EEG topographies provide subject-specific correlates of motor control

Pirondini, Elvira; Coscia, Martina; Minguillón, Jesús; Millán, José del R.; Ville, Dimitri Van De; Micera, Silvestro

doi:10.1038/s41598-017-13482-1

Cited by 38 publications

(40 citation statements)

References 80 publications

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“…This concept has been demonstrated in a previous study using multivariate regression to model the influence of EEG frequency-band power on kinematic synergies during hand grasping (Pei et al, 2019). Another study found significant similarities between EEG microstates and muscle synergies via canonical correlation during hand reaching and grasping (Pirondini et al, 2017). To our knowledge, comparative analyses incorporating EEG and muscle synergies have not been applied to ambulation.…”

Section: Discussionmentioning

confidence: 85%

“…Significant periods of synergy activation were marked as regions that exceeded half of the maximum temporal profile after offset subtraction and overlap were visually compared between significant ERSP modulations and synergy activations at the group level. The proposed analysis makes no assumptions regarding the type of relationship between cortical signals and synergy activations as in previously described, regression-based studies (Pirondini et al, 2017;Pei et al, 2019) and is used only as a preliminary investigation.…”

Section: Synergy-ic Overlapmentioning

confidence: 99%

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Children With Unilateral Cerebral Palsy Utilize More Cortical Resources for Similar Motor Output During Treadmill Gait

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Damiano

Kim

et al. 2020

Front. Hum. Neurosci.

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Children with unilateral cerebral palsy (CP) walk independently although with an asymmetrical, more poorly coordinated pattern compared to their peers. While gait biomechanics in unilateral CP and their alteration from those without CP have been well documented, cortical mechanisms underlying gait remain inadequately understood. To the best of our knowledge, this is the first study utilizing electroencephalography (EEG) during treadmill gait in older children with and without CP. Lower limb surface electromyographic (EMG) data were collected and muscle synergy analyses performed to quantify motor output. Our primary goal was to evaluate the relationships between cortical and muscle activation within and across groups and hemispheres to provide novel insights into neural control of gait and how it may be disrupted by an early unilateral brain injury. Participants included 9 children with unilateral CP, mean age 16.0 ± 2.7 years, and 12 with typical development (TD), mean age 14.8 ± 3.0 years. EEG data were collected during a standing baseline and treadmill walking at selfselected speed. EMG of 16 lower limb muscles were also collected bilaterally and synchronized with EEG. No significant group differences were found in synergy number or structure across groups. Six cortical clusters were identified as having gait-related activation and all contained participants from both CP and TD groups; however, the percent of individuals per group appearing in different clusters varied. Notably, the cluster least represented in CP was the non-dominant motor region. Both groups showed muband ERD in the motor clusters during gait although sustained beta-band ERD was not evident in TD. The CP group showed greater cortical activation than TD during walking as measured by mu-and beta-ERD in the dominant and non-dominant motor and parietal regions and elevated low gamma-activity in the frontal and parietal areas, a unique finding in CP. CP showed greater bilateral motor EEG-EMG coherence in the gamma-band with the hallucis longus compared to TD. In summary, individuals with CP display increased cortical activation during gait possibly relating to differences in distal motor control of the more affected side. Strategies that iteratively reduce cortical activation while improving selective motor control are needed in CP.

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Section: Discussionmentioning

confidence: 85%

Section: Synergy-ic Overlapmentioning

confidence: 99%

Children With Unilateral Cerebral Palsy Utilize More Cortical Resources for Similar Motor Output During Treadmill Gait

Short

Damiano

Kim

et al. 2020

Front. Hum. Neurosci.

View full text Add to dashboard Cite

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“…The microstate G corresponds to the activation of the right inferior parietal lobe, extending to the superior temporal gyrus and also the cerebellum ( Khanna et al, 2015 ). Both areas are closely related to motor behavior ( Pirondini et al, 2017 ). Therefore, the appearance of microstate G after levodopa intake is strongly consistent with the improvement of motor symptoms.…”

Section: Discussionmentioning

confidence: 99%

EEG Microstates Change in Response to Increase in Dopaminergic Stimulation in Typical Parkinson’s Disease Patients

et al. 2018

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Objectives: Characterizing pharmacological response in Parkinson’s Disease (PD) patients may be a challenge in early stages but gives valuable clues for diagnosis. Neurotropic drugs may modulate Electroencephalography (EEG) microstates (MS). We investigated EEG-MS default-mode network changes in response to dopaminergic stimulation in PD.Methods: Fourteen PD subjects in HY stage III or less were included, and twenty-one healthy controls. All patients were receiving dopaminergic stimulation with levodopa or dopaminergic agonists. Resting EEG activity was recorded before the first daily PD medication dose and 1 h after drug intake resting EEG activity was again recorded. Time and frequency variables for each MS were calculated.Results: Parkinson’s disease subjects MS A duration decreases after levodopa intake, MS B appears more often than before levodopa intake. MS E was not present, but MS G was. There were no significant differences between control subjects and patients after medication intake.Conclusion: Clinical response to dopaminergic drugs in PD is characterized by clear changes in MS profile.Significance: This work demonstrates that there are clear EEG MS markers of PD dopaminergic stimulation state. The characterization of the disease and its response to dopaminergic medication may be of help for early therapeutic diagnosis.

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“…Hence this index has been used to detect motor imagery or to indicate motor imagery performance in brain-computer interface training for stroke recovery ( 2 , 12 ). Classification techniques such as linear discriminant analysis (LDA) and support vector machines have been adopted to identify changing topographies during natural motor behaviors ( 13 ), brain state dynamics during neurodevelopment ( 14 ) and brain features during brain-computer interface control ( 15 ). An increase in classification accuracy under the same classification model after intervention may indicate an improvement in brain state transformation ability, demonstrating that different mental states can be classified more clearly and separately after training with the same classification model used.…”

Section: Introductionmentioning

confidence: 99%

Differentiated Effects of Robot Hand Training With and Without Neural Guidance on Neuroplasticity Patterns in Chronic Stroke

et al. 2018

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Robot-assisted training combined with neural guided strategy has been increasingly applied to stroke rehabilitation. However, the induced neuroplasticity is seldom characterized. It is still uncertain whether this kind of guidance could enhance the long-term training effect for stroke motor recovery. This study was conducted to explore the clinical improvement and the neurological changes after 20-session guided or non-guided robot hand training using two measures: changes in brain discriminant ability between motor-imagery and resting states revealed from electroencephalography (EEG) signals and changes in brain network variability revealed from resting-state functional magnetic resonance imaging (fMRI) data in 24 chronic stroke subjects. The subjects were randomly assigned to receive either combined action observation (AO) with EEG-guided robot-hand training (RobotEEG_AO, n = 13) or robot-hand training without AO and EEG guidance (Robotnon−EEG_Text, n = 11). The robot hand in RobotEEG_AO group was activated only when significant mu suppression (8–12 Hz) was detected from subjects' EEG signals in ipsilesional hemisphere, while the robot hand in Robotnon−EEG_Text group was randomly activated regardless of their EEG signals. Paretic upper-limb motor functions were evaluated at three time-points: before, immediately after and 6 months after the interventions. Only RobotEEG_AO group showed a long-term significant improvement in their upper-limb motor functions while no significant and long-lasting training effect on the paretic motor functions was shown in Robotnon−EEG_Text group. Significant neuroplasticity changes were only observed in RobotEEG_AO group as well. The brain discriminant ability based on the ipsilesional EEG signals significantly improved after intervention. For brain network variability, the whole brain was first divided into six functional subnetworks, and significant increase in the temporal variability was found in four out of the six subnetworks, including sensory-motor areas, attention network, auditory network, and default mode network after intervention. Our results revealed the differences in the long-term training effect and the neuroplasticity changes following the two interventional strategies: with and without neural guidance. The findings might imply that sustainable motor function improvement could be achieved through proper neural guidance, which might provide insights into strategies for effective stroke rehabilitation. Furthermore, neuroplasticity could be promoted more profoundly by the intervention with proper neurofeedback, and might be shaped in relation to better motor skill acquisition.

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EEG topographies provide subject-specific correlates of motor control

Cited by 38 publications

References 80 publications

Children With Unilateral Cerebral Palsy Utilize More Cortical Resources for Similar Motor Output During Treadmill Gait

Children With Unilateral Cerebral Palsy Utilize More Cortical Resources for Similar Motor Output During Treadmill Gait

EEG Microstates Change in Response to Increase in Dopaminergic Stimulation in Typical Parkinson’s Disease Patients

Differentiated Effects of Robot Hand Training With and Without Neural Guidance on Neuroplasticity Patterns in Chronic Stroke

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