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#networkneuroscience — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #networkneuroscience, aggregated by home.social.

  1. I’m excited to share that our article has been published: “Brain Topology Disruption in Early-Onset Dementia: Review of Current Findings and the Need for Network Resilience-Focused Models” (dx.doi.org/10.1002/brb3.70903)

    In this review, we highlight several important insights:

    - A summary of how early‐onset forms of dementia (including Alzheimer’s disease, frontotemporal dementia (FTD), and behavioral variant FTD) show disruption in brain network topology (both structural and functional) rather than purely focal pathology.

    - Evidence that brain networks lose their optimal organisational properties (e.g., balance of segregation and integration) in early‐onset dementia, reflecting decline in network resilience. For example, previous work has shown disrupted segregation/integration in large‐scale brain networks in Alzheimer’s/MCI.

    - The concept of network resilience as a key lens: rather than only asking “where damage occurs”, the paper argues we should ask “how the network topology fails to compensate, reorganise or maintain function under pathology”. This shifts the view to resilience‐focused models.

    - Review of methodological findings: how graph‐theoretic metrics (clustering coefficient, global/local efficiency, modularity, assortativity, small‐worldness) are being applied to neuroimaging and electrophysiology in early dementia.

    - Gaps and opportunities: the need for models that integrate network resilience, longitudinal data, multimodal connectivity (structural + functional + electrophysiological) and early‐onset cohorts; and the translational potential for biomarkers and interventions that support network integrity rather than just reduce pathology.

    I believe this work contributes to bridging neuroscience, network theory, and clinical neurology, and invites discussion on how we can design interventions that strengthen brain network resilience in dementia.

    Thanks to my co-authors (Hema Nawani, Sredha Sunil) and reviewers, and a huge thank you to our professor Veeky Baths for his guidance and support throughout this work.

    If you’re working in cognitive neuroscience, network approaches to brain disorders, early‐onset dementia, connectomics or translational neurology, let’s collaborate to make a real impact.

    #Neuroscience #BrainNetworks #Dementia #EarlyOnsetDementia #Neurodegeneration #NetworkResilience #ClinicalNeuroscience #GraphTheory #NetworkNeuroscience #ComputationalNeuroscience

  2. I’m excited to share that our article has been published: “Brain Topology Disruption in Early-Onset Dementia: Review of Current Findings and the Need for Network Resilience-Focused Models” (dx.doi.org/10.1002/brb3.70903)

    In this review, we highlight several important insights:

    - A summary of how early‐onset forms of dementia (including Alzheimer’s disease, frontotemporal dementia (FTD), and behavioral variant FTD) show disruption in brain network topology (both structural and functional) rather than purely focal pathology.

    - Evidence that brain networks lose their optimal organisational properties (e.g., balance of segregation and integration) in early‐onset dementia, reflecting decline in network resilience. For example, previous work has shown disrupted segregation/integration in large‐scale brain networks in Alzheimer’s/MCI.

    - The concept of network resilience as a key lens: rather than only asking “where damage occurs”, the paper argues we should ask “how the network topology fails to compensate, reorganise or maintain function under pathology”. This shifts the view to resilience‐focused models.

    - Review of methodological findings: how graph‐theoretic metrics (clustering coefficient, global/local efficiency, modularity, assortativity, small‐worldness) are being applied to neuroimaging and electrophysiology in early dementia.

    - Gaps and opportunities: the need for models that integrate network resilience, longitudinal data, multimodal connectivity (structural + functional + electrophysiological) and early‐onset cohorts; and the translational potential for biomarkers and interventions that support network integrity rather than just reduce pathology.

    I believe this work contributes to bridging neuroscience, network theory, and clinical neurology, and invites discussion on how we can design interventions that strengthen brain network resilience in dementia.

    Thanks to my co-authors (Hema Nawani, Sredha Sunil) and reviewers, and a huge thank you to our professor Veeky Baths for his guidance and support throughout this work.

    If you’re working in cognitive neuroscience, network approaches to brain disorders, early‐onset dementia, connectomics or translational neurology, let’s collaborate to make a real impact.

    #Neuroscience #BrainNetworks #Dementia #EarlyOnsetDementia #Neurodegeneration #NetworkResilience #ClinicalNeuroscience #GraphTheory #NetworkNeuroscience #ComputationalNeuroscience

  3. By ironical serendiripy, drift, change, synchronicity, or else:

    Two new papers with thoughtful #NetworkNeuroscience critique!

    » Beyond Networks:
    Explaining Dynamics in the Natural and Social Sciences «
    @yoginho et al.
    doi.org/10.31219/osf.io/htc78

    » Circular and unified analysis in network neuroscience «
    Mika Rubinov
    doi.org/10.7554/eLife.79559

    With different framework approaches, conclusions, while complimentary & so needed!

    #ComplexSystems
    #NetworkScience
    #SystemsNeuroscience
    #neurodon
    #neurobuzz

  4. By ironical serendiripy, drift, change, synchronicity, or else:

    Two new papers with thoughtful #NetworkNeuroscience critique!

    » Beyond Networks:
    Explaining Dynamics in the Natural and Social Sciences «
    @yoginho et al.
    doi.org/10.31219/osf.io/htc78

    » Circular and unified analysis in network neuroscience «
    Mika Rubinov
    doi.org/10.7554/eLife.79559

    With different framework approaches, conclusions, while complimentary & so needed!

    #ComplexSystems
    #NetworkScience
    #SystemsNeuroscience
    #neurodon
    #neurobuzz

  5. @manlius

    Another One Bites the Dust!

    Nice @thetransmitter writeup for broad audience
    thetransmitter.org/methods/mis
    Yet the 6 appendices alone have many bits to learn from!

    Benchmark models
    Represent all important existing knowledge about our phenomenon of interest

    Speculative models
    Represent new hypotheses

    Strawman models
    Represent weak null hypotheses

    Circular analyses
    Almost invariably accept speculative models against strawman models

    Mika Rubinov
    doi.org/10.7554/eLife.79559
    #NetworkNeuroscience

  6. @manlius

    Another One Bites the Dust!

    Nice @thetransmitter writeup for broad audience
    thetransmitter.org/methods/mis
    Yet the 6 appendices alone have many bits to learn from!

    Benchmark models
    Represent all important existing knowledge about our phenomenon of interest

    Speculative models
    Represent new hypotheses

    Strawman models
    Represent weak null hypotheses

    Circular analyses
    Almost invariably accept speculative models against strawman models

    Mika Rubinov
    doi.org/10.7554/eLife.79559
    #NetworkNeuroscience

  7. In case you miss the streaming Neuropizza of Tiziana Currieri, here is the talk about Connectomic disruption for Traumatic #brain injury:
    youtube.com/watch?v=d-AbdpYjJV

    #TBI #networkneuroscience #neuroscience #network #traumaticbraininjury
    @SanoScience

  8. In case you miss the streaming Neuropizza of Tiziana Currieri, here is the talk about Connectomic disruption for Traumatic #brain injury:
    youtube.com/watch?v=d-AbdpYjJV

    #TBI #networkneuroscience #neuroscience #network #traumaticbraininjury
    @SanoScience

  9. And here we go!

    The new issue (n° 11) of #ComplexityThoughts is out!

    #NetworkScience #UrbanSystems, #NetworkNeuroscience #OriginOfLife

    _________

    Do you find it useful and you are not yet subscribed? It's free, check it out or recommend it to a friend: manlius.substack.com/

    @networkscience @complexsystems @neuroscience

  10. And here we go!

    The new issue (n° 11) of #ComplexityThoughts is out!

    #NetworkScience #UrbanSystems, #NetworkNeuroscience #OriginOfLife

    _________

    Do you find it useful and you are not yet subscribed? It's free, check it out or recommend it to a friend: manlius.substack.com/

    @networkscience @complexsystems @neuroscience

  11. Young researchers: are you looking for a fantastic summer school on network science?

    Our Mediterranean School of Complex Networks is at its 8th in-person edition!

    Great lectures and speakers, a friendly environment and a fantastic venue (Sicily). What are you waiting for?

    Info: mediterraneanschoolcomplex.net

    Please, spread the word and boost!

    #NetworkMedicine #Networks #NetworkScience #NetworkNeuroscience @netscisociety @networkscience @complexsystems @neuroscience

  12. Young researchers: are you looking for a fantastic summer school on network science?

    Our Mediterranean School of Complex Networks is at its 8th in-person edition!

    Great lectures and speakers, a friendly environment and a fantastic venue (Sicily). What are you waiting for?

    Info: mediterraneanschoolcomplex.net

    Please, spread the word and boost!

    #NetworkMedicine #Networks #NetworkScience #NetworkNeuroscience @netscisociety @networkscience @complexsystems @neuroscience

  13. ”we show that LSD and psilocybin reduce control energy required for brain state transitions compared to placebo. Furthermore, across individuals, reduction in control energy correlates with more frequent state transitions and increased entropy of brain state dynamics”

    nature.com/articles/s41467-022

    #NetworkNeuroscience @neuroscience

  14. ”we show that LSD and psilocybin reduce control energy required for brain state transitions compared to placebo. Furthermore, across individuals, reduction in control energy correlates with more frequent state transitions and increased entropy of brain state dynamics”

    nature.com/articles/s41467-022

    #NetworkNeuroscience @neuroscience

  15. Do we need to hardwire hierarchical connectivity in recurrent neural networks to achieve predictive coding (PC)?

    PC is an emergent consequence of an energy efficiency principle, leading to separate subpopulations of prediction and error units.

    cell.com/patterns/fulltext/S26

    #ComplexSystems #NetworkNeuroscience #BioInspiredComputing #ComputationalBiology

    @neuroscience @networkscience @complexsystems

    @PessoaBrain @WiringtheBrain @kordinglab @ricard_sole @albertcardona @c4computation

  16. Do we need to hardwire hierarchical connectivity in recurrent neural networks to achieve predictive coding (PC)?

    PC is an emergent consequence of an energy efficiency principle, leading to separate subpopulations of prediction and error units.

    cell.com/patterns/fulltext/S26

    #ComplexSystems #NetworkNeuroscience #BioInspiredComputing #ComputationalBiology

    @neuroscience @networkscience @complexsystems

    @PessoaBrain @WiringtheBrain @kordinglab @ricard_sole @albertcardona @c4computation

  17. Would you subscribe to a weekly/biweekly newsletter about recommended papers (or threads) that I (biasedly) find interesting/useful about #ComplexSystems #ComplexNetworks #NetworkScience #NetworkMedicine #NetworkNeuroscience #NetworkEpidemiology #HumanBehavior #CollectiveBehavior #PopulationHealth ?

    I curate different lists (of things I read) that might be worth sharing.

    #poll #survey