Andrea Santoro

Latest work at #EUSIPCO25!🚀
We bring Topological Signal Processing to the brain 🧠 — showing that edge-based approaches outperform classical GSP in task decoding.

Great collab with M.Nurisso & @lordgrilo.bsky.social 🙌
Paper 👉 eusipco2025.org/wp-content/u...

#Neuroimaging #SignalProcessing #TSP

Next week (on the 15th and 16th), with @yasserroudi.bsky.social and Federico Turkheimer we will organize a workshop on the "The Topology of Human and Synthetic Minds"

Please do join us!
(Registration is free but required for access/catering!)

lordgrilo.github.io/topology-nat...

🚨🚨 New preprint just dropped! In collaboration with @colltoaction.bsky.social, Cliff Joslyn, @fralotito.bsky.social, Audun Myers, Joshua Pickard, Brenda Praggastis, and Przemysław Szufel, we define a new data sharing standard for higher-order networks. arxiv.org/abs/2507.11520

Thrilled to finally share a huge piece of my PhD project!
Our paper “The Topological Architecture of Brain Identity” is now out on bioRxiv: biorxiv.org/content/10.1... 🧵 1/n

Huge thanks for this fun collaboration to past and present members of the NPLab — Matteo Neri, @poetz.bsky.social, Davide Orsenigo, Matteo Diano, @marilyngatica.bsky.social, @lordgrilo.bsky.social 🙌🧠

14/ This work takes an important step toward a unified roadmap for navigating the complex, fragmented landscape of higher-order brain connectivity.

13/ In short:

✅ HOIs provide richer, biologically grounded insights into brain function
✅ The research landscape is now organized — synergy, redundancy, topology
✅ HOIs better capture traits; FC better captures states
✅ Tools are available for broader use (HOI toolbox, TDA code, etc.)

12/ One standout: topological scaffolds. They act as integrators — capturing synergy in nodes, and structure-function coupling at edges. They're central in linking connectivity patterns to behavior.

11/ Even dopamine levels relate: lower dopamine -> more flexible task-related reconfiguration.

10/ HOIs also help explain how the brain reconfigures during different tasks. Social/emotional tasks show more synergy, while sensorimotor ones lean on redundancy.

9/ This shows a key trade-off:

🔍 If you want to understand who a person is (trait-level): use HOIs
⚡ If you want to know what they're doing (state-level): FC is often enough

8/🧠 For task decoding, though, classic FC is still one of the top methods.

7/ When it comes to applications, HOIs show their power:

🎯 For brain fingerprinting (ID'ing individuals), HOI metrics outperform classical functional connectivity (FC)

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

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. 🧭

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

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.

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.

🧵 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. 🧠

🧠 Want to understand how different higher-order methods compare in brain connectivity analysis?

Check out our new preprint — a fantastic collab with past & present NPL members @lordgrilo.bsky.social :
🔗 www.biorxiv.org/content/10.1...
A thread🧵

The topology of synergy: linking topological and information-theoretic approaches to higher-order interactions in complex systems The study of irreducible higher-order interactions has become a core topic of study in complex systems. Two of the most well-developed frameworks, topological data analysis and multivariate informatio...

New pre-print just dropped, with @doctorjosh.bsky.social, @alicepatania.bsky.social, and Pedro Mediano.

In it we ask: when an algebraic topologist and an information theorist talk about "higher-order" structure, are they talking about the same thing?

A 🧵1/n

arxiv.org/abs/2504.10140

Connectome architecture favours within-module diffusion and between-module routing.

Really cool multi-species work from Caio Seguin on module-defined communication policies in connectomes!

www.biorxiv.org/content/10.1...

Pandemic monitoring with global aircraft-based wastewater surveillance networks - Nature Medicine By simulating the implementation of airport-based wastewater surveillance sites at the global level, a modeling study shows how this early warning system would perform in identifying sources of pandem...

Wastewater from airplane toilets?
We introduce a global Aircraft-Based Wastewater Surveillance Network (WWSN) for pandemic monitoring in Nature Medicine 🔗 doi.org/10.1038/s415...

Aircraft-based wastewater surveillance allows for real-time, non-invasive monitoring of global pathogen spread
Short 🧵

Thrilled to announce that I've been awarded a #MSCA fellowship! I'll continue my work at CENTAI in Turin with @lordgrilo, while collaborating with the NERV team in Paris with @DeVicoFallani at the intersection of neuroscience & higher-order interactions. Thanks to everyone who supported me!

Also! The symposium on higher-order interactions, chaired by @manishsaggar.bsky.social and @lordgrilo.bsky.social, was accepted.

Absolute must-attend if you're at OHBM 2025, with talks from: @popeme.bsky.social, @andreasantoro.bsky.social, and @novelli-leo.bsky.social!

@ohbmofficial.bsky.social

And here we go! First position on my ERC grant is officially open. Fully funded 3.5 years PhD position at NetSI London working with me and the @nplab.bsky.social on modeling and reconstructing higher-order systems.
Application deadline: 16th February 2025.
Bring your A game!

Higher-order connectomics of human brain function reveals local topological signatures of task decoding, individual identification, and behavior - Nature Communications Here, the authors perform a higher-order analysis of fMRI data, revealing that accounting for group interactions greatly enhances task decoding, brain fingerprinting, and brain-behavior associations c...

Higher-order connectomics of human brain function reveals local topological signatures of task decoding, individual identification, and behavior www.nature.com/articles/s41...

9/n This topological perspective parallels ongoing research efforts using information-theoretic approaches, emphasizing the importance of considering complex, multi-region interactions to truly understand brain function. 🌌

8/n Our findings reveal that higher-order approaches are preferable in certain contexts for exploring brain dynamics, uncovering insights that pairwise models might overlook.

7/n 3️⃣ Brain-Behavior Associations: With higher-order connectivity, we observed stronger links between brain activity and behavior, especially for complex cognitive abilities. Pairwise approaches showed weaker relationships.