1/11 Happy to share our TICS paper on using the flexibility of one of the most basic cognitive functions, perception, to understand one of the most complex cognitive dysfunctions, psychiatric conditions (also my first formal work in computational psychiatry 🎉)
📄: www.cell.com/trends/cogni...
🧵 : 👇
NEW PAPER. Why do larger networks train better?
"Because they contain more candidate *sub*networks that can learn the task" → lottery tickets
This popular explanation uses an appealing but misleading metaphor🧵
We propose an intuitive alternative grounded in theory: escape dimensions
So excited to see this finally out!! 🤩🎉 A big thank you to our reviewers for their helpful feedback and to @modirshanechi.bsky.social and Wulfram Gerstner for the wonderful collaboration!
Incredibly grateful to @cmiehl.bsky.social and @gjorjulijana.bsky.social for their thoughtful and spot-on Preview "Novelty beyond counting" of our recent work in Neuron with @modirshanechi.bsky.social and @gerstnerlab.bsky.social! 🧠✨ It's a real honor 🙏 www.cell.com/neuron/fullt...
Excited to share that our study on how cell-type-specific synaptic scaling mechanisms regulate memory representations in associative learning is now published! www.jneurosci.org/content/earl...
New job posting! If you're interested in working with our group, check it out. 3 year position (with possibility to extend) at >100k. alleninstitute.org/careers/jobs...
Some incredibly exciting news that still feels a bit surreal: I am starting my research group @mpicybernetics.bsky.social!
The best part? We are hiring at all levels!
Curious about the science we plan to tackle, read along :)
#NeuroSky
Novelty is not just about whats new, but also what feels new given past experience. New study from Sophia Becker in Wulfram Gerstner’s @epfl-brainmind.bsky.social lab posits a model showing how similarity between familiar and novel stimuli shapes exploration and learning - doi.org/10.1016/j.ne...
How does circuit structure shape neural activity? The lab of @epfl-brainmind.bsky.social Prof. Wulfram Gerstner shows that distinct neural circuits can produce similar low-dimensional dynamics, while retaining clear signatures in single neuron and population activity data: doi.org/10.1016/j.ne...
Perceptual multistability, observed across species and sensory modalities, offers
valuable insights into numerous cognitive functions and dysfunctions. For instance,
differences in temporal dynamics a...
Ever heard of the lottery ticket hypothesis?
Our new paper shows that lottery tickets are not a useful metaphor to explain the success of overparameterized neural networks - and suggests an alternative metaphor: escape dimensions
Flavio Martinelli
Excitatory synaptic scaling regulates network dynamics by proportionally adjusting excitatory synaptic strengths after sensory perturbations. During associative learning, blocking excitatory scaling i...
www.jneurosci.org
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Online Now: Perceptual multistability: a multifaceted window into brain dysfunctions
Sophia Becker
Sophia Becker
Novelty is not just about whats new, but also what feels new given past experience. New study from Sophia Becker in Wulfram Gerstner’s @epfl-brainmind.bsky.social lab posits a model showing how similarity between familiar and novel stimuli shapes exploration and learning - doi.org/10.1016/j.ne...
Yue Kris Wu
Laura Driscoll
Roxana Zeraati
EPFL Brain Mind Institute
EPFL Brain Mind Institute
NEW PAPER. Why do larger networks train better?
"Because they contain more candidate *sub*networks that can learn the task" → lottery tickets
This popular explanation uses an appealing but misleading metaphor🧵
We propose an intuitive alternative grounded in theory: escape dimensions
Perceptual multistability, observed across species and sensory modalities, offers valuable insights into numerous cognitive functions and dysfunctions. For instance, differences in temporal dynamics and information integration during percept formation often distinguish clinical from nonclinical populations. Computational psychiatry can elucidate these variations through two primary approaches: (i) Bayesian modeling, which treats perception as an unconscious inference, and (ii) an active, information-seeking perspective (e.g., reinforcement learning), which frames perceptual switches as internal actions. Our synthesis aims to leverage multistability to bridge these computational psychiatry subfields, linking human and animal studies as well as connecting behavior to underlying neural mechanisms. Perceptual multistability emerges as a promising noninvasive tool for clinical applications, facilitating translational research and enhancing our mechanistic understanding of cognitive processes and their impairments.