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Samuel Liebana

@samuel-liebana.bsky.social
93 followers 98 following 9 posts

Research Fellow at the Gatsby Unit, UCL Q: How do we learn?

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Reposted by Samuel Liebana
Ruairidh McLennan Battleday @battleday.bsky.social · 05/03/2026
📢📢 Announcing this year's conference on the Mathematics of Neuroscience & AI (Rome, 9-12th June). We’ve got a stellar line-up and venue, and invite everyone to join: www.neuromonster.org
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Reposted by Samuel Liebana
Blake Richards @tyrellturing.bsky.social · 27/03/2026
A great entry into the proposals available for physiologically plausible gradient descent! I think the way they use dendrite targeting inhibition in this model is particularly elegant. Time to start testing these ideas folks!!! #neuroscience 🧪 #NeuroAI
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Reposted by Samuel Liebana
The Transmitter @thetransmitter.bsky.social · 10/11/2025
Adopting an engineering mindset will help the field focus its research priorities, writes @timothyoleary.bsky.social. #neuroskyence www.thetransmitter.org/systems-neur...
thetransmitter.org
Neuroscience needs engineers—for more reasons than you think
Adopting an engineering mindset will help the field focus its research priorities.
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Samuel Liebana @samuel-liebana.bsky.social · 10/11/2025
Honored to have a research highlight featuring our work! A comprehensive overview of our results and their impact for future research and applications: www.nature.com/articles/s41...
nature.com
Dopamine as a teaching signal: understanding its role in shaping individual behavior - Signal Transduction and Targeted Therapy
Signal Transduction and Targeted Therapy - Dopamine as a teaching signal: understanding its role in shaping individual behavior
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Reposted by Samuel Liebana
Kris Jensen @kristorpjensen.bsky.social · 24/09/2025
I’m super excited to finally put my recent work with @behrenstimb.bsky.social on bioRxiv, where we develop a new mechanistic theory of how PFC structures adaptive behaviour using attractor dynamics in space and time! www.biorxiv.org/content/10.1...
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Reposted by Samuel Liebana
CMC Unit @cmc-unit.bsky.social · 18/09/2025
In our Learning Club @cmc-lab.bsky.social today (Aug 18, Thu, 2pm CET), Samuel Liebana will tell us about his paper (www.cell.com/cell/fulltex... [joint work w/ @saxelab.bsky.social & @laklab.bsky.social]. Want to attend, send an empty email to virtual-talk-link-request@cmclab.org to get the link!
cell.com
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Reposted by Samuel Liebana
Malcolm Campbell @malcolmgcampbell.bsky.social · 19/09/2025
🚨Our preprint is online!🚨 www.biorxiv.org/content/10.1... How do #dopamine neurons perform the key calculations in reinforcement #learning? Read on to find out more! 🧵
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Reposted by Samuel Liebana
Armin Lak @laklab.bsky.social · 20/09/2025
Beautiful and clear results showing that temporal difference error calculation is hardwired in the dopamine/striatum mircocircuits: www.biorxiv.org/content/10.1... from @malcolmgcampbell.bsky.social and @naoshigeuchida.bsky.social
biorxiv.org
A hardwired neural circuit for temporal difference learning
The neurotransmitter dopamine plays a major role in learning by acting as a teaching signal to update the brain's predictions about rewards. A leading theory proposes that this process is analogous to...
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Reposted by Samuel Liebana
Sainsbury Wellcome Centre @sainsburywellcome.bsky.social · 11/06/2025
Read the full paper ‘Dopamine encodes deep network teaching signals for individual learning trajectories’ in @cellpress.bsky.social ⬇️ www.cell.com/cell/fulltex... ‪@yulonglilab.bsky.social‬‬‬ @saxelab.bsky.social ‪@oxforddpag.bsky.social‬‬‬ @laklab.bsky.social
cell.com
Dopamine encodes deep network teaching signals for individual learning trajectories
Longitudinal tracking of long-term learning behavior and striatal dopamine reveals that dopamine teaching signals shape individually diverse yet systematic learning trajectories, captured mathematical...
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Reposted by Samuel Liebana
Blake Richards @tyrellturing.bsky.social · 10/07/2025
Super excited to see this paper from Armin Lak & colleagues out! (I've seen @saxelab.bsky.social present it before.) www.cell.com/cell/fulltex... tl;dr: The learning trajectories that individual mice take correspond to different saddle points in a deep net's loss landscape. 🧠📈 🧪 #NeuroAI
cell.com
Dopamine encodes deep network teaching signals for individual learning trajectories
Longitudinal tracking of long-term learning behavior and striatal dopamine reveals that dopamine teaching signals shape individually diverse yet systematic learning trajectories, captured mathematical...
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Reposted by Samuel Liebana
Andrew Saxe @saxelab.bsky.social · 04/06/2025
How does in-context learning emerge in attention models during gradient descent training? Sharing our new Spotlight paper @icmlconf.bsky.social: Training Dynamics of In-Context Learning in Linear Attention arxiv.org/abs/2501.16265 Led by Yedi Zhang with @aaditya6284.bsky.social and Peter Latham
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Reposted by Samuel Liebana
Andrew Saxe @saxelab.bsky.social · 14/07/2025
Excited to share new work @icmlconf.bsky.social by Loek van Rossem exploring the development of computational algorithms in recurrent neural networks. Hear it live tomorrow, Oral 1D, Tues 15 Jul West Exhibition Hall C: icml.cc/virtual/2025... Paper: openreview.net/forum?id=3go... (1/11)
icml.cc
ICML Poster Algorithm Development in Neural Networks: Insights from the Streaming Parity TaskICML 2025
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Samuel Liebana @samuel-liebana.bsky.social · 15/06/2025
Does the brain learn by gradient descent? It's a pleasure to share our paper at @cp-cell.bsky.social, showing how mice learning over long timescales display key hallmarks of gradient descent (GD). The culmination of my PhD supervised by @laklab.bsky.social, @saxelab.bsky.social and Rafal Bogacz!
cell.com
Dopamine encodes deep network teaching signals for individual learning trajectories
Longitudinal tracking of long-term learning behavior and striatal dopamine reveals that dopamine teaching signals shape individually diverse yet systematic learning trajectories, captured mathematical...
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Reposted by Samuel Liebana
Cell - a Cell Press journal @cp-cell.bsky.social · 11/06/2025
Now online! Dopamine encodes deep network teaching signals for individual learning trajectories
dlvr.it
Dopamine encodes deep network teaching signals for individual learning trajectories
Longitudinal tracking of long-term learning behavior and striatal dopamine reveals that dopamine teaching signals shape individually diverse yet systematic learning trajectories, captured mathematically by the fixed point structure of a deep neural network.
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Reposted by Samuel Liebana
Armin Lak @laklab.bsky.social · 11/06/2025
Our work, out at Cell, shows that the brain’s dopamine signals teach each individual a unique learning trajectory. Collaborative experiment-theory effort, led by Sam Liebana in the lab. The first experiment my lab started just shy of 6y ago & v excited to see it out: www.cell.com/cell/fulltex...
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Reposted by Samuel Liebana
Sainsbury Wellcome Centre @sainsburywellcome.bsky.social · 11/06/2025
New research shows long-term learning is shaped by dopamine signals that act as partial reward prediction errors. The study in mice reveals how early behavioural biases predict individual learning trajectories. Find out more ⬇️ www.sainsburywellcome.org/web/blog/lon...
Schematic of the study
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