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

Pressure Variation in a Fluid at Rest01:11

Pressure Variation in a Fluid at Rest

773
In a fluid at rest, the pressure at any point beneath the fluid surface depends solely on the depth, not on the container's shape or size. This principle, known as hydrostatic pressure, arises because, in stationary fluids, there is no acceleration, meaning the forces within the fluid balance out. Only vertical forces, caused by the weight of the fluid above, contribute to pressure changes with depth.
When measuring pressure at two different levels within the fluid, the difference in...
773
Spontaneity02:21

Spontaneity

29.0K
A spontaneous process is one that occurs naturally under certain conditions. A nonspontaneous process, on the other hand, will not take place unless it is “driven” by the continual input of energy from an external source. Processes have a natural tendency to occur in one direction under a given set of conditions. Water will naturally flow downhill (spontaneous process), but uphill flow (nonspontaneous process) requires outside intervention such as the use of a pump. Iron exposed to...
29.0K
What is Variation?01:14

What is Variation?

17.6K
Apart from the measures of central tendency, distribution, outliers, and the changing characteristics of data with time, an important characteristic of any data set is its variation or spread. In some data sets, the data values are concentrated closely near the mean; in others, the data values are more widely spread out from the mean.
The range, standard deviation, standard error, and variance are the different measures of variation.
Range: The range is the difference between its maximum and...
17.6K
The Resting Membrane Potential01:21

The Resting Membrane Potential

142.1K
Overview
142.1K
Resting Membrane Potential01:24

Resting Membrane Potential

21.5K
The relative difference in electrical charge, or voltage, between the inside and the outside of a cell membrane, is called the membrane potential. It is generated by differences in permeability of the membrane to various ions and the concentrations of these ions across the membrane.
The Inside of a Neuron is More Negative
The membrane potential of a cell can be measured by inserting a microelectrode into a cell and comparing the charge to a reference electrode in the extracellular fluid. The...
21.5K
Variation01:19

Variation

7.8K
An important characteristic of any set of data is the variation in the data. In some data sets, the data values are concentrated closely near the mean; in other data sets, the data values are more widely spread out from the mean. The most common measure of variation, or spread, is the standard deviation, which is the square root of variance.
When independent and dependent variables are plotted on a scatter plot, the slope of a line is a value that describes the rate of change between the two...
7.8K

You might also read

Related Articles

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

Sort by
Same author

Letter to the editor regarding "Electrophysiological monitoring of the trigeminal nerve sensory root using sensory-masseter response for microvascular decompression in trigeminal neuralgia".

Acta neurochirurgica·2026
Same author

Preoperative embolization in intracranial meningioma surgery: An updated systematic review and meta-analysis.

Surgical neurology international·2026
Same author

Letter to the Editor Regarding Early Postoperative Hypesthesia After Microvascular Decompression for Trigeminal Neuralgia is a Predictor of Long-Term Pain Relief: A Long-Term Cohort Study.

World neurosurgery·2026
Same author

AI at the Sella Turcica: Multi-Model Large Language Model Evaluation in Pituitary Adenomas.

Brain & spine·2026
Same author

Letter to the Editor. Responsible integration of AI in microsurgical training.

Journal of neurosurgery·2026
Same author

Hemispherectomy in infants: an institutional experience with 21 patients.

Journal of neurosurgery. Pediatrics·2026

Related Experiment Video

Updated: Jan 26, 2026

Electrocorticographic Recording of Cerebral Cortex Areas Manipulated Using an Adeno-Associated Virus Targeting Cofilin in Mice
08:44

Electrocorticographic Recording of Cerebral Cortex Areas Manipulated Using an Adeno-Associated Virus Targeting Cofilin in Mice

Published on: February 21, 2021

4.8K

Spontaneous Variation in Electrocorticographic Resting-State Connectivity.

Kaitlyn Casimo1, Tara M Madhyastha2, Andrew L Ko3

  • 11 Graduate Program in Neuroscience, Center for Neurotechnology, University of Washington, Seattle, Washington.

Brain Connectivity
|April 20, 2019
PubMed
Summary

Electrocorticography (ECoG) reveals that strong phase locking and amplitude correlation in resting-state functional connectivity are linked to stability. This study provides insights into brain network dynamics and intersession variability.

Keywords:
electrocorticographyspontaneous variationssynchrony

More Related Videos

Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy
07:13

Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy

Published on: May 27, 2020

7.1K
Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity
10:43

Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity

Published on: July 1, 2014

15.7K

Related Experiment Videos

Last Updated: Jan 26, 2026

Electrocorticographic Recording of Cerebral Cortex Areas Manipulated Using an Adeno-Associated Virus Targeting Cofilin in Mice
08:44

Electrocorticographic Recording of Cerebral Cortex Areas Manipulated Using an Adeno-Associated Virus Targeting Cofilin in Mice

Published on: February 21, 2021

4.8K
Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy
07:13

Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy

Published on: May 27, 2020

7.1K
Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity
10:43

Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity

Published on: July 1, 2014

15.7K

Area of Science:

  • Neuroscience
  • Systems Neuroscience
  • Computational Neuroscience

Background:

  • Previous research utilized fMRI, EEG, and MEG to study resting-state functional connectivity (rsFC) and its spontaneous variations.
  • These modalities have limitations in spatial resolution and frequency range for capturing detailed neural dynamics.

Purpose of the Study:

  • To characterize spontaneous, intersession variation in rsFC using electrocorticography (ECoG), a method with high spatial and temporal resolution.
  • To investigate the relationship between different connectivity measures (PLV, amplitude correlation, coherence) and the longitudinal stability of brain networks.

Main Methods:

  • ECoG data was analyzed for pairwise electrode connectivity using phase locking value (PLV), amplitude correlation, and coherence across six frequency bands.
  • Electrodes were grouped into 10 functional regions, and intraclass correlation (ICC) was used to assess longitudinal stability.
  • Connectivity patterns were examined within and between specific brain regions, including the parahippocampal/entorhinal cortex, dorsolateral prefrontal cortex, and inferior parietal lobule.

Main Results:

  • Stronger PLV (≥0.4) in theta to gamma bands and high amplitude correlation (R² ≥0.6) across all bands correlated with substantial stability (ICC ≥0.6).
  • Within-region PLVs demonstrated marked stability across all frequencies, while dorsolateral prefrontal cortex connectivity was generally weak and unstable.
  • The study confirmed links between functional connectivity strength and intersession variability, extending findings to higher frequencies and offering greater spatial specificity than scalp electrophysiology.

Conclusions:

  • Resting-state functional connectivity strength, particularly via PLV and amplitude correlation, is a key predictor of network stability.
  • ECoG offers a valuable tool for studying brain network dynamics with high resolution, providing a baseline for future research on task- or disease-related perturbations.
  • Findings highlight region-specific connectivity patterns and stability, informing our understanding of brain organization and function.