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Blokirali ste korisnika/cu @Braden_Brinkman
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And one of them is reportedly based on Beast Wars...? Don't you toy with my 90's childhood dreams internet, just be true and https://twitter.com/DEADLINE/status/1221943929899118592 …pic.twitter.com/RIPxKjC97L
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@mabuice@gkochocker you might be interested in this!Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Giving a talk at 2 pm Eastern NA on recent work investigating spiking network models using methods from the non-perturbative renormalization group! Streaming live here: http://scgp.stonybrook.edu/live https://twitter.com/SBUNeurobiology/status/1218163562872483840 …
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Braden! proslijedio/la je Tweet
4yo in backseat after preschool: "Mom, did you know we're all animals?" Mom: "Yes, that's right! We're anima-" 4yo, confidently: "I'm a lamb."
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Braden! proslijedio/la je TweetHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Braden! proslijedio/la je Tweet
37 years with
#T1D today & this list pretty much still stands. I’m grateful to the DIY community for making more self-management options available. Everyone with diabetes should have helpful, accessible options, and for goodness’ sake, we need#insulin4all.
to all fellow PWD.https://twitter.com/hwitteman/status/690727072411578369 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Braden! proslijedio/la je Tweet
When I finish something and realize I never put it on my to-do list, I write it in just so that I can have the satisfaction of deleting it.https://twitter.com/Yascha_Mounk/status/1219370418051698693 …
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Braden! proslijedio/la je Tweet
2020 Wolf Prize in Mathematics awarded jointly to Simon Donaldson (Simons Center, Stony Brook) and Yakov Eliashberg (Stanford University). Listen to my interview with the great Donaldson in the podcast ‘The Universe Speaks in Numbers’...https://wolffund.org.il/2020/01/13/simon-donaldson/ …
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Braden! proslijedio/la je TweetHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Braden! proslijedio/la je Tweet
Fresh on
@bioRxiv. Latent trajectory analysis of MT ensemble spike trains reveals mis-aligned subspaces of stimulus and decision codes.#tweeprint https://www.biorxiv.org/content/10.1101/2019.12.20.884189v1.full … Collaboration with Huk lab.@yuanz271@jcbytspic.twitter.com/O0grpowbPF
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Finally, some citations! E-I Net: http://www.pking.org/research/EINet/ SAILnet (E-I Net parent): http://www.jzlab.org/sailcodes.html Decreased GABA w/ age expts: https://www.ncbi.nlm.nih.gov/pubmed/18158105 Increased excitability + decreased selectivity expts: https://www.ncbi.nlm.nih.gov/pubmed/16298251 + more in paper! 10/N, N=10
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If Seth Talyansky ever applies to work in your lab, I highly recommend you accept (& fast, before someone else does!) 9/N
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So we decided to modify learning rules after network reached steady state, & Seth continued working on the project remotely, finally resulting in this preprint! He did a tremendous job & I'm very lucky to have had the privilege to work on this with him! 8/N
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Our original approach was to train network to 'maturity' & scale down inhibitory synaptic weights to reflect expt'ly observed GABA loss, then show loss of orientation selectivity. It kind of worked, but wasn't result of an aging-like *process*, & Seth wanted to do more 7/N
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Seth, now an undergrad at Stanford, started this project as part of
@stonybrooku's Simons Summer Research Program for high school students. The idea resulted from reading up on expt results to work in his interest in aging, & thinking about what was doable in 6 wks 6/NPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
If broken learning rule is interpreted as homeostatic mechanism regulating network target firing, our results suggest that breakdown in such homeostatic mechanisms w/ age is a possible cause of expt'ly observed changes in old brains & an avenue to investigate further 5/N
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We tested how functional performance changed by measuring neural selectivity to oriented gratings; expts show this sensitivity decreases w/ age. We also find that our 'aged' network loses selectivity, and show that it's due to loss of Gabor-like receptive fields 4/Npic.twitter.com/FN46kPg84h
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This change was anticipated to produce increased network excitability in old 'age', as observed in expts. Indeed, not only does excitability increase, but synaptic weights decrease, consistent w/ expts that observe decreased GABAergic neuron density in old brains 3/Npic.twitter.com/7afxwaAq9g
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We model how (healthy!) aging impacts network physiology & performance using E-I Net, a spiking network model trained on images. After initial training phase, we 'break' the learning rule regulating neural firing to allow rate to increase w/ more training, the 'aging' phase 2/Npic.twitter.com/4ntxjLwYlD
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Earlier this week I posted 1st
@biorxivpreprint as PI! "Dysregulation of neural excitability replicates physiological and functional changes in aging visual cortex." 1st author Seth Talyansky's interest in brain aging sparked initial idea for project https://www.biorxiv.org/content/10.1101/2020.01.06.896324v1 … 1/NPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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