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Prikvačeni tweet
New
@biorxivpreprint on the distribution of information across neurons of large neural populations, with MohammadMehdi Kafashan,@awjaffe,@selmaanchettih, @RNugeiraNeuro, Iñigo Arandia-Romero, Chris Harvey, and@MorenoBote:https://doi.org/10.1101/2020.01.10.902171 …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jan Drugowitsch proslijedio/la je Tweet
Happy to announce CoSMo 2020! Aug 2-16 @ London, ON We have revamped our summer school on Computational Sensory-Motor Neuroscience to integrate traditional modeling with modern ML! With
@KordingLab@Schrater_Lab@meganakpeters http://www.compneurosci.com/CoSMo/Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Jan Drugowitsch proslijedio/la je Tweet
Our article is out today
@SfNJournals! Great collaboration with Nicole Peltier, Akiyuki Anzai, Greg DeAngelis,@JulioMTNeuro and@MorenoBote. See below for a short description 1/Nhttps://www.jneurosci.org/content/40/5/1066.abstract?etoc …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Jan Drugowitsch proslijedio/la je Tweet
Distributional reinforcement learning (RL) algorithms predict the entire ‘distribution’ of future rewards not just the average and improve the AI performance. This work presents evidence that the brain’s dopamine system uses distributional RL.https://www.nature.com/articles/s41586-019-1924-6 …
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A quick reminder to never cite predatory journals: one of them just published an almost verbatim copy of @AKutschireiter's (lab member) previous
@SciReports article https://doi.org/10.1038/s41598-017-06519-y …pic.twitter.com/qPlfUVwX3F
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Jan Drugowitsch proslijedio/la je Tweet
PhD and Post-Doc positions are available in my lab. Do you love math, respect philosophy and have a passion for comp neuro? Then you can be a good fit. Talented candidates, please send me a CV to ruben.moreno@upf.edu. Funding from HHMIpic.twitter.com/0mO4lyzT3X
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Furthermore, until the DOI link works, you can access the preprint athttps://www.biorxiv.org/content/10.1101/2020.01.10.902171v1 …
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... and here is Ramon's correct Twitter handle:
@RNogueiraNeuroPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Overall, these findings suggest that the brain uses a widely distributed, but nonetheless redundant code that supports recovering most information from smaller subpopulations.
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Furthermore, we found that most neurons in visual cortex contain relevant information about the stimulus. Notably, for the purpose of decoding, we found that a random set of neurons in visual cortex is as good as an "optimized" set of neurons.pic.twitter.com/zUdmtiNMcr
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This predicts that tens of thousands of neurons are required to encode 95% of the information about visual stimulus direction, a number much smaller than the number of neurons in V1.pic.twitter.com/PbLZTyEBxO
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Using the theory of information-limiting correlations, we compartmentalized noise correlations into information-limiting and non-limiting components, and then extrapolated to predict how information grows when neural populations are even larger.pic.twitter.com/LVhx7PF5Dl
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We found that information scales sublinearly with population size, due to the presence of correlated noise in these populations.pic.twitter.com/HP19xXOiI8
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To distinguish these possibilities we recorded from primary visual cortex of mice observing moving visual stimuli, and asked how information about the motion direction is distributed across hundreds of simultaneously recorded neurons.
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We asked how information is distributed across such populations within a given brain area. If distributed roughly evenly, total information scales linearly with the number of recorded neurons. If highly redundant, total information saturates.pic.twitter.com/lXj3c4HLgQ
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Jan Drugowitsch proslijedio/la je Tweet
We're hiring! Join our lab for a postdoc in computational neuroscience in New York https://sites.google.com/site/rubencoencagli/202001_PostdocAd.pdf?attredirects=0 …
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For some holiday fun: adaptive worst-case Minesweeper https://pwmarcz.pl/kaboom/
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Jan Drugowitsch proslijedio/la je Tweet
The Williamson Lab is still looking to hire postdocs! Anyone interested in using cool technologies (2P, optogenetics, ephys, and machine learning) to study how auditory cortical organization leads to purposeful behavior, just get in touch! Please retweet!https://www.williamsonlaboratory.com/opportunities
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... and for those interested in the nitty-gritty details, here is the code: https://github.com/DrugowitschLab/DDMLearningWithConfidence … 8/
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