Induced Gamma-Band Activity During Voluntary Movement: EEG Analysis for Clinical Purposes

Amo, Carlos; Castillo, Miguel Ortiz del; Barea, Rafael; Santiago, Luis de; Martínez-Arribas, Alejandro; Amo-Lopez, P.; Boquete, Luciano

doi:10.1123/mc.2015-0010

Cited by 10 publications

(17 citation statements)

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“…This is because the more right-handed the subject is, the greater the area of the cerebral cortex used to move the right hand as compared with the left hand [29]. The same applies for ERS values in the left hand in left-handed subjects.…”

Section: Resultsmentioning

confidence: 99%

“…The recording procedures were explained in detail in a previous publication [29]. Briefly, the experiment was comprised of two parts.…”

Section: Methodsmentioning

confidence: 99%

“…The typical method to quantify induced GBA is comprised of the following steps: (a) band pass filtering and artifact rejection; (b) computing the power spectral density for a selected frequency range; and (c) quantifying the variations in GBA that are induced by a motor task (motor GBA) in relation to basal cortical activity (basal GBA) [29]. The decreases or increases in motor GBA, in relation to the basal level, are known as event-related desynchronization (ERD) and event-related synchronization (ERS), respectively [30].…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Gamma-Band Activity from Human EEG Using Empirical Mode Decomposition

Amo

Santiago

Barea

et al. 2017

Sensors

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The purpose of this paper is to determine whether gamma-band activity detection is improved when a filter, based on empirical mode decomposition (EMD), is added to the pre-processing block of single-channel electroencephalography (EEG) signals. EMD decomposes the original signal into a finite number of intrinsic mode functions (IMFs). EEGs from 25 control subjects were registered in basal and motor activity (hand movements) using only one EEG channel. Over the basic signal, IMF signals are computed. Gamma-band activity is computed using power spectrum density in the 30–60 Hz range. Event-related synchronization (ERS) was defined as the ratio of motor and basal activity. To evaluate the performance of the new EMD based method, ERS was computed from the basic and IMF signals. The ERS obtained using IMFs improves, from 31.00% to 73.86%, on the original ERS for the right hand, and from 22.17% to 47.69% for the left hand. As EEG processing is improved, the clinical applications of gamma-band activity will expand.

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Section: Resultsmentioning

confidence: 99%

“…The recording procedures were explained in detail in a previous publication [29]. Briefly, the experiment was comprised of two parts.…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analysis of Gamma-Band Activity from Human EEG Using Empirical Mode Decomposition

Amo

Santiago

Barea

et al. 2017

Sensors

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“…Details of the methodology employed in the experiment and in acquisition and analysis of the data in the EEG recordings have been published previously [17]. In brief, each subject is seated facing a computer monitor.…”

Section: Participants and Experiments Descriptionmentioning

confidence: 99%

“…Several papers describe GBA recorded using non-invasive, low-cost and easily accessible methods such as conventional surface electroencephalograms (EEGs). The evaluation of activity in the gamma band using EEG records for actual, but not imaginary movements, was investigated in [12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Induced Gamma-Band Activity during Actual and Imaginary Movements: EEG Analysis

Usanos

Boquete

Santiago

et al. 2020

Sensors

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The purpose of this paper is to record and analyze induced gamma-band activity (GBA) (30–60 Hz) in cerebral motor areas during imaginary movement and to compare it quantitatively with activity recorded in the same areas during actual movement using a simplified electroencephalogram (EEG). Brain activity (basal activity, imaginary motor task and actual motor task) is obtained from 12 healthy volunteer subjects using an EEG (Cz channel). GBA is analyzed using the mean power spectral density (PSD) value. Event-related synchronization (ERS) is calculated from the PSD values of the basal GBA (GBAb), the GBA of the imaginary movement (GBAim) and the GBA of the actual movement (GBAac). The mean GBAim and GBAac values for the right and left hands are significantly higher than the GBAb value (p = 0.007). No significant difference is detected between mean GBA values during the imaginary and actual movement (p = 0.242). The mean ERS values for the imaginary movement (ERSimM (%) = 23.52) and for the actual movement (ERSacM = 27.47) do not present any significant difference (p = 0.117). We demonstrated that ERS could provide a useful way of indirectly checking the function of neuronal motor circuits activated by voluntary movement, both imaginary and actual. These results, as a proof of concept, could be applied to physiology studies, brain–computer interfaces, and diagnosis of cognitive or motor pathologies.

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Regression-based reconstruction of human grip force trajectories with noninvasive scalp electroencephalography

et al. 2019

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Objective. Robotic devices show promise in restoring motor abilities to individuals with upper limb paresis or amputations. However, these systems are still limited in obtaining reliable signals from the human body to effectively control them. We propose that these robotic devices can be controlled through scalp electroencephalography (EEG), a neuroimaging technique that can capture motor commands through brain rhythms. In this work, we studied if EEG can be used to predict an individual's grip forces produced by the hand. Approach. Brain rhythms and grip forces were recorded from able-bodied human subjects while they performed an isometric force production task and a grasp-and-lift task. Grip force trajectories were reconstructed with a linear model that incorporated delta band (0.1-1 Hz) voltage potentials and spectral power in the theta (4-8 Hz), alpha (8-13 Hz), beta (13-30 Hz), low gamma (30-50 Hz), mid gamma (70-110 Hz), and high gamma (130-200 Hz) bands. Trajectory reconstruction models were trained and tested through 10-fold cross validation. Main results. Modest accuracies were attained in reconstructing grip forces during isometric force production (median r = 0.42), and the grasp-and-lift task (median r = 0.51). Predicted trajectories were also analyzed further to assess the linear models' performance based on task requirements. For the isometric force production task, we found that predicted grip trajectories did not yield static grip forces that were distinguishable in magnitude across three task conditions. For the grasp-and-lift task, we estimate there would be an approximate 25% error in distinguishing when a user wants to hold or release an object. Significance. These findings indicate that EEG, a noninvasive neuroimaging modality, has predictive information in neural features associated with finger force control and can potentially contribute to the development of brain machine interfaces (BMI) for performing activities of daily living.

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Induced Gamma-Band Activity During Voluntary Movement: EEG Analysis for Clinical Purposes

Cited by 10 publications

References 0 publications

Analysis of Gamma-Band Activity from Human EEG Using Empirical Mode Decomposition

Analysis of Gamma-Band Activity from Human EEG Using Empirical Mode Decomposition

Induced Gamma-Band Activity during Actual and Imaginary Movements: EEG Analysis

Regression-based reconstruction of human grip force trajectories with noninvasive scalp electroencephalography

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