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

Kinetic Molecular Theory and Gas Laws Explain Properties of Gas Molecules02:34

Kinetic Molecular Theory and Gas Laws Explain Properties of Gas Molecules

37.3K
The test of the kinetic molecular theory (KMT) and its postulates is its ability to explain and describe the behavior of a gas. The various gas laws (Boyle’s, Charles’s, Gay-Lussac’s, Avogadro’s, and Dalton’s laws) can be derived from the assumptions of the KMT, which have led chemists to believe that the assumptions of the theory accurately represent the properties of gas molecules.
37.3K
Second Law of Thermodynamics02:49

Second Law of Thermodynamics

26.7K
In the quest to identify a property that may reliably predict the spontaneity of a process, a promising candidate has been identified: entropy. Processes that involve an increase in entropy of the system (ΔS > 0) are very often spontaneous; however, examples to the contrary are plentiful. By expanding consideration of entropy changes to include the surroundings, a significant conclusion regarding the relation between this property and spontaneity may be reached. In thermodynamic models, the...
26.7K
Second Law of Thermodynamics00:53

Second Law of Thermodynamics

68.0K
The Second Law of Thermodynamics states that entropy, or the amount of disorder in a system, increases each time energy is transferred or transformed. Each energy transfer results in a certain amount of energy that is lost—usually in the form of heat—that increases the disorder of the surroundings. This can also be demonstrated in a classic food web. Herbivores harvest chemical energy from plants and release heat and carbon dioxide into the environment. Carnivores harvest the...
68.0K
Scientific Laws and Theories02:31

Scientific Laws and Theories

87.5K
Scientific Laws
87.5K
First Law of Thermodynamics02:16

First Law of Thermodynamics

40.4K
Energy Conservation
40.4K
First Law of Thermodynamics00:37

First Law of Thermodynamics

80.4K
The First Law of Thermodynamics states that energy cannot be created or destroyed, only transformed. This can be demonstrated within a classic food web where light energy from the sun is harnessed as radiant energy by plants, converted into chemical energy, and stored as complex carbohydrates. The vegetation is then consumed by animals and during the digestion process, the sugars release energy as heat. The sugars also produce chemical energy that either gets used up doing work, stored in...
80.4K

You might also read

Related Articles

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

Sort by
Same author

Rhythms and Background (RnB): The Spectroscopy of Sleep Recordings.

eNeuro·2026
Same author

Pre-attentive Pitch Processing of Harmonic Complex Sounds at Sensor and Source Levels: Comparing Simultaneously Recorded EEG and MEG Data.

Brain topography·2025
Same author

sEEG-Suite: An Interactive Pipeline for Semi-Automated Contact Localization and Anatomical Labeling with Brainstorm.

bioRxiv : the preprint server for biology·2025
Same author

Interictal waking and sleep electrophysiological properties of the thalamus in focal epilepsies.

Brain communications·2025
Same author

Epileptogenic zone characteristics determine effectiveness of electrical transcranial stimulation in epilepsy treatment.

Brain communications·2025
Same author

Permutation entropy-derived parameters to estimate the epileptogenic zone network.

Epilepsia·2023

Related Experiment Video

Updated: Jan 22, 2026

Functional Mapping with Simultaneous MEG and EEG
06:04

Functional Mapping with Simultaneous MEG and EEG

Published on: June 14, 2010

18.4K

Differences in MEG and EEG power-law scaling explained by a coupling between spatial coherence and frequency: a

C G Bénar1, C Grova2,3,4,5, V K Jirsa6

  • 1Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France. christian.benar@univ-amu.fr.

Journal of Computational Neuroscience
|July 12, 2019
PubMed
Summary

The spatial and frequency structure of brain signals may explain differences in electroencephalography (EEG) and magnetoencephalography (MEG) power spectra. This suggests neural dynamics play a key role in neuroimaging signal scaling.

Keywords:
Biophysical modelEEGMEGPower-law spectrumScale-free dynamics

More Related Videos

Automated 3D Optical Coherence Tomography to Elucidate Biofilm Morphogenesis Over Large Spatial Scales
09:56

Automated 3D Optical Coherence Tomography to Elucidate Biofilm Morphogenesis Over Large Spatial Scales

Published on: August 21, 2019

7.3K
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

34.4K

Related Experiment Videos

Last Updated: Jan 22, 2026

Functional Mapping with Simultaneous MEG and EEG
06:04

Functional Mapping with Simultaneous MEG and EEG

Published on: June 14, 2010

18.4K
Automated 3D Optical Coherence Tomography to Elucidate Biofilm Morphogenesis Over Large Spatial Scales
09:56

Automated 3D Optical Coherence Tomography to Elucidate Biofilm Morphogenesis Over Large Spatial Scales

Published on: August 21, 2019

7.3K
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

34.4K

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Biophysics

Background:

  • Electrophysiological signals like EEG and MEG display scale-invariance, characterized by a power-law (1/f) spectrum.
  • Observed differences in EEG and MEG spectral slopes may stem from various factors, including tissue properties.

Purpose of the Study:

  • To investigate the impact of source signal's space/frequency structure on neuroimaging signal scaling properties.
  • To determine if spatial scale and frequency distribution can explain spectral differences between EEG and MEG.

Main Methods:

  • Simulations combining contributions from cortical patches of varying sizes (0.4–104.2 cm²).
  • Assigning high frequencies to small patches and low frequencies to large patches on a logarithmic scale.
  • Testing parameters including space/frequency structure and spatial scale ratios.

Main Results:

  • The space/frequency structure of signals can account for observed differences in EEG and MEG scale-free spectra.
  • Both EEG and MEG showed diminished spectral differences below a specific spatial scale, indicating a resolution limit.
  • Findings are consistent with previous experimental data on EEG and MEG spectral properties.

Conclusions:

  • The spatio-temporal structure of neural dynamics is a significant factor explaining EEG/MEG spectral scaling differences.
  • This study offers a potential mechanism for experimental findings, complementing other explanations.
  • Results can enhance the analysis of power-law measures in EEG/MEG and inform computational brain modeling.