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#neuronmodel

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Fabrizio Musacchio<p>This <a href="https://sigmoid.social/tags/tutorial" class="mention hashtag" rel="tag">#<span>tutorial</span></a> explores the oscillatory <a href="https://sigmoid.social/tags/PopulationDynamics" class="mention hashtag" rel="tag">#<span>PopulationDynamics</span></a> of generalized <a href="https://sigmoid.social/tags/IntegrateAndFire" class="mention hashtag" rel="tag">#<span>IntegrateAndFire</span></a> (GIF) neurons simulated with <a href="https://sigmoid.social/tags/NESTSimulator" class="mention hashtag" rel="tag">#<span>NESTSimulator</span></a>. The GIF <a href="https://sigmoid.social/tags/NeuronModel" class="mention hashtag" rel="tag">#<span>NeuronModel</span></a> is a biophysically detailed model that captures the essential features of spiking neurons, including <a href="https://sigmoid.social/tags/SpikeFrequencyAdaptation" class="mention hashtag" rel="tag">#<span>SpikeFrequencyAdaptation</span></a> and <a href="https://sigmoid.social/tags/DynamicThreshold" class="mention hashtag" rel="tag">#<span>DynamicThreshold</span></a> behavior:</p><p>🌍 <a href="https://www.fabriziomusacchio.com/blog/2024-07-14-oscillating_gif_neuron_population/" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">https://www.</span><span class="ellipsis">fabriziomusacchio.com/blog/202</span><span class="invisible">4-07-14-oscillating_gif_neuron_population/</span></a></p><p><a href="https://sigmoid.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="tag">#<span>ComputationalNeuroscience</span></a> <a href="https://sigmoid.social/tags/Python" class="mention hashtag" rel="tag">#<span>Python</span></a> <a href="https://sigmoid.social/tags/Neuroscience" class="mention hashtag" rel="tag">#<span>Neuroscience</span></a></p>
Fabrizio Musacchio<p>From <a href="https://sigmoid.social/tags/VanDerPolOscillator" class="mention hashtag" rel="tag">#<span>VanDerPolOscillator</span></a> to the <a href="https://sigmoid.social/tags/FitzHughNagumoModel" class="mention hashtag" rel="tag">#<span>FitzHughNagumoModel</span></a>: Explore the dynamics of a simplified <a href="https://sigmoid.social/tags/NeuronModel" class="mention hashtag" rel="tag">#<span>NeuronModel</span></a> used to describe <a href="https://sigmoid.social/tags/ActionsPotential" class="mention hashtag" rel="tag">#<span>ActionsPotential</span></a> in neurons.</p><p>🌍 <a href="https://www.fabriziomusacchio.com/blog/2024-04-07-fitzhugh_nagumo_model/" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">https://www.</span><span class="ellipsis">fabriziomusacchio.com/blog/202</span><span class="invisible">4-04-07-fitzhugh_nagumo_model/</span></a></p><p><a href="https://sigmoid.social/tags/CompNeuro" class="mention hashtag" rel="tag">#<span>CompNeuro</span></a> <a href="https://sigmoid.social/tags/computationalneuroscience" class="mention hashtag" rel="tag">#<span>computationalneuroscience</span></a> <a href="https://sigmoid.social/tags/computationalmodeling" class="mention hashtag" rel="tag">#<span>computationalmodeling</span></a> <a href="https://sigmoid.social/tags/PythonTutorial" class="mention hashtag" rel="tag">#<span>PythonTutorial</span></a> <a href="https://sigmoid.social/tags/PhasePlaneAnalysis" class="mention hashtag" rel="tag">#<span>PhasePlaneAnalysis</span></a></p>
Fabrizio Musacchio<p>New <a href="https://sigmoid.social/tags/preprint" class="mention hashtag" rel="tag">#<span>preprint</span></a> by Aaron Spieler et al. on ELM (Expressive Leaky <a href="https://sigmoid.social/tags/Memory" class="mention hashtag" rel="tag">#<span>Memory</span></a>) neurons, a biologically inspired cortical <a href="https://sigmoid.social/tags/neuronmodel" class="mention hashtag" rel="tag">#<span>neuronmodel</span></a>, showing promise in solving long-horizon tasks (complex computations) with remarkable efficiency.</p><p>📔 Spieler et al. (2023), &quot;The ELM Neuron: an Efficient and Expressive Cortical Neuron Model Can Solve Long-Horizon Tasks&quot;, <a href="https://doi.org/10.48550/arXiv.2306.16922" target="_blank" rel="nofollow noopener" translate="no"><span class="invisible">https://</span><span class="ellipsis">doi.org/10.48550/arXiv.2306.16</span><span class="invisible">922</span></a><br /> <br /><a href="https://sigmoid.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="tag">#<span>ComputationalNeuroscience</span></a> <a href="https://sigmoid.social/tags/CompNeuro" class="mention hashtag" rel="tag">#<span>CompNeuro</span></a></p>
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