Tanguy Fardet<p>I just discovered the ARC-AGI initiative and the associated test to estimate how close "AI" models are from <a href="https://fediscience.org/tags/AGI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AGI</span></a></p><p><a href="https://arcprize.org/arc-agi" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">arcprize.org/arc-agi</span><span class="invisible"></span></a></p><p>While I found the initiative interesting, I'm not sure I understand what in this test really guarantees that the model is capable of some form of generalization and problem-solving.<br>Wouldn't it be possible for specialized pattern-matching/discovering algorithms to solve such problems?<br>I imagine some computer scientists, mathematicians or computational neuroscientists have already had a look at this, so would anyone knows of some articles/blogs on the topic?</p><p>Maybe <span class="h-card" translate="no"><a href="https://scholar.social/@wim_v12e" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>wim_v12e</span></a></span>? Is this something you already looked at?</p><p><a href="https://fediscience.org/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://fediscience.org/tags/machineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>machineLearning</span></a> <a href="https://fediscience.org/tags/neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>neuroscience</span></a> <a href="https://fediscience.org/tags/cognition" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>cognition</span></a> <a href="https://fediscience.org/tags/computationalNeuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>computationalNeuroscience</span></a> <a href="https://fediscience.org/tags/neuralNets" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>neuralNets</span></a> <a href="https://fediscience.org/tags/lazyWeb" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>lazyWeb</span></a></p>
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#computationalneuroscience
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Ankur Sinha "FranciscoD"<p>A new release of PyNeuroML is available, please update your installations:</p><p><a href="https://github.com/NeuroML/pyNeuroML/releases" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">github.com/NeuroML/pyNeuroML/r</span><span class="invisible">eleases</span></a></p><p>```<br>pip install --upgrade pyneuroml<br>```</p><p><a href="https://fosstodon.org/tags/NeuroML" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NeuroML</span></a> <a href="https://fosstodon.org/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalNeuroscience</span></a> <a href="https://fosstodon.org/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Neuroscience</span></a> <a href="https://fosstodon.org/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Python</span></a> <a href="https://fosstodon.org/tags/AcademicChatter" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AcademicChatter</span></a></p>
Dan Goodman<p>Almost last call to register for UK neural computation conference in London July 10-11. Registration deadline is July 1st. We have some great talks and posters as well as a session on funding with ARIA.</p><p>Look forward to seeing you all there. Now click here 👇</p><p><a href="https://neuralcomputation.uk/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">neuralcomputation.uk/</span><span class="invisible"></span></a></p><p><a href="https://neuromatch.social/tags/neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>neuroscience</span></a> <a href="https://neuromatch.social/tags/compneuro" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>compneuro</span></a> <a href="https://neuromatch.social/tags/computationalneuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>computationalneuroscience</span></a></p>
Neuromatch<p>At Neuromatch Academy & Climatematch Academy, we’re not just running courses. Neuromatch is investing in the next generation of computational scientists, changemakers, & interdisciplinary thinkers.</p><p>As part of this mission, we offer Professional Development sessions that give our students & TAs real-world tools and insight before the coursework begins.</p><p>🤓Want to get involved with Neuromatch? Join our mailing list: <a href="https://neuromatch.io/mailing-list/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">neuromatch.io/mailing-list/</span><span class="invisible"></span></a></p><p><a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalNeuroscience</span></a> <a href="https://neuromatch.social/tags/ClimateScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ClimateScience</span></a> <a href="https://neuromatch.social/tags/OpenScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenScience</span></a></p>
Laurent Perrinet<p>Researchers in France are working on creating a French network of researchers to organize interaction, communication and training in <a href="https://neuromatch.social/tags/computationalneuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>computationalneuroscience</span></a> </p><p>If you are a CompNeuro working in France, consider joining, and registering to our mailing list: <a href="https://listes.services.cnrs.fr/wws/subscribe/rt_neurocomp" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">listes.services.cnrs.fr/wws/su</span><span class="invisible">bscribe/rt_neurocomp</span></a></p><p><a href="https://bsky.app/profile/lauradugue.bsky.social/post/3lo6rrtvb3k2v" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">bsky.app/profile/lauradugue.bs</span><span class="invisible">ky.social/post/3lo6rrtvb3k2v</span></a><br><a href="https://www.linkedin.com/posts/laura-dugu%C3%A9-59964756_rtneurocomp-r%C3%A9seau-fran%C3%A7ais-de-neurosciences-activity-7324039702427090944-LKsN" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">linkedin.com/posts/laura-dugu%</span><span class="invisible">C3%A9-59964756_rtneurocomp-r%C3%A9seau-fran%C3%A7ais-de-neurosciences-activity-7324039702427090944-LKsN</span></a></p>
Neurofrontiers<p>A few weeks ago, I shared a differential equations tutorial for beginners, written from the perspective of a neuroscientist who's had to grapple with the computational part. Following up on that, I've now tackled the first real beast encountered by most computational neuroscience students: the Hodgkin-Huxley model. </p><p>While remaining incredibly elegant to this day, this model is also a mathematically dense system of equations that can overwhelm and discourage beginners, especially those with non-mathematical backgrounds. Similar to the first tutorial, I've tried to build intuition step-by-step, starting with a simple RC circuit, layering in Na⁺ and K⁺ channels, and ending with the full spike-generation story. </p><p>Feedback is welcome, especially from fellow non-math converts.<br><a href="https://neurofrontiers.blog/building-a-virtual-neuron-2/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">neurofrontiers.blog/building-a</span><span class="invisible">-virtual-neuron-2/</span></a></p><p><a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalNeuroscience</span></a> <a href="https://neuromatch.social/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Python</span></a> <a href="https://neuromatch.social/tags/hodgkinHuxleyModel" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>hodgkinHuxleyModel</span></a> <a href="https://neuromatch.social/tags/math" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>math</span></a> <a href="https://neuromatch.social/tags/biophysics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>biophysics</span></a> </p><p>From: <span class="h-card" translate="no"><a href="https://neuromatch.social/@neurofrontiers" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>neurofrontiers</span></a></span><br><a href="https://neuromatch.social/@neurofrontiers/114150087773204813" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">neuromatch.social/@neurofronti</span><span class="invisible">ers/114150087773204813</span></a></p>
Dan Goodman<p>How do babies and blind people learn to localise sound without labelled data? We propose that innate mechanisms can provide coarse-grained error signals to boostrap learning.</p><p>New preprint from <span class="h-card" translate="no"><a href="https://mastodon.social/@yang_chu" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>yang_chu</span></a></span>. </p><p><a href="https://arxiv.org/abs/2001.10605" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">arxiv.org/abs/2001.10605</span><span class="invisible"></span></a></p><p>Thread below 👇</p><p><a href="https://neuromatch.social/tags/neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>neuroscience</span></a> <a href="https://neuromatch.social/tags/computationalneuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>computationalneuroscience</span></a> <a href="https://neuromatch.social/tags/compneuro" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>compneuro</span></a> <a href="https://neuromatch.social/tags/compneurosci" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>compneurosci</span></a></p>
Dan Goodman<p>Preview of the talk I'm giving on Friday. <a href="https://neuromatch.social/tags/neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>neuroscience</span></a> <a href="https://neuromatch.social/tags/CompNeuro" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CompNeuro</span></a> <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalNeuroscience</span></a></p>
Neurofrontiers<p>When I transitioned from cognitive to computational neuroscience, I found myself in a bit of a bind. I had learned calculus, but I had progressed little beyond pattern recognition: I knew which rules to apply to find solutions to which equations, but the equations themselves lacked any sort of real meaning for me. </p><p>So I struggled with understanding how formulas could be implemented in code and why the code I was reading could be described by those formulas. Resources explaining math “for neuroscientists” were unfortunately quite useless for me, because they usually presented the necessary equations for describing various neural systems, assuming the presence of that basic understanding/intuition I lacked. </p><p>Of course, I figured things out eventually (otherwise I wouldn’t be writing about it), but I’m 85% sure I’m not the only one who’s ever struggled with this, and so I wrote the tutorial I wish I could’ve had. If you’re in a similar position, I hope you’ll find it useful. And if not, maybe it helps you get a glimpse into the struggles of the non-math people in your life. Either way, it has cats.</p><p><a href="https://neurofrontiers.blog/building-a-virtual-neuron-1/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">neurofrontiers.blog/building-a</span><span class="invisible">-virtual-neuron-1/</span></a></p><p><a href="https://neuromatch.social/tags/neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>neuroscience</span></a> <a href="https://neuromatch.social/tags/math" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>math</span></a> <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalNeuroscience</span></a> <a href="https://neuromatch.social/tags/tutorial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>tutorial</span></a> <a href="https://neuromatch.social/tags/academia" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>academia</span></a></p>
Ankur Sinha "FranciscoD"<p><a href="https://fosstodon.org/tags/NeuroML" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NeuroML</span></a> is participating in <a href="https://fosstodon.org/tags/GSoC2025" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GSoC2025</span></a> again this year under <span class="h-card" translate="no"><a href="https://neuromatch.social/@INCF" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>INCF</span></a></span> . We're looking for people with some experience of <a href="https://fosstodon.org/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalNeuroscience</span></a> to work on developing <a href="https://fosstodon.org/tags/standardised" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>standardised</span></a> biophysically detailed computational models using <a href="https://fosstodon.org/tags/NeuroML" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NeuroML</span></a> <a href="https://fosstodon.org/tags/PyNN" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PyNN</span></a> and <a href="https://fosstodon.org/tags/OpenSourceBrain" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSourceBrain</span></a>. </p><p>Please spread the word, especially to students interested in modelling. We will help them learn the NeuroML ecosystem so they can use its standardised pipeline in their work.</p><p><a href="https://docs.neuroml.org/NeuroMLOrg/OutreachTraining.html#google-summer-of-code" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">docs.neuroml.org/NeuroMLOrg/Ou</span><span class="invisible">treachTraining.html#google-summer-of-code</span></a> </p><p>CC <a href="https://fosstodon.org/tags/AcademicChatter" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AcademicChatter</span></a></p>
Dan Goodman<p>I'm giving an online talk starting in 15m (as part of UCL's NeuroAI series).</p><p>It's on neural architectures and our current line of research trying to figure out what they might be good for (including some philosophy: what might an answer to this question even look like?).</p><p>Sign up (free) at this link to get the zoom link:</p><p><a href="https://www.eventbrite.co.uk/e/ucl-neuroai-talk-series-tickets-1189972031379?utm-campaign=social&utm-content=attendeeshare&utm-medium=discovery&utm-term=listing&utm-source=cp&aff=ebdsshcopyurl" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">eventbrite.co.uk/e/ucl-neuroai</span><span class="invisible">-talk-series-tickets-1189972031379?utm-campaign=social&utm-content=attendeeshare&utm-medium=discovery&utm-term=listing&utm-source=cp&aff=ebdsshcopyurl</span></a></p><p><a href="https://neuromatch.social/tags/neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>neuroscience</span></a> <a href="https://neuromatch.social/tags/compneuro" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>compneuro</span></a> <a href="https://neuromatch.social/tags/computationalneuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>computationalneuroscience</span></a> <a href="https://neuromatch.social/tags/neuroai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>neuroai</span></a></p>
El Duvelle Neuro<p>With the current situation in the <a href="https://neuromatch.social/tags/US" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>US</span></a>, several of my former colleagues there are looking for a <a href="https://neuromatch.social/tags/PostDocJob" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PostDocJob</span></a> in <a href="https://neuromatch.social/tags/Europe" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Europe</span></a>, to do <a href="https://neuromatch.social/tags/BehaviouralNeuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>BehaviouralNeuroscience</span></a> or <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalNeuroscience</span></a> in <a href="https://neuromatch.social/tags/SpatialCognition" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SpatialCognition</span></a> (or adjacent). <br>Lots of hashtags I know..</p><p>Do you know a <a href="https://neuromatch.social/tags/EU" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>EU</span></a> or <a href="https://neuromatch.social/tags/UK" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>UK</span></a> <a href="https://neuromatch.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Neuroscience</span></a> lab looking to hire a postdoc in these fields? Let me know and I'll pass it on to them!</p><p>Edit: adding <a href="https://neuromatch.social/tags/RodentResearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RodentResearch</span></a> and <a href="https://neuromatch.social/tags/humanresearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>humanresearch</span></a> for the species concerned (in this case)</p>
Dan Goodman<p>Come along to my (free, online) UCL NeuroAI talk next week on neural architectures. What are they good for? All will finally be revealed and you'll never have to think about that question again afterwards. Yep. Definitely that.</p><p>🗓️ Wed 12 Feb 2025 <br>⏰ 2-3pm GMT<br>ℹ️ Details and registration: <a href="https://www.eventbrite.co.uk/e/ucl-neuroai-talk-series-tickets-1216638381149" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">eventbrite.co.uk/e/ucl-neuroai</span><span class="invisible">-talk-series-tickets-1216638381149</span></a></p><p><a href="https://neuromatch.social/tags/neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>neuroscience</span></a> <a href="https://neuromatch.social/tags/CompNeuro" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CompNeuro</span></a> <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalNeuroscience</span></a> <a href="https://neuromatch.social/tags/NeuroAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NeuroAI</span></a></p>
Neuromatch<p>🚀 Neuromatch Academy 2025 is coming! 🚀</p><p>📢 Key Dates:<br>📍 Feb 24 – Applications Open!<br>📍 Mar 23 – Deadline (Midnight in your timezone)<br>📍 Mid-April – Decisions Announced<br>📍 Early May – Enrollment Deadline</p><p>Join a global community & dive into Computational Neuroscience, Deep Learning, Comp Tools for Climate Science, or NeuroAI! Don’t miss out—apply & tag a friend! 🌍✨</p><p><a href="https://neuromatch.social/tags/NMA2025" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NMA2025</span></a> <a href="https://neuromatch.social/tags/AIForAll" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIForAll</span></a> <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalNeuroscience</span></a> <a href="https://neuromatch.social/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DeepLearning</span></a></p>
Ankur Sinha "FranciscoD"<p>We are very happy to provide a consolidated update on the <a href="https://fosstodon.org/tags/NeuroML" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NeuroML</span></a> ecosystem in our <span class="h-card" translate="no"><a href="https://fediscience.org/@eLife" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>eLife</span></a></span> paper, “The NeuroML ecosystem for standardized multi-scale modeling in neuroscience”: <a href="https://doi.org/10.7554/eLife.95135.3" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">doi.org/10.7554/eLife.95135.3</span><span class="invisible"></span></a></p><p><a href="https://fosstodon.org/tags/NeuroML" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NeuroML</span></a> is a standard and software ecosystem for data-driven biophysically detailed <a href="https://fosstodon.org/tags/ComputationalModelling" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalModelling</span></a> endorsed by the <span class="h-card" translate="no"><a href="https://neuromatch.social/@INCF" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>INCF</span></a></span> and CoMBINE, and includes a large community of users and software developers. </p><p><a href="https://fosstodon.org/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Neuroscience</span></a> <a href="https://fosstodon.org/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalNeuroscience</span></a> <a href="https://fosstodon.org/tags/ComputationalModelling" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalModelling</span></a> 1/x</p>
Dan Goodman<p>What's the right way to think about modularity in the brain? This devilish 😈 question is a big part of my research now, and it started with this paper with <span class="h-card" translate="no"><a href="https://neuromatch.social/@GabrielBena" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>GabrielBena</span></a></span> finally published after the first preprint in 2021! </p><p><a href="https://www.nature.com/articles/s41467-024-55188-9" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">nature.com/articles/s41467-024</span><span class="invisible">-55188-9</span></a></p><p>We know the brain is physically structured into distinct areas ("modules"?). We also know that some of these have specialised function. But is there a necessary connection between these two statements? What is the relationship - if any - between 'structural' and 'functional' modularity?</p><p>TLDR if you don't want to read the rest: there is no necessary relationship between the two, although when resources are tight, functional modularity is more likely to arise when there's structural modularity. We also found that functional modularity can change over time! Longer version follows.</p><p><a href="https://neuromatch.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Neuroscience</span></a> <a href="https://neuromatch.social/tags/CompNeuro" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CompNeuro</span></a> <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalNeuroscience</span></a></p>
Dan Goodman<p>New preprint! With Swathi Anil and <span class="h-card" translate="no"><a href="https://neuromatch.social/@marcusghosh" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>marcusghosh</span></a></span>.</p><p>If you want to get the most out of a multisensory signal, you should take it's temporal structure into account. But which neural architectures do this best? 🧵👇</p><p><a href="https://www.biorxiv.org/content/10.1101/2024.12.19.629348v1" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">biorxiv.org/content/10.1101/20</span><span class="invisible">24.12.19.629348v1</span></a></p><p><a href="https://neuromatch.social/tags/neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>neuroscience</span></a> <a href="https://neuromatch.social/tags/computationalneuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>computationalneuroscience</span></a> <a href="https://neuromatch.social/tags/compneuro" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>compneuro</span></a></p>
INCF<p>Are you interested in a masters or PhD in computational neuroscience? Don't miss <span class="h-card" translate="no"><a href="https://bird.makeup/users/bccn_berlin" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>bccn_berlin</span></a></span>'s hybrid event!</p><p>🧠 International graduate program(s) computational neuroscience<br>📅 29-Jan-2025, 15-18 CET<br>📍 BCCN Lecture hall & Zoom</p><p>Learn more & register: bit.ly/4h0zj9y</p><p><a href="https://neuromatch.social/tags/neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>neuroscience</span></a> <a href="https://neuromatch.social/tags/neuroinformatics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>neuroinformatics</span></a> <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalNeuroscience</span></a></p>
El Duvelle Neuro<p>Please share these 2 PhD positions in <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalNeuroscience</span></a> co-supervised by Dr. Elisa Massi <a href="https://neuromatch.social/tags/ETIS" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ETIS</span></a> Lab -- CY Cergy Paris Université (France):</p><p>They both start from September 2025, but the application deadline is on the <strong>30th of January 2025</strong> </p><ol><li><p>SMaRT-RL: Stress & Hippocampal Replay in Reinforcement Learning: <a href="https://dim-cbrains.fr/en/phd-program/dim-cbrains?search=canamero" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">dim-cbrains.fr/en/phd-program/</span><span class="invisible">dim-cbrains?search=canamero</span></a></p></li><li><p>SYSNEMEHISPIN: Memory Formation with Spiking Neural Models: <a href="https://www.dim-cbrains.fr/en/phd-program/dim-cbrains?search=manos" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">dim-cbrains.fr/en/phd-program/</span><span class="invisible">dim-cbrains?search=manos</span></a></p></li></ol><p>Interested candidates can apply after their registration on the DIM C-BRAINS platform: <a href="https://dim-cbrains.fr/en/platform/login" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">dim-cbrains.fr/en/platform/log</span><span class="invisible">in</span></a> </p><p>These are funded for 3 years, the normal PhD duration in France.</p><p><em>These scholarships aim at enhancing international mobility and are reserved for candidates that have recently studied or worked outside France.</em></p><p><a href="https://neuromatch.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Neuroscience</span></a> <a href="https://neuromatch.social/tags/PhDPosition" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PhDPosition</span></a> <a href="https://neuromatch.social/tags/FindAPhD" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FindAPhD</span></a></p>
Brian simulator<p>In the spirit of end-of-year celebrations, we've just released Brian 2.8 🌠 <br>Alongside the usual helping of small improvements and fixes, this release comes with an important performance improvement for random number generation in C++ standalone mode.</p><p>Head to the release notes for more details! <a href="https://brian2.readthedocs.io/en/2.8.0/introduction/release_notes.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">brian2.readthedocs.io/en/2.8.0</span><span class="invisible">/introduction/release_notes.html</span></a></p><p><a href="https://neuromatch.social/tags/FOSS" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FOSS</span></a> <a href="https://neuromatch.social/tags/ComputationalNeuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalNeuroscience</span></a> <a href="https://neuromatch.social/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Python</span></a></p>
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