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New preprint on brain fingerprinting based on information decomposition and topological analysis of fMRI data. Dream team 🚀 simone poetto Giovanni Petri Demian Battaglia Giovanni Rabuffo Andrea Santoro and more biorxiv.org/content/10.110…

🧠 Want to understand how different higher-order methods compare in brain connectivity analysis? Check out our new preprint — a fantastic collab with past & present NPLab members: 🔗 biorxiv.org/content/10.110…

NPLab Matteo Neri simone poetto Marilyn Gatica Giovanni Petri 🧵 1/ Over the past years, brain connectivity research has moved beyond simple pairwise interactions. A wide range of higher-order interaction (HOI) methods — from information theory to topological data analysis — have emerged. But the field is quite fragmented. Let's dive in🧠

NPLab Matteo Neri simone poetto Marilyn Gatica Giovanni Petri 2/ Brain models often focus on pairs of regions, but real interactions might involve groups acting together HOI methods aim to capture this, from detecting synergy and redundancy using different information-theoretic approaches to mapping topological cycles in brain networks.

NPLab Matteo Neri simone poetto Marilyn Gatica Giovanni Petri 3/ Yet with all these new tools — PhiID, O-information, PED, persistent homology, triangles, scaffolds — no one knew how they compared, what they captured, or when to use which. This paper tackles this directly with a comprehensive comparison across 10 HOI metrics.

NPLab Matteo Neri simone poetto Marilyn Gatica Giovanni Petri 4/ First big insight: HOI metrics fall into 3 categories: 🔴 Redundant: capture overlapping info (e.g., within sensory networks) 🔵 Synergistic: capture integrative info (e.g., across systems) 🟣 Topological: bridge the two, identifying mesoscale structures

NPLab Matteo Neri simone poetto Marilyn Gatica Giovanni Petri 5/ Despite different math, rank differences of all HOI metrics align with the brain's core hierarchy: from sensory (unimodal) to associative (transmodal) cortex. This “HOI axis” reflects fundamental computational principles embedded in the brain’s layout. 🧭

NPLab Matteo Neri simone poetto Marilyn Gatica Giovanni Petri 6/ But there’s more. These metrics also reflect the brain’s neurochemistry: •Redundant metrics correlate with metabolic maps •Synergistic & topological metrics align with receptor distributions

NPLab Matteo Neri simone poetto Marilyn Gatica Giovanni Petri 7/ When it comes to applications, HOIs show their power: 🎯 For brain fingerprinting (ID'ing individuals), HOI metrics outperform classical functional connectivity (FC)

Andrea Santoro NPLab Matteo Neri simone poetto Marilyn Gatica Giovanni Petri Huge effort from all authors. What a great work linking information decomposion and topological analysis approaches to fMRI!

Our preprint is out and I couldn’t be more excited! 🔥 Huge thanks to such an incredible team 🙌🏻 Andrea Santoro Matteo Neri, simone poetto , Davide Orsenigo , Matteo Diano, Giovanni Petri NPLab 👇👇👇

If you're here today at CNS*2025 🧠, we're at the workshop! Come say hi to our amazing speaers Giovanni Petri simone poetto Andrea Brovelli Demian Battaglia FunSy Patricio Orio Jesús Cortes .... OC: Joseph Lizier

Excellent post distinguishing mechanisms from behaviours! 👇🏽👇🏽👇🏽 (We have a similar discussion in the context of high-order stuff here: arxiv.org/abs/2203.12041)

You're into neuroscience and AI? 🧠 🤖 You're working on the mathematics that drives biological and artificial neural networks? We want to hear from you! Submit to NeurReps 2025 at NeurIPS Conference! 📅 Deadline: Aug 22 📄 Two tracks: 9p proceedings & 4p extended abstracts