Dataset Information

Quantifying the alignment error and the effect of incomplete somatosensory feedback on motor performance in a virtual brain-computer-interface setup.

ABSTRACT: Invasive brain-computer-interfaces (BCIs) aim to improve severely paralyzed patient's (e.g. tetraplegics) quality of life by using decoded movement intentions to let them interact with robotic limbs. We argue that the performance in controlling an end-effector using a BCI depends on three major factors: decoding error, missing somatosensory feedback and alignment error caused by translation and/or rotation of the end-effector relative to the real or perceived body. Using a virtual reality (VR) model of an ideal BCI decoder with healthy participants, we found that a significant performance loss might be attributed solely to the alignment error. We used a shape-drawing task to investigate and quantify the effects of robot arm misalignment on motor performance independent from the other error sources. We found that a 90° rotation of the robot arm relative to the participant leads to the worst performance, while we did not find a significant difference between a 45° rotation and no rotation. Additionally, we compared a group of subjects with indirect haptic feedback with a group without indirect haptic feedback to investigate the feedback-error. In the group without feedback, we found a significant difference in performance only when no rotation was applied to the robot arm, supporting that a form of haptic feedback is another important factor to be considered in BCI control.

SUBMITTER: Lienkamper R

PROVIDER: S-EPMC7907076 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Quantifying the alignment error and the effect of incomplete somatosensory feedback on motor performance in a virtual brain-computer-interface setup.

Lienkämper Robin R Dyck Susanne S Saif-Ur-Rehman Muhammad M Metzler Marita M Ali Omair O Klaes Christian C

Scientific reports 20210225 1

Invasive brain-computer-interfaces (BCIs) aim to improve severely paralyzed patient's (e.g. tetraplegics) quality of life by using decoded movement intentions to let them interact with robotic limbs. We argue that the performance in controlling an end-effector using a BCI depends on three major factors: decoding error, missing somatosensory feedback and alignment error caused by translation and/or rotation of the end-effector relative to the real or perceived body. Using a virtual reality (VR) m ...[more]

PMID: 33633302

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Project description:Background and purposeFor rehabilitation strategies to be effective, training should be based on principles of motor learning, such as feedback-error learning, that facilitate adaptive processes in the nervous system by inducing errors and recalibration of sensory and motor systems. This case report suggests that locomotor resistance training can enhance somatosensory and corticospinal excitability and modulate resting-state brain functional connectivity in a patient with motor-incomplete spinal cord injury (SCI).Case descriptionThe short-term cortical plasticity of a 31-year-old man who had sustained an incomplete SCI 9.5 years previously was explored in response to body-weight-supported treadmill training with velocity-dependent resistance applied with a robotic gait orthosis. The following neurophysiological and neuroimaging measures were recorded before and after training. Sensory evoked potentials were elicited by electrical stimulation of the tibial nerve and recorded from the somatosensory cortex. Motor evoked potentials were generated with transcranial magnetic stimulation applied over the tibialis anterior muscle representation in the primary motor cortex. Resting-state functional magnetic resonance imaging was performed to evaluate short-term changes in patterns of brain activity associated with locomotor training.OutcomesSomatosensory excitability and corticospinal excitability were observed to increase after locomotor resistance training. Motor evoked potentials increased (particularly at higher stimulation intensities), and seed-based resting-state functional magnetic resonance imaging analyses revealed increased functional connectivity strength in the motor cortex associated with the less affected side after training.DiscussionThe observations suggest evidence of short-term cortical plasticity in 3 complementary neurophysiological measures after one session of locomotor resistance training. Future investigation in a sample of people with incomplete SCI will enhance the understanding of potential neural mechanisms underlying the behavioral response to locomotor resistance training.

Project description:Brain-computer interfaces (BCIs) benefit greatly from performance feedback, but current systems lack automatic, task-independent feedback. Cortical responses elicited from user error have the potential to serve as state-based feedback to BCI decoders. To gain a better understanding of local error potentials, we investigate responsive cortical power underlying error-related potentials (ErrPs) from the human cortex during a one-dimensional center-out BCI task, tracking the topography of high-gamma (70-100 Hz) band power (HBP) specific to BCI error. We measured electrocorticography (ECoG) in three human subjects during dynamic, continuous control over BCI cursor velocity. Subjects used motor imagery and rest to move the cursor toward and subsequently dwell within a target region. We then identified and labeled epochs where the BCI decoder incorrectly moved the cursor in the direction opposite of the subject's expectations (i.e., BCI error). We found increased HBP in various cortical areas 100-500 ms following BCI error with respect to epochs of correct, intended control. Significant responses were noted in primary somatosensory, motor, premotor, and parietal areas and generally regardless of whether the subject was using motor imagery or rest to move the cursor toward the target. Parts of somatosensory, temporal, and parietal areas exclusively had increased HBP when subjects were using motor imagery. In contrast, only part of the parietal cortex near the angular gyrus exclusively had an increase in HBP during rest. This investigation is, to our knowledge, the first to explore cortical fields changes in the context of continuous control in ECoG BCI. We present topographical changes in HBP characteristic specific to the generation of error. By focusing on continuous control, instead of on discrete control for simple selection, we investigate a more naturalistic setting and provide high ecological validity for characterizing error potentials. Such potentials could be considered as design elements for co-adaptive BCIs in the future as task-independent feedback to the decoder, allowing for more robust and individualized BCIs.

Dataset Information

Quantifying the alignment error and the effect of incomplete somatosensory feedback on motor performance in a virtual brain-computer-interface setup.

Publications

Quantifying the alignment error and the effect of incomplete somatosensory feedback on motor performance in a virtual brain-computer-interface setup.

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