Johanna Meeh
- Department of Psychiatry and Psychotherapy, University of Münster, Münster, Germany
| | - Ruben C. Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Irene Neuner
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany
- Institute of Neuroscience and Medicine 4, Forschungszentrum Jülich, Jülich, Germany
| | - Pegah Sarkheil
- Department of Psychiatry and Psychotherapy, University of Münster, Münster, Germany
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Kumari R, Jarjees M, Susnoschi-Luca I, Purcell M, Vučković A. Effective Connectivity in Spinal Cord Injury-Induced Neuropathic Pain. SENSORS (BASEL, SWITZERLAND) 2022; 22:6337. [PMID: 36080805 PMCID: PMC9460641 DOI: 10.3390/s22176337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Revised: 08/05/2022] [Accepted: 08/19/2022] [Indexed: 06/15/2023]
Abstract
AIM The aim of this study was to differentiate the effects of spinal cord injury (SCI) and central neuropathic pain (CNP) on effective connectivity during motor imagery of legs, where CNP is typically experienced. METHODS Multichannel EEG was recorded during motor imagery of the legs in 3 groups of people: able-bodied (N = 10), SCI with existing CNP (N = 10), and SCI with no CNP (N = 20). The last group was followed up for 6 months to check for the onset of CNP. Source reconstruction was performed to obtain cortical activity in 17 areas spanning sensorimotor regions and pain matrix. Effective connectivity was calculated using the directed transfer function in 4 frequency bands and compared between groups. RESULTS A total of 50% of the SCI group with no CNP developed CNP later. Statistically significant differences in effective connectivity were found between all groups. The differences between groups were not dependent on the frequency band. Outflows from the supplementary motor area were greater for the able-bodied group while the outflows from the secondary somatosensory cortex were greater for the SCI groups. The group with existing CNP showed the least differences from the able-bodied group, appearing to reverse the effects of SCI. The connectivities involving the pain matrix were different between able-bodied and SCI groups irrespective of CNP status, indicating their involvement in motor networks generally. SIGNIFICANCE The study findings might help guide therapeutic interventions targeted at the brain for CNP alleviation as well as motor recovery post SCI.
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Affiliation(s)
- Radha Kumari
- Biomedical Engineering Research Division, University of Glasgow, Glasgow G12 8QQ, UK
| | - Mohammed Jarjees
- Biomedical Engineering Research Division, University of Glasgow, Glasgow G12 8QQ, UK
- Medical Instrumentation Techniques Engineering Department, Northern Technical University, Mosul 41002, Iraq
| | - Ioana Susnoschi-Luca
- Biomedical Engineering Research Division, University of Glasgow, Glasgow G12 8QQ, UK
| | - Mariel Purcell
- Queen Elizabeth National Spinal Injuries Unit, Queen Elizabeth University Hospital, Glasgow G51 4TF, UK
| | - Aleksandra Vučković
- Biomedical Engineering Research Division, University of Glasgow, Glasgow G12 8QQ, UK
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Zou Y, Li J, Fan Y, Zhang C, Kong Y. Functional near-infrared spectroscopy during motor imagery and motor execution in healthy adults. ZHONG NAN DA XUE XUE BAO. YI XUE BAN = JOURNAL OF CENTRAL SOUTH UNIVERSITY. MEDICAL SCIENCES 2022; 47:920-927. [PMID: 36039589 PMCID: PMC10930295 DOI: 10.11817/j.issn.1672-7347.2022.210689] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Indexed: 06/15/2023]
Abstract
OBJECTIVES Studies on the influence of motor imagery (MI) on brain structure and function are limited to traditional imaging techniques and the mechanism for MI therapy is not clear. By observing the brain activation mode during MI and motor execution (ME) in healthy adults, this study aims to use near-infrared brain imaging technology to provide theoretical basis for the treatment of MI. METHODS A total of 30 healthy adults recruited to the public from June 2021 to August 2021. The MI and ME of the right knee movement served as the task mode. Block design was repeated 5 times alternately in a 20 s task period and a 30 s resting period. The activation patterns of brain regions were compared between the 2 tasks, and the regression coefficient was calculated to reflect the activation intensity of each brain region by Nirspark and SPSS 23.0 softwares. RESULTS Lane 2, 3, 4, 5, 7, 9, 19, 20, 21, 24, 25, 26, 27, 32, 33, and 34 were significantly activated during the ME task (P<0.05, corrected by FDR) and lane 2, 5, 9, 16, 27, 29, 33, 34, and 35 were significantly activated during the MI task (P<0.05, corrected by FDR). According to the channel brain region registration information, the brain region activation pattern was similar during both MI and ME tasks in healthy adults, including left primary motor cortex (LM1), left primary sensory cortex (LS1), prefrontal pole, Broca area, and right supramarginal gyrus. Both LM1 and left pre-motor cortex (LPMC) were activated during MI in healthy adults, whereas dorsolateral prefrontal cortex (DLPFC) and only LM1 of the motor region were activated during ME. Compared to MI, the activation intensity of left sensory and left motor cortex was significantly enhanced in ME, and that of left and right prefrontal cortex especially left and right pars triangularis Broca's area (P<0.001, corrected by FDR) were significantly enhanced. CONCLUSIONS The rationality of MI therapy is proved by functional near-infrared spectroscopy. The involvement of DLPFC in motor decision-making may regulate the two-way feedback of premoter cortex-M1 during ME; and Broca area, closely related to the motor program understanding, participates in MI and ME.
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Affiliation(s)
- Ying Zou
- Medical School, Yueyang Vocational Technical College, Yueyang Hunan 414000.
| | - Jing Li
- Department of Rehabilitation, Second Xiangya Hospital, Central South University, Changsha 410011, China
| | - Yongmei Fan
- Department of Rehabilitation, Second Xiangya Hospital, Central South University, Changsha 410011, China
| | - Changjie Zhang
- Department of Rehabilitation, Second Xiangya Hospital, Central South University, Changsha 410011, China
| | - Ying Kong
- Department of Rehabilitation, Second Xiangya Hospital, Central South University, Changsha 410011, China.
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Madkhali Y, Aldehmi N, Pollick F. Functional Localizers for Motor Areas of the Brain Using fMRI. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2022; 2022:7589493. [PMID: 35669664 PMCID: PMC9167083 DOI: 10.1155/2022/7589493] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 04/23/2022] [Accepted: 05/10/2022] [Indexed: 11/17/2022]
Abstract
Neuroimaging researchers increasingly take advantage of the known functional properties of brain regions to localize motor regions in the brain and investigate changes in their activity under various conditions. Using this noninvasive functional MRI (fMRI) method makes it possible to identify and localize brain activation. There are many localizers that can be used to identify brain areas, namely, motor areas such as functional localizer, anatomical localizer, or Atlas mask. Eighteen right-handed participants were recruited for this research to test the reliability of five localizers for primary motor cortex (M1), supplementary motor area (SMA), premotor cortex (PMC), motor cerebellum, and motor thalamus. Motor execution task, namely, hand clenching was used to activate M1, SMA, and motor cerebellum. A combined action observation and motor imagery (AOMI) task was used to functionally activate PMC. Finally, a mask based on Talairach coordinates Atlas was created and used to identify the motor thalamus. Our results show that all localizers were successfully activated in the desired regions of interest. Motor execution successfully activated M1, SMA, and motor cerebellum. A novel localizer based on AOMI was successfully activated in PMC, and the motor thalamus mask obtained from the thalamus mask was successfully implemented on each participant. In conclusion, all five localizers tested in this research were reliable and can be used for rt-fMRI neurofeedback research to define the regions of interest.
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Affiliation(s)
- Yahia Madkhali
- Faculty of Applied Medical Sciences, Jazan University, Jizan, Saudi Arabia
| | - Norah Aldehmi
- College of Medical, Veterinary and Life Sciences (MVLS), University of Glasgow, Glasgow, UK
| | - Frank Pollick
- School of Psychology, University of Glasgow, Glasgow, UK
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Ciarlo A, Russo AG, Ponticorvo S, Di Salle F, Lührs M, Goebel R, Esposito F. Semantic fMRI neurofeedback: A Multi-Subject Study at 3 Tesla. J Neural Eng 2022; 19. [PMID: 35561669 DOI: 10.1088/1741-2552/ac6f81] [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: 09/13/2021] [Accepted: 05/13/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Real-time fMRI neurofeedback is a non-invasive procedure allowing the self-regulation of brain functions via enhanced self-control of fMRI based neural activation. In semantic real-time fMRI neurofeedback, an estimated relation between multivariate fMRI activation patterns and abstract mental states is exploited for a multi-dimensional feedback stimulus via real-time representational similarity analysis (rt-RSA). Here, we assessed the performances of this framework in a multi-subject multi-session study on a 3T MRI clinical scanner. APPROACH Eighteen healthy volunteers underwent two semantic real-time fMRI neurofeedback sessions on two different days. In each session, participants were first requested to engage in specific mental states while local fMRI patterns of brain activity were recorded during stimulated mental imagery of concrete objects (pattern generation). The obtained neural representations were to be replicated and modulated by the participants in subsequent runs of the same session under the guidance of a rt-RSA generated visual feedback (pattern modulation). Performance indicators were derived from the rt-RSA output to assess individual abilities in replicating (and maintaining over time) a target pattern. Simulations were carried out to assess the impact of the geometric distortions implied by the low-dimensional representation of patterns' dissimilarities in the visual feedback. MAIN RESULTS Sixteen subjects successfully completed both semantic real-time fMRI neurofeedback sessions. Considering some performance indicators, a significant improvement between the first and the second runs, and within run increasing modulation performances were observed, whereas no improvements were found between sessions. Simulations confirmed that in a small percentage of cases visual feedback could be affected by metric distortions due to dimensionality reduction implicit to the rt-RSA approach. SIGNIFICANCE Our results proved the feasibility of the semantic real-time fMRI neurofeedback at 3T, showing that subjects can successfully modulate and maintain a target mental state, guided by rt-RSA derived feedback. Further development is needed to encourage future clinical applications.
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Affiliation(s)
- Assunta Ciarlo
- University of Salerno - Baronissi Campus, Via S. Allende, Baronissi, Campania, 84081, ITALY
| | | | - Sara Ponticorvo
- University of Salerno - Baronissi Campus, Via S. Allende, Baronissi, Campania, 84081, ITALY
| | - Francesco Di Salle
- Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno - Baronissi Campus, Via S. Allende, Baronissi, Campania, 84081, ITALY
| | - Michael Lührs
- Department of Cognitive Neuroscience, Maastricht University, P.O. Box 616, Maastricht, Limburg, 6200 MD, NETHERLANDS
| | - Rainer Goebel
- Faculty of Psychology, University of Maastricht, P.O. Box 616, 6200 MD Maastricht, The Netherlands, Maastricht, 6200 MD, NETHERLANDS
| | - Fabrizio Esposito
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli School of Medicine and Surgery, Piazza L. Miraglia, Napoli, 80138, ITALY
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Tian D, Izumi SI. Transcranial Magnetic Stimulation and Neocortical Neurons: The Micro-Macro Connection. Front Neurosci 2022; 16:866245. [PMID: 35495053 PMCID: PMC9039343 DOI: 10.3389/fnins.2022.866245] [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: 01/31/2022] [Accepted: 02/28/2022] [Indexed: 12/20/2022] Open
Abstract
Understanding the operation of cortical circuits is an important and necessary task in both neuroscience and neurorehabilitation. The functioning of the neocortex results from integrative neuronal activity, which can be probed non-invasively by transcranial magnetic stimulation (TMS). Despite a clear indication of the direct involvement of cortical neurons in TMS, no explicit connection model has been made between the microscopic neuronal landscape and the macroscopic TMS outcome. Here we have performed an integrative review of multidisciplinary evidence regarding motor cortex neurocytology and TMS-related neurophysiology with the aim of elucidating the micro–macro connections underlying TMS. Neurocytological evidence from animal and human studies has been reviewed to describe the landscape of the cortical neurons covering the taxonomy, morphology, circuit wiring, and excitatory–inhibitory balance. Evidence from TMS studies in healthy humans is discussed, with emphasis on the TMS pulse and paradigm selectivity that reflect the underlying neural circuitry constitution. As a result, we propose a preliminary neuronal model of the human motor cortex and then link the TMS mechanisms with the neuronal model by stimulus intensity, direction of induced current, and paired-pulse timing. As TMS bears great developmental potential for both a probe and modulator of neural network activity and neurotransmission, the connection model will act as a foundation for future combined studies of neurocytology and neurophysiology, as well as the technical advances and application of TMS.
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Affiliation(s)
- Dongting Tian
- Department of Physical Medicine and Rehabilitation, Tohoku University Graduates School of Medicine, Sendai, Japan
- *Correspondence: Dongting Tian,
| | - Shin-Ichi Izumi
- Department of Physical Medicine and Rehabilitation, Tohoku University Graduates School of Medicine, Sendai, Japan
- Graduate School of Biomedical Engineering, Tohoku University, Sendai, Japan
- Shin-Ichi Izumi,
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Zhang X, Li L, Huang G, Zhang L, Liang Z, Shi L, Zhang Z. A Multisensory fMRI Investigation of Nociceptive-Preferential Cortical Regions and Responses. Front Neurosci 2021; 15:635733. [PMID: 33935632 PMCID: PMC8079658 DOI: 10.3389/fnins.2021.635733] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 03/23/2021] [Indexed: 11/13/2022] Open
Abstract
The existence of nociceptive-specific brain regions has been a controversial issue for decades. Multisensory fMRI studies, which examine fMRI activities in response to various types of sensory stimulation, could help identify nociceptive-specific brain regions, but previous studies are limited by sample size and they did not differentiate nociceptive-specific regions and nociceptive-preferential regions, which have significantly larger responses to nociceptive input. In this study, we conducted a multisensory fMRI experiment on 80 healthy participants, with the aim to determine whether there are certain brain regions that specifically or preferentially respond to nociceptive stimulation. By comparing the evoked fMRI responses across four sensory modalities, we found a series of brain regions specifically or preferentially involved in nociceptive sensory input. Particularly, we found different parts of some cortical regions, such as insula and cingulate gyrus, play different functional roles in the processing of nociceptive stimulation. Hence, this multisensory study improves our understanding of the functional integrations and segregations of the nociceptive-related regions.
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Affiliation(s)
- Xiaoxia Zhang
- Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, China.,Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, China.,Marshall Laboratory of Biomedical Engineering, Shenzhen University, Shenzhen, China
| | - Linling Li
- Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, China.,Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, China.,Marshall Laboratory of Biomedical Engineering, Shenzhen University, Shenzhen, China
| | - Gan Huang
- Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, China.,Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, China.,Marshall Laboratory of Biomedical Engineering, Shenzhen University, Shenzhen, China
| | - Li Zhang
- Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, China.,Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, China.,Marshall Laboratory of Biomedical Engineering, Shenzhen University, Shenzhen, China
| | - Zhen Liang
- Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, China.,Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, China.,Marshall Laboratory of Biomedical Engineering, Shenzhen University, Shenzhen, China
| | - Li Shi
- Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, China.,Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, China.,Marshall Laboratory of Biomedical Engineering, Shenzhen University, Shenzhen, China
| | - Zhiguo Zhang
- Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, China.,Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, China.,Marshall Laboratory of Biomedical Engineering, Shenzhen University, Shenzhen, China.,Peng Cheng Laboratory, Shenzhen, China
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