EEG-based Classification of Lower Limb Motor Imagery with Brain Network Analysis

Gu, Lingjia; Yu, Zhenhua; Ma, Tian; Wang, Haixian; Li, Zhanli; Fan, Hui

doi:10.1016/j.neuroscience.2020.04.006

Cited by 58 publications

(64 citation statements)

References 62 publications

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“…That is why connectivity between motor and sensory cortical areas represents a mechanistic explanation for how holistic imagery performance can be achieved. In agreement with these considerations, online feedback dependency on connectivity estimates during task performance (equivalent to post-stimulus connectivity) has recently been shown to enhance BCI classification (Gu et al, 2020).…”

Section: Discussionmentioning

confidence: 71%

Sensorimotor Functional Connectivity: A Neurophysiological Factor Related to BCI Performance

et al. 2020

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Brain-Computer Interfaces (BCIs) are systems that allow users to control devices using brain activity alone. However, the ability of participants to command BCIs varies from subject to subject. About 20% of potential users of sensorimotor BCIs do not gain reliable control of the system. The inefficiency to decode user's intentions requires the identification of neurophysiological factors determining “good” and “poor” BCI performers. One of the important neurophysiological aspects in BCI research is that the neuronal oscillations, used to control these systems, show a rich repertoire of spatial sensorimotor interactions. Considering this, we hypothesized that neuronal connectivity in sensorimotor areas would define BCI performance. Analyses for this study were performed on a large dataset of 80 inexperienced participants. They took part in a calibration and an online feedback session recorded on the same day. Undirected functional connectivity was computed over sensorimotor areas by means of the imaginary part of coherency. The results show that post- as well as pre-stimulus connectivity in the calibration recording is significantly correlated to online feedback performance in μ and feedback frequency bands. Importantly, the significance of the correlation between connectivity and BCI feedback accuracy was not due to the signal-to-noise ratio of the oscillations in the corresponding post and pre-stimulus intervals. Thus, this study demonstrates that BCI performance is not only dependent on the amplitude of sensorimotor oscillations as shown previously, but that it also relates to sensorimotor connectivity measured during the preceding training session. The presence of such connectivity between motor and somatosensory systems is likely to facilitate motor imagery, which in turn is associated with the generation of a more pronounced modulation of sensorimotor oscillations (manifested in ERD/ERS) required for the adequate BCI performance. We also discuss strategies for the up-regulation of such connectivity in order to enhance BCI performance.

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Section: Discussionmentioning

confidence: 71%

Sensorimotor Functional Connectivity: A Neurophysiological Factor Related to BCI Performance

et al. 2020

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“…Contrary to studies reported on somatotopic unilateral or bilateral forward (i.e., prefrontal and/or frontal) and backward (i.e., parietal) activations when participants were instructed to perform MI tasks of the right or left hand (Li et al, 2019 ; Alanis-Espinosa and Gutiérrez, 2020 ) and the left or right foot (Gu et al, 2020 ), the current investigation did not report somatotopic motor and/or somesthetic activations, i.e., motor and/or somesthetic representations of the upper and lower limbs. The inconsistencies between our results and the above-mentioned findings could be understood from a methodological point of view.…”

Section: Discussionmentioning

confidence: 76%

“…Open issues exist with regard to the neural involvement of the primary motor cortex in MI tasks, but studies have shown that the engagement of fingers, toes, and tongue leads to the activation of different subdivisions of the primary motor cortex together with the premotor cortex (Ehrsson et al, 2003 ). The premotor cortex and primary somatosensory area have demonstrated significant connections of unilateral left and right foot imagery movements in healthy participants (Gu et al, 2020 ). It was also proposed that regardless of the effector related to the observed movement, i.e., toe, finger, or tongue, the somatotopic organization reflecting the sensory homunculus would be engaged (Penfield and Baldrey, 1937 ; Penfield and Rasmussen, 1950 ; Stippich et al, 2002 ).…”

Section: Introductionmentioning

confidence: 99%

Neural Kinesthetic Contribution to Motor Imagery of Body Parts: Tongue, Hands, and Feet

Giannopulu

Mizutani

2021

Front. Hum. Neurosci.

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Motor imagery (MI) is assimilated to a perception-action process, which is mentally represented. Although several models suggest that MI, and its equivalent motor execution, engage very similar brain areas, the mechanisms underlying MI and their associated components are still under investigation today. Using 22 Ag/AgCl EEG electrodes, 19 healthy participants (nine males and 10 females) with an average age of 25.8 years old (sd = 3.5 years) were required to imagine moving several parts of their body (i.e., first-person perspective) one by one: left and right hand, tongue, and feet. Network connectivity analysis based on graph theory, together with a correlational analysis, were performed on the data. The findings suggest evidence for motor and somesthetic neural synchronization and underline the role of the parietofrontal network for the tongue imagery task only. At both unilateral and bilateral cortical levels, only the tongue imagery task appears to be associated with motor and somatosensory representations, that is, kinesthetic representations, which might contribute to verbal actions. As such, the present findings suggest the idea that imagined tongue movements, involving segmentary kinesthetic actions, could be the prerequisite of language.

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“…Online feedback dependency on connectivity estimates during task performance (equivalent to post-stimulus connectivity) has recently been shown to enhance BCI classification (Gu et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Sensorimotor functional connectivity: a neurophysiological factor related to BCI performance

Vidaurre

Haufe

Jorajuría

et al. 2020

Preprint

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Brain-Computer Interfaces (BCIs) are systems that allow users to control devices using brain activity alone. However, the ability of participants to command BCIs varies from subject to subject. For BCIs based on the modulation of sensorimotor rhythms as measured by means of electroen-cephalography (EEG), about 20% of potential users do not obtain enough accuracy to gain reliable control of the system. This lack of efficiency of BCI systems to decode user’s intentions requires the identification of neuro-physiological factors determining ‘good’ and ‘poor’ BCI performers. Given that the neuronal oscillations, used in BCI, demonstrate rich a repertoire of spatial interactions, we hypothesized that neuronal activity in sensorimotor areas would define some aspects of BCI performance. Analyses for this study were performed on a large dataset of 80 inexperienced participants. They took part in calibration and an online feedback session in the same day. Undirected functional connectivity was computed over sensorimotor areas by means of the imaginary part of coherency. The results show that post-as well as pre-stimulus connectivity in the calibration recordings is significantly correlated to online feedback performance in μ and feedback frequency bands. Importantly, the significance of the correlation between connectivity and BCI feedback accuracy was not due to the signal-to-noise ratio of the oscillations in the corresponding post and pre-stimulus intervals. Thus, this study shows that BCI performance is not only dependent on the amplitude of sensorimotor oscillations as shown previously, but that it also relates to sensorimotor connectivity measured during the preceding training session. The presence of such connectivity between motor and somatosensory systems is likely to facilitate motor imagery, which in turn is associated with the generation of a more pronounced modulation of sen-sorimotor oscillations (manifested in ERD/ERS) required for the adequate BCI performance. We also discuss strategies for the up-regulation of such connectivity in order to enhance BCI performance.

show abstract

EEG-based Classification of Lower Limb Motor Imagery with Brain Network Analysis

Cited by 58 publications

References 62 publications

Sensorimotor Functional Connectivity: A Neurophysiological Factor Related to BCI Performance

Sensorimotor Functional Connectivity: A Neurophysiological Factor Related to BCI Performance

Neural Kinesthetic Contribution to Motor Imagery of Body Parts: Tongue, Hands, and Feet

Sensorimotor functional connectivity: a neurophysiological factor related to BCI performance

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