Performance Variation of a Somatosensory BCI Based on Imagined Sensation: A Large Population Study

Yao, Lin; Jiang, Ning; Mrachacz-Kersting, Natalie; Zhu, Xiangyang; Farina, Dario; Wang, Yueming

doi:10.1109/tnsre.2022.3198970

Cited by 18 publications

(26 citation statements)

References 63 publications

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“…In this study, we complemented the previous findings, where changes in EEG rhythms were found during TI (12,16,17), with the demonstration that TI effects on the TMS-evoked responses in the forearm and hand muscles were different from those of kMI and TS.…”

Section: Discussionsupporting

confidence: 77%

“…Unsurprisingly, TI specifically activates the primary somatosensory cortex (10,11,13,14), as well as the areas subserving the act of mentally imagery, namely the prefrontal cortex (11) and parietal cortex (15). TI-induced cortical activities can be revealed using electroencephalographic (EEG) recordings, where event related desynchronization (ERD) of the mu rhythm is the most prominent effect (12,16,17).…”

Section: Introductionmentioning

confidence: 99%

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Tactile versus Motor Imagery: Differences in Corticospinal Excitability Assessed with single-pulse TMS

Morozova,

Nasibullina,

Yakovlev

et al. 2023

Preprint

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Tactile Imagery (TI) remains a fairly understudied phenomenon despite an increased attention to this topic in recent years. Here we investigated the effects of TI on corticospinal excitability by measuring motor evoked potentials (MEPs) induced by single-pulse transcranial magnetic stimulation (TMS). The effects of TI were compared with those of tactile stimulation (TS) and kinesthetic motor imagery (kMI). Twenty two participants were asked to perform three tasks in random order: imagine finger tapping (kMI); perceive vibration sensations on the middle finger (TS); and mentally reproduce these tactile sensations (TI). We found no statistically significant difference in MEP amplitudes between baseline and TS condition, whereas both TI and kMI facilitated corticospinal excitability. MEP amplitudes during TI were significantly lower compared to MEP amplitudes during kMI condition. This finding confirms the differential effects of TI and kMI on corticospinal excitability, which has practical implications for the development of imagery-based brain-computer interfaces (BCIs), particularly the ones intended to improve neurorehabilitation by evoking plastic changes in sensorimotor circuitry.

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Section: Discussionsupporting

confidence: 77%

Section: Introductionmentioning

confidence: 99%

Tactile versus Motor Imagery: Differences in Corticospinal Excitability Assessed with single-pulse TMS

Morozova,

Nasibullina,

Yakovlev

et al. 2023

Preprint

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“…To the best of our knowledge, this is the first study to propose and validate such a BCI using compound tactile imagery. The three-class compound tactile imagery BCI in the current study showed an average accuracy of 77.74 ± 6.98%, which were comparable to the conventional two-class TI-based BCI for left vs. right hand discrimination by Yao et al [ 22 ], which demonstrated a mean classification accuracy of 78.9 ± 13.2%. Such compound TI shows promise in developing a novel paradigm where TI can be combined with MI-based BCI to expand the number of BCI inputs.…”

Section: Discussionsupporting

confidence: 71%

“…TI-based BCI classification has shown promise in improving BCI performance. A recent study on 106 healthy subjects investigated the accuracy of TI-based BCI discrimination and found 70.7% of subjects achieved a performance above 70% [ 22 ], suggesting TI as a new modality for BCI development. However, studies on TI-based BCI are few and have largely evaluated left- and right-hand discrimination [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of EEG Oscillatory Patterns and Classification of Compound Limb Tactile Imagery

et al. 2023

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Objective: The purpose of this study was to investigate the cortical activity and digit classification performance during tactile imagery (TI) of a vibratory stimulus at the index, middle, and thumb digits within the left hand in healthy individuals. Furthermore, the cortical activities and classification performance of the compound TI were compared with similar compound motor imagery (MI) with the same digits as TI in the same subjects. Methods: Twelve healthy right-handed adults with no history of upper limb injury, musculoskeletal condition, or neurological disorder participated in the study. The study evaluated the event-related desynchronization (ERD) response and brain–computer interface (BCI) classification performance on discriminating between the digits in the left-hand during the imagery of vibrotactile stimuli to either the index, middle, or thumb finger pads for TI and while performing a motor activity with the same digits for MI. A supervised machine learning technique was applied to discriminate between the digits within the same given limb for both imagery conditions. Results: Both TI and MI exhibited similar patterns of ERD in the alpha and beta bands at the index, middle, and thumb digits within the left hand. While TI had significantly lower ERD for all three digits in both bands, the classification performance of TI-based BCI (77.74 ± 6.98%) was found to be similar to the MI-based BCI (78.36 ± 5.38%). Conclusions: The results of this study suggest that compound tactile imagery can be a viable alternative to MI for BCI classification. The study contributes to the growing body of evidence supporting the use of TI in BCI applications, and future research can build on this work to explore the potential of TI-based BCI for motor rehabilitation and the control of external devices.

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“…A regular BCI system has a brain monitoring system, a signal preprocessing stage, a stage for extracting features of the preprocessed signal, and a classification stage where features are decoded into commands or messages. Some manners of BCI activation are evoked potentials, brain rhythms, and motor imagery, among others (Scherer et al, 2007 ; Yao et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Analysis of instantaneous brain interactions contribution to a motor imagery classification task

Cuervo

Saa

Solano

2022

Front. Comput. Neurosci.

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The purpose of this study is to analyze the contribution of the interactions between electrodes, measured either as correlation or as Jaccard distance, to the classification of two actions in a motor imagery paradigm, namely, left-hand movement and right-hand movement. The analysis is performed in two classifier models, namely, a static (linear discriminant analysis, LDA) model and a dynamic (hidden conditional random field, HCRF) model. The impact of using the sliding window technique (SWT) in the static and dynamic models is also analyzed. The study proved that their combination with temporal features provides significant information to improve the classification in a two-class motor imagery task for LDA (average accuracy: 0.7192 no additional features, 0.7617 by adding correlation, 0.7606 by adding Jaccard distance; p < 0.001) and HCRF (average accuracy: 0.7370 no additional features, 0.7764 by adding correlation, 0.7793 by adding Jaccard distance; p < 0.001). Also, we showed that adding interactions between electrodes improves significantly the performance of each classifier, regarding the nature of the interaction measure or the classifier itself.

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Performance Variation of a Somatosensory BCI Based on Imagined Sensation: A Large Population Study

Cited by 18 publications

References 63 publications

Tactile versus Motor Imagery: Differences in Corticospinal Excitability Assessed with single-pulse TMS

Tactile versus Motor Imagery: Differences in Corticospinal Excitability Assessed with single-pulse TMS

Evaluation of EEG Oscillatory Patterns and Classification of Compound Limb Tactile Imagery

Analysis of instantaneous brain interactions contribution to a motor imagery classification task

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