@YuLikeNeuro

Yu Group at Carnegie Mellon University. Neuroscience, brain-computer interfaces, machine learning

 Pittsburgh, PA
users.ece.cmu.edu/~byronyu
Joined February 2021
  • Tweets108
  • Following9
  • Followers2.8K
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Replying to @YuLikeNeuro
If you have a background in neural technologies or related disciplines, and are enthusiastic about teaching, we encourage you to apply here: apply.interfolio.com/184248
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We (CMU Biomedical Engineering and Neuroscience Institute) are seeking to hire a new teaching-track faculty member for our new joint MS program in Neural Technologies (MiNT).
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We are excited to share our work on dynamical constraints on neural population activity, published as a cover article in @NatureNeuro. It was led by Emily Oby, @AlanDegenhart, @ErinnGrigsby, with @aaronbatista and team. nature.com/articles/s41593-0… (1/n)
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Here is the cover image (credit Avesta Rastan): (8/n)
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Thank you to @neuroamyo for a wonderful News & Views piece: nature.com/articles/s41593-0… (n/n)
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📣 The 11th Statistical Analysis of Neuronal Data (SAND11) workshop will be held June 11-13, 2025 in New York at the @FlatironInst with generous support from @SimonsFdn! Submissions for talks+posters are due March 21. See our website for details 👇 sandworkshop.github.io
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We've posted a new paper about how to speed up statistical methods for analyzing multi-area recordings by orders of magnitude: arxiv.org/abs/2412.16773 This work was led by Evren Gokcen, with Anna Jasper (Einstein), Adam Kohn (Einstein), and Christian Machens (Champalimaud).
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Transformative work happens through collaboration. New research from @CMUEngineering & @PittEngineering validates principles that researchers have brought out in neural network models for decades. @YuLikeNeuro @cmu_bme engineering.cmu.edu/news-eve…

The one-way paths of neural population activity

A collaborative team of researchers from Carnegie Mellon University and the University of Pittsburgh designed a clever experiment using a brain-controlled interface to determine whether one-way...

engineering.cmu.edu
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Using a brain–computer interface to challenge monkeys to override their natural time courses of neural activity reveals that the time courses are highly robust, suggestive of network-level computational mechanisms @aaronbatista @YuLikeNeuro @AlanDegenhart @ErinnGrigsb nature.com/articles/s41593-0…
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Byron Yu retweeted
Yuki Minai@curi_ms5 Dec 2024
I'm excited to share our #NeurIPS2024 paper with @jsoldadomagrane @SmithLabNeuro @YuLikeNeuro! We develop a new brain stimulation framework (MiSO) to drive neural population activity toward specified states. Paper: openreview.net/pdf?id=Gb0mXh… Poster Session 4 East, Dec 12 16:30 [1/n]
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We are excited to share our new method, SNOPS (Spiking Network Optimization using Population Statistics), published in @NatComputSci. It was led by @Shenghao_W, with @cc_huang11, Adam Snyder, @SmithLabNeuro, and @BrentDoiron. nature.com/articles/s43588-0… (1/n)

Automated customization of large-scale spiking network models to neuronal population activity

Nature Computational Science - An automatic framework, SNOPS, is developed for configuring a spiking network model to reproduce neuronal recordings. It is used to discover previously unknown...

nature.com
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SNOPS can also identify specific combinations of activity statistics that the model cannot reproduce, thereby guiding model development. (5/n)
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We encourage you to try SNOPS here: github.com/ShenghaoWu/Spikin… (n/n)

GitHub - ShenghaoWu/SpikingNetworkOptimization: Code for SNOPS

Code for SNOPS. Contribute to ShenghaoWu/SpikingNetworkOptimization development by creating an account on GitHub.

github.com
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