#nestsimulator — Public Fediverse posts

The Urbanczik-Senn plasticity model is a powerful framework for understanding synaptic #plasticity in #NeuralNetworks. It integrates dendritic prediction errors to unify supervised, unsupervised, and #ReinforcementLearning under a single rule. Its predictive coding mechanism and robust learning dynamics make it valuable for simulating neural processing and exploring plasticity. Here’s a short simulation using the #NESTsimulator:

🌍 https://www.fabriziomusacchio.com/blog/2026-02-22-urbanczik_senn_plasticity/

#CompNeuro #Neuroscience

Incorporating structural #plasticity in #SpikingNeuralNetworks (#SNN) enables dynamic #synaptic connectivity, reflecting the #brain's adaptability. By modeling synaptic growth and pruning based on #calcium concentration, we can simulate processes such as #learning and #MemoryFormation. In this post, I reproduce the #NESTSimulator tutorial on structural plasticity, demonstrating its impact on network stability and #homeostasis:

🌍 https://www.fabriziomusacchio.com/blog/2026-02-01-structural_plasticity/

#CompNeuro #Neuroscience #NeuralNetworks

Incorporating structural #plasticity in #SpikingNeuralNetworks (#SNN) enables dynamic #synaptic connectivity, reflecting the #brain's adaptability. By modeling synaptic growth and pruning based on #calcium concentration, we can simulate processes such as #learning and #MemoryFormation. In this post, I reproduce the #NESTSimulator tutorial on structural plasticity, demonstrating its impact on network stability and #homeostasis:

🌍 https://www.fabriziomusacchio.com/blog/2026-02-01-structural_plasticity/

#CompNeuro #Neuroscience #NeuralNetworks

Incorporating structural #plasticity in #SpikingNeuralNetworks (#SNN) enables dynamic #synaptic connectivity, reflecting the #brain's adaptability. By modeling synaptic growth and pruning based on #calcium concentration, we can simulate processes such as #learning and #MemoryFormation. In this post, I reproduce the #NESTSimulator tutorial on structural plasticity, demonstrating its impact on network stability and #homeostasis:

🌍 https://www.fabriziomusacchio.com/blog/2026-02-01-structural_plasticity/

#CompNeuro #Neuroscience #NeuralNetworks

Incorporating structural #plasticity in #SpikingNeuralNetworks (#SNN) enables dynamic #synaptic connectivity, reflecting the #brain's adaptability. By modeling synaptic growth and pruning based on #calcium concentration, we can simulate processes such as #learning and #MemoryFormation. In this post, I reproduce the #NESTSimulator tutorial on structural plasticity, demonstrating its impact on network stability and #homeostasis:

🌍 https://www.fabriziomusacchio.com/blog/2026-02-01-structural_plasticity/

#CompNeuro #Neuroscience #NeuralNetworks

Incorporating structural #plasticity in #SpikingNeuralNetworks (#SNN) enables dynamic #synaptic connectivity, reflecting the #brain's adaptability. By modeling synaptic growth and pruning based on #calcium concentration, we can simulate processes such as #learning and #MemoryFormation. In this post, I reproduce the #NESTSimulator tutorial on structural plasticity, demonstrating its impact on network stability and #homeostasis:

🌍 https://www.fabriziomusacchio.com/blog/2026-02-01-structural_plasticity/

#CompNeuro #Neuroscience #NeuralNetworks

🧠 Pastorelli et al. (2025) present a "simplified two-compartment #neuron with #CalciumDynamics capturing #brain-state-specific apical-amplification, -isolation and -drive". This Ca-#AdEx model replicates distinct #dendritic mechanisms across wakefulness, #NREM & #REM sleep using a compact ThetaPlanes transfer function. Cool implementation using the #NESTsimulator 💻!

🌍 https://doi.org/10.3389/fncom.2025.1566196

#Neuroscience #CompNeuro

I recently played around with #RateModels using #NESTsimulator. Compared to #SNN, RM focus on average firing rates of #NeuronPopulations, simplifying analysis of large networks. They effectively capture collective dynamics like #oscillations and #synchronization, though they miss precise spike timing details. Thus, both approaches have their merits. Here is a brief overview:

🌍 https://www.fabriziomusacchio.com/blog/2025-08-28-rate_models/

#CompNeuro #Neuroscience #Python #PythonTutorial #SpikingNeuralNetwork

Here is a direct follow-up on this, now showing how to implement #GapJunctions in a network of #spiking #neurons (#SNN) using the #NESTsimulator. We simulate a network of 500 inhibitory neurons with gap junctions and analyze the effects on #synchrony and #oscillations. The code is also available on GitHub. Feel free to modify and expand upon it 🤗

🌍 https://www.fabriziomusacchio.com/blog/2025-09-17-gap_junctions_network_example/

#CompNeuro #Neuroscience https://sigmoid.social/@pixeltracker/115044925455984072

📝 New blog post: #GapJunctions (#ElectricalSynapses) enable direct electrical and chemical communication between #neurons, synchronizing activity and supporting rapid signal propagation. Their #modeling is crucial for understanding #NeuralNetworkDynamics, #oscillations, and #brain 🧠 function. Here is a brief summary including a small #PythonTutorial using the #NESTsimulator.

🌍 https://www.fabriziomusacchio.com/blog/2025-08-15-gap_junctions/

#CompNeuro #Neuroscience #Python #OpenSource