
CMC lab
47 posts

CMC lab
@CompNeuro_lab
Computational Machinery of Cognition (CMC) lab focuses on computational and neural machinery of goal-driven behavior | PI: @neuroprinciples | @tudresden_de


Wanna compare dynamics across neural data, RNNs, or dynamical systems? We got a fast and furious method🏎️ The 1st preprint of my PhD 🥳 fast dynamical similarity analysis (fastDSA): 📜: arxiv.org/abs/2511.22828 💻: github.com/CMC-lab/fastDSA I’ll be @CosyneMeeting - happy to chat 😉

Wanna compare dynamics across neural data, RNNs, or dynamical systems? We got a fast and furious method🏎️ The 1st preprint of my PhD 🥳 fast dynamical similarity analysis (fastDSA): 📜: arxiv.org/abs/2511.22828 💻: github.com/CMC-lab/fastDSA I’ll be @CosyneMeeting - happy to chat 😉




Happy to share my first post-doc paper with Peter Dayan just published at @NeuroCellPress "Multistability, Perceptual Value, and Internal Foraging" Paper (free access before Oct 18th): authors.elsevier.com/a/1ffq33BtfH1Y… No access? Email me at neuron2022@shervinsafavi.org 🧵👇


In our Learning Club @CompNeuro_lab today (Sep 25, Thu, 2pm CET), @DengPan18 will tell us about his recent paper (👇) [joint work w/ Rushworth lab]. Want to attend, send an empty email to virtual-talk-link-request@cmclab.org to get the link!

🚨We believe this is a major step forward in how we study hippocampus function in healthy humans. Using novel behavioral tasks, fMRI, RL & RNN modeling, and transcranial ultrasound stimulation (TUS), we demonstrate the causal role of hippocampus in relational structure learning.


Causal necessity of human hippocampus for structure-based inference in learning biorxiv.org/content/10.110… #biorxiv_neursci



Still curious about uncovering internal state — completely unsupervised? We start in 30 minutes.

#CCN2025, Poster C160: We present MoDSA – a fully unsupervised method for identifying behaviorally relevant neural states in both biological & artificial systems. From macaque V4 recordings to deep RL agents, MoDSA robustly detects state transitions without labels. See You there!





Happy to share my second paper with Peter Dayan on our decision-theoretic approach to perceptual multistability (see the tweeprint of the first paper here x.com/neuroprinciple…): A decision-theoretic model of multistability biorxiv.org/content/10.110…