ArticleNeuroImage2014
Extracting kinetic information from human motor cortical signals.
Article in NeuroImage, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 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
40 citing papers in PubMed, 79 citations in OpenAlex.
- Trial
- Distinct Neural Modes Carry Information About Attempted Grasp Timing and Force in the Sensorimotor Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- Decoding hand kinetics and kinematics using somatosensory cortex activity in active and passive movement.iScience · 2023Article
- Quantifying Hand Strength and Isometric Pinch Individuation Using a Flexible Pressure Sensor Grid.Sensors (Basel, Switzerland) · 2023Article
- Quantitative assessments of finger individuation with an instrumented glove.Journal of neuroengineering and rehabilitation · 2023Article
- Large-scale brain networks and intra-axial tumor surgery: a narrative review of functional mapping techniques, critical needs, and scientific opportunities.Frontiers in human neuroscience · 2023Review
- Noninvasively recorded high-gamma signals improve synchrony of force feedback in a novel neurorehabilitation brain-machine interface for brain injury.Journal of neural engineering · 2022Article
- Modulation of Gamma Spectral Amplitude and Connectivity During Reaching Predicts Peak Velocity and Movement Duration.Frontiers in neuroscience · 2022Article
- A stack LSTM structure for decoding continuous force from local field potential signal of primary motor cortex (M1).BMC bioinformatics · 2021Article
- Investigating Data Cleaning Methods to Improve Performance of Brain-Computer Interfaces Based on Stereo-Electroencephalography.Frontiers in neuroscience · 2021Article
- Neural Representation of Observed, Imagined, and Attempted Grasping Force in Motor Cortex of Individuals with Chronic Tetraplegia.Scientific reports · 2020Article
- Power Modulations of ECoG Alpha/Beta and Gamma Bands Correlate With Time-Derivative of Force During Hand Grasp.Frontiers in neuroscience · 2020Article
- Refinement of High-Gamma EEG Features From TBI Patients With Hemicraniectomy Using an ICA Informed by Simulated Myoelectric Artifacts.Frontiers in neuroscience · 2020Article
- 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
- Hemicraniectomy in Traumatic Brain Injury: A Noninvasive Platform to Investigate High Gamma Activity for Brain Machine Interfaces.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2019Article
- Attempted Arm and Hand Movements can be Decoded from Low-Frequency EEG from Persons with Spinal Cord Injury.Scientific reports · 2019Article
- Brain-Machine Interfaces: Powerful Tools for Clinical Treatment and Neuroscientific Investigations.The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry · 2019Review
- Toward Electrophysiology-Based Intelligent Adaptive Deep Brain Stimulation for Movement Disorders.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2019Review
- Differential Representation of Articulatory Gestures and Phonemes in Precentral and Inferior Frontal Gyri.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 4 institutions in 2 countries.
Funding
Abstract
Brain machine interfaces (BMIs) have the potential to provide intuitive control of neuroprostheses to restore grasp to patients with paralyzed or amputated upper limbs. For these neuroprostheses to function, the ability to accurately control grasp force is critical. Grasp force can be decoded from neuronal spikes in monkeys, and hand kinematics can be decoded using electrocorticogram (ECoG) signals recorded from the surface of the human motor cortex. We hypothesized that kinetic information about grasping could also be extracted from ECoG, and sought to decode continuously-graded grasp force. In this study, we decoded isometric pinch force with high accuracy from ECoG in 10 human subjects. The predicted signals explained from 22% to 88% (60 ± 6%, mean ± SE) of the variance in the actual force generated. We also decoded muscle activity in the finger flexors, with similar accuracy to force decoding. We found that high gamma band and time domain features of the ECoG signal were most informative about kinetics, similar to our previous findings with intracortical LFPs. In addition, we found that peak cortical representations of force applied by the index and little fingers were separated by only about 4mm. Thus, ECoG can be used to decode not only kinematics, but also kinetics of movement. This is an important step toward restoring intuitively-controlled grasp to impaired patients.
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.