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Josh Glaser proslijedio/la je Tweet
Cosyne schedules are up! Be sure to come to our workshop (organized w/
@mikio_aoi@anqiwu_angela@joshuaiglaser and Matt Whiteway) "Interpretable computational neuroscience: What are we modeling and what does it have to do with the brain?"https://sites.google.com/view/cosyneinterpretablecompneuro/about …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Josh Glaser proslijedio/la je Tweet
I'm very excited to share that my work with
@PresNCM and@joshuaiglaser on S1 representation of reaching is now published in eLife! Thanks to some insightful reviewer comments, I think it's become a much stronger paper now. Begin thread... (1/6)https://elifesciences.org/articles/48198Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Josh Glaser proslijedio/la je Tweet
Excited to share what
@jpillowtime@scott_linderman and I have been working on recently! We unify and generalize statistical models of neural dynamics during decision-making using switching state-space models https://arxiv.org/abs/2001.04571 pic.twitter.com/KKtSGPhKhN
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Josh Glaser proslijedio/la je Tweet
So let's say you record 100 neurons from each of 5 animals in response to 2 different stimuli... or count dendritic spines on 100 neurons in each of 10 animals, with half of animals subjected to 1 of 2 drug conditions... Then you've got hierarchical data. (THREAD)https://twitter.com/biorxiv_neursci/status/1188921499681480704 …
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Josh Glaser proslijedio/la je Tweet
During natural scene search, the frontal eye field represents the prior probability of a saccade direction. Paper finally out with
@joshuaiglaser, Wood, Segraves :https://academic.oup.com/cercor/advance-article/doi/10.1093/cercor/bhz216/5588869?guestAccessKey=8ec8f346-d3c1-4b30-8daf-597e7937047b …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Josh Glaser proslijedio/la je Tweet
Check out our new preprint on using multi-area recurrent neural networks to better understand decision-making. This is joint work with first author
@MichaelKleinman and co-senior author@ChandMuse.http://biorxiv.org/content/10.1101/798553v1 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
We've turned our "Machine learning for neural decoding" paper into a tutorial. Check it out! w/
@arisbenjamin@KordingLab@raeedcho@mattperich@PresNCM https://arxiv.org/abs/1708.00909 And our code package:https://github.com/kordingLab/neural_decoding …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Josh Glaser proslijedio/la je Tweet
"Due to random chance, some percentage of models will outperform other ones, even if they are all just as good as each other. Maths doesn’t care if it was one team that tested 100 models, or 100 teams."https://lukeoakdenrayner.wordpress.com/2019/09/19/ai-competitions-dont-produce-useful-models/ …
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Josh Glaser proslijedio/la je Tweet
Neuroscience needs interpretable models of neural population activity. Great new review relating this to latent variable models.https://buff.ly/2HgAjrg
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Josh Glaser proslijedio/la je Tweet
Animals will respond differently to the same inputs when they are hungry/sated, attentive/bored, etc. But how do we know what state the animal is in? In this preprint with
@jpillowtime@MurthyLab, we show how you can do that automatically!
https://www.biorxiv.org/content/10.1101/691196v1 …pic.twitter.com/wPQsAKz82p
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Josh Glaser proslijedio/la je Tweet
We have a new preprint on bioRxiv Area 2 neural coding in monkeys it describes I want you to read it But so I could tweet it I wrote these six limericks to serve as a guide! (1/6)
@joshuaiglaser@PresNCMhttp://biorxiv.org/content/10.1101/643205v1 …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Josh Glaser proslijedio/la je Tweet
Hierarchical Recurrent State Space Models Reveal Discrete and Continuous Dynamics of Neural Activity in C. elegans https://www.biorxiv.org/content/10.1101/621540v1 … This has been a big part of my postdoc and I'm glad to finally share it! Huge thanks to my coauthors/mentors Annika, Dave, Manuel, and Liam.
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Josh Glaser proslijedio/la je Tweet
Omitted variable bias is what makes confounding problematic. I love
@ihstevenson's analysis of the effect of the omitted variable bias on GLMs:https://www.mitpressjournals.org/doi/full/10.1162/neco_a_01138 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Josh Glaser proslijedio/la je Tweet
Call for Applications: NeuroNex Junior Scientist Workshop on Advanced Neural Data Analysis, Aug 26-29 2019. Details here: https://ctn.zi.columbia.edu/junior
#wanda19Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Josh Glaser proslijedio/la je Tweet
Check out our new review on the importance of analyzing population activity in neuroscience! "Towards the neural population doctrine." https://www.sciencedirect.com/science/article/pii/S0959438818300990 …
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A final version of our review on the roles of supervised ML in neuroscience is out! w/
@arisbenjamin@aha_momentum@KordingLab https://authors.elsevier.com/c/1Ydmu14SFlxI6u …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
In fact, a greater proportion of EMG was explained by a nonlinear gain than a linear mapping. This can help to explain how motor cortex controls the wide range of forces encountered in the real world. 3/3
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In a single task, muscle EMGs can be predicted relatively well using a linear mapping from the activity of motor cortex neurons. However, when using multiple tasks that span a wide range of forces, we found that this mapping was highly nonlinear. 2/3
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We're excited to share our new paper w/
@snaufel,@presncm,@kordinglab https://www.physiology.org/doi/pdf/10.1152/jn.00329.2018 … 1/3Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Josh Glaser proslijedio/la je Tweet
New preprint by brilliant
@JosueNassar in my group. A new state-space model with multi-scale hierarchical dynamics prior. https://arxiv.org/abs/1811.12386 Collaboration with@scott_linderman and Monica Bugallo#sciencestorm#neuroscience#Bayesian#MachineLearning 1/6pic.twitter.com/127P61uIBn
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