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Gopalakrishnan R, Cunningham DA, Hogue O, Schroedel M, Campbell BA, Baker KB, Machado AG. Electrophysiological Correlates of Dentate Nucleus Deep Brain Stimulation for Poststroke Motor Recovery. J Neurosci 2024; 44:e2149232024. [PMID: 38724284 PMCID: PMC11223455 DOI: 10.1523/jneurosci.2149-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 04/23/2024] [Accepted: 04/24/2024] [Indexed: 07/05/2024] Open
Abstract
While ipsilesional cortical electroencephalography has been associated with poststroke recovery mechanisms and outcomes, the role of the cerebellum and its interaction with the ipsilesional cortex is still largely unknown. We have previously shown that poststroke motor control relies on increased corticocerebellar coherence (CCC) in the low beta band to maintain motor task accuracy and to compensate for decreased excitability of the ipsilesional cortex. We now extend our work to investigate corticocerebellar network changes associated with chronic stimulation of the dentato-thalamo-cortical pathway aimed at promoting poststroke motor rehabilitation. We investigated the excitability of the ipsilesional cortex, the dentate (DN), and their interaction as a function of treatment outcome measures. Relative to baseline, 10 human participants (two women) at the end of 4-8 months of DN deep brain stimulation (DBS) showed (1) significantly improved motor control indexed by computerized motor tasks; (2) significant increase in ipsilesional premotor cortex event-related desynchronization that correlated with improvements in motor function; and (3) significant decrease in CCC, including causal interactions between the DN and ipsilesional cortex, which also correlated with motor function improvements. Furthermore, we show that the functional state of the DN in the poststroke state and its connectivity with the ipsilesional cortex were predictive of motor outcomes associated with DN-DBS. The findings suggest that as participants recovered, the ipsilesional cortex became more involved in motor control, with less demand on the cerebellum to support task planning and execution. Our data provide unique mechanistic insights into the functional state of corticocerebellar-cortical network after stroke and its modulation by DN-DBS.
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Affiliation(s)
- Raghavan Gopalakrishnan
- Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, Ohio 44195
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio 44195
- Cleveland FES Center, Cleveland, Ohio 44106
| | - David A Cunningham
- Cleveland FES Center, Cleveland, Ohio 44106
- Physical Medicine and Rehabilitation, Case Western Reserve University School of Medicine, Cleveland, Ohio 44106
- Center for Rehabilitation Research, MetroHealth Systems, Cleveland, Ohio 44109
| | - Olivia Hogue
- Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, Ohio 44195
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio 44195
| | - Madeleine Schroedel
- Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, Ohio 44195
| | - Brett A Campbell
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio 44195
| | - Kenneth B Baker
- Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, Ohio 44195
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio 44195
| | - Andre G Machado
- Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, Ohio 44195
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio 44195
- Department of Neurosurgery, Neurological Institute, Cleveland Clinic, Cleveland, Ohio 44195
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Mark JI, Riddle J, Gangwani R, Huang B, Fröhlich F, Cassidy JM. Cross-Frequency Coupling as a Biomarker for Early Stroke Recovery. Neurorehabil Neural Repair 2024; 38:506-517. [PMID: 38842027 PMCID: PMC11179969 DOI: 10.1177/15459683241257523] [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] [Indexed: 06/07/2024]
Abstract
BACKGROUND The application of neuroimaging-based biomarkers in stroke has enriched our understanding of post-stroke recovery mechanisms, including alterations in functional connectivity based on synchronous oscillatory activity across various cortical regions. Phase-amplitude coupling, a type of cross-frequency coupling, may provide additional mechanistic insight. OBJECTIVE To determine how the phase of prefrontal cortex delta (1-3 Hz) oscillatory activity mediates the amplitude of motor cortex beta (13-20 Hz) oscillations in individual's early post-stroke. METHODS Participants admitted to an inpatient rehabilitation facility completed resting and task-based EEG recordings and motor assessments around the time of admission and discharge along with structural neuroimaging. Unimpaired controls completed EEG procedures during a single visit. Mixed-effects linear models were performed to assess within- and between-group differences in delta-beta prefrontomotor coupling. Associations between coupling and motor status and injury were also determined. RESULTS Thirty individuals with stroke and 17 unimpaired controls participated. Coupling was greater during task versus rest conditions for all participants. Though coupling during affected extremity task performance decreased during hospitalization, coupling remained elevated at discharge compared to controls. Greater baseline coupling was associated with better motor status at admission and discharge and positively related to motor recovery. Coupling demonstrated both positive and negative associations with injury involving measures of lesion volume and overlap injury to anterior thalamic radiation, respectively. CONCLUSIONS This work highlights the utility of prefrontomotor cross-frequency coupling as a potential motor status and recovery biomarker in stroke. The frequency- and region-specific neurocircuitry featured in this work may also facilitate novel treatment strategies in stroke.
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Affiliation(s)
- Jasper I. Mark
- Human Movement Science Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Health Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Justin Riddle
- Department of Psychology, Florida State University, Tallahassee, FL, USA
| | - Rachana Gangwani
- Human Movement Science Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Health Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Benjamin Huang
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Flavio Fröhlich
- Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jessica M. Cassidy
- Department of Health Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Yu P, Dong R, Wang X, Tang Y, Liu Y, Wang C, Zhao L. Neuroimaging of motor recovery after ischemic stroke - functional reorganization of motor network. Neuroimage Clin 2024; 43:103636. [PMID: 38950504 DOI: 10.1016/j.nicl.2024.103636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2024] [Revised: 06/01/2024] [Accepted: 06/27/2024] [Indexed: 07/03/2024]
Abstract
The long-term motor outcome of acute stroke patients may be correlated to the reorganization of brain motor network. Abundant neuroimaging studies contribute to understand the pathological changes and recovery of motor networks after stroke. In this review, we summarized how current neuroimaging studies have increased understanding of reorganization and plasticity in post stroke motor recovery. Firstly, we discussed the changes in the motor network over time during the motor-activation and resting states, as well as the overall functional integration trend of the motor network. These studies indicate that the motor network undergoes dynamic bilateral hemispheric functional reorganization, as well as a trend towards network randomization. In the second part, we summarized the current study progress in the application of neuroimaging technology to early predict the post-stroke motor outcome. In the third part, we discuss the neuroimaging techniques commonly used in the post-stroke recovery. These methods provide direct or indirect visualization patterns to understand the neural mechanisms of post-stroke motor recovery, opening up new avenues for studying spontaneous and treatment-induced recovery and plasticity after stroke.
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Affiliation(s)
- Pei Yu
- School of Acupuncture and Massage, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Ruoyu Dong
- Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine, Beijing, China
| | - Xiao Wang
- School of Acupuncture and Massage, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Yuqi Tang
- School of Acupuncture and Massage, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Yaning Liu
- School of Acupuncture and Massage, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Can Wang
- School of Acupuncture and Massage, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Ling Zhao
- School of Acupuncture and Massage, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
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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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Li M, Zou F, Zheng T, Zou W, Li H, Lin Y, Peng L, Zheng S. Electroacupuncture alters brain network functional connectivity in subacute stroke: A randomised crossover trial. Medicine (Baltimore) 2024; 103:e37686. [PMID: 38579054 PMCID: PMC10994512 DOI: 10.1097/md.0000000000037686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 03/01/2024] [Indexed: 04/07/2024] Open
Abstract
BACKGROUND Electroacupuncture (EA) is a promising rehabilitation treatment for upper-limb motor recovery in stroke patients. However, the neurophysiological mechanisms underlying its clinical efficacy remain unclear. This study aimed to explore the immediate modulatory effects of EA on brain network functional connectivity and topological properties. METHODS The randomized, single-blinded, self-controlled two-period crossover trial was conducted among 52 patients with subacute subcortical stroke. These patients were randomly allocated to receive either EA as the initial intervention or sham electroacupuncture (SEA) as the initial intervention. After a washout period of 24 hours, participants underwent the alternate intervention (SEA or EA). Resting state electroencephalography signals were recorded synchronously throughout both phases of the intervention. The functional connectivity (FC) of the parietofrontal network and small-world (SW) property indices of the whole-brain network were compared across the entire course of the two interventions. RESULTS The results demonstrated that EA significantly altered ipsilesional parietofrontal network connectivity in the alpha and beta bands (alpha: F = 5.05, P = .011; beta: F = 3.295, P = .047), whereas no significant changes were observed in the SEA group. When comparing between groups, EA significantly downregulated ipsilesional parietofrontal network connectivity in both the alpha and beta bands during stimulation (alpha: t = -1.998, P = .049; beta: t = -2.342, P = .022). Significant differences were also observed in the main effects of time and the group × time interaction for the SW index (time: F = 5.516, P = .026; group × time: F = 6.892, P = .01). In terms of between-group comparisons, the EA group exhibited a significantly higher SW index than the SEA group at the post-stimulation stage (t = 2.379, P = .018). CONCLUSION These findings suggest that EA downregulates ipsilesional parietofrontal network connectivity and enhances SW properties, providing a potential neurophysiological mechanism for facilitating motor performance in stroke patients.
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Affiliation(s)
- Mingfen Li
- Taihe Hospital, Hubei University of Medicine, Shiyan, China
- College of Acupuncture and Orthopedics, Hubei University of Chinese Medicine, Wuhan, China
| | - Fei Zou
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Tingting Zheng
- Taihe Hospital, Hubei University of Medicine, Shiyan, China
| | - Weigeng Zou
- Taihe Hospital, Hubei University of Medicine, Shiyan, China
| | - Haifeng Li
- Taihe Hospital, Hubei University of Medicine, Shiyan, China
| | - Yifang Lin
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Li Peng
- College of Acupuncture and Orthopedics, Hubei University of Chinese Medicine, Wuhan, China
| | - Su Zheng
- Taihe Hospital, Hubei University of Medicine, Shiyan, China
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Lassi M, Dalise S, Bandini A, Spina V, Azzollini V, Vissani M, Micera S, Mazzoni A, Chisari C. Neurophysiological underpinnings of an intensive protocol for upper limb motor recovery in subacute and chronic stroke patients. Eur J Phys Rehabil Med 2024; 60:13-26. [PMID: 37987741 DOI: 10.23736/s1973-9087.23.07922-4] [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: 11/22/2023]
Abstract
BACKGROUND Upper limb (UL) motor impairment following stroke is a leading cause of functional limitations in activities of daily living. Robot-assisted therapy supports rehabilitation, but how its efficacy and the underlying neural mechanisms depend on the time after stroke is yet to be assessed. AIM We investigated the response to an intensive protocol of robot-assisted rehabilitation in sub-acute and chronic stroke patients, by analyzing the underlying changes in clinical scores, electroencephalography (EEG) and end-effector kinematics. We aimed at identifying neural correlates of the participants' upper limb motor function recovery, following an intensive 2-week rehabilitation protocol. DESIGN Prospective cohort study. SETTING Inpatients and outpatients from the Neurorehabilitation Unit of Pisa University Hospital, Italy. POPULATION Sub-acute and chronic stroke survivors. METHODS Thirty-one stroke survivors (14 sub-acute, 17 chronic) with mild-to-moderate UL paresis were enrolled. All participants underwent ten rehabilitative sessions of task-oriented exercises with a planar end-effector robotic device. All patients were evaluated with the Fugl-Meyer Assessment Scale and the Wolf Motor Function Test, at recruitment (T0), end-of-treatment (T1), and one-month follow-up (T2). Along with clinical scales, kinematic parameters and quantitative EEG were collected for each patient. Kinematics metrics were related to velocity, acceleration and smoothness of the movement. Relative power in four frequency bands was extracted from the EEG signals. The evolution over time of kinematic and EEG features was analyzed, in correlation with motor recovery. RESULTS Both groups displayed significant gains in motility after treatment. Sub-acute patients displayed more pronounced clinical improvements, significant changes in kinematic parameters, and a larger increase in Beta-band in the motor area of the affected hemisphere. In both groups these improvements were associated to a decrease in the Delta-band of both hemispheres. Improvements were retained at T2. CONCLUSIONS The intensive two-week rehabilitation protocol was effective in both chronic and sub-acute patients, and improvements in the two groups shared similar dynamics. However, stronger cortical and behavioral changes were observed in sub-acute patients suggesting different reorganizational patterns. CLINICAL REHABILITATION IMPACT This study paves the way to personalized approaches to UL motor rehabilitation after stroke, as highlighted by different neurophysiological modifications following recovery in subacute and chronic stroke patients.
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Affiliation(s)
- Michael Lassi
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Stefania Dalise
- Neurorehabilitation Unit, Pisa University Hospital, Pisa, Italy
| | - Andrea Bandini
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
- Health Science Interdisciplinary Research Center, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Vincenzo Spina
- Neurorehabilitation Unit, Pisa University Hospital, Pisa, Italy
| | | | - Matteo Vissani
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
- Harvard Medical School, Boston, MA, USA
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Silvestro Micera
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
- Bertarelli Foundation Chair in Translational Neural Engineering, Center for Neuroprosthetics and Institute of Bioengineering, École Polytechnique Fèdèrale de Lausanne, Lausanne, Switzerland
| | - Alberto Mazzoni
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Carmelo Chisari
- Neurorehabilitation Unit, Pisa University Hospital, Pisa, Italy -
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Ti CHE, Hu C, Yuan K, Chu WCW, Tong RKY. Uncovering the Neural Mechanisms of Inter-Hemispheric Balance Restoration in Chronic Stroke Through EMG-Driven Robot Hand Training: Insights From Dynamic Causal Modeling. IEEE Trans Neural Syst Rehabil Eng 2024; 32:1-11. [PMID: 38051622 DOI: 10.1109/tnsre.2023.3339756] [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: 12/07/2023]
Abstract
EMG-driven robot hand training can facilitate motor recovery in chronic stroke patients by restoring the interhemispheric balance between motor networks. However, the underlying mechanisms of reorganization between interhemispheric regions remain unclear. This study investigated the effective connectivity (EC) between the ventral premotor cortex (PMv), supplementary motor area (SMA), and primary motor cortex (M1) using Dynamic Causal Modeling (DCM) during motor tasks with the paretic hand. Nineteen chronic stroke subjects underwent 20 sessions of EMG-driven robot hand training, and their Action Reach Arm Test (ARAT) showed significant improvement ( β =3.56, [Formula: see text]). The improvement was correlated with the reduction of inhibitory coupling from the contralesional M1 to the ipsilesional M1 (r=0.58, p=0.014). An increase in the laterality index was only observed in homotopic M1, but not in the premotor area. Additionally, we identified an increase in resting-state functional connectivity (FC) between bilateral M1 ( β =0.11, p=0.01). Inter-M1 FC demonstrated marginal positive relationships with ARAT scores (r=0.402, p=0.110), but its changes did not correlate with ARAT improvements. These findings suggest that the improvement of hand functions brought about by EMG-driven robot hand training was driven explicitly by task-specific reorganization of motor networks. Particularly, the restoration of interhemispheric balance was induced by a reduction in interhemispheric inhibition from the contralesional M1 during motor tasks of the paretic hand. This finding sheds light on the mechanistic understanding of interhemispheric balance and functional recovery induced by EMG-driven robot training.
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Zeng G, Zhou Y, Yang Y, Ruan L, Tan L, Luo H, Ruan J. Neural oscillations after acute large artery atherosclerotic cerebral infarction during resting state and sleep spindles. J Sleep Res 2023; 32:e13889. [PMID: 36944554 DOI: 10.1111/jsr.13889] [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: 12/14/2022] [Revised: 03/01/2023] [Accepted: 03/07/2023] [Indexed: 03/23/2023]
Abstract
Electroencephalogram-microstate analysis was conducted using low-resolution electromagnetic tomography (LORETA)-KEY to evaluate dynamic brain network changes in patients with acute large artery atherosclerotic cerebral infarction (LAACI) during the rest and sleep stages. This study included 35 age- and sex-matched healthy controls and 34 patients with acute LAACI. Each participant performed a 3-h, 19-channel video electroencephalogram test. Subsequently, 20 epochs of 2-s sleep spindles during stage N2 sleep and five epochs of 10-s electroencephalogram data in the resting state for each participant were obtained. In both the resting state and sleep spindles, patients with LAACI displayed altered neural oscillations. The parameters of microstate A (coverage, occurrence, and duration) increased during the resting state in the patients with LAACI compared with healthy controls. The coverage and occurrence of microstate B and D were reduced in the LAACI group compared with the healthy controls (p < 0.05). Moreover, during sleep spindles, the duration of microstate A and the transition probability from microstate A and B to C decreased, but the coverage of microstate B and the transition rate from microstate B to D increased (p < 0.05) in the LAACI group compared with the healthy controls. These results enable better understanding of how neural oscillations are modified in patients with LAACI during the resting state and sleep spindles. Following LAACI, the dynamic brain network undergoes changes during sleep spindles and the resting state. Continued long-term investigations are required to determine how well these changes in brain dynamics reflect the clinical characteristics of patients with LAACI.
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Affiliation(s)
- Guoli Zeng
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Department of Neurology, Luzhou People's Hospital, Luzhou, China
| | - Yan Zhou
- Department of Neurology, Jianyang People's Hospital, Jianyang, China
| | - Yushu Yang
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Laboratory of Neurological Diseases and Brain Function, Luzhou, China
| | - Lili Ruan
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Laboratory of Neurological Diseases and Brain Function, Luzhou, China
| | - Linjie Tan
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Laboratory of Neurological Diseases and Brain Function, Luzhou, China
| | - Hua Luo
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Laboratory of Neurological Diseases and Brain Function, Luzhou, China
| | - Jianghai Ruan
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- Laboratory of Neurological Diseases and Brain Function, Luzhou, China
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Reibelt A, Quandt F, Schulz R. Posterior parietal cortical areas and recovery after motor stroke: a scoping review. Brain Commun 2023; 5:fcad250. [PMID: 37810465 PMCID: PMC10551853 DOI: 10.1093/braincomms/fcad250] [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: 05/24/2023] [Revised: 08/25/2023] [Accepted: 09/25/2023] [Indexed: 10/10/2023] Open
Abstract
Brain imaging and electrophysiology have significantly enhanced our current understanding of stroke-related changes in brain structure and function and their implications for recovery processes. In the motor domain, most studies have focused on key motor areas of the frontal lobe including the primary and secondary motor cortices. Time- and recovery-dependent alterations in regional anatomy, brain activity and inter-regional connectivity have been related to recovery. In contrast, the involvement of posterior parietal cortical areas in stroke recovery is poorly understood although these regions are similarly important for important aspects of motor functioning in the healthy brain. Just in recent years, the field has increasingly started to explore to what extent posterior parietal cortical areas might undergo equivalent changes in task-related activation, regional brain structure and inter-regional functional and structural connectivity after stroke. The aim of this scoping review is to give an update on available data covering these aspects and thereby providing novel insights into parieto-frontal interactions for systems neuroscience stroke recovery research in the upper limb motor domain.
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Affiliation(s)
- Antonia Reibelt
- Experimental Electrophysiology and Neuroimaging Lab, Department of Neurology, University Medical Center Hamburg Eppendorf, 20246 Hamburg, Germany
| | - Fanny Quandt
- Experimental Electrophysiology and Neuroimaging Lab, Department of Neurology, University Medical Center Hamburg Eppendorf, 20246 Hamburg, Germany
| | - Robert Schulz
- Experimental Electrophysiology and Neuroimaging Lab, Department of Neurology, University Medical Center Hamburg Eppendorf, 20246 Hamburg, Germany
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Li M, Zheng S, Zou W, Li H, Wang C, Peng L. Electroencephalography-based parietofrontal connectivity modulated by electroacupuncture for predicting upper limb motor recovery in subacute stroke. Medicine (Baltimore) 2023; 102:e34886. [PMID: 37682180 PMCID: PMC10489200 DOI: 10.1097/md.0000000000034886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 08/02/2023] [Indexed: 09/09/2023] Open
Abstract
BACKGROUND Predicting motor recovery in stroke patients is essential for effective rehabilitation planning and goal setting. However, intervention-specific biomarkers for such predictions are limited. This study investigates the potential of electroacupuncture (EA) - induced brain network connectivity as a prognostic biomarker for upper limb motor recovery in stroke. METHODS A randomized crossover and prospective observational study was conducted involving 40 stroke patients within 30 days of onset. Patients underwent both EA and sham electroacupuncture (SEA) interventions. Simultaneously, resting electroencephalography signals were recorded to assess brain response. Patients' motor function was monitored for 3 months and categorized into Poor and proportional (Prop) recovery groups. The correlations between the targeted brain network of parietofrontal (PF) functional connectivity (FC) during the different courses of the 2 EA interventions and partial least squares regression models were constructed to predict upper limb motor recovery. RESULTS Before the EA intervention, only ipsilesional PF network FC in the beta band correlated with motor recovery (r = -0.37, P = .041). Post-EA intervention, significant correlations with motor recovery were found in the beta band of the contralesional PF network FC (r = -0.43, P = .018) and the delta and theta bands of the ipsilesional PF network FC (delta: r = -0.59, P = .0004; theta: r = -0.45, P = .0157). No significant correlations were observed for the SEA intervention (all P > .05). Specifically, the delta band ipsilesional PF network FC after EA stimulation significantly differed between Poor and Prop groups (t = 3.474, P = .002, Cohen's d = 1.287, Poor > Prop). Moreover, the partial least squares regression model fitted after EA stimulation exhibited high explanatory power (R2 = 0.613), predictive value (Q2 = 0.547), and the lowest root mean square error (RMSE = 0.192) for predicting upper limb proportional recovery compared to SEA. CONCLUSION EA-induced PF network FC holds potential as a robust prognostic biomarker for upper limb motor recovery, providing valuable insights for clinical decision-making.
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Affiliation(s)
- Mingfen Li
- College of Acupuncture and Orthopedics, Hubei University of Chinese Medicine, Wuhan City, China
- Taihe Hospital, Hubei University of Medicine, Shiyan City, China
| | - Su Zheng
- Taihe Hospital, Hubei University of Medicine, Shiyan City, China
| | - Weigeng Zou
- Taihe Hospital, Hubei University of Medicine, Shiyan City, China
| | - Haifeng Li
- Taihe Hospital, Hubei University of Medicine, Shiyan City, China
| | - Chan Wang
- Taihe Hospital, Hubei University of Medicine, Shiyan City, China
| | - Li Peng
- College of Acupuncture and Orthopedics, Hubei University of Chinese Medicine, Wuhan City, China
- Shiyan Hospital of Traditional Chinese Medicine, Hubei University of Chinese Medicine, Shiyan City, China
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Stroke-Related Alterations in the Brain's Functional Connectivity Response Associated with Upper Limb Multi-Joint Linkage Movement. Brain Sci 2023; 13:brainsci13020338. [PMID: 36831881 PMCID: PMC9954203 DOI: 10.3390/brainsci13020338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 02/01/2023] [Accepted: 02/14/2023] [Indexed: 02/18/2023] Open
Abstract
Stroke is one of the primary causes of motor disorders, which can seriously affect the patient's quality of life. However, the assessment of the upper limb affected by stroke is commonly based on scales, and the characteristics of brain reorganization induced by limb movement are not clear. Thus, this study aimed to investigate stroke-related cortical reorganization based on functional near infrared spectroscopy (fNIRS) during upper limb multi-joint linkage movement with reference to the Fugl-Meyer Assessment of the upper extremities (FMA-UE). In total, 15 stroke patients and 15 healthy subjects participated in this study. The functional connectivity (FC) between channels and the regions of interest (ROI) was calculated by Pearson's correlation coefficient. The results showed that compared with the control group, the FC between the prefrontal cortex and the motor cortex was significantly increased in the resting state and the affected upper limb's multi-joint linkage movements, while the FC between the motor cortex was significantly decreased during the unaffected upper limb's multi-joint linkage movements. Moreover, the significantly increased ROI FC in the resting state showed a significantly positive correlation with FMA-UE in stroke patients (p < 0.05). This study highlights a new biomarker for evaluating the function of movement in stroke patients and provides guidance for rehabilitation training.
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Milani G, Antonioni A, Baroni A, Malerba P, Straudi S. Relation Between EEG Measures and Upper Limb Motor Recovery in Stroke Patients: A Scoping Review. Brain Topogr 2022; 35:651-666. [PMID: 36136166 DOI: 10.1007/s10548-022-00915-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 09/04/2022] [Indexed: 11/25/2022]
Abstract
Current clinical practice does not leverage electroencephalography (EEG) measurements in stroke patients, despite its potential to contribute to post-stroke recovery predictions. We review the literature on the effectiveness of various quantitative and qualitative EEG-based measures after stroke as a tool to predict upper limb motor outcome, in relation to stroke timeframe and applied experimental tasks. Moreover, we aim to provide guidance on the use of EEG in the assessment of upper limb motor recovery after stroke, suggesting a high potential for some metrics in the appropriate context. We identified relevant papers (N = 16) from databases ScienceDirect, Web of Science and MEDLINE, and assessed their methodological quality with the Joanna Briggs Institute (JBI) Critical Appraisal. We applied the Preferred Reporting Systems for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) Framework. Identified works used EEG to identify properties including event-related activation, spectral power in physiologically relevant bands, symmetry in brain dynamics, functional connectivity, cortico-muscular coherence and rhythmic coordination. EEG was acquired in resting state or in relation to behavioural conditions. Motor outcome was mainly evaluated with the Upper Limb Fugl-Meyer Assessment. Despite great variability in the literature, data suggests that the most promising EEG quantifiers for predicting post-stroke motor outcome are event-related measures. Measures of spectral power in physiologically relevant bands and measures of brain symmetry also show promise. We suggest that EEG measures may improve our understanding of stroke brain dynamics during recovery, and contribute to establishing a functional prognosis and choosing the rehabilitation approach.
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Affiliation(s)
- Giada Milani
- IIT@Unife Center for Translational Neurophysiology, Istituto Italiano di Tecnologia, Ferrara, Italy.,Department of Neuroscience and Rehabilitation, Ferrara University Hospital, Ferrara, Italy
| | - Annibale Antonioni
- Unit of Clinical Neurology, Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara, Italy
| | - Andrea Baroni
- Department of Neuroscience and Rehabilitation, Ferrara University Hospital, Ferrara, Italy
| | - Paola Malerba
- Battelle Center for Mathematical Medicine and Center for Biobehavioral Health, The Ohio State University, Columbus, OH, USA
| | - Sofia Straudi
- Department of Neuroscience and Rehabilitation, Ferrara University Hospital, Ferrara, Italy. .,Department of Neuroscience and Rehabilitation, University of Ferrara, Via Luigi Borsari 46, 44121, Ferrara, Italy.
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Borras M, Romero S, Alonso JF, Bachiller A, Serna LY, Migliorelli C, Mananas MA. Influence of the number of trials on evoked motor cortical activity in EEG recordings. J Neural Eng 2022; 19. [PMID: 35926471 DOI: 10.1088/1741-2552/ac86f5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 08/04/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Improvements in electroencephalography enable the study of the localization of active brain regions during motor tasks. Movement-related cortical potentials (MRCPs), and event-related desynchronization (ERD) and synchronization (ERS) are the main motor-related cortical phenomena/neural correlates observed when a movement is elicited. When assessing neurological diseases, averaging techniques are commonly applied to characterize motor related processes better. In this case, a large number of trials is required to obtain a motor potential that is representative enough of the subject's condition. This study aimed to assess the effect of a limited number of trials on motor-related activity corresponding to different upper limb movements (elbow flexion/extension, pronation/supination and hand open/close). APPROACH An open dataset consisting on 15 healthy subjects was used for the analysis. A Monte Carlo simulation approach was applied to analyse, in a robust way, different typical time- and frequency-domain features, topography, and low-resolution tomography (LORETA). MAIN RESULTS Grand average potentials, and topographic and tomographic maps showed few differences when using fewer trials, but shifts in the localization of motor-related activity were found for several individuals. MRCP and beta ERD features were more robust to a limited number of trials, yielding differences lower than 20% for cases with 50 trials or more. Strong correlations between features were obtained for subsets above 50 trials. However, the inter-subject variability increased as the number of trials decreased. The elbow flexion/extension movement showed a more robust performance for a limited number of trials, both in population and in individual-based analysis. SIGNIFICANCE Our findings suggested that 50 trials can be an appropriate number to obtain stable motor-related features in terms of differences in the averaged motor features, correlation, and changes in topography and tomography.
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Affiliation(s)
- Marta Borras
- Eng. Sistemes. Automàtica i inf. ind., Universitat Politècnica de Catalunya, Campus Diagonal Sud. Edifici U. C. Pau Gargallo, 5. 08028 Barcelona, Barcelona, 08034, SPAIN
| | - Sergio Romero
- Automatic Control Department (ESAII), Universitat Politecnica de Catalunya, Barcelona, Barcelona, Catalunya, 08034, SPAIN
| | - Joan F Alonso
- Universitat Politècnica de Catalunya, Campus Diagonal Sud. Edifici U. C. Pau Gargallo, 5, Barcelona, Catalunya, 08034, SPAIN
| | - Alejandro Bachiller
- Automatic Control Department, Universitat Politècnica de Catalunya, EDIFICI H, AVDA. DIAGONAL, 647, Office 4.26, Barcelona, Catalunya, 08034, SPAIN
| | - Leidy Y Serna
- Eng. Sistemes. Automàtica i inf. ind., Universitat Politècnica de Catalunya, Campus Diagonal Sud. Edifici U. C. Pau Gargallo, 5. 08028 Barcelona, Barcelona, 08034, SPAIN
| | - Carolina Migliorelli
- Unit of Digital Health, Eurecat Centre Tecnològic de Catalunya, Av. Universitat Autònoma, 23 - 08290 Cerdanyola del Vallès (Barcelona), Barcelona, Catalunya, 08290, SPAIN
| | - Miguel A Mananas
- Departamento de Ingeniería de Sistemas, Universitat Politècnica de Catalunya, Campus Diagonal Sud. Edifici U. C. Pau Gargallo, 5., Barcelona, Catalunya, 08034, SPAIN
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Patel J, Pattison I, Glassen M, Saleh S, Qiu Q, Fluet GG, Kaplan E, Tunik E, Nolan K, Merians AS, Adamovich SV. EEG Based Resting State Connectivity Changes in the Motor Cortex Associated with Upper Limb Motor Recovery in the Subacute Period Post-Stroke. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:4801-4804. [PMID: 36086133 DOI: 10.1109/embc48229.2022.9870886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Stroke is a heterogeneous condition that would benefit from valid biomarkers of recovery for research and in the clinic. We evaluated the change in resting state connectivity (RSC) via electroencephalography (EEG) in motor areas, as well as motor recovery of the affected upper limb, in the subacute phase post-stroke. Fifteen participants who had sustained a subcortical stroke were included in this study. The group made significant gains in upper limb impairment as measured by the Upper Extremity Fugl-Meyer Assessment (UEFMA) from baseline to four months post-stroke (24.78 (SD 5.4)). During this time, there was a significant increase in RSC in the beta band from contralesional M1 to ipsilesional M1. We propose that this change in RSC may have contributed to the motor recovery seen in this group. Clinical Relevance- This study evaluates resting state connectivity measured via EEG as a neural biomarker of recovery post-stroke. Biomarkers can help clinicians understand the potential for recovery after stroke and thus help them to establish therapy goals and determine treatment plans.
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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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Cassidy JM, Mark JI, Cramer SC. Functional connectivity drives stroke recovery: shifting the paradigm from correlation to causation. Brain 2021; 145:1211-1228. [PMID: 34932786 DOI: 10.1093/brain/awab469] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [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 behavioral 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: [1] Strength, [2] Consistency [3] Specificity, [4] Temporality, [5] Biological gradient, [6] Plausibility, [7] Coherence, [8] Experiment, and [9] 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 magnetic resonance imaging, electroencephalography, magnetoencephalography, and functional near-infrared spectroscopy in describing and predicting post-stroke behavioral 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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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: 12] [Impact Index Per Article: 4.0] [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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