ReviewThe European journal of neuroscience2019
Encoding of kinetic and kinematic movement parameters in the sensorimotor cortex: A Brain-Computer Interface perspective.
Review in The European journal of neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 28 citations in OpenAlex.
- Overlap in neural representations of coordinated wrist and finger movements in human motor cortex.bioRxiv : the preprint server for biology · 2026Article
- The individuality of plantar pressure indices enables the reduction of descriptive gait data required for diagnostic purposes.Scientific reports · 2025Article
- A Generalist Intracortical Motor Decoder.bioRxiv : the preprint server for biology · 2025Article
- Editorial: Neural mechanisms of motor planning in assisted voluntary movement.Frontiers in human neuroscience · 2025Article
- Decoding the brain-machine interaction for upper limb assistive technologies: advances and challenges.Frontiers in human neuroscience · 2025Review
- Beta-band power classification of go/no-go arm-reaching responses in the human hippocampus.Journal of neural engineering · 2024Article
- Robot-Aided Motion Analysis in Neurorehabilitation: Benefits and Challenges.Diagnostics (Basel, Switzerland) · 2023Review
- Cortical processing during robot and functional electrical stimulation.Frontiers in systems neuroscience · 2023Article
- Role of path information in visual perception of joint stiffness.PLoS computational biology · 2022Article
- TDCS effects on pointing task learning in young and old adults.Scientific reports · 2021Article
- Encoding of kinetic and kinematic movement parameters in the sensorimotor cortex: A Brain-Computer Interface perspective.The European journal of neuroscience · 2019Review
- High-frequency band temporal dynamics in response to a grasp force task.Journal of neural engineering · 2019Article
- Article
- Article
- The Neural Representation of Force across Grasp Types in Motor Cortex of Humans with Tetraplegia.eNeuroArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
For severely paralyzed people, Brain-Computer Interfaces (BCIs) can potentially replace lost motor output and provide a brain-based control signal for augmentative and alternative communication devices or neuroprosthetics. Many BCIs focus on neuronal signals acquired from the hand area of the sensorimotor cortex, employing changes in the patterns of neuronal firing or spectral power associated with one or more types of hand movement. Hand and finger movement can be described by two groups of movement features, namely kinematics (spatial and motion aspects) and kinetics (muscles and forces). Despite extensive primate and human research, it is not fully understood how these features are represented in the SMC and how they lead to the appropriate movement. Yet, the available information may provide insight into which features are most suitable for BCI control. To that purpose, the current paper provides an in-depth review on the movement features encoded in the SMC. Even though there is no consensus on how exactly the SMC generates movement, we conclude that some parameters are well represented in the SMC and can be accurately used for BCI control with discrete as well as continuous feedback. However, the vast evidence also suggests that movement should be interpreted as a combination of multiple parameters rather than isolated ones, pleading for further exploration of sensorimotor control models for accurate BCI control.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.