#computationalneuroscience — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #computationalneuroscience, aggregated by home.social.
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Spike-timing-dependent #plasticity (#STDP) is a core rule in #ComputationalNeuroscience that adjusts #synaptic strength based on precise pre- vs. postsynaptic #spike timing, enabling #TemporalCoding and #learning in #SNN. In this post, I summarize its mathematical formulation, functional consequences for learning and #memory along with a simple #Python example:
🌍 https://www.fabriziomusacchio.com/blog/2026-02-12-stdp/
#CompNeuro #Neuroscience #SNN #NeuralDynamics #NeuralPlasticity
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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” (http://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
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🧠 New #preprint! Confavreux et al. use meta-learning to uncover thousands of diverse, local #plasticity rule quadruplets that stabilize #RecurrentSpikingNetworks — and incidentally support #memory functions like novelty detection, replay, & contextual prediction. A striking case of function emerging from stability.
📄 https://doi.org/10.1101/2025.05.28.656584
#Neuroscience #Plasticity #ComputationalNeuroscience #CompNeuro #SNN #SpikingNeurons
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Before building more complex neural networks in #NESTSimulator, it is crucial to understand its connections rules. I’ve put together an overview of all available rules, which mainly follows NEST's documentation (https://nest-simulator.readthedocs.io/en/stable/synapses/connectivity_concepts.html#connectivity-concepts)
🌍 https://www.fabriziomusacchio.com/blog/2024-06-25-nest_connection_concepts/
#CompNeuro #ComputationalNeuroscience #Neuroscience #SNN #SpikingNeuronalNetwork #NEST
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From #VanDerPolOscillator to the #FitzHughNagumoModel: Explore the dynamics of a simplified #NeuronModel used to describe #ActionsPotential in neurons.
🌍 https://www.fabriziomusacchio.com/blog/2024-04-07-fitzhugh_nagumo_model/
#CompNeuro #computationalneuroscience #computationalmodeling #PythonTutorial #PhasePlaneAnalysis
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Rethinking the #hippocampal #cognitivemap as a #metalearning computational module – New publication by Luca Ambrogioni &
H. Freyja Ólafsdóttir (2023) -
Logs from the open #INCF #OCNS #SoftwareWG meeting in March are here https://ocns.github.io/SoftwareWG/2023/03/20/wg-meeting-15-march-2023.html #OpenScience #Community #FOSS #Neuroscience #ComputationalNeuroscience
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The #INCF #OCNS Software WG software highlight is starting in ~20 minutes (1600UTC) !
Michalis Pagkalos will discuss #Dendrify, a framework for incorporating dendrites to spiking neural networks
https://ocns.github.io/SoftwareWG/2023/01/27/dev-session-michalis-pagkalos-dendrify.html
#OpenScience #Neuroscience #ComputationalNeuroscience #Dendrites
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Logs from the monthly open #INCF #OCNS Software Working Group meeting in January are now here:
https://ocns.github.io/SoftwareWG/2023/02/01/wg-meeting-16-january-2023.html
#Neuroscience #OpenScience #CompNeuro #ComputationalNeuroscience
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Please join the #INCF #OCNS Software WG at our next software highlight session on Feb 7 at 1600 UTC. Michalis Pagkalos will discuss #Dendrify, a framework for incorporating dendrites to spiking neural networks https://ocns.github.io/SoftwareWG/2023/01/27/dev-session-michalis-pagkalos-dendrify.html #OpenScience #Neuroscience #ComputationalNeuroscience #Dendrites