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Farcy C, Chauvigné LAS, Laganaro M, Corre M, Ptak R, Guggisberg AG. Neural mechanisms underlying improved new-word learning with high-density transcranial direct current stimulation. Neuroimage 2024; 294:120649. [PMID: 38759354 DOI: 10.1016/j.neuroimage.2024.120649] [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: 01/25/2024] [Revised: 04/04/2024] [Accepted: 05/14/2024] [Indexed: 05/19/2024] Open
Abstract
Neurobehavioral studies have provided evidence for the effectiveness of anodal tDCS on language production, by stimulation of the left Inferior Frontal Gyrus (IFG) or of left Temporo-Parietal Junction (TPJ). However, tDCS is currently not used in clinical practice outside of trials, because behavioral effects have been inconsistent and underlying neural effects unclear. Here, we propose to elucidate the neural correlates of verb and noun learning and to determine if they can be modulated with anodal high-definition (HD) tDCS stimulation. Thirty-six neurotypical participants were randomly allocated to anodal HD-tDCS over either the left IFG, the left TPJ, or sham stimulation. On day one, participants performed a naming task (pre-test). On day two, participants underwent a new-word learning task with rare nouns and verbs concurrently to HD-tDCS for 20 min. The third day consisted of a post-test of naming performance. EEG was recorded at rest and during naming on each day. Verb learning was significantly facilitated by left IFG stimulation. HD-tDCS over the left IFG enhanced functional connectivity between the left IFG and TPJ and this correlated with improved learning. HD-tDCS over the left TPJ enabled stronger local activation of the stimulated area (as indexed by greater alpha and beta-band power decrease) during naming, but this did not translate into better learning. Thus, tDCS can induce local activation or modulation of network interactions. Only the enhancement of network interactions, but not the increase in local activation, leads to robust improvement of word learning. This emphasizes the need to develop new neuromodulation methods influencing network interactions. Our study suggests that this may be achieved through behavioral activation of one area and concomitant activation of another area with HD-tDCS.
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Affiliation(s)
- Camille Farcy
- Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospital of Geneva, Av. de Beau-Séjour 26, Geneva 1211, Switzerland
| | - Lea A S Chauvigné
- Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospital of Geneva, Av. de Beau-Séjour 26, Geneva 1211, Switzerland
| | - Marina Laganaro
- Neuropsycholinguistics Laboratory, University of Geneva, Geneva, Switzerland
| | - Marion Corre
- Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospital of Geneva, Av. de Beau-Séjour 26, Geneva 1211, Switzerland
| | - Radek Ptak
- Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospital of Geneva, Av. de Beau-Séjour 26, Geneva 1211, Switzerland
| | - Adrian G Guggisberg
- Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospital of Geneva, Av. de Beau-Séjour 26, Geneva 1211, Switzerland; Universitäre Neurorehabilitation, Universitätsklinik für Neurologie, Inselspital, University Hospital of Berne, Berne 3010, Switzerland.
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Phang CR, Su KH, Cheng YY, Chen CH, Ko LW. Time synchronization between parietal-frontocentral connectivity with MRCP and gait in post-stroke bipedal tasks. J Neuroeng Rehabil 2024; 21:101. [PMID: 38872209 PMCID: PMC11170849 DOI: 10.1186/s12984-024-01330-z] [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: 03/05/2023] [Accepted: 06/20/2023] [Indexed: 06/15/2024] Open
Abstract
BACKGROUND In post-stroke rehabilitation, functional connectivity (FC), motor-related cortical potential (MRCP), and gait activities are common measures related to recovery outcomes. However, the interrelationship between FC, MRCP, gait activities, and bipedal distinguishability have yet to be investigated. METHODS Ten participants were equipped with EEG devices and inertial measurement units (IMUs) while performing lower limb motor preparation (MP) and motor execution (ME) tasks. MRCP, FCs, and bipedal distinguishability were extracted from the EEG signals, while the change in knee degree during the ME phase was calculated from the gait data. FCs were analyzed with pairwise Pearson's correlation, and the brain-wide FC was fed into support vector machine (SVM) for bipedal classification. RESULTS Parietal-frontocentral connectivity (PFCC) dysconnection and MRCP desynchronization were related to the MP and ME phases, respectively. Hemiplegic limb movement exhibited higher PFCC strength than nonhemiplegic limb movement. Bipedal classification had a short-lived peak of 75.1% in the pre-movement phase. These results contribute to a better understanding of the neurophysiological functions during motor tasks, with respect to localized MRCP and nonlocalized FC activities. The difference in PFCCs between both limbs could be a marker to understand the motor function of the brain of post-stroke patients. CONCLUSIONS In this study, we discovered that PFCCs are temporally dependent on lower limb gait movement and MRCP. The PFCCs are also related to the lower limb motor performance of post-stroke patients. The detection of motor intentions allows the development of bipedal brain-controlled exoskeletons for lower limb active rehabilitation.
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Affiliation(s)
- Chun-Ren Phang
- International Ph.D. Program in Interdisciplinary Neuroscience (UST), College of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
- Center for Intelligent Drug Systems and Smart Bio-devices (IDS2B), College of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Kai-Hsiang Su
- Center for Intelligent Drug Systems and Smart Bio-devices (IDS2B), College of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
- Department of Biological Science and Technology, College of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Yuan-Yang Cheng
- Department of Physical Medicine and Rehabilitation, Taichung Veterans General Hospital, Taichung, Taiwan
- Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chia-Hsin Chen
- Department of Physical Medicine and Rehabilitation, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
- School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
- Regenerative Medicine and Cell Therapy Research Center, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Li-Wei Ko
- International Ph.D. Program in Interdisciplinary Neuroscience (UST), College of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
- Center for Intelligent Drug Systems and Smart Bio-devices (IDS2B), College of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
- Department of Biological Science and Technology, College of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
- Institute of Electrical and Control Engineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
- Department of Biomedical Science and Environment Biology, Kaohsiung Medical University, Kaohsiung, Taiwan.
- Drug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung, Taiwan.
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Lin PJ, Li W, Zhai X, Li Z, Sun J, Xu Q, Pan Y, Ji L, Li C. Explainable Deep-Learning Prediction for Brain-Computer Interfaces Supported Lower Extremity Motor Gains Based on Multistate Fusion. IEEE Trans Neural Syst Rehabil Eng 2024; 32:1546-1555. [PMID: 38578854 DOI: 10.1109/tnsre.2024.3384498] [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: 04/07/2024]
Abstract
Predicting the potential for recovery of motor function in stroke patients who undergo specific rehabilitation treatments is an important and major challenge. Recently, electroencephalography (EEG) has shown potential in helping to determine the relationship between cortical neural activity and motor recovery. EEG recorded in different states could more accurately predict motor recovery than single-state recordings. Here, we design a multi-state (combining eyes closed, EC, and eyes open, EO) fusion neural network for predicting the motor recovery of patients with stroke after EEG-brain-computer-interface (BCI) rehabilitation training and use an explainable deep learning method to identify the most important features of EEG power spectral density and functional connectivity contributing to prediction. The prediction accuracy of the multi-states fusion network was 82%, significantly improved compared with a single-state model. The neural network explanation result demonstrated the important region and frequency oscillation bands. Specifically, in those two states, power spectral density and functional connectivity were shown as the regions and bands related to motor recovery in frontal, central, and occipital. Moreover, the motor recovery relation in bands, the power spectrum density shows the bands at delta and alpha bands. The functional connectivity shows the delta, theta, and alpha bands in the EC state; delta, theta, and beta mid at the EO state are related to motor recovery. Multi-state fusion neural networks, which combine multiple states of EEG signals into a single network, can increase the accuracy of predicting motor recovery after BCI training, and reveal the underlying mechanisms of motor recovery in brain activity.
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Shamsi F, Aligholi H, Karimi MT, Borhani-Haghighi A, Nami M. Quantitative EEG for the Monitoring of Walking Recovery in Chronic Stroke Patients Receiving Action Observation Training. J Mot Behav 2024; 56:428-438. [PMID: 38408745 DOI: 10.1080/00222895.2024.2320904] [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: 04/13/2023] [Accepted: 02/14/2024] [Indexed: 02/28/2024]
Abstract
The current study aimed to evaluate the effects of action observation on the walking ability and oscillatory brain activity of chronic stroke patients. Fourteen chronic stroke patients were allocated randomly to the action observation (AO) or sham observation (SO) groups. Both groups received 12 sessions of intervention. Each session composed of 12 min of observational training, which depicted exercises for the experimental group but nature pictures for the sham group and 40 min of occupational therapy, which was the same for the both groups. Walking ability was assessed by a motion analysis system and brain activity was monitored using quantitative electroencephalography (QEEG) before and after the intervention. Brain asymmetry at alpha frequency, the percentage of stance phase, and step length showed significant changes in the AO group. Only the change in global alpha power was significantly correlated with the change in velocity after the intervention in AO group. Despite more improvements in walking and brain activity of patients in the AO group, our study failed to show significant correlations between the brain activity changes and functional improvements after the intervention, which might be mainly due to the small sample size in our study. Trial registration: IRCT20181014041333N1.
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Affiliation(s)
- Fatemeh Shamsi
- Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
- Neuroscience Laboratory (Brain, Cognition and Behavior), Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Hadi Aligholi
- Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
- Neuroscience Laboratory (Brain, Cognition and Behavior), Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Mohammad Taghi Karimi
- Rehabilitation Sciences Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | | | - Mohammad Nami
- Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
- Neuroscience Laboratory (Brain, Cognition and Behavior), Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
- Neuroscience Center, Instituto de Investigaciones Científicas Servicios de Alta Tecnología (INDICASAT AIP), City of Knowledge, Panama City, Panama
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Rösch J, Emanuel Vetter D, Baldassarre A, Souza VH, Lioumis P, Roine T, Jooß A, Baur D, Kozák G, Blair Jovellar D, Vaalto S, Romani GL, Ilmoniemi RJ, Ziemann U. Individualized treatment of motor stroke: A perspective on open-loop, closed-loop and adaptive closed-loop brain state-dependent TMS. Clin Neurophysiol 2024; 158:204-211. [PMID: 37945452 DOI: 10.1016/j.clinph.2023.10.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 09/11/2023] [Accepted: 10/18/2023] [Indexed: 11/12/2023]
Affiliation(s)
- Johanna Rösch
- Department of Neurology and Stroke, University of Tübingen, Tübingen, Germany; Hertie-Institute for Clinical Brain Research, Tübingen, Germany
| | - David Emanuel Vetter
- Department of Neurology and Stroke, University of Tübingen, Tübingen, Germany; Hertie-Institute for Clinical Brain Research, Tübingen, Germany
| | - Antonello Baldassarre
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Victor H Souza
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki, Aalto University and Helsinki University Hospital, Helsinki, Finland
| | - Pantelis Lioumis
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki, Aalto University and Helsinki University Hospital, Helsinki, Finland
| | - Timo Roine
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki, Aalto University and Helsinki University Hospital, Helsinki, Finland
| | - Andreas Jooß
- Department of Neurology and Stroke, University of Tübingen, Tübingen, Germany; Hertie-Institute for Clinical Brain Research, Tübingen, Germany
| | - David Baur
- Department of Neurology and Stroke, University of Tübingen, Tübingen, Germany; Hertie-Institute for Clinical Brain Research, Tübingen, Germany
| | - Gábor Kozák
- Department of Neurology and Stroke, University of Tübingen, Tübingen, Germany; Hertie-Institute for Clinical Brain Research, Tübingen, Germany
| | - D Blair Jovellar
- Department of Neurology and Stroke, University of Tübingen, Tübingen, Germany; Hertie-Institute for Clinical Brain Research, Tübingen, Germany
| | - Selja Vaalto
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; HUS Diagnostic Center, Clinical Neurophysiology, Clinical Neurosciences, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Gian Luca Romani
- Institute for Advanced Biomedical Technologies, University of Chieti-Pescara, Chieti, Italy
| | - Risto J Ilmoniemi
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki, Aalto University and Helsinki University Hospital, Helsinki, Finland
| | - Ulf Ziemann
- Department of Neurology and Stroke, University of Tübingen, Tübingen, Germany; Hertie-Institute for Clinical Brain Research, Tübingen, Germany.
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Bernardes TS, Santos KCS, Nascimento MR, Filho CANES, Bazan R, Pereira JM, de Souza LAPS, Luvizutto GJ. Effects of anodal transcranial direct current stimulation over motor cortex on resting-state brain activity in the early subacute stroke phase: A power spectral density analysis. Clin Neurol Neurosurg 2024; 237:108134. [PMID: 38335706 DOI: 10.1016/j.clineuro.2024.108134] [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: 09/27/2023] [Revised: 01/06/2024] [Accepted: 01/24/2024] [Indexed: 02/12/2024]
Abstract
INTRODUCTION Despite promising results, the effects of transcranial direct current stimulation (tDCS) in the early stages of stroke and its impact on brain activity have been poorly studied. Therefore, this study aimed to investigate the effect of tDCS applied over the ipsilesional motor cortex on resting-state brain activity in the early subacute phase of stroke. METHODS This is a pilot, randomized, double-blind, proof-of-concept study. The patients with stroke were randomly assigned into two groups: anodal tDCS (A-tDCS) or sham tDCS (S-tDCS). For A-tDCS, the anode was placed over the ipsilesional motor cortex, while the cathode was placed over the left or right supraorbital area (Fp2 for left stroke or Fp1 for right stroke). For the real stimulation, a constant current of 1.0 mA was delivered for 20 min and then ramped down linearly for 30 s, maintaining a resistance below 10 kΩ. For the sham stimulation, the stimulator was turned on, and the current intensity was gradually increased for 30 s, tapered off over 30 s, and maintained for 30 min without stimulation. Each stimulation was performed for three consecutive sessions with an interval of 1 h between them. The primary outcome was spectral electroencephalography (EEG) analysis based on the Power Spectral Density (PSD) determined by EEG records of areas F3, F4, C3, C4, P3, and P4. Brain Vision Analyzer software processed the signals, EEG power spectral density (PSD) was calculated before and after stimulation, and alpha, beta, delta, and theta power were analyzed. The secondary outcomes included hemodynamic variables based on the difference between baseline (D0) and post-intervention session (D1) values of systolic (SBP) and diastolic (DBP) blood pressure, heart rate (HR), respiratory rate (RR) and peripheral oxygen saturation (SPO2). Mann-Whitney test was used to compare position measurements of two independent samples; Fisher's exact test was used to compare two proportions; paired Wilcoxon signed-rank test was used to compare the median differences in the within-group comparison, and Spearman correlations matrix among spectral power analysis between EEG bands was performed to verify consistency of occurrence of oscillations. Statistical significance was set at P < 0.05. RESULTS An increase in PSD in the alpha frequency in the P4 region was observed after the intervention in the A-tDCS group, as compared to the placebo group (before = 6.13; after = 10.45; p < 0.05). In the beta frequency, an increase in PSD was observed in P4 (before = 4.40; after = 6.79; p < 0.05) and C4 (before = 4.43; after = 6.94; p < 0.05) after intervention in the A-tDCS group. There was a reduction in PSD at delta frequency in C3 (before = 293.8; after = 58.6; p < 0.05) after intervention in the A-tDCS group. In addition, it was observed a strong relationship between alpha and theta power in the A-tDCS group before and after intervention. However, the sham group showed correlations between more power bands (alpha and theta, alpha and delta, and delta and theta) after intervention. There was no difference in hemodynamic variables between the intra- (before and after stimulation) and inter-groups (mean difference). CONCLUSION Anodal tDCS over the ipsilesional motor cortex had significant effects on the brain electrical activity in the early subacute stroke phase, increasing alpha and beta wave activities in sensorimotor regions while reducing slow delta wave activity in motor regions. These findings highlight the potential of anodal tDCS as a therapeutic intervention in the early stroke phase.
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Affiliation(s)
- Tiago Soares Bernardes
- Department of Medicine, Universidade Federal do Triângulo Mineiro (UFTM), Uberaba, Minas Gerais, Brazil
| | - Kelly Cristina Sousa Santos
- Department of Applied Physical Therapy, Universidade Federal do Triângulo Mineiro (UFTM), Uberaba, Minas Gerais, Brazil
| | - Monalisa Resende Nascimento
- Department of Applied Physical Therapy, Universidade Federal do Triângulo Mineiro (UFTM), Uberaba, Minas Gerais, Brazil
| | | | - Rodrigo Bazan
- Department of Neurology, Psychology, and Psychiatry, Botucatu Medical School (UNESP), Botucatu, SP, Brazil
| | - Janser Moura Pereira
- Statistical Department, Universidade Federal de Uberlândia (UFU), Uberlândia, MG, Brazil
| | | | - Gustavo José Luvizutto
- Department of Applied Physical Therapy, Universidade Federal do Triângulo Mineiro (UFTM), Uberaba, Minas Gerais, Brazil.
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Tang CW, Zich C, Quinn AJ, Woolrich MW, Hsu SP, Juan CH, Lee IH, Stagg CJ. Post-stroke upper limb recovery is correlated with dynamic resting-state network connectivity. Brain Commun 2024; 6:fcae011. [PMID: 38344655 PMCID: PMC10853981 DOI: 10.1093/braincomms/fcae011] [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: 02/02/2023] [Revised: 11/25/2023] [Accepted: 01/22/2024] [Indexed: 03/02/2024] Open
Abstract
Motor recovery is still limited for people with stroke especially those with greater functional impairments. In order to improve outcome, we need to understand more about the mechanisms underpinning recovery. Task-unbiased, blood flow-independent post-stroke neural activity can be acquired from resting brain electrophysiological recordings and offers substantial promise to investigate physiological mechanisms, but behaviourally relevant features of resting-state sensorimotor network dynamics have not yet been identified. Thirty-seven people with subcortical ischaemic stroke and unilateral hand paresis of any degree were longitudinally evaluated at 3 weeks (early subacute) and 12 weeks (late subacute) after stroke. Resting-state magnetoencephalography and clinical scores of motor function were recorded and compared with matched controls. Magnetoencephalography data were decomposed using a data-driven hidden Markov model into 10 time-varying resting-state networks. People with stroke showed statistically significantly improved Action Research Arm Test and Fugl-Meyer upper extremity scores between 3 weeks and 12 weeks after stroke (both P < 0.001). Hidden Markov model analysis revealed a primarily alpha-band ipsilesional resting-state sensorimotor network which had a significantly increased life-time (the average time elapsed between entering and exiting the network) and fractional occupancy (the occupied percentage among all networks) at 3 weeks after stroke when compared with controls. The life-time of the ipsilesional resting-state sensorimotor network positively correlated with concurrent motor scores in people with stroke who had not fully recovered. Specifically, this relationship was observed only in ipsilesional rather in contralesional sensorimotor network, default mode network or visual network. The ipsilesional sensorimotor network metrics were not significantly different from controls at 12 weeks after stroke. The increased recruitment of alpha-band ipsilesional resting-state sensorimotor network at subacute stroke served as functionally correlated biomarkers exclusively in people with stroke with not fully recovered hand paresis, plausibly reflecting functional motor recovery processes.
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Affiliation(s)
- Chih-Wei Tang
- Institute of Brain Science, Brain Research Center, National Yang Ming Chiao Tung University, Taipei City 112, Taiwan
- Department of Neurology, Far Eastern Memorial Hospital, New Taipei City 220, Taiwan
| | - Catharina Zich
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, Oxford OX3 9DU, UK
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, OX1 3TH, UK
| | - Andrew J Quinn
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, Oxford OX3 9DU, UK
- Department of Psychiatry, Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 7JX, UK
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham B15 2TT, UK
| | - Mark W Woolrich
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, Oxford OX3 9DU, UK
- Department of Psychiatry, Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 7JX, UK
| | - Shih-Pin Hsu
- Institute of Brain Science, Brain Research Center, National Yang Ming Chiao Tung University, Taipei City 112, Taiwan
| | - Chi-Hung Juan
- Institute of Cognitive Neuroscience, National Central University, Taoyuan City 320, Taiwan
| | - I Hui Lee
- Institute of Brain Science, Brain Research Center, National Yang Ming Chiao Tung University, Taipei City 112, Taiwan
- Division of Cerebrovascular Diseases, Neurological Institute, Taipei Veterans General Hospital, Taipei City 112, Taiwan
| | - Charlotte J Stagg
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, Oxford OX3 9DU, UK
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, OX1 3TH, UK
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Vimolratana O, Aneksan B, Siripornpanich V, Hiengkaew V, Prathum T, Jeungprasopsuk W, Khaokhiew T, Vachalathiti R, Klomjai W. Effects of anodal tDCS on resting state eeg power and motor function in acute stroke: a randomized controlled trial. J Neuroeng Rehabil 2024; 21:6. [PMID: 38172973 PMCID: PMC10765911 DOI: 10.1186/s12984-023-01300-x] [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: 05/04/2023] [Accepted: 12/21/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Anodal transcranial direct current stimulation (tDCS) is a beneficial adjunctive tool in stroke rehabilitation. However, only a few studies have investigated its effects on acute stroke and recruited only individuals with mild motor deficits. This study investigated the effect of five consecutive sessions of anodal tDCS and conventional physical therapy on brain activity and motor outcomes in individuals with acute stroke, with low and high motor impairments. METHODS Thirty participants were recruited and randomly allocated to either the anodal or sham tDCS group. Five consecutive sessions of tDCS (1.5 mA anodal or sham tDCS for 20 min) were administered, followed by conventional physical therapy. Electroencephalography (EEG), Fugl-Meyer Motor Assessment (FMA), and Wolf Motor Function Test (WMFT) were performed at pre-, post-intervention (day 5), and 1-month follow-up. Sub-analyses were performed on participants with low and high motor impairments. The relationship between EEG power and changes in motor functions was assessed. RESULTS Linear regression showed a significant positive correlation between beta bands and the FMA score in the anodal group. Elevated high frequency bands (alpha and beta) were observed at post-intervention and follow-up in all areas of both hemispheres in the anodal group, while only in the posterior area of the non-lesioned hemisphere in the sham group; however, such elevation induced by tDCS was not greater than sham. Lower limb function assessed by FMA was improved in the anodal group compared with the sham group at post-intervention and follow-up only in those with low motor impairment. For the upper limb outcomes, no difference between groups was found. CONCLUSIONS Five consecutive days of anodal tDCS and physical therapy in acute stroke did not result in a superior improvement of beta bands that commonly related to stroke recovery over sham, but improved lower extremity functions with a post-effect at 1-month follow-up in low motor impairment participants. The increase of beta bands in the lesioned brain in the anodal group was associated with improvement in lower limb function. TRIAL REGISTRATION NCT04578080, date of first registration 10/01/2020.
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Affiliation(s)
- O Vimolratana
- Faculty of Physical Therapy, Mahidol University, 999 Phuttamonthon 4 Road, Salaya, Nakhon Pathom, 73170, Thailand
- Neuro Electrical Stimulation Laboratory, Faculty of Physical Therapy, Mahidol University, Nakhon Pathom, 73170, Thailand
- School of Integrative Medicine, Mae Fah Luang University, Chiang Rai, 57100, Thailand
| | - B Aneksan
- Faculty of Physical Therapy, Mahidol University, 999 Phuttamonthon 4 Road, Salaya, Nakhon Pathom, 73170, Thailand
- Neuro Electrical Stimulation Laboratory, Faculty of Physical Therapy, Mahidol University, Nakhon Pathom, 73170, Thailand
| | - V Siripornpanich
- Institute of Molecular Biosciences, Mahidol University, Nakhon Pathom, 73170, Thailand
| | - V Hiengkaew
- Faculty of Physical Therapy, Mahidol University, 999 Phuttamonthon 4 Road, Salaya, Nakhon Pathom, 73170, Thailand
| | - T Prathum
- Faculty of Physical Therapy, Mahidol University, 999 Phuttamonthon 4 Road, Salaya, Nakhon Pathom, 73170, Thailand
- Neuro Electrical Stimulation Laboratory, Faculty of Physical Therapy, Mahidol University, Nakhon Pathom, 73170, Thailand
| | - W Jeungprasopsuk
- Faculty of Medical Technology, Mahidol University, Nakhon Pathom, 73170, Thailand
| | - T Khaokhiew
- Faculty of Medical Technology, Mahidol University, Nakhon Pathom, 73170, Thailand
| | - R Vachalathiti
- Faculty of Physical Therapy, Mahidol University, 999 Phuttamonthon 4 Road, Salaya, Nakhon Pathom, 73170, Thailand
| | - W Klomjai
- Faculty of Physical Therapy, Mahidol University, 999 Phuttamonthon 4 Road, Salaya, Nakhon Pathom, 73170, Thailand.
- Neuro Electrical Stimulation Laboratory, Faculty of Physical Therapy, Mahidol University, Nakhon Pathom, 73170, Thailand.
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Zueva MV, Neroeva NV, Zhuravleva AN, Bogolepova AN, Kotelin VV, Fadeev DV, Tsapenko IV. Fractal Phototherapy in Maximizing Retina and Brain Plasticity. ADVANCES IN NEUROBIOLOGY 2024; 36:585-637. [PMID: 38468055 DOI: 10.1007/978-3-031-47606-8_31] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
The neuroplasticity potential is reduced with aging and impairs during neurodegenerative diseases and brain and visual system injuries. This limits the brain's capacity to repair the structure and dynamics of its activity after lesions. Maximization of neuroplasticity is necessary to provide the maximal CNS response to therapeutic intervention and adaptive reorganization of neuronal networks in patients with degenerative pathology and traumatic injury to restore the functional activity of the brain and retina.Considering the fractal geometry and dynamics of the healthy brain and the loss of fractality in neurodegenerative pathology, we suggest that the application of self-similar visual signals with a fractal temporal structure in the stimulation therapy can reactivate the adaptive neuroplasticity and enhance the effectiveness of neurorehabilitation. This proposition was tested in the recent studies. Patients with glaucoma had a statistically significant positive effect of fractal photic therapy on light sensitivity and the perimetric MD index, which shows that methods of fractal stimulation can be a novel nonpharmacological approach to neuroprotective therapy and neurorehabilitation. In healthy rabbits, it was demonstrated that a long-term course of photostimulation with fractal signals does not harm the electroretinogram (ERG) and retina structure. Rabbits with modeled retinal atrophy showed better dynamics of the ERG restoration during daily stimulation therapy for a week in comparison with the controls. Positive changes in the retinal function can indirectly suggest the activation of its adaptive plasticity and the high potential of stimulation therapy with fractal visual stimuli in a nonpharmacological neurorehabilitation, which requires further study.
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Affiliation(s)
- Marina V Zueva
- Department of Clinical Physiology of Vision, Helmholtz National Medical Research Center of Eye Diseases, Moscow, Russia
| | - Natalia V Neroeva
- Department of Pathology of the Retina and Optic Nerve, Helmholtz National Medical Research Center of Eye Diseases, Moscow, Russia
| | - Anastasia N Zhuravleva
- Department of Glaucoma, Helmholtz National Medical Research Center of Eye Diseases, Moscow, Russia
| | - Anna N Bogolepova
- Department of neurology, neurosurgery and medical genetics, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Vladislav V Kotelin
- Department of Clinical Physiology of Vision, Helmholtz National Medical Research Center of Eye Diseases, Moscow, Russia
| | - Denis V Fadeev
- Scientific Experimental Center Department, Helmholtz National Medical Research Center of Eye Diseases, Moscow, Russia
| | - Irina V Tsapenko
- Department of Clinical Physiology of Vision, Helmholtz National Medical Research Center of Eye Diseases, Moscow, Russia
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10
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Zhang X, Nan J, Xu M, Chen L, Ni G, Ming D. PSIs of EEG With Refined Frequency Decomposition Could Prognose Motor Recovery Before Rehabilitation Intervention. IEEE Trans Neural Syst Rehabil Eng 2023; 31:3760-3771. [PMID: 37721877 DOI: 10.1109/tnsre.2023.3316210] [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: 09/20/2023]
Abstract
Stroke often leads to permanent impairment in motor function. Accurate and quantitative prognosis of potential motor recovery before rehabilitation intervention can help healthcare centers improve resources organization and enable individualized intervention. The context of this paper investigated the potential of using electroencephalography (EEG) functional connectivity (FC) measures as biomarkers for assessing and prognosing improvement of Fugl-Meyer Assessment in upper extremity motor function ( ∆FMU) among participants with chronic stroke. EEG data from resting and motor imagery task were recorded from 13 participants with chronic stroke. Three functional connectivity methods, which were Pearson correlation measure (PCM), weighted Phase Lag Index (wPLI) and phase synchronization index (PSI), were investigated, under three regions of interest (inter-hemispheric, intra-hemispheric, and whole-brain), in two statues (resting and motor imagery), with 15 refined center frequencies. We applied correlation analysis to identify the optimal center frequencies and pairs of synchronized channels that were consistently associated with ∆FMU . Predictive models were generated using regression analysis algorithms based on optimized center frequencies and channel pairs identified from the proposed analysis method, with leave-one-out cross-validation. We found that PSI in the Alpha band (with center frequency of 9Hz) was the most sensitive FC measures for prognosing motor recovery. Strong and significant correlations were identified between the predictions and actual ∆FMU scores both in the resting state ( [Formula: see text], [Formula: see text], N=13) and motor imagery ( [Formula: see text], [Formula: see text], N=13). Our results suggested that EEG connectivity measured with PSI in resting state could be a promising biomarker for quantifying motor recovery before motor rehabilitation intervention.
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11
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Giri A, Mosher JC, Adler A, Pantazis D. An F-ratio-based method for estimating the number of active sources in MEG. Front Hum Neurosci 2023; 17:1235192. [PMID: 37780957 PMCID: PMC10537939 DOI: 10.3389/fnhum.2023.1235192] [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: 06/05/2023] [Accepted: 08/22/2023] [Indexed: 10/03/2023] Open
Abstract
Introduction Magnetoencephalography (MEG) is a powerful technique for studying the human brain function. However, accurately estimating the number of sources that contribute to the MEG recordings remains a challenging problem due to the low signal-to-noise ratio (SNR), the presence of correlated sources, inaccuracies in head modeling, and variations in individual anatomy. Methods To address these issues, our study introduces a robust method for accurately estimating the number of active sources in the brain based on the F-ratio statistical approach, which allows for a comparison between a full model with a higher number of sources and a reduced model with fewer sources. Using this approach, we developed a formal statistical procedure that sequentially increases the number of sources in the multiple dipole localization problem until all sources are found. Results Our results revealed that the selection of thresholds plays a critical role in determining the method's overall performance, and appropriate thresholds needed to be adjusted for the number of sources and SNR levels, while they remained largely invariant to different inter-source correlations, translational modeling inaccuracies, and different cortical anatomies. By identifying optimal thresholds and validating our F-ratio-based method in simulated, real phantom, and human MEG data, we demonstrated the superiority of our F-ratio-based method over existing state-of-the-art statistical approaches, such as the Akaike Information Criterion (AIC) and Minimum Description Length (MDL). Discussion Overall, when tuned for optimal selection of thresholds, our method offers researchers a precise tool to estimate the true number of active brain sources and accurately model brain function.
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Affiliation(s)
- Amita Giri
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - John C. Mosher
- Department of Neurology, McGovern Medical School, Texas Institute for Restorative Neurotechnologies, UTHealth, Houston, TX, United States
| | - Amir Adler
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States
- Department of Electrical Engineering, Braude College of Engineering, Karmiel, Israel
| | - Dimitrios Pantazis
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States
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12
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Asadi B, Fard KR, Ansari NN, Marco Á, Calvo S, Herrero P. The Effect of dry Needling in Chronic Stroke with a complex Network Approach: A Case Study. Clin EEG Neurosci 2023; 54:179-188. [PMID: 35957591 DOI: 10.1177/15500594221120136] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Background: Dry Needling (DN) has been demonstrated to be effective in improving sensorimotor function and spasticity in patients with chronic stroke. Electroencephalogram (EEG) has been used to analyze if DN has effects on the central nervous system of patients with stroke. There are no studies on how DN works in patients with chronic stroke based on EEG analysis using complex networks. Objective: The aim of this study was to assess how DN works when it is applied in a patient with stroke, using the graph theory. Methods: One session of DN was applied to the spastic brachialis muscle of a 62-year-old man with right hemiplegia after stroke. EEG was used to analyze the effects of DN following metrics that measure the topological configuration: 1) network density, 2) clustering coefficient, 3) average shortest path length, 4) betweenness centrality, and 5) small-worldness. Measurements were taken before and during DN. Results: An improvement of the brain activity was observed in this patient with stroke after the application of DN, which led to variations of local parameters of the brain network in the delta, theta and alpha bands, and inclined towards those of the healthy control bands. Conclusions: This case study showed the positive effects of DN on brain network of a patient with chronic stroke.
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Affiliation(s)
- Borhan Asadi
- Department of Computer Engineering and Information Technology, 185151University of Qom, Qom, Iran
| | - Kheirollah Rahsepar Fard
- Department of Computer Engineering and Information Technology, 185151University of Qom, Qom, Iran
| | - Noureddin Nakhostin Ansari
- Department of Physiotherapy, School of Rehabilitation, 48439Tehran University of Medical Sciences, Tehran, Iran.,Research Center for War-affected People, 48439Tehran University of Medical Sciences, Tehran, Iran
| | - Álvaro Marco
- Department of Electronic Engineering and Communications, Aragon Institute of Engineering Research, 16765University of Zaragoza, Zaragoza, Spain
| | - Sandra Calvo
- Department of Physiatry and Nursing, Faculty of Health Sciences, IIS Aragon, 16765University of Zaragoza, Zaragoza, Spain
| | - Pablo Herrero
- Department of Physiatry and Nursing, Faculty of Health Sciences, IIS Aragon, 16765University of Zaragoza, Zaragoza, Spain
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Kern K, Vukelić M, Guggenberger R, Gharabaghi A. Oscillatory neurofeedback networks and poststroke rehabilitative potential in severely impaired stroke patients. Neuroimage Clin 2023; 37:103289. [PMID: 36525745 PMCID: PMC9791174 DOI: 10.1016/j.nicl.2022.103289] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 12/03/2022] [Accepted: 12/12/2022] [Indexed: 12/15/2022]
Abstract
Motor restoration after severe stroke is often limited. However, some of the severely impaired stroke patients may still have a rehabilitative potential. Biomarkers that identify these patients are sparse. Eighteen severely impaired chronic stroke patients with a lack of volitional finger extension participated in an EEG study. During sixty-six trials of kinesthetic motor imagery, a brain-machine interface turned event-related beta-band desynchronization of the ipsilesional sensorimotor cortex into opening of the paralyzed hand by a robotic orthosis. A subgroup of eight patients participated in a subsequent four-week rehabilitation training. Changes of the movement extent were captured with sensors which objectively quantified even discrete improvements of wrist movement. Albeit with the same motor impairment level, patients could be differentiated into two groups, i.e., with and without task-related increase of bilateral cortico-cortical phase synchronization between frontal/premotor and parietal areas. This fronto-parietal integration (FPI) was associated with a significantly higher volitional beta modulation range in the ipsilesional sensorimotor cortex. Following the four-week training, patients with FPI showed significantly higher improvement in wrist movement than those without FPI. Moreover, only the former group improved significantly in the upper extremity Fugl-Meyer-Assessment score. Neurofeedback-related long-range oscillatory coherence may differentiate severely impaired stroke patients with regard to their rehabilitative potential, a finding that needs to be confirmed in larger patient cohorts.
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Affiliation(s)
- Kevin Kern
- Institute for Neuromodulation and Neurotechnology, University of Tübingen, Germany
| | - Mathias Vukelić
- Institute for Neuromodulation and Neurotechnology, University of Tübingen, Germany
| | - Robert Guggenberger
- Institute for Neuromodulation and Neurotechnology, University of Tübingen, Germany
| | - Alireza Gharabaghi
- Institute for Neuromodulation and Neurotechnology, University of Tübingen, Germany.
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14
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Khademi F, Naros G, Nicksirat A, Kraus D, Gharabaghi A. Rewiring Cortico-Muscular Control in the Healthy and Poststroke Human Brain with Proprioceptive β-Band Neurofeedback. J Neurosci 2022; 42:6861-6877. [PMID: 35940874 PMCID: PMC9463986 DOI: 10.1523/jneurosci.1530-20.2022] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 06/02/2022] [Accepted: 06/04/2022] [Indexed: 11/21/2022] Open
Abstract
In severely affected stroke survivors, cortico-muscular control is disturbed and volitional upper limb movements often absent. Mental rehearsal of the impaired movement in conjunction with sensory feedback provision are suggested as promising rehabilitation exercises. Knowledge about the underlying neural processes, however, remains vague. In male and female chronic stroke patients with hand paralysis, a brain-computer interface controlled a robotic orthosis and turned sensorimotor β-band desynchronization during motor imagery (MI) of finger extension into contingent hand opening. Healthy control subjects performed the same task and received the same proprioceptive feedback with a robotic orthosis or visual feedback only. Only when proprioceptive feedback was provided, cortico-muscular coherence (CMC) increased with a predominant information flow from the sensorimotor cortex to the finger extensors. This effect (1) was specific to the β frequency band, (2) transferred to a motor task (MT), (3) was proportional to subsequent corticospinal excitability (CSE) and correlated with behavioral changes in the (4) healthy and (5) poststroke condition; notably, MI-related enhancement of β-band CMC in the ipsilesional premotor cortex correlated with motor improvements after the intervention. In the healthy and injured human nervous system, synchronized activation of motor-related cortical and spinal neural pools facilitates, in accordance with the communication-through-coherence hypothesis, cortico-spinal communication and may, thereby, be therapeutically relevant for functional restoration after stroke, when voluntary movements are no longer possible.SIGNIFICANCE STATEMENT This study provides insights into the neural processes that transfer effects of brain-computer interface neurofeedback to subsequent motor behavior. Specifically, volitional control of cortical oscillations and proprioceptive feedback enhances both cortical activity and behaviorally relevant connectivity to the periphery in a topographically circumscribed and frequency-specific way. This enhanced cortico-muscular control can be induced in the healthy and poststroke brain. Thereby, activating the motor cortex with mental rehearsal of the impaired movement and closing the loop by robot-assisted feedback synchronizes ipsilesional premotor cortex and spinal neural pools in the β frequency band. This facilitates, in accordance with the communication-through-coherence hypothesis, cortico-spinal communication and may, thereby, be therapeutically relevant for functional restoration after stroke, when voluntary movements are no longer possible.
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Affiliation(s)
- Fatemeh Khademi
- Institute for Neuromodulation and Neurotechnology, University Hospital and University of Tübingen, Tübingen 72076, Germany
| | - Georgios Naros
- Institute for Neuromodulation and Neurotechnology, University Hospital and University of Tübingen, Tübingen 72076, Germany
| | - Ali Nicksirat
- Institute for Neuromodulation and Neurotechnology, University Hospital and University of Tübingen, Tübingen 72076, Germany
| | - Dominic Kraus
- Institute for Neuromodulation and Neurotechnology, University Hospital and University of Tübingen, Tübingen 72076, Germany
| | - Alireza Gharabaghi
- Institute for Neuromodulation and Neurotechnology, University Hospital and University of Tübingen, Tübingen 72076, Germany
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15
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Rosenich E, Hillier SL, Low A, Hordacre B. Cognitive reserve modifies the relationship between neural function, neural injury and upper-limb recovery after stroke. J Stroke Cerebrovasc Dis 2022; 31:106557. [DOI: 10.1016/j.jstrokecerebrovasdis.2022.106557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 05/03/2022] [Accepted: 05/08/2022] [Indexed: 11/17/2022] Open
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16
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Varied Response of EEG Rhythm to Different tDCS Protocols and Lesion Hemispheres in Stroke Subjects with Upper Limb Dysfunction. Neural Plast 2022; 2022:7790730. [PMID: 35941932 PMCID: PMC9356883 DOI: 10.1155/2022/7790730] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 06/28/2022] [Indexed: 11/29/2022] Open
Abstract
Transcranial direct current stimulation (tDCS) provides a way to modulate the cortical activity and promote motor rehabilitation following stroke. However, evidence indicates that the response to tDCS is highly variable. This study was aimed at exploring rhythmic response of Electroencephalography (EEG) to three tDCS protocols in stroke subjects. We hypothesize that tDCS protocols may interact with stoke characteristics, and electrode placement may affect cortical activity which could be reflected by the EEG rhythm. 32 subjects with unilateral stroke were recruited to a single-blinded, randomized, and controlled crossover experiment. All of the subjects underwent four tDCS protocols (anodal (atDCS), cathodal (ctDCS), and bilateral tDCS (bi-tDCS) and sham) with an interval of at least 1 week. Resting-state EEG was acquired before and after the stimulation. We tested the change of EEG spectral power after tDCS and the difference of change among four protocols using the paired-sample t-test and repeated measures analysis of variance. Then, we investigated the clinical factors affecting the above changes using the linear and quadratic regression model. According to the results, EEG responded to atDCS and bi-tDCS protocols on alpha and beta rhythm and subjects with a left lesion had higher response than those with the right lesion. Besides that, the change of alpha and beta power after atDCS and of beta power after bi-tDCS showed association with clinical characteristics only in subjects with the left lesion. In conclusion, the study found varied EEG response with different protocols, lesion hemispheres, and other clinical characteristics supporting the individualized cortical oscillatory effect induced by tDCS.
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17
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Leonardi G, Ciurleo R, Cucinotta F, Fonti B, Borzelli D, Costa L, Tisano A, Portaro S, Alito A. The role of brain oscillations in post-stroke motor recovery: An overview. Front Syst Neurosci 2022; 16:947421. [PMID: 35965998 PMCID: PMC9373799 DOI: 10.3389/fnsys.2022.947421] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 07/13/2022] [Indexed: 11/25/2022] Open
Abstract
Stroke is the second cause of disability and death worldwide, highly impacting patient’s quality of life. Several changes in brain architecture and function led by stroke can be disclosed by neurophysiological techniques. Specifically, electroencephalogram (EEG) can disclose brain oscillatory rhythms, which can be considered as a possible outcome measure for stroke recovery, and potentially shaped by neuromodulation techniques. We performed a review of randomized controlled trials on the role of brain oscillations in patients with post-stroke searching the following databases: Pubmed, Scopus, and the Web of Science, from 2012 to 2022. Thirteen studies involving 346 patients in total were included. Patients in the control groups received various treatments (sham or different stimulation modalities) in different post-stroke phases. This review describes the state of the art in the existing randomized controlled trials evaluating post-stroke motor function recovery after conventional rehabilitation treatment associated with neuromodulation techniques. Moreover, the role of brain pattern rhythms to modulate cortical excitability has been analyzed. To date, neuromodulation approaches could be considered a valid tool to improve stroke rehabilitation outcomes, despite more high-quality, and homogeneous randomized clinical trials are needed to determine to which extent motor functional impairment after stroke can be improved by neuromodulation approaches and which one could provide better functional outcomes. However, the high reproducibility of brain oscillatory rhythms could be considered a promising predictive outcome measure applicable to evaluate patients with stroke recovery after rehabilitation.
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Affiliation(s)
- Giulia Leonardi
- Department of Physical and Rehabilitation Medicine and Sports Medicine, Policlinico “G. Martino,”Messina, Italy
| | | | | | - Bartolo Fonti
- IRCCS Centro Neurolesi Bonino-Pulejo, Messina, Italy
| | - Daniele Borzelli
- Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
| | - Lara Costa
- Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy
| | - Adriana Tisano
- Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy
| | - Simona Portaro
- Department of Physical and Rehabilitation Medicine and Sports Medicine, Policlinico “G. Martino,”Messina, Italy
| | - Angelo Alito
- Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
- *Correspondence: Angelo Alito,
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18
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Chen Y, Wang C, Song P, Sun C, Zhang Y, Zhao X, Du J. Alpha rhythm of electroencephalography was modulated differently by three transcranial direct current stimulation protocols in patients with ischemic stroke. Front Hum Neurosci 2022; 16:887849. [PMID: 35911595 PMCID: PMC9334563 DOI: 10.3389/fnhum.2022.887849] [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: 03/02/2022] [Accepted: 06/28/2022] [Indexed: 11/13/2022] Open
Abstract
The heterogeneity of transcranial direct current stimulation (tDCS) protocols and clinical profiles may explain variable results in modulating excitability in the motor cortex after stroke. However, the cortical electrical effects induced by different tDCS protocols remain unclear. Here, we aimed to compare rhythm changes in electroencephalography (EEG) induced by three tDCS position protocols and the association between tDCS effects and clinical factors in stroke. Nineteen patients with chronic ischemic stroke underwent four experimental sessions with three tDCS protocols [anodal (atDCS), cathodal (ctDCS), and bilateral (bi-tDCS)] and a sham protocol, according to a single-blind randomized crossover design. Resting-state EEG was acquired before and after each protocol. First, a paired-sample t-test was used to examine the difference in spectral power between pre- and post-stimulation. Then, linear and quadratic regression models were used separately to describe the association between the clinical factors of stroke and changes in spectral power which was significantly different between pre- and post-tDCS. Finally, repeated measures analysis of variance with lesion hemisphere, stimulation protocol, and the location was performed to investigate the effects of tDCS over time. The induced effect of tDCS was mainly reflected in the alpha rhythms. The alpha power was increased by atDCS, especially low-alpha (8–10 Hz), in localized areas of the central and distant areas of the frontal and parietal lobes. Bi-tDCS also affected alpha power but in a smaller area that mainly focused on high-alpha rhythms (10–13 Hz). However, ctDCS and sham had no significant effects on any EEG rhythm. The clinical factors of time since stroke and motor impairment level were related to the change in high-alpha induced by atDCS and bi-tDCS following quadratic regression models. The above-mentioned modulation effect lasted for 20 min without attenuation. In conclusion, our findings provide evidence that the alpha rhythm of EEG is modulated differently by different tDCS protocols and that high alpha is affected by clinical characteristics such as post-stroke time and motor deficits, which is of great significance for understanding the modulation effect of different tDCS protocols on stroke and the guidance of protocols to promote motor recovery following stroke.
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Affiliation(s)
- Yuanyuan Chen
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Chunfang Wang
- Department of Rehabilitation Medicine, Tianjin Union Medical Centre, Rehabilitation Medical Research Center of Tianjin, Tianjin, China
| | - Peiqing Song
- Department of Rehabilitation Medicine, Tianjin Union Medical Centre, Rehabilitation Medical Research Center of Tianjin, Tianjin, China
| | - Changcheng Sun
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Department of Rehabilitation Medicine, Tianjin Union Medical Centre, Rehabilitation Medical Research Center of Tianjin, Tianjin, China
| | - Ying Zhang
- Department of Rehabilitation Medicine, Tianjin Union Medical Centre, Rehabilitation Medical Research Center of Tianjin, Tianjin, China
- *Correspondence: Ying Zhang,
| | - Xin Zhao
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Xin Zhao,
| | - Jingang Du
- Department of Rehabilitation Medicine, Tianjin Union Medical Centre, Rehabilitation Medical Research Center of Tianjin, Tianjin, China
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Humphries JB, Mattos DJS, Rutlin J, Daniel AGS, Rybczynski K, Notestine T, Shimony JS, Burton H, Carter A, Leuthardt EC. Motor Network Reorganization Induced in Chronic Stroke Patients with the Use of a Contralesionally-Controlled Brain Computer Interface. BRAIN-COMPUTER INTERFACES 2022. [DOI: 10.1080/2326263x.2022.2057757] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Joseph B. Humphries
- Departments of Neurosurgery, Washington University in St. Louis, St. Louis, MO, USA
| | | | - Jerrel Rutlin
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Andy G. S. Daniel
- Departments of Neurosurgery, Washington University in St. Louis, St. Louis, MO, USA
| | | | - Theresa Notestine
- Neurosurgery, Washington University in St. Louis, St. Louis, MO, USA
| | - Joshua S. Shimony
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Harold Burton
- Neuroscience, Washington University in St. Louis, St. Louis, MO, USA
| | - Alexandre Carter
- Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Eric C. Leuthardt
- Departments of Neurosurgery, Washington University in St. Louis, St. Louis, MO, USA
- Neurosurgery, Washington University in St. Louis, St. Louis, MO, USA
- Neuroscience, Washington University in St. Louis, St. Louis, MO, USA
- Mechanical Engineering and Materials Science, Washington University in St. Louis, St. Louis, MO, USA
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Cassidy JM, Mark JI, Cramer SC. Functional connectivity drives stroke recovery: shifting the paradigm from correlation to causation. Brain 2022; 145:1211-1228. [PMID: 34932786 PMCID: PMC9630718 DOI: 10.1093/brain/awab469] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 11/20/2021] [Accepted: 11/26/2021] [Indexed: 11/14/2022] Open
Abstract
Stroke is a leading cause of disability, with deficits encompassing multiple functional domains. The heterogeneity underlying stroke poses significant challenges in the prediction of post-stroke recovery, prompting the development of neuroimaging-based biomarkers. Structural neuroimaging measurements, particularly those reflecting corticospinal tract injury, are well-documented in the literature as potential biomarker candidates of post-stroke motor recovery. Consistent with the view of stroke as a 'circuitopathy', functional neuroimaging measures probing functional connectivity may also prove informative in post-stroke recovery. An important step in the development of biomarkers based on functional neural network connectivity is the establishment of causality between connectivity and post-stroke recovery. Current evidence predominantly involves statistical correlations between connectivity measures and post-stroke behavioural status, either cross-sectionally or serially over time. However, the advancement of functional connectivity application in stroke depends on devising experiments that infer causality. In 1965, Sir Austin Bradford Hill introduced nine viewpoints to consider when determining the causality of an association: (i) strength; (ii) consistency; (iii) specificity; (iv) temporality; (v) biological gradient; (vi) plausibility; (vii) coherence; (viii) experiment; and (ix) analogy. Collectively referred to as the Bradford Hill Criteria, these points have been widely adopted in epidemiology. In this review, we assert the value of implementing Bradford Hill's framework to stroke rehabilitation and neuroimaging. We focus on the role of neural network connectivity measurements acquired from task-oriented and resting-state functional MRI, EEG, magnetoencephalography and functional near-infrared spectroscopy in describing and predicting post-stroke behavioural status and recovery. We also identify research opportunities within each Bradford Hill tenet to shift the experimental paradigm from correlation to causation.
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Affiliation(s)
- Jessica M Cassidy
- Department of Allied Health Sciences, Division of Physical Therapy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jasper I Mark
- Department of Allied Health Sciences, Division of Physical Therapy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Steven C Cramer
- Department of Neurology, University of California, Los Angeles; and California Rehabilitation Institute, Los Angeles, CA, USA
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Shah-Basak P, Sivaratnam G, Teti S, Deschamps T, Kielar A, Jokel R, Meltzer JA. Electrophysiological connectivity markers of preserved language functions in post-stroke aphasia. Neuroimage Clin 2022; 34:103036. [PMID: 35561556 PMCID: PMC9111985 DOI: 10.1016/j.nicl.2022.103036] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 04/19/2022] [Accepted: 05/04/2022] [Indexed: 11/17/2022]
Abstract
Post-stroke aphasia is a consequence of localized stroke-related damage as well as global disturbances in a highly interactive and bilaterally-distributed language network. Aphasia is increasingly accepted as a network disorder and it should be treated as such when examining the reorganization and recovery mechanisms after stroke. In the current study, we sought to investigate reorganized patterns of electrophysiological connectivity, derived from resting-state magnetoencephalography (rsMEG), in post-stroke chronic (>6 months after onset) aphasia. We implemented amplitude envelope correlations (AEC), a metric of connectivity commonly used to describe slower aspects of interregional communication in resting-state electrophysiological data. The main focus was on identifying the oscillatory frequency bands and frequency-specific spatial topology of connections associated with preserved language abilities after stroke. RsMEG was recorded for 5 min in 21 chronic stroke survivors with aphasia and in 20 matched healthy controls. Source-level MEG activity was reconstructed and summarized within 72 atlas-defined brain regions (or nodes). A 72 × 72 leakage-corrected connectivity (of AEC) matrix was obtained for frequencies from theta to low-gamma (4–50 Hz). Connectivity was compared between groups, and, the correlations between connectivity and subscale scores from the Western Aphasia Battery (WAB) were evaluated in the stroke group, using partial least squares analyses. Posthoc multiple regression analyses were also conducted on a graph theory measure of node strengths, derived from significant connectivity results, to control for node-wise properties (local spectral power and lesion sizes) and demographic and stroke-related variables. Connectivity among the left hemisphere regions, i.e. those ipsilateral to the stroke lesion, was greatly reduced in stroke survivors with aphasia compared to matched healthy controls in the alpha (8–13 Hz; p = 0.011) and beta (15–30 Hz; p = 0.001) bands. The spatial topology of hypoconnectivity in the alpha vs. beta bands was distinct, revealing a greater involvement of ventral frontal, temporal and parietal areas in alpha, and dorsal frontal and parietal areas in beta. The node strengths from alpha and beta group differences remained significant after controlling for nodal spectral power. AEC correlations with WAB subscales of object naming and fluency were significant. Greater alpha connectivity was associated with better naming performance (p = 0.045), and greater connectivity in both the alpha (p = 0.033) and beta (p = 0.007) bands was associated with better speech fluency performance. The spatial topology was distinct between these frequency bands. The node strengths remained significant after controlling for age, time post stroke onset, nodal spectral power and nodal lesion sizes. Our findings provide important insights into the electrophysiological connectivity profiles (frequency and spatial topology) potentially underpinning preserved language abilities in stroke survivors with aphasia.
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Affiliation(s)
- Priyanka Shah-Basak
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada; Canadian Partnership for Stroke Recovery, Ottawa, ON, Canada.
| | - Gayatri Sivaratnam
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Selina Teti
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Tiffany Deschamps
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada
| | - Aneta Kielar
- Department of Speech, Language, and Hearing Sciences, University of Arizona, Tucson, AZ, USA
| | - Regina Jokel
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada; Canadian Partnership for Stroke Recovery, Ottawa, ON, Canada; Department of Speech-Language Pathology, University of Toronto, Toronto, ON, Canada
| | - Jed A Meltzer
- Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada; Canadian Partnership for Stroke Recovery, Ottawa, ON, Canada; Department of Speech-Language Pathology, University of Toronto, Toronto, ON, Canada; Department of Psychology, University of Toronto, Toronto, ON, Canada
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22
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Gallina J, Zanon M, Mikulan E, Pietrelli M, Gambino S, Ibáñez A, Bertini C. Alterations in resting-state functional connectivity after brain posterior lesions reflect the functionality of the visual system in hemianopic patients. Brain Struct Funct 2022; 227:2939-2956. [PMID: 35585290 DOI: 10.1007/s00429-022-02502-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 04/21/2022] [Indexed: 12/13/2022]
Abstract
Emerging evidence suggests a role of the posterior cortices in regulating alpha oscillatory activity and organizing low-level processing in non-alpha frequency bands. Therefore, posterior brain lesions, which damage the neural circuits of the visual system, might affect functional connectivity patterns of brain rhythms. To test this hypothesis, eyes-closed resting state EEG signal was acquired from patients with hemianopia with left and right posterior lesions, patients without hemianopia with more anterior lesions and healthy controls. Left-lesioned hemianopics showed reduced intrahemispheric connectivity in the range of upper alpha only in the lesioned hemisphere, whereas right-lesioned hemianopics exhibited reduced intrahemispheric alpha connectivity in both hemispheres. In terms of network topology, these impairments were characterized by reduced local functional segregation, with no associated change in global functional integration. This suggests a crucial role of posterior cortices in promoting functional connectivity in the range of alpha. Right-lesioned hemianopics revealed also additional impairments in the theta range, with increased connectivity in this frequency band, characterized by both increased local segregated activity and decreased global integration. This indicates that lesions to right posterior cortices lead to stronger impairments in alpha connectivity and induce additional alterations in local and global low-level processing, suggesting a specialization of the right hemisphere in generating alpha oscillations and in coordinating complex interplays with lower frequency bands. Importantly, hemianopic patient's visual performance in the blind field was linked to alpha functional connectivity, corroborating the notion that alpha oscillatory patterns represent a biomarker of the integrity and the functioning of the underlying visual system.
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Affiliation(s)
- Jessica Gallina
- Centre for Studies and Research in Cognitive Neuroscience, University of Bologna, Cesena, Italy.,Department of Psychology, University of Bologna, Bologna, Italy
| | - Marco Zanon
- Centre for Studies and Research in Cognitive Neuroscience, University of Bologna, Cesena, Italy.,Department of Psychology, University of Bologna, Bologna, Italy.,Neuroscience Area, International School for Advanced Studies (SISSA), Trieste, Italy
| | - Ezequiel Mikulan
- Department of Biomedical and Clinical Sciences "L. Sacco", University of Milan, Milan, Italy
| | - Mattia Pietrelli
- Centre for Studies and Research in Cognitive Neuroscience, University of Bologna, Cesena, Italy.,Department of Psychology, University of Bologna, Bologna, Italy.,Department of Psychiatry, University of WI-Madison, Wisconsin, USA
| | - Silvia Gambino
- Centre for Studies and Research in Cognitive Neuroscience, University of Bologna, Cesena, Italy.,Department of Psychology, University of Bologna, Bologna, Italy
| | - Agustín Ibáñez
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile.,Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina.,Global Brain Health Institute, University of California-San Francisco, San Francisco, CA, USA.,Trinity College Dublin, Dublin, Ireland
| | - Caterina Bertini
- Centre for Studies and Research in Cognitive Neuroscience, University of Bologna, Cesena, Italy. .,Department of Psychology, University of Bologna, Bologna, Italy.
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23
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Sun R, Wong WW, Wang J, Wang X, Tong RKY. Functional brain networks assessed with surface electroencephalography for predicting motor recovery in a neural guided intervention for chronic stroke. Brain Commun 2022; 3:fcab214. [PMID: 35350709 PMCID: PMC8936428 DOI: 10.1093/braincomms/fcab214] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 06/04/2021] [Accepted: 07/28/2021] [Indexed: 12/12/2022] Open
Abstract
Predicting whether a chronic stroke patient is likely to benefit from a specific intervention can help patients establish reasonable expectations. It also provides the basis for candidates selecting for the intervention. Recent convergent evidence supports the value of network-based approach for understanding the relationship between dysfunctional neural activity and motor deficits after stroke. In this study, we applied resting-state brain connectivity networks to investigate intervention-specific predictive biomarkers of motor improvement in 22 chronic stroke participants who received either combined action observation with EEG-guided robot-hand training (Neural Guided-Action Observation Group, n = 12, age: 34–68 years) or robot-hand training without action observation and EEG guidance (non-Neural Guided-text group, n = 10, age: 42–57 years). The robot hand in Neural Guided-Action Observation training was activated only when significant mu suppression (8–12 Hz) was detected from participant’s EEG signals in ipsilesional hemisphere while it was randomly activated in non-Neural Guided-text training. Only the Neural Guided-Action Observation group showed a significant long-term improvement in their upper-limb motor functions (P < 0.5). In contrast, no significant training effect on the paretic motor functions was found in the non-Neural Guided-text group (P > 0.5). The results of brain connectivity estimated via EEG coherence showed that the pre-training interhemispheric connectivity of delta, theta, alpha and contralesional connectivity of beta were motor improvement related in the Neural Guided-Action Observation group. They can not only differentiate participants with good and poor recovery (interhemispheric delta: P = 0.047, Hedges’ g = 1.409; interhemispheric theta: P = 0.046, Hedges’ g = 1.333; interhemispheric alpha: P = 0.038, Hedges’ g = 1.536; contralesional beta: P = 0.027, Hedges’ g = 1.613) but also significantly correlated with post-training intervention gains (interhemispheric delta: r = −0.901, P < 0.05; interhemispheric theta: r = −0.702, P < 0.05; interhemispheric alpha: r = −0.641, P < 0.05; contralesional beta: r = −0.729, P < 0.05). In contrast, no EEG coherence was significantly correlated with intervention gains in the non-Neural Guided-text group (all Ps>0.05). Partial least square regression showed that the combination of pre-training interhemispheric and contralesional local connectivity could precisely predict intervention gains in the Neural Guided-Action Observation group with a strong correlation between predicted and observed intervention gains (r = 0.82r=0.82) and between predicted and observed intervention outcomes (r = 0.90r=0.90). In summary, EEG-based resting-state brain connectivity networks may serve clinical decision-making by offering an approach to predicting Neural Guided-Action Observation training-induced motor improvement.
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Affiliation(s)
- Rui Sun
- The Laboratory of Neuroscience for Education, Faculty of Education, the University of Hong Kong, Pokfulam, Hong Kong, China
| | - Wan-Wa Wong
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Jing Wang
- School of Mechanical Engineering, Xi'an Jiaotong University, Shaanxi, China
| | - Xin Wang
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Raymond K Y Tong
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong, China
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24
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Pusil S, Torres-Simon L, Chino B, López ME, Canuet L, Bilbao Á, Maestú F, Paúl N. Resting-State Beta-Band Recovery Network Related to Cognitive Improvement After Stroke. Front Neurol 2022; 13:838170. [PMID: 35280290 PMCID: PMC8914082 DOI: 10.3389/fneur.2022.838170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 02/03/2022] [Indexed: 11/29/2022] Open
Abstract
Background Stroke is the second leading cause of death worldwide and it causes important long-term cognitive and physical deficits that hamper patients' daily activity. Neuropsychological rehabilitation (NR) has increasingly become more important to recover from cognitive disability and to improve the functionality and quality of life of these patients. Since in most stroke cases, restoration of functional connectivity (FC) precedes or accompanies cognitive and behavioral recovery, understanding the electrophysiological signatures underlying stroke recovery mechanisms is a crucial scientific and clinical goal. Methods For this purpose, a longitudinal study was carried out with a sample of 10 stroke patients, who underwent two neuropsychological assessments and two resting-state magnetoencephalographic (MEG) recordings, before and after undergoing a NR program. Moreover, to understand the degree of cognitive and neurophysiological impairment after stroke and the mechanisms of recovery after cognitive rehabilitation, stroke patients were compared to 10 healthy controls matched for age, sex, and educational level. Findings After intra and inter group comparisons, we found the following results: (1) Within the stroke group who received cognitive rehabilitation, almost all cognitive domains improved relatively or totally; (2) They exhibit a pattern of widespread increased in FC within the beta band that was related to the recovery process (there were no significant differences between patients who underwent rehabilitation and controls); (3) These FC recovery changes were related with the enhanced of cognitive performance. Furthermore, we explored the capacity of the neuropsychological scores before rehabilitation, to predict the FC changes in the brain network. Significant correlations were found in global indexes from the WAIS-III: Performance IQ (PIQ) and Perceptual Organization index (POI) (i.e., Picture Completion, Matrix Reasoning, and Block Design).
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Affiliation(s)
- Sandra Pusil
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Spain
| | - Lucía Torres-Simon
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Spain
| | - Brenda Chino
- Institute of Neuroscience, Autonomous University of Barcelona, Barcelona, Spain
| | - María Eugenia López
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Spain
| | - Leonides Canuet
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Spain
| | - Álvaro Bilbao
- National Centre for Brain Injury Treatment, Centro de Referencia Estatal de Atención Al Daño Cerebral (CEADAC), Madrid, Spain
| | - Fernando Maestú
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Spain
| | - Nuria Paúl
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Spain
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25
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Gangwani R, Cain A, Collins A, Cassidy JM. Leveraging Factors of Self-Efficacy and Motivation to Optimize Stroke Recovery. Front Neurol 2022; 13:823202. [PMID: 35280288 PMCID: PMC8907401 DOI: 10.3389/fneur.2022.823202] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 01/13/2022] [Indexed: 01/01/2023] Open
Abstract
The International Classification of Functioning, Disability and Health framework recognizes that an individual's functioning post-stroke reflects an interaction between their health condition and contextual factors encompassing personal and environmental factors. Personal factors significantly impact rehabilitation outcomes as they determine how an individual evaluates their situation and copes with their condition in daily life. A key personal factor is self-efficacy-an individual's belief in their capacity to achieve certain outcomes. Self-efficacy influences an individual's motivational state to execute behaviors necessary for achieving desired rehabilitation outcomes. Stroke rehabilitation practice and research now acknowledge self-efficacy and motivation as critical elements in post-stroke recovery, and increasing evidence highlights their contributions to motor (re)learning. Given the informative value of neuroimaging-based biomarkers in stroke, elucidating the neurological underpinnings of self-efficacy and motivation may optimize post-stroke recovery. In this review, we examine the role of self-efficacy and motivation in stroke rehabilitation and recovery, identify potential neural substrates underlying these factors from current neuroimaging literature, and discuss how leveraging these factors and their associated neural substrates has the potential to advance the field of stroke rehabilitation.
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Affiliation(s)
- Rachana Gangwani
- Department of Allied Health Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Human Movement Sciences Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Amelia Cain
- Department of Allied Health Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Amy Collins
- Department of Allied Health Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Jessica M. Cassidy
- Department of Allied Health Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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26
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Páscoa dos Santos F, Verschure PFMJ. Excitatory-Inhibitory Homeostasis and Diaschisis: Tying the Local and Global Scales in the Post-stroke Cortex. Front Syst Neurosci 2022; 15:806544. [PMID: 35082606 PMCID: PMC8785563 DOI: 10.3389/fnsys.2021.806544] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Accepted: 11/29/2021] [Indexed: 12/28/2022] Open
Abstract
Maintaining a balance between excitatory and inhibitory activity is an essential feature of neural networks of the neocortex. In the face of perturbations in the levels of excitation to cortical neurons, synapses adjust to maintain excitatory-inhibitory (EI) balance. In this review, we summarize research on this EI homeostasis in the neocortex, using stroke as our case study, and in particular the loss of excitation to distant cortical regions after focal lesions. Widespread changes following a localized lesion, a phenomenon known as diaschisis, are not only related to excitability, but also observed with respect to functional connectivity. Here, we highlight the main findings regarding the evolution of excitability and functional cortical networks during the process of post-stroke recovery, and how both are related to functional recovery. We show that cortical reorganization at a global scale can be explained from the perspective of EI homeostasis. Indeed, recovery of functional networks is paralleled by increases in excitability across the cortex. These adaptive changes likely result from plasticity mechanisms such as synaptic scaling and are linked to EI homeostasis, providing a possible target for future therapeutic strategies in the process of rehabilitation. In addition, we address the difficulty of simultaneously studying these multiscale processes by presenting recent advances in large-scale modeling of the human cortex in the contexts of stroke and EI homeostasis, suggesting computational modeling as a powerful tool to tie the meso- and macro-scale processes of recovery in stroke patients.
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Affiliation(s)
- Francisco Páscoa dos Santos
- Eodyne Systems SL, Barcelona, Spain
- Laboratory of Synthetic, Perceptive, Emotive and Cognitive Systems (SPECS), Institute for Bioengineering of Catalonia (IBEC), Barcelona, Spain
- Department of Information and Communications Technologies (DTIC), Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Paul F. M. J. Verschure
- Laboratory of Synthetic, Perceptive, Emotive and Cognitive Systems (SPECS), Institute for Bioengineering of Catalonia (IBEC), Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
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27
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Brancaccio A, Tabarelli D, Belardinelli P. A New Framework to Interpret Individual Inter-Hemispheric Compensatory Communication after Stroke. J Pers Med 2022; 12:jpm12010059. [PMID: 35055374 PMCID: PMC8778334 DOI: 10.3390/jpm12010059] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 12/14/2021] [Accepted: 12/30/2021] [Indexed: 12/15/2022] Open
Abstract
Stroke constitutes the main cause of adult disability worldwide. Even after application of standard rehabilitation protocols, the majority of patients still show relevant motor impairment. Outcomes of standard rehabilitation protocols have led to mixed results, suggesting that relevant factors for brain re-organization after stroke have not been considered in explanatory models. Therefore, finding a comprehensive model to optimally define patient-dependent rehabilitation protocols represents a crucial topic in clinical neuroscience. In this context, we first report on the rehabilitation models conceived thus far in the attempt of predicting stroke rehabilitation outcomes. Then, we propose a new framework to interpret results in stroke literature in the light of the latest evidence regarding: (1) the role of the callosum in inter-hemispheric communication, (2) the role of prefrontal cortices in exerting a control function, and (3) diaschisis mechanisms. These new pieces of evidence on the role of callosum can help to understand which compensatory mechanism may take place following a stroke. Moreover, depending on the individual impairment, the prefrontal control network will play different roles according to the need of high-level motor control. We believe that our new model, which includes crucial overlooked factors, will enable clinicians to better define individualized motor rehabilitation protocols.
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28
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Vatinno AA, Schranz C, Simpson A, Ramakrishnan V, Bonilha L, Seo NJ. Predicting upper extremity motor improvement following therapy using EEG-based connectivity in chronic stroke. NeuroRehabilitation 2022; 50:105-113. [PMID: 34776421 PMCID: PMC8821328 DOI: 10.3233/nre-210171] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND Uncertain prognosis presents a challenge for therapists in determining the most efficient course of rehabilitation treatment for individual patients. Cortical Sensorimotor network connectivity may have prognostic utility for upper extremity motor improvement because the integrity of the communication within the sensorimotor network forms the basis for neuroplasticity and recovery. OBJECTIVE To investigate if pre-intervention sensorimotor connectivity predicts post-stroke upper extremity motor improvement following therapy. METHODS Secondary analysis of a pilot triple-blind randomized controlled trial. Twelve chronic stroke survivors underwent 2-week task-practice therapy, while receiving vibratory stimulation for the treatment group and no stimulation for the control group. EEG connectivity was obtained pre-intervention. Motor improvement was quantified as change in the Box and Block Test from pre to post-therapy. The association between ipsilesional sensorimotor connectivity and motor improvement was examined using regression, controlling for group. For negative control, contralesional/interhemispheric connectivity and conventional predictors (initial clinical motor score, age, time post-stroke, lesion volume) were examined. RESULTS Greater ipsilesional sensorimotor alpha connectivity was associated with greater upper extremity motor improvement following therapy for both groups (p < 0.05). Other factors were not significant. CONCLUSION EEG connectivity may have a prognostic utility for individual patients' upper extremity motor improvement following therapy in chronic stroke.
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Affiliation(s)
- Amanda A Vatinno
- Department of Health Sciences and Research, College of Health Professions, Medical University of South Carolina (MUSC), Charleston, SC
| | - Christian Schranz
- Department of Health Sciences and Research, College of Health Professions, MUSC
| | - Annie Simpson
- Department of Healthcare Leadership and Management, Department of Health Sciences and Research, College of Health Professions, MUSC
| | | | | | - Na Jin Seo
- Division of Occupational Therapy, Department of Rehabilitation Sciences, Department of Health Sciences and Research, MUSC, Ralph H. Johnson VA Medical Center
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29
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Angerhöfer C, Colucci A, Vermehren M, Hömberg V, Soekadar SR. Post-stroke Rehabilitation of Severe Upper Limb Paresis in Germany - Toward Long-Term Treatment With Brain-Computer Interfaces. Front Neurol 2021; 12:772199. [PMID: 34867760 PMCID: PMC8637332 DOI: 10.3389/fneur.2021.772199] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 10/29/2021] [Indexed: 12/03/2022] Open
Abstract
Severe upper limb paresis can represent an immense burden for stroke survivors. Given the rising prevalence of stroke, restoration of severe upper limb motor impairment remains a major challenge for rehabilitation medicine because effective treatment strategies are lacking. Commonly applied interventions in Germany, such as mirror therapy and impairment-oriented training, are limited in efficacy, demanding for new strategies to be found. By translating brain signals into control commands of external devices, brain-computer interfaces (BCIs) and brain-machine interfaces (BMIs) represent promising, neurotechnology-based alternatives for stroke patients with highly restricted arm and hand function. In this mini-review, we outline perspectives on how BCI-based therapy can be integrated into the different stages of neurorehabilitation in Germany to meet a long-term treatment approach: We found that it is most appropriate to start therapy with BCI-based neurofeedback immediately after early rehabilitation. BCI-driven functional electrical stimulation (FES) and BMI robotic therapy are well suited for subsequent post hospital curative treatment in the subacute stage. BCI-based hand exoskeleton training can be continued within outpatient occupational therapy to further improve hand function and address motivational issues in chronic stroke patients. Once the rehabilitation potential is exhausted, BCI technology can be used to drive assistive devices to compensate for impaired function. However, there are several challenges yet to overcome before such long-term treatment strategies can be implemented within broad clinical application: 1. developing reliable BCI systems with better usability; 2. conducting more research to improve BCI training paradigms and 3. establishing reliable methods to identify suitable patients.
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Affiliation(s)
- Cornelius Angerhöfer
- Clinical Neurotechnology Lab, Department of Psychiatry and Neurosciences, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Annalisa Colucci
- Clinical Neurotechnology Lab, Department of Psychiatry and Neurosciences, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Mareike Vermehren
- Clinical Neurotechnology Lab, Department of Psychiatry and Neurosciences, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Volker Hömberg
- Department of Neurology, SRH Gesundheitszentrum Bad Wimpfen GmbH, Bad Wimpfen, Germany
| | - Surjo R Soekadar
- Clinical Neurotechnology Lab, Department of Psychiatry and Neurosciences, Charité-Universitätsmedizin Berlin, Berlin, Germany
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30
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Cassidy JM, Wodeyar A, Srinivasan R, Cramer SC. Coherent neural oscillations inform early stroke motor recovery. Hum Brain Mapp 2021; 42:5636-5647. [PMID: 34435705 PMCID: PMC8559506 DOI: 10.1002/hbm.25643] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 08/11/2021] [Accepted: 08/16/2021] [Indexed: 12/24/2022] Open
Abstract
Neural oscillations may contain important information pertaining to stroke rehabilitation. This study examined the predictive performance of electroencephalography‐derived neural oscillations following stroke using a data‐driven approach. Individuals with stroke admitted to an inpatient rehabilitation facility completed a resting‐state electroencephalography recording and structural neuroimaging around the time of admission and motor testing at admission and discharge. Using a lasso regression model with cross‐validation, we determined the extent of motor recovery (admission to discharge change in Functional Independence Measurement motor subscale score) prediction from electroencephalography, baseline motor status, and corticospinal tract injury. In 27 participants, coherence in a 1–30 Hz band between leads overlying ipsilesional primary motor cortex and 16 leads over bilateral hemispheres predicted 61.8% of the variance in motor recovery. High beta (20–30 Hz) and alpha (8–12 Hz) frequencies contributed most to the model demonstrating both positive and negative associations with motor recovery, including high beta leads in supplementary motor areas and ipsilesional ventral premotor and parietal regions and alpha leads overlying contralesional temporal–parietal and ipsilesional parietal regions. Electroencephalography power, baseline motor status, and corticospinal tract injury did not significantly predict motor recovery during hospitalization (R2 = 0–6.2%). Findings underscore the relevance of oscillatory synchronization in early stroke rehabilitation while highlighting contributions from beta and alpha frequency bands and frontal, parietal, and temporal–parietal regions overlooked by traditional hypothesis‐driven prediction models.
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Affiliation(s)
- Jessica M Cassidy
- Department of Allied Health Sciences, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Anirudh Wodeyar
- Department of Cognitive Sciences, University of California Irvine, Irvine, California, USA
| | - Ramesh Srinivasan
- Department of Cognitive Sciences, University of California Irvine, Irvine, California, USA.,Department of Biomedical Engineering, University of California Irvine, Irvine, California, USA
| | - Steven C Cramer
- Department of Neurology, University of California, Los Angeles, Los Angeles, California, USA.,California Rehabilitation Institute, Los Angeles, California, USA
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31
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Keator LM, Yourganov G, Basilakos A, Hillis AE, Hickok G, Bonilha L, Rorden C, Fridriksson J. Independent contributions of structural and functional connectivity: Evidence from a stroke model. Netw Neurosci 2021; 5:911-928. [PMID: 35024536 PMCID: PMC8746188 DOI: 10.1162/netn_a_00207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 08/12/2021] [Indexed: 11/08/2022] Open
Abstract
Altered functional connectivity is related to severity of language impairment in poststroke aphasia. However, it is not clear whether this finding specifically reflects loss of functional coherence, or more generally, is related to decreased structural connectivity due to cortical necrosis. The aim of the current study was to investigate this issue by factoring out structural connectivity from functional connectivity measures and then relating the residual data to language performance poststroke. Ninety-seven participants with a history of stroke were assessed using language impairment measures (Auditory Verbal Comprehension and Spontaneous Speech scores from the Western Aphasia Battery-Revised) and MRI (structural, diffusion tensor imaging, and resting-state functional connectivity). We analyzed the association between functional connectivity and language and controlled for multiple potential neuroanatomical confounders, namely structural connectivity. We identified functional connections within the left hemisphere ventral stream where decreased functional connectivity, independent of structural connectivity, was associated with speech comprehension impairment. These connections exist in frontotemporal and temporoparietal regions. Our results suggest poor speech comprehension in aphasia is at least partially caused by loss of cortical synchrony in a left hemisphere ventral stream network and is not only reflective of localized necrosis or structural connectivity.
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Affiliation(s)
- Lynsey M. Keator
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Grigori Yourganov
- Department of Psychology, University of South Carolina, Columbia, SC, USA
| | - Alexandra Basilakos
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Argye E. Hillis
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Physical Medicine and Rehabilitation, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Cognitive Science, Johns Hopkins University, Baltimore, MD, USA
| | - Gregory Hickok
- Department of Cognitive Sciences, Department of Language Science, University of California, Irvine, CA, USA
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
| | - Christopher Rorden
- Department of Psychology, University of South Carolina, Columbia, SC, USA
- McCausland Center for Brain Imaging, University of South Carolina, Columbia, SC, USA
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
- McCausland Center for Brain Imaging, University of South Carolina, Columbia, SC, USA
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Phang CR, Ko LW, Chang WC, Yu KH, Chen CH. Immediate Plasticity of Parietal-Frontocentral Functional Connections in Music-Reality based Post-Stroke Rehabilitation. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:5828-5831. [PMID: 34892445 DOI: 10.1109/embc46164.2021.9631023] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Post-stroke neuronal plasticity was always viewed as a localized gain-of-functionality. The reorganization of neurons neighboring the lesioned brain tissues is able to compensate for the function of damaged neurons. However, it was also proposed that distant interconnected brain regions could be affected by stroke. Changes in functional connections across the brain were found associated with motor deficiency and recovery. Parietal-frontocentral functional connectivity was found related to the performance of motor imagery. This study aims to evaluate the EEG-based parietal-frontocentral functional connectivity in post-stroke patients, and to investigate the immediate effect of rehabilitation training toward these connections. Pairwise functional connectivity was extracted from healthy subjects and post-stroke patients during standing and walking. Significant reductions in P3-FC4 and P3-C4 connectivity strengths were found in post-stroke patients during both standing and walking conditions. Immediate improvement in the reduced connections was observed with the intervention of a previously proposed, motivation-based rehabilitation system, which was known as the mixed-reality music rehabilitation (MR2) system. This indicates the relationship between left parietal functional connectivity and stroke-related motor performance. These findings suggest the feasibility to evaluate the immediate plasticity of functional connectivity during post-stroke rehabilitation.
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Feasibility of Reconstructing Source Functional Connectivity with Low-Density EEG. Brain Topogr 2021; 34:709-719. [PMID: 34415477 PMCID: PMC8556201 DOI: 10.1007/s10548-021-00866-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 08/02/2021] [Indexed: 10/24/2022]
Abstract
OBJECTIVES Functional connectivity (FC) is increasingly used as target for neuromodulation and enhancement of performance. A reliable assessment of FC with electroencephalography (EEG) currently requires a laboratory environment with high-density montages and a long preparation time. This study investigated the feasibility of reconstructing source FC with a low-density EEG montage towards a usage in real life applications. METHODS Source FC was reconstructed with inverse solutions and quantified as node degree of absolute imaginary coherence in alpha frequencies. We used simulated coherent point sources as well as two real datasets to investigate the impact of electrode density (19 vs. 128 electrodes) and usage of template vs. individual MRI-based head models on localization accuracy. In addition, we checked whether low-density EEG is able to capture inter-individual variations in coherence strength. RESULTS In numerical simulations as well as real data, a reduction of the number of electrodes led to less reliable reconstructions of coherent sources and of coupling strength. Yet, when comparing different approaches to reconstructing FC from 19 electrodes, source FC obtained with beamformers outperformed sensor FC, FC computed after independent component analysis, and source FC obtained with sLORETA. In particular, only source FC based on beamformers was able to capture neural correlates of motor behavior. CONCLUSION Reconstructions of FC from low-density EEG is challenging, but may be feasible when using source reconstructions with beamformers.
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Takeuchi N, Izumi SI. Motor Learning Based on Oscillatory Brain Activity Using Transcranial Alternating Current Stimulation: A Review. Brain Sci 2021; 11:1095. [PMID: 34439714 PMCID: PMC8392205 DOI: 10.3390/brainsci11081095] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 08/17/2021] [Accepted: 08/18/2021] [Indexed: 12/15/2022] Open
Abstract
Developing effective tools and strategies to promote motor learning is a high-priority scientific and clinical goal. In particular, motor-related areas have been investigated as potential targets to facilitate motor learning by noninvasive brain stimulation (NIBS). In addition to shedding light on the relationship between motor function and oscillatory brain activity, transcranial alternating current stimulation (tACS), which can noninvasively entrain oscillatory brain activity and modulate oscillatory brain communication, has attracted attention as a possible technique to promote motor learning. This review focuses on the use of tACS to enhance motor learning through the manipulation of oscillatory brain activity and its potential clinical applications. We discuss a potential tACS-based approach to ameliorate motor deficits by correcting abnormal oscillatory brain activity and promoting appropriate oscillatory communication in patients after stroke or with Parkinson's disease. Interpersonal tACS approaches to manipulate intra- and inter-brain communication may result in pro-social effects and could promote the teaching-learning process during rehabilitation sessions with a therapist. The approach of re-establishing oscillatory brain communication through tACS could be effective for motor recovery and might eventually drive the design of new neurorehabilitation approaches based on motor learning.
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Affiliation(s)
- Naoyuki Takeuchi
- Department of Physical Therapy, Akita University Graduate School of Health Sciences 1-1-1, Hondo, Akita 010-8543, Japan
| | - Shin-Ichi Izumi
- Department of Physical Medicine and Rehabilitation, Tohoku University Graduate School of Medicine, Sendai 980-8575, Japan;
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Storch S, Samantzis M, Balbi M. Driving Oscillatory Dynamics: Neuromodulation for Recovery After Stroke. Front Syst Neurosci 2021; 15:712664. [PMID: 34366801 PMCID: PMC8339272 DOI: 10.3389/fnsys.2021.712664] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 06/21/2021] [Indexed: 12/18/2022] Open
Abstract
Stroke is a leading cause of death and disability worldwide, with limited treatments being available. However, advances in optic methods in neuroscience are providing new insights into the damaged brain and potential avenues for recovery. Direct brain stimulation has revealed close associations between mental states and neuroprotective processes in health and disease, and activity-dependent calcium indicators are being used to decode brain dynamics to understand the mechanisms underlying these associations. Evoked neural oscillations have recently shown the ability to restore and maintain intrinsic homeostatic processes in the brain and could be rapidly deployed during emergency care or shortly after admission into the clinic, making them a promising, non-invasive therapeutic option. We present an overview of the most relevant descriptions of brain injury after stroke, with a focus on disruptions to neural oscillations. We discuss the optical technologies that are currently used and lay out a roadmap for future studies needed to inform the next generation of strategies to promote functional recovery after stroke.
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Affiliation(s)
- Sven Storch
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Montana Samantzis
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Matilde Balbi
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
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Hordacre B, Goldsworthy MR, Welsby E, Graetz L, Ballinger S, Hillier S. Resting State Functional Connectivity Is Associated With Motor Pathway Integrity and Upper-Limb Behavior in Chronic Stroke. Neurorehabil Neural Repair 2020; 34:547-557. [PMID: 32436426 DOI: 10.1177/1545968320921824] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Background. Resting state functional connectivity (RSFC) is a developmental priority for stroke recovery. Objective. To determine whether (1) RSFC differs between stroke survivors based on integrity of descending motor pathways; (2) RSFC is associated with upper-limb behavior in chronic stroke; and (3) the relationship between interhemispheric RSFC and upper-limb behavior differs based on descending motor pathway integrity. Methods. A total of 36 people with stroke (aged 64.4 ± 11.1 years, time since stroke 4.0 ± 2.8 years) and 25 healthy adults (aged 67.3 ± 6.7 years) participated in this study. RSFC was estimated from electroencephalography (EEG) recordings. Integrity of descending motor pathways was ascertained using transcranial magnetic stimulation to determine motor-evoked potential (MEP) status and magnetic resonance imaging to determine lesion overlap and fractional anisotropy of the corticospinal tract (CST). For stroke participants, upper-limb motor behavior was assessed using the Fugl-Meyer test, Action Research Arm Test and grip strength. Results. β-Frequency interhemispheric sensorimotor RSFC was greater for MEP+ stroke participants compared with MEP- (P = .020). There was a significant positive correlation between β RSFC and upper-limb behavior (P = .004) that appeared to be primarily driven by the MEP+ group. A hierarchical regression identified that the addition of β RSFC to measures of CST integrity explained greater variance in upper-limb behavior (R2 change = 0.13; P = .01). Conclusions. This study provides insight to understand the role of EEG-based measures of interhemispheric network activity in chronic stroke. Resting state interhemispheric connectivity was positively associated with upper-limb behavior for stroke survivors where residual integrity of descending motor pathways was maintained.
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Affiliation(s)
- Brenton Hordacre
- University of South Australia, IIMPACT in Health, Adelaide, Australia
| | - Mitchell R Goldsworthy
- Lifespan Human Neurophysiology group, Adelaide Medical School, The University of Adelaide, Australia
| | - Ellana Welsby
- University of South Australia, IIMPACT in Health, Adelaide, Australia
| | - Lynton Graetz
- Lifespan Human Neurophysiology group, Adelaide Medical School, The University of Adelaide, Australia
| | - Sophie Ballinger
- Lifespan Human Neurophysiology group, Adelaide Medical School, The University of Adelaide, Australia
| | - Susan Hillier
- University of South Australia, IIMPACT in Health, Adelaide, Australia
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Chernoff BL, Teghipco A, Garcea FE, Belkhir R, Sims MH, Paul DA, Tivarus ME, Smith SO, Hintz E, Pilcher WH, Mahon BZ. Reorganized language network connectivity after left arcuate fasciculus resection: A case study. Cortex 2020; 123:173-184. [PMID: 31812105 DOI: 10.1016/j.cortex.2019.07.022] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Revised: 02/18/2019] [Accepted: 07/02/2019] [Indexed: 01/07/2023]
Abstract
Understanding the neural mechanisms that support spontaneous recovery of cognitive abilities can place important constraints on mechanistic theories of brain organization and function, and holds potential to inform clinical interventions. Connectivity-based MRI measures have emerged as a way to study how recovery from brain injury is modulated by changes in intra- and inter-hemispheric connectivity. Here we report a detailed and multi-modal case study of a 26 year-old male who presented with a left inferior parietal glioma infiltrating the left arcuate fasciculus. The patient underwent pre- and post-operative functional MRI and Diffusion Tensor Imaging, as well as behavioral assessments of language, motor, vision and praxis. The surgery for removal of the tumor was carried out with the patient awake, and direct electrical stimulation mapping was used to evaluate cortical language centers. The patient developed a specific difficulty with repeating sentences toward the end of the surgery, after resection of the tumor and partial transection of the arcuate fasciculus. The patient recovered from the sentence repetition impairments over several months after the operation. Coincident with the patient's cognitive recovery, we document a pattern whereby intra-hemispheric functional connectivity was reduced in the left hemisphere, while inter-hemispheric connectivity increased between classic left hemisphere language regions and their right hemisphere homologues. These findings suggest that increased synchrony between the two hemispheres, in the setting of focal transection of the left arcuate fasciculus, can facilitate functional recovery.
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Affiliation(s)
| | - Alex Teghipco
- Department of Cognitive Sciences, University of California Irvine, USA
| | | | - Raouf Belkhir
- Department of Psychology, Carnegie Mellon University, USA
| | - Max H Sims
- Department of Neurology, University of Rochester, USA
| | - David A Paul
- Department of Neurosurgery, University of Rochester Medical Center, USA
| | - Madalina E Tivarus
- Department of Imaging Sciences, University of Rochester Medical Center, USA; Department of Neuroscience, University of Rochester Medical Center, USA
| | - Susan O Smith
- Department of Neurosurgery, University of Rochester Medical Center, USA
| | - Eric Hintz
- Department of Neurosurgery, University of Rochester Medical Center, USA
| | - Webster H Pilcher
- Department of Neurosurgery, University of Rochester Medical Center, USA
| | - Bradford Z Mahon
- Department of Psychology, Carnegie Mellon University, USA; Department of Neurology, University of Rochester, USA; Department of Neurosurgery, University of Rochester Medical Center, USA.
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Pietrelli M, Zanon M, Làdavas E, Grasso PA, Romei V, Bertini C. Posterior brain lesions selectively alter alpha oscillatory activity and predict visual performance in hemianopic patients. Cortex 2019; 121:347-361. [DOI: 10.1016/j.cortex.2019.09.008] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2019] [Revised: 07/09/2019] [Accepted: 09/20/2019] [Indexed: 10/25/2022]
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Hoshino T, Oguchi K, Inoue K, Hoshino A, Hoshiyama M. Relationship between upper limb function and functional neural connectivity among motor related-areas during recovery stage after stroke. Top Stroke Rehabil 2019; 27:57-66. [DOI: 10.1080/10749357.2019.1658429] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Takashi Hoshino
- Department of Rehabilitation, Kariya Toyota General Hospital, Kariya, Japan
- Department of Rehabilitation Sciences, Graduate School of Medicine, Nagoya University, Nagoya, Japan
| | - Kazuyo Oguchi
- Department of Rehabilitation, Kariya Toyota General Hospital, Kariya, Japan
| | - Kenji Inoue
- Department of Clinical Laboratory, Kariya Toyota General Hospital, Kariya, Japan
| | - Aiko Hoshino
- Department of Rehabilitation Sciences, Graduate School of Medicine, Nagoya University, Nagoya, Japan
| | - Minoru Hoshiyama
- Department of Rehabilitation Sciences, Graduate School of Medicine, Nagoya University, Nagoya, Japan
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Guggisberg AG, Koch PJ, Hummel FC, Buetefisch CM. Brain networks and their relevance for stroke rehabilitation. Clin Neurophysiol 2019; 130:1098-1124. [PMID: 31082786 DOI: 10.1016/j.clinph.2019.04.004] [Citation(s) in RCA: 108] [Impact Index Per Article: 21.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Revised: 03/04/2019] [Accepted: 04/08/2019] [Indexed: 12/21/2022]
Abstract
Stroke has long been regarded as focal disease with circumscribed damage leading to neurological deficits. However, advances in methods for assessing the human brain and in statistics have enabled new tools for the examination of the consequences of stroke on brain structure and function. Thereby, it has become evident that stroke has impact on the entire brain and its network properties and can therefore be considered as a network disease. The present review first gives an overview of current methodological opportunities and pitfalls for assessing stroke-induced changes and reorganization in the human brain. We then summarize principles of plasticity after stroke that have emerged from the assessment of networks. Thereby, it is shown that neurological deficits do not only arise from focal tissue damage but also from local and remote changes in white-matter tracts and in neural interactions among wide-spread networks. Similarly, plasticity and clinical improvements are associated with specific compensatory structural and functional patterns of neural network interactions. Innovative treatment approaches have started to target such network patterns to enhance recovery. Network assessments to predict treatment response and to individualize rehabilitation is a promising way to enhance specific treatment effects and overall outcome after stroke.
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Affiliation(s)
- Adrian G Guggisberg
- Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospital Geneva, Switzerland.
| | - Philipp J Koch
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), Swiss Federal Institute of Technology (EPFL), 1202 Geneva, Switzerland; Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), Swiss Federal Institute of Technology Valais (EPFL Valais), Clinique Romande de Réadaptation, 1951 Sion, Switzerland
| | - Friedhelm C Hummel
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), Swiss Federal Institute of Technology (EPFL), 1202 Geneva, Switzerland; Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), Swiss Federal Institute of Technology Valais (EPFL Valais), Clinique Romande de Réadaptation, 1951 Sion, Switzerland; Department of Clinical Neuroscience, University Hospital Geneva, 1202 Geneva, Switzerland
| | - Cathrin M Buetefisch
- Depts of Neurology, Rehabilitation Medicine, Radiology, Emory University, Atlanta, GA, USA
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Vecchio F, Caliandro P, Reale G, Miraglia F, Piludu F, Masi G, Iacovelli C, Simbolotti C, Padua L, Leone E, Alù F, Colosimo C, Rossini PM. Acute cerebellar stroke and middle cerebral artery stroke exert distinctive modifications on functional cortical connectivity: A comparative study via EEG graph theory. Clin Neurophysiol 2019; 130:997-1007. [PMID: 31005052 DOI: 10.1016/j.clinph.2019.03.017] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Revised: 02/18/2019] [Accepted: 03/13/2019] [Indexed: 01/06/2023]
Abstract
OBJECTIVE We tested whether acute cerebellar stroke may determine changes in brain network architecture as defined by cortical sources of EEG rhythms. METHODS Graph parameters of 41 consecutive stroke patients (<5 days from the event) were studied using eLORETA EEG sources. Network rearrangements of stroke patients were investigated in delta, alpha 2, beta 2 and gamma bands in comparison with healthy subjects. RESULTS The delta network remodeling was similar in cerebellar and middle cerebral artery strokes, with a reduction of small-worldness. Beta 2 and gamma small-worldness, in the right hemisphere of patients with cerebellar stroke, increase respect to healthy subjects, while alpha 2 small-worldness increases only among patients with a middle cerebral artery stroke. CONCLUSIONS The network remodeling characteristics are independent on the size of the ischemic lesion. In the early post-acute stages cerebellar stroke differs from the middle cerebral artery one because it does not cause alpha 2 network remodeling while it determines a high frequency network reorganization in beta 2 and gamma bands with an increase of small-worldness characteristics. SIGNIFICANCE These findings demonstrate changes in the balance of local segregation and global integration induced by cerebellar acute stroke in high EEG frequency bands. They need to be integrated with appropriate follow-up to explore whether further network changes are attained during post-stroke outcome stabilization.
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Affiliation(s)
- Fabrizio Vecchio
- Brain Connectivity Laboratory, IRCCS San Raffaele Pisana, Rome, Italy
| | - Pietro Caliandro
- Unità Operativa Complessa di Neurologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Giuseppe Reale
- Institute of Neurology, Area of Neuroscience, Catholic University of The Sacred Heart, Rome, Italy
| | | | - Francesca Piludu
- Department of radiologic sciences, Catholic University, Fondazione Policlincio Universitario A. Gemelli, Rome, Italy
| | - Gianvito Masi
- Institute of Neurology, Area of Neuroscience, Catholic University of The Sacred Heart, Rome, Italy
| | | | - Chiara Simbolotti
- Unità Operativa Complessa di Neurologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Luca Padua
- Unità operativa di neuroriabilitazione ad alta intensità, Fondazione Policlinico Universitario A. Gemelli. IRCCS, Roma
| | - Edoardo Leone
- Department of radiologic sciences, Catholic University, Fondazione Policlincio Universitario A. Gemelli, Rome, Italy
| | - Francesca Alù
- Brain Connectivity Laboratory, IRCCS San Raffaele Pisana, Rome, Italy
| | - Cesare Colosimo
- Department of radiologic sciences, Catholic University, Fondazione Policlincio Universitario A. Gemelli, Rome, Italy
| | - Paolo Maria Rossini
- Unità Operativa Complessa di Neurologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy; Institute of Neurology, Area of Neuroscience, Catholic University of The Sacred Heart, Rome, Italy
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Dynamics of brain connectivity after stroke. Rev Neurosci 2019; 30:605-623. [DOI: 10.1515/revneuro-2018-0082] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2018] [Accepted: 11/18/2018] [Indexed: 01/04/2023]
Abstract
Abstract
Recovery from a stroke is a dynamic time-dependent process, in which the central nervous system reorganises to accommodate for the impact of the injury. The purpose of this paper is to review recent longitudinal studies of changes in brain connectivity after stroke. A systematic review of research papers reporting functional or effective connectivity at two or more time points in stroke patients was conducted. Stroke leads to an early reduction of connectivity in the motor network. With recovery time, the connectivity increases and can reach the same levels as in healthy participants. The increase in connectivity is correlated with functional motor gains. A new, more randomised pattern of connectivity may then emerge in the longer term. In some instances, a pattern of increased connectivity even higher than in healthy controls can be observed, and is related either to a specific time point or to a specific neural structure. Rehabilitation interventions can help improve connectivity between specific regions. Moreover, motor network connectivity undergoes reorganisation during recovery from a stroke and can be related to behavioural recovery. A detailed analysis of changes in connectivity pattern may enable a better understanding of adaptation to a stroke and how compensatory mechanisms in the brain may be supported by rehabilitation.
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A systematic review investigating the relationship of electroencephalography and magnetoencephalography measurements with sensorimotor upper limb impairments after stroke. J Neurosci Methods 2018; 311:318-330. [PMID: 30118725 DOI: 10.1016/j.jneumeth.2018.08.009] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Revised: 07/17/2018] [Accepted: 08/09/2018] [Indexed: 02/03/2023]
Abstract
BACKGROUND Predicting sensorimotor upper limb outcome receives continued attention in stroke. Neurophysiological measures by electroencephalography (EEG) and magnetoencephalography (MEG) could increase the accuracy of predicting sensorimotor upper limb recovery. NEW METHOD The aim of this systematic review was to summarize the current evidence for EEG/MEG-based measures to index neural activity after stroke and the relationship between abnormal neural activity and sensorimotor upper limb impairment. Relevant papers from databases EMBASE, CINHAL, MEDLINE and pubMED were identified. Methodological quality of selected studies was assessed with the Modified Downs and Black form. Data collected was reported descriptively. RESULTS Seventeen papers were included; 13 used EEG and 4 used MEG applications. Findings showed that: (a) the presence of somatosensory evoked potentials in the acute stage are related to better outcome of upper limb motor impairment from 10 weeks to 6 months post-stroke; (b) an interhemispheric imbalance of cortical oscillatory signals associated with upper limb impairment; and (c) predictive models including beta oscillatory cortical signal factors with corticospinal integrity and clinical measures could enhance upper limb motor prognosis. COMPARING WITH EXISTING METHOD The combination of neurological biomarkers with clinical measures results in higher statistical power than using neurological biomarkers alone when predicting motor recovery in stroke. CONCLUSIONS Alterations in neural activity by means of EEG and MEG are demonstrated from the early post-stroke stage onwards, and related to sensorimotor upper limb impairment. Future work exploring cortical oscillatory signals in the acute stage could provide further insight about prediction of upper limb sensorimotor recovery.
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Mottaz A, Corbet T, Doganci N, Magnin C, Nicolo P, Schnider A, Guggisberg AG. Modulating functional connectivity after stroke with neurofeedback: Effect on motor deficits in a controlled cross-over study. NEUROIMAGE-CLINICAL 2018; 20:336-346. [PMID: 30112275 PMCID: PMC6091229 DOI: 10.1016/j.nicl.2018.07.029] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Revised: 07/13/2018] [Accepted: 07/27/2018] [Indexed: 01/03/2023]
Abstract
Synchronization of neural activity as measured with functional connectivity (FC) is increasingly used to study the neural basis of brain disease and to develop new treatment targets. However, solid evidence for a causal role of FC in disease and therapy is lacking. Here, we manipulated FC of the ipsilesional primary motor cortex in ten chronic human stroke patients through brain-computer interface technology with visual neurofeedback. We conducted a double-blind controlled crossover study to test whether manipulation of FC through neurofeedback had a behavioral effect on motor performance. Patients succeeded in increasing FC in the motor cortex. This led to improvement in motor function that was significantly greater than during neurofeedback training of a control brain area and proportional to the degree of FC enhancement. This result provides evidence that FC has a causal role in neurological function and that it can be effectively targeted with therapy. Stroke patients participated in clinical trial on neurofeedback of functional connectivity. Patients learned to enhance synchrony of neural activity in their motor cortex. This led to reduced motor impairment. Evidence for a causal role of neural synchrony in neurological deficits and recovery.
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Affiliation(s)
- Anaïs Mottaz
- Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospitals Geneva, Avenue de Beau-Séjour 26, 1211 Geneva, Switzerland
| | - Tiffany Corbet
- Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospitals Geneva, Avenue de Beau-Séjour 26, 1211 Geneva, Switzerland
| | - Naz Doganci
- Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospitals Geneva, Avenue de Beau-Séjour 26, 1211 Geneva, Switzerland
| | - Cécile Magnin
- Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospitals Geneva, Avenue de Beau-Séjour 26, 1211 Geneva, Switzerland
| | - Pierre Nicolo
- Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospitals Geneva, Avenue de Beau-Séjour 26, 1211 Geneva, Switzerland
| | - Armin Schnider
- Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospitals Geneva, Avenue de Beau-Séjour 26, 1211 Geneva, Switzerland
| | - Adrian G Guggisberg
- Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospitals Geneva, Avenue de Beau-Séjour 26, 1211 Geneva, Switzerland.
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Chao ZC, Sawada M, Isa T, Nishimura Y. Dynamic Reorganization of Motor Networks During Recovery from Partial Spinal Cord Injury in Monkeys. Cereb Cortex 2018; 29:3059-3073. [DOI: 10.1093/cercor/bhy172] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Revised: 06/28/2018] [Indexed: 11/12/2022] Open
Abstract
Abstract
After spinal cord injury (SCI), the motor-related cortical areas can be a potential substrate for functional recovery in addition to the spinal cord. However, a dynamic description of how motor cortical circuits reorganize after SCI is lacking. Here, we captured the comprehensive dynamics of motor networks across SCI in a nonhuman primate model. Using electrocorticography over the sensorimotor areas in monkeys, we collected broadband neuronal signals during a reaching-and-grasping task at different stages of recovery of dexterous finger movements after a partial SCI at the cervical levels. We identified two distinct network dynamics: grasping-related intrahemispheric interactions from the contralesional premotor cortex (PM) to the contralesional primary motor cortex (M1) in the high-γ band (>70 Hz), and motor-preparation-related interhemispheric interactions from the contralesional to ipsilesional PM in the α and low-β bands (10–15 Hz). The strengths of these networks correlated to the time course of behavioral recovery. The grasping-related network showed enhanced activation immediately after the injury, but gradually returned to normal while the strength of the motor-preparation-related network gradually increased. Our findings suggest a cortical compensatory mechanism after SCI, where two interdependent motor networks redirect activity from the contralesional hemisphere to the other hemisphere to facilitate functional recovery.
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Affiliation(s)
- Zenas C Chao
- Department of Neuroscience, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Department of Developmental Physiology, National Institute for Physiological Sciences, Okazaki, Japan
| | - Masahiro Sawada
- Department of Developmental Physiology, National Institute for Physiological Sciences, Okazaki, Japan
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tadashi Isa
- Department of Neuroscience, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Department of Developmental Physiology, National Institute for Physiological Sciences, Okazaki, Japan
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yukio Nishimura
- Department of Neuroscience, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Department of Developmental Physiology, National Institute for Physiological Sciences, Okazaki, Japan
- Neural Prosthesis Project, Department of Dementia and Higher Brain Function, Tokyo Metropolitan Institute of Medical Science, Setagaya-ku, Tokyo, Japan
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Pellicciari MC, Bonnì S, Ponzo V, Cinnera AM, Mancini M, Casula EP, Sallustio F, Paolucci S, Caltagirone C, Koch G. Dynamic reorganization of TMS-evoked activity in subcortical stroke patients. Neuroimage 2018; 175:365-378. [DOI: 10.1016/j.neuroimage.2018.04.011] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2017] [Revised: 04/04/2018] [Accepted: 04/06/2018] [Indexed: 12/21/2022] Open
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48
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Carvalho R, Azevedo E, Marques P, Dias N, Cerqueira JJ. Physiotherapy based on problem-solving in upper limb function and neuroplasticity in chronic stroke patients: A case series. J Eval Clin Pract 2018; 24:552-560. [PMID: 29691951 DOI: 10.1111/jep.12921] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2017] [Revised: 02/27/2018] [Accepted: 03/02/2018] [Indexed: 12/13/2022]
Abstract
RATIONALE, AIMS, AND OBJECTIVES Upper limb recovery is one of the main concerns of stroke neurorehabilitation. Neuroplasticity might underlie such recovery, particularly in the chronic phase. The purpose of this study was to assess the effect of physiotherapy based on problem-solving in recovering arm function in chronic stroke patients and explore its neuroplastic changes. METHODS A small sample research design with a n of 3 using a pre-post test design was carried out. Neuroplasticity and function were assessed by using functional magnetic resonance imaging (during motor imagery and performance), action research arm test, motor assessment scale, and Fugl-Meyer assessment scale, at 3 sequential time periods: baseline(m0-before a 4-week period without physiotherapy), pre-treatment(m1), and post-treatment(m2). Minimal clinical important differences and a recovery score were assessed. Assessors were blinded to moment assignment. Patients1 underwent physiotherapy sessions, 50 minutes, 5 days/week for 4 weeks. Four control subjects served as a reference for functional magnetic resonance imaging changes. RESULTS All patients recovered more than 20% after intervention. Stroke patients had similar increased areas as healthy subjects during motor execution but not during imagination at baseline. Consequently, all patients increased activity in the contralateral precentral area after intervention. CONCLUSIONS This study indicates that 4 weeks of physiotherapy promoted the recovery of arm function and neuroplasticity in all chronic stroke patients. Future research is recommended to determine the efficacy of this therapy.
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Affiliation(s)
- Raquel Carvalho
- Department of Physical Therapy, CESPU, Institute of Research and Advanced Training in Health Sciences and Technologies, Portugal.,Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, Portugal
| | - Elsa Azevedo
- Department of Neurology, Hospital São João and Faculty of Medicine of University of Porto, Portugal
| | - Paulo Marques
- Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, Portugal.,ICVS/3B's-PT Government Associate Laboratory, Braga/Guimarães, Portugal
| | - Nuno Dias
- Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, Portugal.,ICVS/3B's-PT Government Associate Laboratory, Braga/Guimarães, Portugal.,DIGARC, Polytechnic Institute of Cavado and Ave, Barcelos, Portugal
| | - João José Cerqueira
- Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, Portugal.,ICVS/3B's-PT Government Associate Laboratory, Braga/Guimarães, Portugal
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49
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Alteration and Role of Interhemispheric and Intrahemispheric Connectivity in Motor Network After Stroke. Brain Topogr 2018; 31:708-719. [DOI: 10.1007/s10548-018-0644-9] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Accepted: 04/12/2018] [Indexed: 01/25/2023]
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50
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Hordacre B, Moezzi B, Ridding MC. Neuroplasticity and network connectivity of the motor cortex following stroke: A transcranial direct current stimulation study. Hum Brain Mapp 2018; 39:3326-3339. [PMID: 29655257 DOI: 10.1002/hbm.24079] [Citation(s) in RCA: 68] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2017] [Revised: 03/25/2018] [Accepted: 03/30/2018] [Indexed: 12/11/2022] Open
Abstract
Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique that has potential for clinical utility in neurorehabilitation. However, recent evidence indicates that the responses to tDCS are highly variable. This study investigated whether electroencephalographic (EEG) measures of functional connectivity of the target network were associated with the response to ipsilesional anodal tDCS in stroke survivors. Ten chronic stroke patients attended two experimental sessions in a randomized cross-over trial and received anodal or sham tDCS. Single-pulse transcranial magnetic stimulation was used to quantify change in corticospinal excitability following tDCS. At the beginning of each session, functional connectivity was estimated using the debiased-weighted phase lag index from EEG recordings at rest. Magnetic resonance imaging identified lesion location and lesion volume. Partial least squares regression identified models of connectivity which maximally accounted for variance in anodal tDCS responses. Stronger connectivity of a network with a seed approximating the stimulated ipsilesional motor cortex, and clusters of electrodes approximating the ipsilesional parietal cortex and contralesional frontotemporal cortex in the alpha band (8-13 Hz) was strongly associated with a greater increase of corticospinal excitability following anodal tDCS. This association was not observed following sham stimulation. Addition of a structural measure(s) of injury (lesion volume) provided an improved model fit for connectivity between the seed electrode and ipsilesional parietal cortex, but not the contralesional frontotemporal cortex. TDCS has potential to greatly assist stroke rehabilitation and functional connectivity appears a robust and specific biomarker of response which may assist clinical translation of this therapy.
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Affiliation(s)
- Brenton Hordacre
- The Sansom Institute for Health Research, School of Health Sciences, The University of South Australia, Adelaide, 5001, Australia
| | - Bahar Moezzi
- The Robinson Research Institute, Adelaide Medical School, The University of Adelaide, Adelaide, 5005, Australia
| | - Michael C Ridding
- The Robinson Research Institute, Adelaide Medical School, The University of Adelaide, Adelaide, 5005, Australia
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