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Garipelli G, Rossy T, Perez-Marcos D, Jöhr J, Diserens K. Movement-Related Cortical Potentials in Embodied Virtual Mirror Visual Feedback. Front Neurol 2021; 12:646886. [PMID: 34211428 PMCID: PMC8239222 DOI: 10.3389/fneur.2021.646886] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Accepted: 05/14/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Mirror therapy is thought to drive interhemispheric communication, resulting in a balanced activation. We hypothesized that embodied virtual mirror visual feedback (VR-MVF) presented on a computer screen may produce a similar activation. In this proof-of-concept study, we investigated differences in movement-related cortical potentials (MRCPs) in the electroencephalogram (EEG) from different visual feedback of user movements in 1 stroke patient and 13 age-matched adults. Methods: A 60-year-old right-handed (Edinburgh score >95) male ischemic stroke [left paramedian pontine, National Institutes of Health Stroke Scale (NIHSS) = 6] patient and 13 age-matched right-handed (Edinburgh score >80) healthy adults (58 ± 9 years; six female) participated in the study. We recorded 16-electrode electroencephalogram (EEG), while participants performed planar center-out movements in two embodied visual feedback conditions: (i) direct (movements translated to the avatar's ipsilateral side) and (ii) mirror (movements translated to the avatar's contralateral side) with left (direct left/mirror left) or right (direct right/mirror right) arms. Results: As hypothesized, we observed more balanced MRCP hemispheric negativity in the mirror right compared to the direct right condition [statistically significant at the FC4 electrode; 99.9% CI, (0.81, 13)]. MRCPs in the stroke participant showed reduced lateralized negativity in the direct left (non-paretic) situation compared to healthy participants. Interestingly, the potentials were stronger in the mirror left (non-paretic) compared to direct left case, with significantly more bilateral negativity at FC3 [95% CI (0.758 13.2)] and C2 [95% CI (0.04 9.52)]. Conclusions: Embodied mirror visual feedback is likely to influence bilateral sensorimotor cortical subthreshold activity during movement preparation and execution observed in MRCPs in both healthy participants and a stroke patient.
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Affiliation(s)
| | - Tamara Rossy
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | | | - Jane Jöhr
- Acute Neurorehabilitation Unit, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
| | - Karin Diserens
- Acute Neurorehabilitation Unit, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
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2
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Abbasi A, Danielsen NP, Leung J, Muhammad AKMG, Patel S, Gulati T. Epidural cerebellar stimulation drives widespread neural synchrony in the intact and stroke perilesional cortex. J Neuroeng Rehabil 2021; 18:89. [PMID: 34039346 PMCID: PMC8157634 DOI: 10.1186/s12984-021-00881-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 05/19/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Cerebellar electrical stimulation has shown promise in improving motor recovery post-stroke in both rodent and human studies. Past studies have used motor evoked potentials (MEPs) to evaluate how cerebellar stimulation modulates ongoing activity in the cortex, but the underlying mechanisms are incompletely understood. Here we used invasive electrophysiological recordings from the intact and stroke-injured rodent primary motor cortex (M1) to assess how epidural cerebellar stimulation modulates neural dynamics at the level of single neurons as well as at the level of mesoscale dynamics. METHODS We recorded single unit spiking and local field potentials (LFPs) in both the intact and acutely stroke-injured M1 contralateral to the stimulated cerebellum in adult Long-Evans rats under anesthesia. We analyzed changes in the firing rates of single units, the extent of synchronous spiking and power spectral density (PSD) changes in LFPs during and post-stimulation. RESULTS Our results show that post-stimulation, the firing rates of a majority of M1 neurons changed significantly with respect to their baseline rates. These firing rate changes were diverse in character, as the firing rate of some neurons increased while others decreased. Additionally, these changes started to set in during stimulation. Furthermore, cross-correlation analysis showed a significant increase in coincident firing amongst neuronal pairs. Interestingly, this increase in synchrony was unrelated to the direction of firing rate change. We also found that neuronal ensembles derived through principal component analysis were more active post-stimulation. Lastly, these changes occurred without a significant change in the overall spectral power of LFPs post-stimulation. CONCLUSIONS Our results show that cerebellar stimulation caused significant, long-lasting changes in the activity patterns of M1 neurons by altering firing rates, boosting neural synchrony and increasing neuronal assemblies' activation strength. Our study provides evidence that cerebellar stimulation can directly modulate cortical dynamics. Since these results are present in the perilesional cortex, our data might also help explain the facilitatory effects of cerebellar stimulation post-stroke.
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Affiliation(s)
- Aamir Abbasi
- Center for Neural Science and Medicine, Departments of Biomedical Sciences and Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Nathan P Danielsen
- Center for Neural Science and Medicine, Departments of Biomedical Sciences and Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Jennifer Leung
- PhD Program in Biomedical Sciences, Graduate School of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - A K M G Muhammad
- Center for Neural Science and Medicine, Departments of Biomedical Sciences and Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Saahil Patel
- Center for Neural Science and Medicine, Departments of Biomedical Sciences and Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Tanuj Gulati
- Center for Neural Science and Medicine, Departments of Biomedical Sciences and Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA. .,Department of Medicine, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA. .,Department of Bioengineering, Henri Samueli School of Engineering, University of California-Los Angeles, Los Angeles, CA, USA.
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3
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Alder G, Signal N, Vandal AC, Olsen S, Jochumsen M, Niazi IK, Taylor D. Investigating the Intervention Parameters of Endogenous Paired Associative Stimulation (ePAS). Brain Sci 2021; 11:brainsci11020224. [PMID: 33673171 PMCID: PMC7918620 DOI: 10.3390/brainsci11020224] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 01/20/2021] [Accepted: 02/04/2021] [Indexed: 11/16/2022] Open
Abstract
Advances in our understanding of neural plasticity have prompted the emergence of neuromodulatory interventions, which modulate corticomotor excitability (CME) and hold potential for accelerating stroke recovery. Endogenous paired associative stimulation (ePAS) involves the repeated pairing of a single pulse of peripheral electrical stimulation (PES) with endogenous movement-related cortical potentials (MRCPs), which are derived from electroencephalography. However, little is known about the optimal parameters for its delivery. A factorial design with repeated measures delivered four different versions of ePAS, in which PES intensities and movement type were manipulated. Linear mixed models were employed to assess interaction effects between PES intensity (suprathreshold (Hi) and motor threshold (Lo)) and movement type (Voluntary and Imagined) on CME. ePAS interventions significantly increased CME compared to control interventions, except in the case of Lo-Voluntary ePAS. There was an overall main effect for the Hi-Voluntary ePAS intervention immediately post-intervention (p = 0.002), with a sub-additive interaction effect at 30 min’ post-intervention (p = 0.042). Hi-Imagined and Lo-Imagined ePAS significantly increased CME for 30 min post-intervention (p = 0.038 and p = 0.043 respectively). The effects of the two PES intensities were not significantly different. CME was significantly greater after performing imagined movements, compared to voluntary movements, with motor threshold PES (Lo) 15 min post-intervention (p = 0.012). This study supports previous research investigating Lo-Imagined ePAS and extends those findings by illustrating that ePAS interventions that deliver suprathreshold intensities during voluntary or imagined movements (Hi-Voluntary and Hi-Imagined) also increase CME. Importantly, our findings indicate that stimulation intensity and movement type interact in ePAS interventions. Factorial designs are an efficient way to explore the effects of manipulating the parameters of neuromodulatory interventions. Further research is required to ensure that these parameters are appropriately refined to maximise intervention efficacy for people with stroke and to support translation into clinical practice.
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Affiliation(s)
- Gemma Alder
- Health and Rehabilitation Research Institute, Auckland University of Technology, Auckland 0627, New Zealand; (N.S.); (S.O.); (I.K.N.); (D.T.)
- Correspondence:
| | - Nada Signal
- Health and Rehabilitation Research Institute, Auckland University of Technology, Auckland 0627, New Zealand; (N.S.); (S.O.); (I.K.N.); (D.T.)
| | - Alain C. Vandal
- Department of Statistics, University of Auckland, Auckland 1142, New Zealand;
- Ko Awatea, Counties Manukau Health, Auckland 2025, New Zealand
| | - Sharon Olsen
- Health and Rehabilitation Research Institute, Auckland University of Technology, Auckland 0627, New Zealand; (N.S.); (S.O.); (I.K.N.); (D.T.)
| | - Mads Jochumsen
- Department of Health Science and Technology, Aalborg University, 9000 Aalborg, Denmark;
| | - Imran Khan Niazi
- Health and Rehabilitation Research Institute, Auckland University of Technology, Auckland 0627, New Zealand; (N.S.); (S.O.); (I.K.N.); (D.T.)
- Department of Health Science and Technology, Aalborg University, 9000 Aalborg, Denmark;
- Centre for Chiropractic Research, New Zealand College of Chiropractic, Auckland 1060, New Zealand
| | - Denise Taylor
- Health and Rehabilitation Research Institute, Auckland University of Technology, Auckland 0627, New Zealand; (N.S.); (S.O.); (I.K.N.); (D.T.)
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Li H, Huang G, Lin Q, Zhao J, Fu Q, Li L, Mao Y, Wei X, Yang W, Wang B, Zhang Z, Huang D. EEG Changes in Time and Time-Frequency Domain During Movement Preparation and Execution in Stroke Patients. Front Neurosci 2020; 14:827. [PMID: 32973428 PMCID: PMC7468244 DOI: 10.3389/fnins.2020.00827] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 07/15/2020] [Indexed: 12/31/2022] Open
Abstract
This study investigated electroencephalogram (EEG) changes during movement preparation and execution in stroke patients. EEG-based event-related potential (ERP) technology was used to measure brain activity changes. Seventeen stroke patients participated in this study and completed ERP tests that were designed to measure EEG changes during unilateral upper limb movements in preparation and execution stages, with Instruction Response Movement (IRM) and Cued Instruction Response Movement (CIRM) paradigms. EEG data were analyzed using motor potential (MP) in the time domain and the mu-rhythm and beta frequency band response mean value (R-means) in the time-frequency domain. In IRM, the MP amplitude at Cz was higher during hemiplegic arm movement than during unaffected arm movement. MP latency was shorter at Cz and the contralesional motor cortex during hemiplegic arm movement in CIRM compared to IRM. No significant differences were found in R-means among locations, between movement sides in both ERP tests. This study presents the brain activity changes in the time and time-frequency domains in stroke patients during movement preparation and execution and supports the contralesional compensation and adjacent-region compensation mechanism of post-stroke brain reconstruction. These findings may contribute to future rehabilitation research about neuroplasticity and technology development such as the brain-computer interface.
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Affiliation(s)
- Hai Li
- Neurorehabilitation Laboratory, Department of Rehabilitation Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen, China.,Department of Rehabilitation Medicine, Guangdong Engineering Technology Research Center for Rehabilitation Medicine and Clinical Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Gan Huang
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Qiang Lin
- Department of Rehabilitation Medicine, Guangdong Engineering Technology Research Center for Rehabilitation Medicine and Clinical Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Rehabilitation Medicine, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jiangli Zhao
- Department of Rehabilitation Medicine, Guangdong Engineering Technology Research Center for Rehabilitation Medicine and Clinical Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Qiang Fu
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China.,Ira A. Fulton Schools of Engineering, Arizona State University, Tempe, AZ, United States
| | - Le Li
- Department of Rehabilitation Medicine, Guangdong Engineering Technology Research Center for Rehabilitation Medicine and Clinical Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yurong Mao
- Department of Rehabilitation Medicine, Guangdong Engineering Technology Research Center for Rehabilitation Medicine and Clinical Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xijun Wei
- Neurorehabilitation Laboratory, Department of Rehabilitation Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen, China
| | - Wanzhang Yang
- Neurorehabilitation Laboratory, Department of Rehabilitation Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen, China
| | - Bingshui Wang
- Neurorehabilitation Laboratory, Department of Rehabilitation Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen, China
| | - Zhiguo Zhang
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Dongfeng Huang
- Department of Rehabilitation Medicine, Guangdong Engineering Technology Research Center for Rehabilitation Medicine and Clinical Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
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5
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Hishinuma AK, Gulati T, Burish MJ, Ganguly K. Large-scale changes in cortical dynamics triggered by repetitive somatosensory electrical stimulation. J Neuroeng Rehabil 2019; 16:59. [PMID: 31126339 PMCID: PMC6534962 DOI: 10.1186/s12984-019-0520-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Accepted: 03/29/2019] [Indexed: 12/03/2022] Open
Abstract
Background Repetitive somatosensory electrical stimulation (SES) of forelimb peripheral nerves is a promising therapy; studies have shown that SES can improve motor function in stroke subjects with chronic deficits. However, little is known about how SES can directly modulate neural dynamics. Past studies using SES have primarily used noninvasive methods in human subjects. Here we used electrophysiological recordings from the rodent primary motor cortex (M1) to assess how SES affects neural dynamics at the level of single neurons as well as at the level of mesoscale dynamics. Methods We performed acute extracellular recordings in 7 intact adult Long Evans rats under ketamine-xylazine anesthesia while they received transcutaneous SES. We recorded single unit spiking and local field potentials (LFP) in the M1 contralateral to the stimulated arm. We then compared neural firing rate, spike-field coherence (SFC), and power spectral density (PSD) before and after stimulation. Results Following SES, the firing rate of a majority of neurons changed significantly from their respective baseline values. There was, however, a diversity of responses; some neurons increased while others decreased their firing rates. Interestingly, SFC, a measure of how a neuron’s firing is coupled to mesoscale oscillatory dynamics, increased specifically in the δ-band, also known as the low frequency band (0.3- 4 Hz). This increase appeared to be driven by a change in the phase-locking of broad-spiking, putative pyramidal neurons. These changes in the low frequency range occurred without a significant change in the overall PSD. Conclusions Repetitive SES significantly and persistently altered the local cortical dynamics of M1 neurons, changing both firing rates as well as the SFC magnitude in the δ-band. Thus, SES altered the neural firing and coupling to ongoing mesoscale dynamics. Our study provides evidence that SES can directly modulate cortical dynamics.
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Affiliation(s)
- April K Hishinuma
- Neurology & Rehabilitation Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA.,Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Tanuj Gulati
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.,Department of Biomedical Sciences and Neurology, Cedars-Sinai, Los Angeles, CA, USA
| | - Mark J Burish
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.,Department of Neurosurgery, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Karunesh Ganguly
- Neurology & Rehabilitation Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA. .,Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
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6
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Salyers JB. Continuous Wavelet Transform for Decoding Finger Movements From Single-Channel EEG. IEEE Trans Biomed Eng 2018; 66:1588-1597. [PMID: 30334749 DOI: 10.1109/tbme.2018.2876068] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Human body movements can be reflected in brain signals and collected noninvasively with electroencephalography (EEG). Motor-related signals include sensory motor rhythms (also known as the Mu wave) in the upper-alpha band of 8-13 Hz and slow cortical potentials (SCPs) in the low frequency range of 0.1-5 Hz. This study compares the two signals for decoding finger movements. Human subjects were asked to individually lift each of the five digits of their right hand, at the rate of one every 10 s. EEG was recorded using a bipolar montage between ipsilateral and contralateral motor cortices. Electromyograms were obtained for identifying movement onsets. Linear discriminant analysis (LDA) generated significant performance with SCPs but not with Mu. Meanwhile, continuous wavelet transform (CWT) was applied to SCPs or Mu to create a spectrogram for each finger, showing distinctive amplitude and phase patterns. A dprime-based weighting algorithm was used to extract time-frequency features. With a template-matching paradigm, both SCP and Mu spectrograms yielded significant classification accuracies for multiple subjects, with the highest being >50% (chance = 20%). Interestingly, the index finger was better distinguished with Mu for most of the subjects, whereas the ring finger was better distinguished with SCPs. The CWT algorithm outperformed LDA by better decoding the thumb. This study suggests that the time-frequency characteristics of a single-channel EEG, when phase is preserved, contain critical information on finger movements. SCPs and Mu seem to work in an independent but complementary manner.
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7
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Li H, Huang G, Lin Q, Zhao JL, Lo WLA, Mao YR, Chen L, Zhang ZG, Huang DF, Li L. Combining Movement-Related Cortical Potentials and Event-Related Desynchronization to Study Movement Preparation and Execution. Front Neurol 2018; 9:822. [PMID: 30344504 PMCID: PMC6182054 DOI: 10.3389/fneur.2018.00822] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2018] [Accepted: 09/11/2018] [Indexed: 11/23/2022] Open
Abstract
This study applied a comprehensive electroencephalography (EEG) analysis for movement-related cortical potentials (MRCPs) and event-related desynchronization (ERD) in order to understand movement-related brain activity changes during movement preparation and execution stage of unilateral wrist extension. Thirty-four healthy subjects completed two event-related potential tests in the same sequence. Unilateral wrist extension was involved in both tests as the movement task. Instruction Response Movement (IRM) was a brisk movement response task with visual “go” signal, while Cued Instruction Response Movement (CIRM) added a visual cue contenting the direction information to create a prolonged motor preparation stage. Recorded EEG data were segmented and averaged to show time domain changes and then transformed into time-frequency mapping to show the time-frequency changes. All components were calculated and compared among C3, Cz, and C4 locations. The motor potential appeared bilaterally in both tests' movement execution stages, and Cz had the largest peak value among the investigated locations (p < 0.01). In CIRM, a contingent negative variation (CNV) component presented bilaterally during the movement preparation stage with the largest amplitude at Cz. ERD of the mu rhythm (mu ERD) presented bilateral sensorimotor cortices during movement execution stages in both tests and was the smallest at Cz among the investigated locations. In the movement preparation stage of CIRM, mu ERD presented mainly in the contralateral sensory motor cortex area (C3 and C4 for right and left wrist movements, respectively) and showed significant differences between different locations. EEG changes in the time and time-frequency domains showed different topographical features. Movement execution was controlled bilaterally, while movement preparation was controlled mainly by contralateral sensorimotor cortices. Mu ERD was found to have stronger contra-lateralization features in the movement preparation stage and might be a better indicator for detecting movement intentions. This information could be helpful and might provide comprehensive information for studying movement disorders (such as those in post-stroke hemiplegic patients) or for facilitating the development of neuro-rehabilitation engineering technology such as brain computer interface.
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Affiliation(s)
- Hai Li
- Department of Rehabilitation Medicine, Guangdong Engineering Technology Research Center for Rehabilitation Medicine and Clinical Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Gan Huang
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Qiang Lin
- Department of Rehabilitation Medicine, Guangdong Engineering Technology Research Center for Rehabilitation Medicine and Clinical Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Rehabilitation Medicine, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jiang-Li Zhao
- Department of Rehabilitation Medicine, Guangdong Engineering Technology Research Center for Rehabilitation Medicine and Clinical Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Wai-Leung Ambrose Lo
- Department of Rehabilitation Medicine, Guangdong Engineering Technology Research Center for Rehabilitation Medicine and Clinical Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yu-Rong Mao
- Department of Rehabilitation Medicine, Guangdong Engineering Technology Research Center for Rehabilitation Medicine and Clinical Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Ling Chen
- Department of Rehabilitation Medicine, Guangdong Engineering Technology Research Center for Rehabilitation Medicine and Clinical Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zhi-Guo Zhang
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Dong-Feng Huang
- Department of Rehabilitation Medicine, Guangdong Engineering Technology Research Center for Rehabilitation Medicine and Clinical Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Le Li
- Department of Rehabilitation Medicine, Guangdong Engineering Technology Research Center for Rehabilitation Medicine and Clinical Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
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8
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Ramanathan DS, Guo L, Gulati T, Davidson G, Hishinuma AK, Won SJ, Knight RT, Chang EF, Swanson RA, Ganguly K. Low-frequency cortical activity is a neuromodulatory target that tracks recovery after stroke. Nat Med 2018; 24:1257-1267. [PMID: 29915259 PMCID: PMC6093781 DOI: 10.1038/s41591-018-0058-y] [Citation(s) in RCA: 72] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Accepted: 04/25/2018] [Indexed: 12/24/2022]
Abstract
Recent work has highlighted the importance of transient low-frequency oscillatory (LFO; <4 Hz) activity in the healthy primary motor cortex during skilled upper-limb tasks. These brief bouts of oscillatory activity may establish the timing or sequencing of motor actions. Here, we show that LFOs track motor recovery post-stroke and can be a physiological target for neuromodulation. In rodents, we found that reach-related LFOs, as measured in both the local field potential and the related spiking activity, were diminished after stroke and that spontaneous recovery was closely correlated with their restoration in the perilesional cortex. Sensorimotor LFOs were also diminished in a human subject with chronic disability after stroke in contrast to two non-stroke subjects who demonstrated robust LFOs. Therapeutic delivery of electrical stimulation time-locked to the expected onset of LFOs was found to significantly improve skilled reaching in stroke animals. Together, our results suggest that restoration or modulation of cortical oscillatory dynamics is important for the recovery of upper-limb function and that they may serve as a novel target for clinical neuromodulation.
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Affiliation(s)
- Dhakshin S Ramanathan
- Neurology Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
- Mental Health Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA
- Mental Health Service, VA San Diego Health System, San Diego, San Diego, CA, USA
- Department of Psychiatry, University of California, San Diego, San Diego, CA, USA
| | - Ling Guo
- Neurology Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
- Neuroscience Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Tanuj Gulati
- Neurology Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Gray Davidson
- Neurology Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
- Mental Health Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA
| | - April K Hishinuma
- Neurology Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Seok-Joon Won
- Neurology Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Robert T Knight
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
- Department of Psychology, University of California, Berkeley, Berkeley, CA, USA
| | - Edward F Chang
- Department of Neurosurgery, University of California, San Francisco, San Francisco, CA, USA
| | - Raymond A Swanson
- Neurology Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Karunesh Ganguly
- Neurology Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA.
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
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9
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Mrachacz-Kersting N, Jiang N, Stevenson AJT, Niazi IK, Kostic V, Pavlovic A, Radovanovic S, Djuric-Jovicic M, Agosta F, Dremstrup K, Farina D. Efficient neuroplasticity induction in chronic stroke patients by an associative brain-computer interface. J Neurophysiol 2015; 115:1410-21. [PMID: 26719088 DOI: 10.1152/jn.00918.2015] [Citation(s) in RCA: 147] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2015] [Accepted: 12/18/2015] [Indexed: 01/12/2023] Open
Abstract
Brain-computer interfaces (BCIs) have the potential to improve functionality in chronic stoke patients when applied over a large number of sessions. Here we evaluated the effect and the underlying mechanisms of three BCI training sessions in a double-blind sham-controlled design. The applied BCI is based on Hebbian principles of associativity that hypothesize that neural assemblies activated in a correlated manner will strengthen synaptic connections. Twenty-two chronic stroke patients were divided into two training groups. Movement-related cortical potentials (MRCPs) were detected by electroencephalography during repetitions of foot dorsiflexion. Detection triggered a single electrical stimulation of the common peroneal nerve timed so that the resulting afferent volley arrived at the peak negative phase of the MRCP (BCIassociative group) or randomly (BCInonassociative group). Fugl-Meyer motor assessment (FM), 10-m walking speed, foot and hand tapping frequency, diffusion tensor imaging (DTI) data, and the excitability of the corticospinal tract to the target muscle [tibialis anterior (TA)] were quantified. The TA motor evoked potential (MEP) increased significantly after the BCIassociative intervention, but not for the BCInonassociative group. FM scores (0.8 ± 0.46 point difference, P = 0.01), foot (but not finger) tapping frequency, and 10-m walking speed improved significantly for the BCIassociative group, indicating clinically relevant improvements. Corticospinal tract integrity on DTI did not correlate with clinical or physiological changes. For the BCI as applied here, the precise coupling between the brain command and the afferent signal was imperative for the behavioral, clinical, and neurophysiological changes reported. This association may become the driving principle for the design of BCI rehabilitation in the future. Indeed, no available BCIs can match this degree of functional improvement with such a short intervention.
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Affiliation(s)
- Natalie Mrachacz-Kersting
- Center for Sensory-Motor Interaction (SMI), Department of Health Science and Technology, Aalborg University, Aalborg, Denmark;
| | - Ning Jiang
- Department of Neurorehabilitation Engineering, Bernstein Focus Neurotechnology Göttingen, Bernstein Center for Computational Neuroscience, University Medical Center Göttingen, Georg-August University, Göttingen, Germany
| | - Andrew James Thomas Stevenson
- Center for Sensory-Motor Interaction (SMI), Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Imran Khan Niazi
- Center for Sensory-Motor Interaction (SMI), Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Vladimir Kostic
- Neurology Clinic, Clinical Center of Serbia, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Aleksandra Pavlovic
- Neurology Clinic, Clinical Center of Serbia, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Sasa Radovanovic
- Neurology Clinic, Clinical Center of Serbia, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | | | - Federica Agosta
- Neuroimaging Research Unit, Division of Neuroscience, Institute of Experimental Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Kim Dremstrup
- Center for Sensory-Motor Interaction (SMI), Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Dario Farina
- Department of Neurorehabilitation Engineering, Bernstein Focus Neurotechnology Göttingen, Bernstein Center for Computational Neuroscience, University Medical Center Göttingen, Georg-August University, Göttingen, Germany
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