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52 websites were sharing my activity with facebook, like a little blue ghost stalker
https://twitter.com/jengolbeck/status/1222246209676546048 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Ari Benjamin proslijedio/la je Tweet
SYNPLA, a method to identify synapses displaying plasticity after learninghttps://www.pnas.org/content/early/2020/01/22/1919911117 …
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More than any single idea we came up with, having a continued practice of reflection that engaged everyone really boosted how much folks engage with the lab. But we came up with good ideas too. How about you all? What lab practices do you have that you're proud of?
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What makes a good lab? Are group meetings really the best way? In the
@KordingLab we recently reexamined how we organize our weeks, and then redesigned everything in a systematic way (100% democratically!). I blogged about our design process and takeaways: http://kordinglab.com/2019/12/20/lab-redesign.html …pic.twitter.com/P7Z5YG4nLh
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As I understand it, that theorem is the one that says that, if a sender and receiver agree on a code, it requires -log r bits to communicate an event that has probability r
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From Dayan and Abbott Ch. 10: "A theorem due to Shannon describes circumstances under which a generative model that maximizes the likelihood over input data also provides the most efficient way of coding those data, so density estimation is closely related to optimal coding."
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I recently learned that having a efficient neural code (in the Barlow sense) is connected to having a good generative model. Took me by surprise! But makes sense in retrospect
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Modest Mouse was right all along: The universe is shaped exactly like the earth — if you go straight long enough you'll end up where you werehttps://twitter.com/nattyover/status/1191390898086531073 …
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Ari Benjamin proslijedio/la je TweetHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Ari Benjamin proslijedio/la je Tweet
It is now live: Ten common statistical mistakes to watch out for when writing or reviewing a manuscript https://doi.org/10.7554/eLife.48175 … Use the annotation function to leave your comments/ideas/solutionspic.twitter.com/7lZfxGXceG
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I'm proud of this! Very clear (I hope
) introduction to machine learning if you're interested in neural decodinghttps://twitter.com/joshuaiglaser/status/1179041819012866048 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Ah Matt I couldn't find your handle! Everyone should follow
@SmithLabNeuroPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
It’s a hard question that we’ve thought carefully about. There’s an empirical and a theoretical side. Our thoughts are in the Discussion, but please, tell us your thoughts!
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This is obviously about how we understand V4’s activity. But we also think this is a cautionary tale for the vary-stimuli-in-a-parameterized-way approach. When does this approach tell you about a neuron's response on other stimuli & the neuron's general role?
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We then compared these tuning curves to hue tuning curves estimated using artificial stimuli. Were they similar? Not really. Stated cleanly: in different visual contexts, the immediate effect of varying hue upon the response was different.
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We tried reverse-correlation approaches and also a new method: we fit a nonlinear V4 model (based on ImageNet-trained DNNs, Yamins/DiCarlo style) and characterized how tiny perturbations to hue affected the model’s response.
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It took a few years to get it right, but we managed to estimate tuning of macaque V4 neurons from natural scenes. We looked at hue tuning, since there's a already big literature about color responses in V4.
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In V1 there’s a rich literature asking this question by estimating tuning from natural scene responses. But what about in higher areas, like V4? We can’t use the same methods, since responses are so nonlinear.
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So, a classic way to ask "what does neural activity mean?" in the visual cortex is to vary stimuli in a systematic, parameterized way while recording responses. But do those results tell you what activity 'means' in other contexts, like while viewing natural scenes?
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New preprint! Does V4’s tuning to hue on artificial stimuli tell us about its tuning to hue on natural images? Not really. (Twitterified in the thread below) https://www.biorxiv.org/content/10.1101/780478v1 … with
@desipoika,@jugoguj, Matthew Smith, and@KordingLabpic.twitter.com/c7Bu8JFHsm
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