Fabrizio Musacchio<p>Brody and <a href="https://sigmoid.social/tags/Hopfield" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Hopfield</span></a> (2003) showed how networks of <a href="https://sigmoid.social/tags/SpikingNeurons" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>SpikingNeurons</span></a> (<a href="https://sigmoid.social/tags/SNN" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>SNN</span></a>) can be used to process temporal information based on computations on the timing of spikes rather than the rate of spikes. This is particularly relevant in the context of <a href="https://sigmoid.social/tags/OlfactoryProcessing" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>OlfactoryProcessing</span></a>, where the timing of spikes in the olfactory bulb is crucial for encoding odor information. Here is a quick tutorial, that recapitulates the main concepts of that network using <a href="https://sigmoid.social/tags/NEST" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>NEST</span></a> <a href="https://sigmoid.social/tags/simulator" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>simulator</span></a>:</p><p>🌍 <a href="https://www.fabriziomusacchio.com/blog/2024-08-21-olfactory_processing_via_spike_time_bases_computation/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">fabriziomusacchio.com/blog/202</span><span class="invisible">4-08-21-olfactory_processing_via_spike_time_bases_computation/</span></a></p><p><a href="https://sigmoid.social/tags/CompNeuro" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>CompNeuro</span></a></p>