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 Experiment Videos

Self-organized criticality model for brain plasticity.

Lucilla de Arcangelis1, Carla Perrone-Capano, Hans J Herrmann

  • 1Dept. of Information Engineering and CNISM, Second University of Naples, 81031 Aversa (CE), Italy.

Physical Review Letters
|February 21, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Perspective on the paper: GDR MiDi. On dense granular flows.

The European physical journal. E, Soft matter·2026
Same author

Allometric scaling of brain activity explained by avalanche criticality.

Journal of the Royal Society, Interface·2026
Same author

Beyond mobility: A prospective study on diet and metabolism in hereditary spastic paraplegia.

Metabolic brain disease·2026
Same author

Involvement of serotonin receptor 7 in synaptic dysfunctions in a mouse model of autism spectrum disorder.

European journal of pharmacology·2026
Same author

Formyl peptide receptor 2 activation by MR-39 inhibits glioblastoma cell proliferation and invasiveness through suppression of multiple oncogenic pathways.

Journal of translational medicine·2026
Same author

Forest fire as a temperature-pattern-driven depinning problem.

Physical review. E·2025
Same journal

Erratum: Bacterial Turbulence at Compressible Fluid Interfaces [Phys. Rev. Lett. 136, 138301 (2026)].

Physical review letters·2026
Same journal

Unveiling Light-Quark Yukawa Flavor Structure via Dihadron Fragmentation at Lepton Colliders.

Physical review letters·2026
Same journal

Adaptable Route to Fast Coherent State Transport via Bang-Bang-Bang Protocols.

Physical review letters·2026
Same journal

Topological Transition and Emergence of Elasticity of Dislocation in Skyrmion Lattice: Beyond Kittel's Magnetic-Polar Analogy.

Physical review letters·2026
Same journal

Pound-Drever-Hall Method for Superconducting-Qubit Readout.

Physical review letters·2026
Same journal

Coupling a ^{73}Ge Nuclear Spin to an Electrostatically Defined Quantum Dot in Silicon.

Physical review letters·2026
See all related articles

This study models brain activity using self-organized criticality and plasticity, successfully reproducing electroencephalogram (EEG) power spectra. The findings reveal a universal power-law behavior in neural network dynamics, crucial for understanding brain function.

Area of Science:

  • Computational Neuroscience
  • Systems Neuroscience
  • Theoretical Biology

Background:

  • Living neural networks exhibit avalanche activity, a state of critical dynamics.
  • Understanding the principles governing brain activity patterns is essential for neuroscience.

Purpose of the Study:

  • To develop a computational model of neural networks that incorporates self-organized criticality and brain plasticity.
  • To reproduce the power-law spectrum characteristic of electroencephalograms (EEG).

Main Methods:

  • A computational model of an electrical neural network with threshold firing and activity-dependent synapses was developed.
  • The model was analyzed for its activity patterns and power spectra.
  • The model's power spectra were compared to experimentally measured EEG spectra.

Related Experiment Videos

Main Results:

  • The model demonstrated avalanche activity following a power-law distribution.
  • The model's power spectra robustly reproduced the experimentally observed power-law behavior with an exponent of 0.8.
  • This exponent value was consistent across different network structures (small-world lattices) and neuron types (leaky neurons).

Conclusions:

  • The model successfully reproduces EEG power spectra, suggesting self-organized criticality and plasticity are key to brain dynamics.
  • The universality of the observed power-law exponent across various models indicates fundamental principles governing neural activity.
  • This research provides insights into the critical dynamics of the brain and their implications for neural function.