Complex brain networks: graph theoretical analysis of structural and functional systems.

Ed Bullmore, Olaf Sporns

March 2009 Nat Rev Neurosci

Synopsis of Social media discussions

The overall tone reflects high interest and moderate engagement, with multiple references to the article's concepts like small-world topology and graph analysis, and examples such as comparing brain networks to Bitcoin nodes or neural architectures. Words like

A
Agreement
 Moderate agreement

Most discussions acknowledge the significance of the article, especially highlighting its relevance to understanding brain networks and other complex systems.

I
Interest
 High level of interest

The posts show high interest, with many references to the brain’s architecture, small-world networks, and related concepts.

E
Engagement
 Moderate level of engagement

Posts include references to specific methods, like graph theory and brain imaging techniques, indicating some depth of engagement.

I
Impact
 Moderate level of impact

The conversations suggest that the article influences thoughts about network theory in neuroscience, as well as connections to broader fields such as AI and blockchain.

Social Mentions

YouTube

3 Videos

Facebook

4 Posts

Twitter

23 Posts

Blogs

16 Articles

News

22 Articles

Metrics

Video Views

182,259

Total Likes

7,665

Extended Reach

395,346

Social Features

68

Timeline: Posts about article

Top Social Media Posts

Posts referencing the article

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  • Aun No Me Decido
    @aunnomedecido (Twitter)

    @ElJoputismoDC @AnderUri https://t.co/awnfH8Exk5
    view full post

    May 11, 2025

  • Josh Olin
    @JD_2020 (Twitter)

    Regardless, I’m a fan of his rhetoric, https://t.co/6TGFBUZBDU
    view full post

    May 10, 2025

  • Nous Aimons AIMer
    @HalbWiener (Twitter)

    E Bullmore, O Sporns, Complex brain networks: Graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10, 186–198 (2009).
    view full post

    May 4, 2025

  • Mark Neumann
    @MarkNeu82295077 (Twitter)

    https://t.co/kyacan1Zsd
    view full post

    February 24, 2025

  • Louis R Nemzer
    @BiophysicsFL (Twitter)

    Small-world network topology in the brain https://t.co/FoWcRTcrCI
    view full post

    February 23, 2025

    1

  • D.C. ADAMS
    @THENEWSMT (Twitter)

    A Surprising Way Your Brain Is Wired https://t.co/4ixMxqZ0xT via @YouTube
    view full post

    February 21, 2025

  • daniel formolo
    @danielformolo (Twitter)

    Game Theory: https://t.co/UfouRPsP5v Brain: https://t.co/pKYovfmQCV 2/2
    view full post

    February 19, 2025

  • Anthony Ellis
    @skydog811 (Twitter)

    https://t.co/Ev4MK1sZ6R
    view full post

    February 17, 2025

  • Adarsh Dayalan
    @AdarshDayal10 (Twitter)

    Best channel to learn computational neuroscience https://t.co/Z2YNYZUZHz
    view full post

    February 17, 2025

    1

  • Phi Auteria Et -al.
    @PhiAuteria (Twitter)

    Magic of small world architecture. I am a hub architect. https://t.co/hAYfGOFvME
    view full post

    February 16, 2025

    1

  • Charles Swiger
    @chswiger (Twitter)

    Wondering if the global electronic Übermind hive network is going to partitioned into two connected hemispheres like the brain
    view full post

    February 15, 2025

  • Schoolgirl Satellite Bandit
    @BanditSatellite (Twitter)

    A Surprising Way Your Brain Is Wired
    view full post

    February 14, 2025

  • TechnicalBen
    @_TechyBen (Twitter)

    @MiTiBennett The whole of the self is learning. Thanks. https://t.co/uRlpAwyoCU
    view full post

    February 13, 2025

    1

  • TechnicalBen
    @_TechyBen (Twitter)

    @tszzl It's a small world of LLMs... (Connect the LLMs...) https://t.co/uRlpAwyoCU
    view full post

    February 13, 2025

  • Snapolino
    @snapolino (Twitter)

    @ian__major Holy , very good picture of Bitcoin lightning nodes/connections... this kinda looks exactly like the brain! Small world graphs! https://t.co/YpeHwdpr0H
    view full post

    February 13, 2025

    3

  • Quantengeist
    @Light_Cynapse (Twitter)

    https://t.co/GOGUhJLaol
    view full post

    February 13, 2025

  • Crow
    @Crow99386356 (Twitter)

    https://t.co/92KyWsEUvP
    view full post

    February 12, 2025

    2

  • Charles Swiger
    @chswiger (Twitter)

    New video from #ArtemKirsanov
    view full post

    February 12, 2025

    1

  • eventity
    @CaiXueYong (Twitter)

    https://t.co/nSN2boVTMl
    view full post

    February 12, 2025


  • @speakerjohnash (Twitter)

    https://t.co/MPj2Vqfz4p
    view full post

    February 12, 2025

  • Jordan James Etem
    @JordanJamesEtem (Twitter)

    Bullmore, E., & Sporns, O. (2009). Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci, 10(3), 186–198. #Relevance #DeepLearning #USA #Network @GuyKawasaki $AAPL https://t.co/oFpGCkzTXr
    view full post

    December 24, 2021

  • atriz mula kunis
    @lfernando_f (Twitter)

    @Paludo_Gabriel então, só tenho no contexto de neurociência mesmo, não sei se te ajuda :/ esse do Olaf Sporns e Ed Bullmore é bem bom (https://t.co/PHNL6WUvFW) e esse do Mears e Pollard tb (https://t.co/YqB7InrIaW)
    view full post

    January 22, 2021

    1

  • Pilar Navarro
    @Pilar_Navarro (Twitter)

    Complex brain networks: graph theoretical analysis of structural and functional systems https://t.co/worpDlNSAo #neuromarketing
    view full post

    April 26, 2020

Abstract Synopsis

  • The article discusses how recent advances in graph theory are used to analyze complex brain networks, emphasizing features like small-world topology, highly connected hubs, and modularity across different scales and imaging techniques.
  • It reviews various brain imaging methods (such as MRI, diffusion tensor imaging, magnetoencephalography, and electroencephalography) used to study both structural and functional brain networks in humans and animals.
  • The article also explains basic graph theory concepts, addresses technical challenges in the field, and highlights key questions for future research to better understand brain network organization.]