CATNIP Lab is a computational and statistical neuroscience group. Our goal is to obtain an effective systems-level description of relevant neural dynamics in the context of cognitive functions and dysfunctions. To arrive at a model of neural computation tightly tied to biology and experimental observations, we work closely with experimental and clinical collaborators. We develop probabilistic methods for analyzing spatiotemporal neural and non-neural time series to infer neural dynamics models. To facilitate the scientific inference process, we develop real-time machine learning and control methods and design next-generation experiments.
See research page for details.

Recent News
Announcement
Universal approximation over infinite time at NeurIPS 2026
Abel’s paper on universal approximation for dynamical systems has been accepted at NeurIPS 2026, and we will present the poster in Sydney on December 9! He proved that Neural ODEs...
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Announcement
Germán Abrevaya joins the lab
Welcome Germán Abrevaya, who joined CATNIP Lab in July as a postdoctoral researcher at the Champalimaud Centre for the Unknown. He fills the postdoc position we advertised earlier this year....
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Announcement
Integrative neurocybernetic modeling in the era of large-scale neuroscience
Our Perspective on the cybernetic future of large-scale model-centric integrative neuroscience is now on arXiv. Predictive accuracy is not understanding: a Transformer-style foundation model that captures neural time series at...
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COSYNE 2026
COSYNE 2026 is in Lisbon this year (March 12–15 main meeting, March 16–17 workshops in Cascais). #cosyne2026
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