Columbia NeuroTheory Profile
Columbia NeuroTheory

@cu_neurotheory

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3K
Following
270
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123

Center for Theoretical Neuroscience @ZuckermanBrain @Columbia, where experimentation, data analysis, and computational neuroscience come together

Jerome L Greene Science Center
Joined January 2018
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@IntlBrainLab
International Brain Laboratory
1 year
Check out our new tutorial series to learn how to use the Lightning Pose app, on a local workstation or in the cloud. We start from the basics and work up to advanced topics like deep ensembling and active learning: https://t.co/yu2VRibf9r
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@chingfang17
Ching Fang (chingfang.bsky.social)
1 year
New work with @Jack_W_Lindsey, Larry Abbott, Dmitriy Aronov, and @selmaanchettih! We propose a model of episodic memory where memories are bound to “barcode” activity patterns, enabling precise and flexible memory. https://t.co/5fth544FS2
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biorxiv.org
Forming an episodic memory requires binding together disparate elements that co-occur in a single experience. One model of this process is that neurons representing different components of a memory...
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@Starlink
Starlink
25 days
Starlink Mini offers fast, reliable internet on the go—great for traveling, camping, exploring, boating, RVing, and more. Stay connected without dead zones or slow speeds. Order online in under 2 minutes.
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@allemanjm
Matteo
1 year
We live with the limitations of our memory, but don’t really know where they come from. Our new paper ( https://t.co/DYiL0IfxvF) studies "swap errors", which we argue arise during memory manipulation – see thread for more! @timbuschman, @MattPanichello, @wjeffjohnston
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@wjeffjohnston
Jeff Johnston
1 year
How does the brain bind action to value? How does it navigate a tradeoff between this binding and generalization to novel situations? Out today in Nature Neuro! https://t.co/YPiY2uHoFz @JustFineNeuro @NeuroPolarbear @BecketEbs @neuromochi See original 🧵 + updates below
@wjeffjohnston
Jeff Johnston
2 years
How does the brain represent multiple different things at once in a single population of neurons? @JustFineNeuro, @NeuroPolarbear, @BecketEbs, @neuromochi and I show that it uses semi-orthogonal subspaces for each item. Preprint here: https://t.co/CFvI4PHgjP Tweets below! (1/n)
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@naturemethods
Nature Methods
1 year
Lightning Pose is an efficient pose estimation approach that requires few labeled training data owing to its semi-supervised learning strategy and ensembling. @dan_biderman @cu_neurotheory @ZuckermanBrain @IntlBrainLab @Columbia https://t.co/Snw7F05aZA
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@cu_neurotheory
Columbia NeuroTheory
2 years
The Paninski Lab is seeking a research software engineer to work with computational and experimental neuroscience labs at the Zuckerman Institute and International Brain Lab to develop cutting edge tools for analyzing behavioral video data:
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@BrainPrize
The Brain Prize
2 years
Yesterday, we had the immense pleasure of celebrating neuroscience as we awarded Professors @HSompolinsky, Terrence Sejnowski, and Larry Abbott with #TheBrainPrize2024 medals for their pioneering contributions to the fields of computational and theoretical neuroscience. Thank you
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@chingfang17
Ching Fang (chingfang.bsky.social)
2 years
Excited to share a new paper with @neuro_kim: “Predictive auxiliary objectives in deep RL mimic learning in the brain”, which has been accepted as an #ICLR2024 oral and #Cosyne2024 talk! https://t.co/JuzMmWLqKh. A short summary:
openreview.net
The ability to predict upcoming events has been hypothesized to comprise a key aspect of natural and machine cognition. This is supported by trends in deep reinforcement learning (RL), where...
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@taherehtoosi
Tahereh Toosi
2 years
Today I am presenting this work at #NeurIPS2023, 10:45 AM, poster session 3, poster #401.
@taherehtoosi
Tahereh Toosi
2 years
There are plenty of feedback connects in visual cortex, and they contribute to so many perceptual experiences (e.g imagination, de-occlusions, hallucinations), but HOW? In a #NeurIPS2023 paper, we show alignment of the feedback and feedforward is the key! https://t.co/YOmRidwzkY
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@taherehtoosi
Tahereh Toosi
2 years
There are plenty of feedback connects in visual cortex, and they contribute to so many perceptual experiences (e.g imagination, de-occlusions, hallucinations), but HOW? In a #NeurIPS2023 paper, we show alignment of the feedback and feedforward is the key! https://t.co/YOmRidwzkY
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@APalmigiano
Agostina Palmigiano
2 years
📢 Multiple postdoctoral positions in Theoretical Neuroscience available at the Gatsby Computational Neuroscience Unit (PI: A Palmigiano) to develop both normative and data-driven theoretical approaches to link dynamics and computation. Apply by Jan 16! https://t.co/kR0yN34Kim
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ucl.ac.uk
UCL is consistently ranked as one of the top ten universities in the world (QS World University Rankings 2010-2022) and is No.2 in the UK for research power (Research Excellence Framework 2021).
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@APalmigiano
Agostina Palmigiano
2 years
Really happy to share that our reshuffling paper is now out https://t.co/J67ZIBITmJ 🥳. Super fun theory-theory collab, see tweet print by co-first @AlessandroSzeni below for more info
@AlessandroSzeni
Alessandro Sanzeni
2 years
New work with @APalmigiano, Tuan Nguyen, @kendmil, and Nicolas Brunel at @NeuroCellPress : Unveiling the Mechanisms Behind Reshuffling Visual Responses via Optogenetic Stimulation in Mice and Monkeys 🐭🐒 (thread follows)
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@GatsbyUCL
Gatsby Computational Neuroscience Unit
2 years
We are delighted to announce that Dr Agostina Palmigiano (@APalmigiano) will join the Gatsby Unit as Lecturer in January, developing data-driven theoretical approaches to uncover neural mechanisms underlying cognitive functions. Learn more at https://t.co/sJaIdH1YWw
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@chingfang17
Ching Fang (chingfang.bsky.social)
3 years
Excited to share triple (!) joint publications on bio-learning rules for the successor representation. With D. Aronov, L. Abbott, @e_mackevicius, we show RNNs can learn flexible predictive maps. Turns out two other groups were working on similar problems! https://t.co/JJEcdsuRFu
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elifesciences.org
A recurrent network using a simple, biologically plausible learning rule can learn the successor representation, suggesting that long-horizon predictions are computations that are easily accessible...
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@StefanoFusi2
Stefano Fusi
3 years
And this is an alternative cover, again from @matteofarinella, still describing the results of https://t.co/guzcsMyNgl
@RNogueiraNeuro
Ramon Nogueira
3 years
Our recent study with @chrisXrodgers, @TheBrunoCortex, and @StefanoFusi2 was highlighted in @NatRevNeurosci last week, nicely summarized by @jakestarmovemnt. Also, one of the cover proposals that was submitted, beautiful work by the great @matteofarinella https://t.co/9nQ8tRZccC
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@cu_neurotheory
Columbia NeuroTheory
3 years
👏👏
@RNogueiraNeuro
Ramon Nogueira
3 years
Our recent study with @chrisXrodgers, @TheBrunoCortex, and @StefanoFusi2 was highlighted in @NatRevNeurosci last week, nicely summarized by @jakestarmovemnt. Also, one of the cover proposals that was submitted, beautiful work by the great @matteofarinella https://t.co/9nQ8tRZccC
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@cu_neurotheory
Columbia NeuroTheory
3 years
👇🧵!
@RNogueiraNeuro
Ramon Nogueira
3 years
Our article “The geometry of cortical representations of touch in rodents” with @chrisXrodgers @TheBrunoCortex @StefanoFusi2 is finally out! In brief, we found that whisker contacts in mice S1 are represented in approximately orthogonal subspaces https://t.co/BSzOqUPwuL 👇🧵
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@jamespriestley4
James Priestley
3 years
I’m really excited to share that I will start my lab in 2023 at @epflSV in Lausanne as an ELISIR fellow! The lab will combine computational and experimental approaches to study the function of hippocampal-entorhinal circuits in memory formation! Interested in joining? ⬇️
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@NeuroCellPress
Neuron
3 years
New issue is out: https://t.co/ImgPc6z4Dp The cover illustrates an open-source platform for scalable, reproducible data analysis by Taiga Abe (@TrackingNoise) & coll. Find this free featured #NeuroResource here: https://t.co/EnZv2QB9ta
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@MarioDipoppa
Mario Dipoppa
4 years
Thrilled to share that I will be joining the amazing community at @UCLA in 2023 as an Assistant Professor in theoretical neuroscience in the Dept of Neurobiology! My lab will investigate the principles of cortical computations through biologically realistic neural networks.
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