Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Protein-protein Interfaces02:04

Protein-protein Interfaces

14.8K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
14.8K
Protein-Protein Interfaces02:04

Protein-Protein Interfaces

4.5K
4.5K
Nuclear Stability03:18

Nuclear Stability

23.4K
Protons and neutrons, collectively called nucleons, are packed together tightly in a nucleus. With a radius of about 10−15 meters, a nucleus is quite small compared to the radius of the entire atom, which is about 10−10 meters. Nuclei are extremely dense compared to bulk matter, averaging 1.8 × 1014 grams per cubic centimeter. If the earth’s density were equal to the average nuclear density, the earth’s radius would be only about 200 meters.
To hold positively charged protons together...
23.4K
RNA Stability01:53

RNA Stability

35.8K
Intact DNA strands can be found in fossils, while scientists sometimes struggle to keep RNA intact under laboratory conditions. The structural variations between RNA and DNA underlie the differences in their stability and longevity. Because DNA is double-stranded, it is inherently more stable. The single-stranded structure of RNA is less stable but also more flexible and can form weak internal bonds. Additionally, most RNAs in the cell are relatively short, while DNA can be up to 250 million...
35.8K
Stability01:28

Stability

425
The time response of a linear time-invariant (LTI) system can be divided into transient and steady-state responses. The transient response represents the system's initial reaction to a change in input and diminishes to zero over time. In contrast, the steady-state response is the behavior that persists after the transient effects have faded.
The stability of an LTI system is determined by the roots of its characteristic equation, known as poles. A system is stable if it produces a bounded...
425
Stability of structures01:14

Stability of structures

532
In mechanical engineering, the stability of systems under various forces is critical for designing durable and efficient structures. One fundamental way to explore these concepts is by analyzing systems like two rods connected at a pivot point, O, with a torsional spring of spring constant k at the pivot point. This system is similar in appearance to a scissor jack used to change tires on a car. In this case, the arms of the linkage (equivalent to the rods in this system) are entirely vertical,...
532

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A mosaic of whole-body representations on the human precentral gyrus.

Nature·2026
Same author

Closed-loop error damping in human BCI using pre-error motor cortex activity.

bioRxiv : the preprint server for biology·2026
Same author

Limb state accounts for differences between motor imagery and action in motor cortex.

medRxiv : the preprint server for health sciences·2026
Same author

Finding the groove in neural space.

medRxiv : the preprint server for health sciences·2026
Same author

In vivo microelectrode arrays for neuroscience.

Nature reviews. Methods primers·2026
Same author

Mapping the Causal Roles of Non-Primary Motor Areas in Human Reach Planning and Execution.

Human brain mapping·2026
Same journal

Cortex-anchored sensor-space harmonics for event-related EEG.

Journal of neural engineering·2026
Same journal

Neural mechanisms of mixed speech and grasp representation in sensorimotor cortices.

Journal of neural engineering·2026
Same journal

Developing a binary communication protocol between biological neural networks using virtual white matter.

Journal of neural engineering·2026
Same journal

Spatiotemporally distinctive astrocytic and neuronal responses to repetitive intracortical microstimulation.

Journal of neural engineering·2026
Same journal

A neural mass modelling framework for evaluating EEG source localisation of seizure activity.

Journal of neural engineering·2026
Same journal

Functional and effective connectivity methods from SEEG for characterizing epileptogenic networks in refractory epilepsy: a comprehensive review and future directions.

Journal of neural engineering·2026
See all related articles

Related Experiment Video

Updated: Feb 13, 2026

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
06:09

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation

Published on: September 8, 2023

967

Intracortical recording stability in human brain-computer interface users.

John E Downey1,2,3,4, Nathaniel Schwed1,2, Steven M Chase3,5

  • 1Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, United States of America.

Journal of Neural Engineering
|March 20, 2018
PubMed
Summary
This summary is machine-generated.

Neural recordings for brain-computer interfaces (BCIs) can be unstable. This study found that neuron signal stability in the motor cortex varies, but waveform features can predict long-term unit consistency for improved BCI performance.

More Related Videos

Chronic Transcranial Electrical Stimulation and Intracortical Recording in Rats
10:51

Chronic Transcranial Electrical Stimulation and Intracortical Recording in Rats

Published on: May 11, 2018

9.3K
A Graphical User Interface for Software-assisted Tracking of Protein Concentration in Dynamic Cellular Protrusions
08:12

A Graphical User Interface for Software-assisted Tracking of Protein Concentration in Dynamic Cellular Protrusions

Published on: July 11, 2017

7.8K

Related Experiment Videos

Last Updated: Feb 13, 2026

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
06:09

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation

Published on: September 8, 2023

967
Chronic Transcranial Electrical Stimulation and Intracortical Recording in Rats
10:51

Chronic Transcranial Electrical Stimulation and Intracortical Recording in Rats

Published on: May 11, 2018

9.3K
A Graphical User Interface for Software-assisted Tracking of Protein Concentration in Dynamic Cellular Protrusions
08:12

A Graphical User Interface for Software-assisted Tracking of Protein Concentration in Dynamic Cellular Protrusions

Published on: July 11, 2017

7.8K

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Rehabilitation Technology

Background:

  • Intracortical brain-computer interfaces (BCIs) are crucial for restoring communication and interaction for individuals with motor disabilities.
  • BCI performance relies on stable neural recordings from the primary motor cortex, which are known to fluctuate daily.

Purpose of the Study:

  • To quantify the duration of stable neuronal recordings from the motor cortex in long-term BCI users.
  • To identify predictors of neuronal unit stability for enhancing BCI reliability.

Main Methods:

  • Action potentials from individual neurons (units) were recorded extracellularly in two long-term BCI subjects.
  • Neuronal signals were identified by their extracellular waveforms.
  • Waveform features were analyzed to predict the stability of recorded units over time.

Main Results:

  • Identified neuronal units exhibited variable stability, with some remaining consistent for weeks to months.
  • Extracellular waveform characteristics were found to predict the likelihood of a unit's prolonged stability.
  • Signal instability can occur within a single day, while some units show remarkable long-term consistency.

Conclusions:

  • Understanding neuronal unit stability is vital for developing robust motor BCIs.
  • Predicting unit stability using waveform features can help maintain high BCI performance despite neural signal fluctuations.
  • Improved BCI stability will enable longer periods of autonomous operation, maximizing benefits for users.