Shakedown Social

Fabrizio Musacchio📚 New article by Esparza et al. and <a href="https://fosstodon.org/@LMPrida" class="u-url mention" rel="nofollow noopener" target="_blank">@LMPrida</a> : Cell-type-specific <a href="https://sigmoid.social/tags/manifold" class="mention hashtag" rel="nofollow noopener" target="_blank">#manifold</a> analysis discloses independent parallel <a href="https://sigmoid.social/tags/SpatialMaps" class="mention hashtag" rel="nofollow noopener" target="_blank">#SpatialMaps</a> in <a href="https://sigmoid.social/tags/hippocampal" class="mention hashtag" rel="nofollow noopener" target="_blank">#hippocampal</a> <a href="https://sigmoid.social/tags/CA1" class="mention hashtag" rel="nofollow noopener" target="_blank">#CA1</a>. Using <a href="https://sigmoid.social/tags/miniscope" class="mention hashtag" rel="nofollow noopener" target="_blank">#miniscope</a> imaging, they show deep and superficial CA1 <a href="https://sigmoid.social/tags/PyramidalNeurons" class="mention hashtag" rel="nofollow noopener" target="_blank">#PyramidalNeurons</a> encode position and running direction via distinct ring manifolds, manipulable via <a href="https://sigmoid.social/tags/chemogenetics" class="mention hashtag" rel="nofollow noopener" target="_blank">#chemogenetics</a>. Fascinating for revealing parallel, cell-type–specific spatial topologies 👌🌍 <a href="https://doi.org/10.1016/j.neuron.2025.01.022" rel="nofollow noopener" translate="no" target="_blank">https://doi.org/10.1016/j.neuron.2025.01.022</a><a href="https://sigmoid.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#Neuroscience</a> <a href="https://sigmoid.social/tags/CompNeuro" class="mention hashtag" rel="nofollow noopener" target="_blank">#CompNeuro</a>

Elias MB RauFor everyone who can not attend the CCN Conference this year in amsterdam, all keynote lectures can be streamed here:<a href="https://2025.ccneuro.org/keynote-lectures/" rel="nofollow noopener" translate="no" target="_blank">https://2025.ccneuro.org/keynote-lectures/</a>Full schedule with livestream links here: <a href="https://2025.ccneuro.org/schedule-of-events/" rel="nofollow noopener" translate="no" target="_blank">https://2025.ccneuro.org/schedule-of-events/</a>First off, Nancy Kanwisher at 11.30 am (CET)Edit: Not only keynotes but also symposia can be live streamed 🙂 <a href="https://synapse.cafe/tags/ccn2025" class="mention hashtag" rel="nofollow noopener" target="_blank">#ccn2025</a> <a href="https://synapse.cafe/tags/neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#neuroscience</a> <a href="https://synapse.cafe/tags/cognitivescience" class="mention hashtag" rel="nofollow noopener" target="_blank">#cognitivescience</a> <a href="https://synapse.cafe/tags/computationalneuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#computationalneuroscience</a> <a href="https://synapse.cafe/tags/CompNeuro" class="mention hashtag" rel="nofollow noopener" target="_blank">#CompNeuro</a>

Dan GoodmanNew preprint with <a href="https://neuromatch.social/@marcusghosh" class="u-url mention" rel="nofollow noopener" target="_blank">@marcusghosh</a> on how neural network architecture shapes function. We explored a wide range of architectures, and a family of tasks with components of navigation, decision making under uncertainty, multimodal integration and memory. Performance better explained by "computational traits" like sensitivity and memory, than by architectural features. <a href="https://www.biorxiv.org/content/10.1101/2025.07.28.667142v1" rel="nofollow noopener" translate="no" target="_blank">https://www.biorxiv.org/content/10.1101/2025.07.28.667142v1</a><a href="https://neuromatch.social/tags/neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#neuroscience</a> <a href="https://neuromatch.social/tags/compneuro" class="mention hashtag" rel="nofollow noopener" target="_blank">#compneuro</a> <a href="https://neuromatch.social/tags/computationalneuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#computationalneuroscience</a>

Dan GoodmanHow can we test theories in neuroscience? Take a variable predicted to be important by the theory. It could fail to be observed because it's represented in some nonlinear, even distributed way. Or it could be observed but not be causal because the network is a reservoir. How can we deal with this?Increasingly feel like this isn't a theoretical problem but a very practical one that comes up all the time. I'd be interested if anyone has seen anything practical that addresses this.<a href="https://neuromatch.social/tags/neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#neuroscience</a> <a href="https://neuromatch.social/tags/compneuro" class="mention hashtag" rel="nofollow noopener" target="_blank">#compneuro</a>

Alicia Izquierdo, Ph.D.📣 Preprint alert ✨New insights into the tradeoff of effort and delay costs! A collaboration with the Wikenheiser lab <a href="https://neuromatch.social/tags/neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#neuroscience</a> <a href="https://neuromatch.social/tags/compneuro" class="mention hashtag" rel="nofollow noopener" target="_blank">#compneuro</a> <a href="https://www.biorxiv.org/content/10.1101/2025.06.03.657635v1" rel="nofollow noopener" translate="no" target="_blank">https://www.biorxiv.org/content/10.1101/2025.06.03.657635v1</a>

Dan GoodmanHow 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.New preprint from <a href="https://mastodon.social/@yang_chu" class="u-url mention" rel="nofollow noopener" target="_blank">@yang_chu</a>. <a href="https://arxiv.org/abs/2001.10605" rel="nofollow noopener" translate="no" target="_blank">https://arxiv.org/abs/2001.10605</a>Thread below 👇<a href="https://neuromatch.social/tags/neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#neuroscience</a> <a href="https://neuromatch.social/tags/computationalneuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#computationalneuroscience</a> <a href="https://neuromatch.social/tags/compneuro" class="mention hashtag" rel="nofollow noopener" target="_blank">#compneuro</a> <a href="https://neuromatch.social/tags/compneurosci" class="mention hashtag" rel="nofollow noopener" target="_blank">#compneurosci</a>

Dan GoodmanWhat neuroscience / comp neuro papers would you put on a recommended reading list if you wanted to emphasise the creativity, inspiration and joy of the field? I think some suggestions would overlap with the most famous or epochal papers, but some might be quite different.And can you post links if possible? 🙏<a href="https://neuromatch.social/tags/neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#neuroscience</a> <a href="https://neuromatch.social/tags/compneuro" class="mention hashtag" rel="nofollow noopener" target="_blank">#compneuro</a>

Dan GoodmanNew preprint! A simple way to extend the classical evidence weighting model of multimodal integration to solve a much wider range of naturalistic tasks. Spoiler: it's nonlinearity. Works for SNNs/ANNs. 🧵 with <a href="https://neuromatch.social/@marcusghosh" class="u-url mention" rel="nofollow noopener" target="_blank">@marcusghosh</a>, Gabriel Béna, Volker Bormuth<a href="https://www.biorxiv.org/content/10.1101/2023.07.24.550311v1" rel="nofollow noopener" translate="no" target="_blank">https://www.biorxiv.org/content/10.1101/2023.07.24.550311v1</a><a href="https://neuromatch.social/tags/neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#neuroscience</a> <a href="https://neuromatch.social/tags/compneuro" class="mention hashtag" rel="nofollow noopener" target="_blank">#compneuro</a> <a href="https://neuromatch.social/tags/SpikingNeuralNetworks" class="mention hashtag" rel="nofollow noopener" target="_blank">#SpikingNeuralNetworks</a> <a href="https://neuromatch.social/tags/preprint" class="mention hashtag" rel="nofollow noopener" target="_blank">#preprint</a>

Dan Goodman<a href="https://neuromatch.social/tags/introduction" class="mention hashtag" rel="nofollow noopener" target="_blank">#introduction</a> I'm a computational neuroscientist (<a href="https://neuromatch.social/tags/Neuroscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#Neuroscience</a> <a href="https://neuromatch.social/tags/CompNeuro" class="mention hashtag" rel="nofollow noopener" target="_blank">#CompNeuro</a>) and science reformer based at Imperial College London.I like to build things and organisations that make it easier to do better <a href="https://neuromatch.social/tags/science" class="mention hashtag" rel="nofollow noopener" target="_blank">#science</a>.I made the Brian spiking neural network simulator (<a href="https://briansimulator.org" rel="nofollow noopener" target="_blank">https://briansimulator.org</a>) with <a href="https://mastodon.social/@romainbrette" class="u-url mention" rel="nofollow noopener" target="_blank">@romainbrette</a> and <a href="https://neuromatch.social/@mstimberg" class="u-url mention" rel="nofollow noopener" target="_blank">@mstimberg</a>. I co-founded <a href="https://neuromatch.social/tags/Neuromatch" class="mention hashtag" rel="nofollow noopener" target="_blank">#Neuromatch</a> with <a href="https://neuromatch.social/@kordinglab" class="u-url mention" rel="nofollow noopener" target="_blank">@kordinglab</a> and a bunch of others, and the SNUFA community with <a href="https://mas.to/@fzenke" class="u-url mention" rel="nofollow noopener" target="_blank">@fzenke</a>.In my main research, I'm interested in how the brain uses spikes to carry out computations, and what advantages that might have. Increasingly, my work revolves around using methods from <a href="https://neuromatch.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#MachineLearning</a> because that finally lets us build models that actually require intelligence, the unique property of the brain I'm interested in.I also want to make science better. Neuromatch's mission is to democratise science, and with our new open <a href="https://neuromatch.social/tags/publishing" class="mention hashtag" rel="nofollow noopener" target="_blank">#publishing</a> initiative (<a href="https://nmop.io" rel="nofollow noopener" target="_blank">https://nmop.io</a>) I'm hoping we'll be able to dramatically change the murky world of academic publishing.You might (ha!) also see some political commentary from me. I'm a left-wing <a href="https://neuromatch.social/tags/anarchist" class="mention hashtag" rel="nofollow noopener" target="_blank">#anarchist</a>.Happy to discuss any of the above!

Alice Schwarze<a href="https://fediscience.org/tags/introduction" class="mention hashtag" rel="nofollow noopener" target="_blank">#introduction</a> time!I do <a href="https://fediscience.org/tags/appliedmath" class="mention hashtag" rel="nofollow noopener" target="_blank">#appliedmath</a> at Dartmouth College. I am all about using <a href="https://fediscience.org/tags/math" class="mention hashtag" rel="nofollow noopener" target="_blank">#math</a> to model <a href="https://fediscience.org/tags/complexsystems" class="mention hashtag" rel="nofollow noopener" target="_blank">#complexsystems</a> + <a href="https://fediscience.org/tags/networks" class="mention hashtag" rel="nofollow noopener" target="_blank">#networks</a> in <a href="https://fediscience.org/tags/compbio" class="mention hashtag" rel="nofollow noopener" target="_blank">#compbio</a>, <a href="https://fediscience.org/tags/compneuro" class="mention hashtag" rel="nofollow noopener" target="_blank">#compneuro</a> & <a href="https://fediscience.org/tags/compsoc" class="mention hashtag" rel="nofollow noopener" target="_blank">#compsoc</a>, and to improve methods in <a href="https://fediscience.org/tags/datascience" class="mention hashtag" rel="nofollow noopener" target="_blank">#datascience</a> and <a href="https://fediscience.org/tags/ml" class="mention hashtag" rel="nofollow noopener" target="_blank">#ml</a>. (Have worked on <a href="https://fediscience.org/tags/emergence" class="mention hashtag" rel="nofollow noopener" target="_blank">#emergence</a> of correlation patterns and <a href="https://fediscience.org/tags/causalinference" class="mention hashtag" rel="nofollow noopener" target="_blank">#causalinference</a> and now getting into <a href="https://fediscience.org/tags/explanaible" class="mention hashtag" rel="nofollow noopener" target="_blank">#explanaible</a> <a href="https://fediscience.org/tags/machinelearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#machinelearning</a> for <a href="https://fediscience.org/tags/publichealth" class="mention hashtag" rel="nofollow noopener" target="_blank">#publichealth</a> / <a href="https://fediscience.org/tags/mentalhealth" class="mention hashtag" rel="nofollow noopener" target="_blank">#mentalhealth</a>.)Would love to connect with the <a href="https://fediscience.org/tags/mastodonscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#mastodonscience</a> crowd, <a href="https://fediscience.org/tags/womeninmath" class="mention hashtag" rel="nofollow noopener" target="_blank">#womeninmath</a>, <a href="https://fediscience.org/tags/womeninstem" class="mention hashtag" rel="nofollow noopener" target="_blank">#womeninstem</a>, <a href="https://fediscience.org/tags/python" class="mention hashtag" rel="nofollow noopener" target="_blank">#python</a>, <a href="https://fediscience.org/tags/dataviz" class="mention hashtag" rel="nofollow noopener" target="_blank">#dataviz</a> folks, and fellow <a href="https://fediscience.org/tags/cat" class="mention hashtag" rel="nofollow noopener" target="_blank">#cat</a> lovers!

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