Alessandro Gozzi

Exploring the Role of the Rich Club in Network Control of Neurocognitive States Using a network control theoretical framework, we found that the brain's rich club does not optimally control dynamics of the brain. Instead, size-matched sets of random peripheral regions had a sign...

🚨 New paper from @apodschun.bsky.social (with Sebastian Markett, Urs Braun, and myself)

Exploring the Role of the Rich Club in Network Control of Neurocognitive States

onlinelibrary.wiley.com/doi/10.1002/...

Fondazione Telethon sostiene l’IIT negli studi di una nuova terapia genica per la malattia rara CTD - Talk iit La Fondazione Telethon ha rinnovato il supporto alle ricerche di Alessandro Gozzi del Centro dell’IIT a Rovereto per gli studi della malattia genetica rara nota con il nome “Carenza del Trasportatore ...

Nuovo finanziamento da Telethon per @gozziale.bsky.social, coord. del centro IIT di Rovereto, per la ricerca sulla Carenza del Trasportatore della Creatina -CTD. Obiettivo: sviluppo di una terapia genica di II generazione e basi per una futura sperimentazione clinica.
opentalk.iit.it/fondazione-t...

A recent paper in @natureportfolio.nature.com raised concerns about the lesion network mapping method. Our team of 16 coauthors analyzed >1000 lesions and 34 symptoms and found that "The methodological foundations of lesion network mapping remain sound" www.biorxiv.org/content/10.6...

a man wearing headphones is sitting in front of a microphone . ALT: a man wearing headphones is sitting in front of a microphone .

New preprint 📣

Do you use the @alleninstitute.org mouse brain connectome?

In work led by Vikram Nathan we found issues with existing connectome representations, fixed them, showed the impact on connectome measures.

Do you wonder what they are?
Do you wonder what they do?

tinyurl.com/5y9mft4e

Ten simple rules for building a collaborative coding culture

This was such a fun collaboration with @analog-ashley.bsky.social and team, including some of our own @sciencebanshee.bsky.social and @shen4brains.bsky.social And h/t to Alana McPherson for the infographic!

dx.plos.org/10.1371/jour...

thanks Thomas!!!! I knew you'd like our work ;-)

NeuroStats2026

Save the date 👆🧵 Neuroimaging Statistics Workshop, 12-13 June, @ohbmofficial.bsky.social 2026 satellite meeting, w/ @ohbmossig.bsky.social's BrainHack. Keith Worsley lecture by Sir. John Aston, + great work at Neuro/Stats/ML/AI interface. Registration opens soon! sites.google.com/view/nsw2026

Very cool!

Finally, huge credit to soon-to-be-PhD @chiarapepe.bsky.social who led this work with exceptional rigor and vision, and to @jcmariani.bsky.social who co-led and shaped the project throughout. And grateful to @erc.europa.eu and @iitalk.bsky.social for supporting this research! 14/14

If you’d like to play with these data or run your own analyses, all datasets (fUSI + fMRI) and the full analysis code are openly available here
zenodo.org/records/1848... 🚀
13/n

Take-home message: you can map the mouse functional connectome easily and conveniently with transcranial fUSI. As a long-time fMRI user, I’m genuinely struck by how much lower the technical and infrastructural barrier is compared with MRI!
12/n

Best part: the state transitions aren’t random! They form a structured grammar that converges onto three stable attractor-like co-activation modes, matching hallmark fMRI dynamics.
12/n

But static maps are only half the story. Resting brain activity moves through states. fUSI captures this too: activity falls into recurring co-activation patterns, organized into paired opposites (CAP/anti-CAPs).
11/n

But we didn’t stop at one correlation number. We found that structure–function coupling is best understood as four major axes, i.e., 4 dominant “wiring-to-function motifs” shaping the whole connectome
10/n

Next question (the fun one): are these fUSI networks actually grounded in anatomical wiring? Yes: functional connectivity aligns with the structural connectome, strongly and systematically
9/n

But fUSI isn’t just “fMRI-lite”. It has its own signature: connectivity patterns are way stronger and reproducible in cortical regions than fMRI, but are more focal and less robust subcortically (so depth sensitivity matters!)
8/n

Head-to-head against matched rsfMRI, the agreement is very encouraging: we recovered the same large-scale networks with highly similar spatial topographies. This cross-modal convergence is the key “trust test” for fUSI as a connectomics tool!
7/n

First payoff: fUSI cleanly recovers the familiar “cast of characters” in functional connectome mapping, including a default-mode network. The connectivity matrix also shows clear modular organization and left–right symmetry, exactly what you’d expect from a connectome-scale signal
6/n

Next challenge: resting-state networks in rodents are fragile. We thus identified a very simple and reliable protocol that maintains long-range connectivity while preserving slow, intrinsic arousal fluctuations (tracked via pupil dynamics)
5/n

To obtain large-scale connectome level coverage, we cycled across multiple brain planes repeatedly, fast enough to rebuild a brain-wide picture over time
4/n

We devised a non-invasive, transcranial protocol (no cranial window), and recorded spontaneous activity to reconstruct whole-brain functional connectivity from those fluctuations. We did so using an fMRI-inspired image preprocessing and analyses pipeline tuned for multi-slice fUSI
3/n

fUSI is an emerging hemodynamic imaging modality that’s quiet, portable, fast, and high-resolution. However, to date the application of fUSI in rodents has mostly mapped evoked activity. So we asked: can fUSI recover the same large-scale network structure we trust from rsfMRI?
2/n

🚨Do we need a large, expensive MRI scanner to map whole-brain networks in the mouse? Not necessarily!

In our new preprint ▶️ tinyurl.com/3a2h4r9f
we show that transcranial functional ultrasound (fUSI) can map connectome-scale networks with striking agreement to fMRI
🧵👇

Coding with AI - Better Code, Better Science

My new chapter of Better Code, Better Science on AI-assisted coding is now complete! It's been completely revised in an attempt to futureproof it. Comments welcome. bettercodebetterscience.github.io/book/ai-codi...

Inter-individual variability of neurotransmitter receptor and transporter density in the human brain | doi.org/10.1007/s004...

How do neuroreceptor distributions vary across people?

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Confondere il possesso di capacità cognitive sofisticate con il possesso di coscienza...

We found that:
1️⃣ Transcranial fUSI reveals canonical cortical & subcortical networks with high spatial concordance to fMRI
2️⃣ fUSI network dynamics are shaped by recurring co-activation patterns within 3 dominant attractor states
3️⃣Networks are robustly embedded in the mouse structural connectome

🐭🧠 Can fUSI truly map canonical mouse resting-state networks — and how does it compare to fMRI?

I’m excited to share the work of my PhD in our new preprint!👉 doi.org/10.64898/202...

Go check it out — it’s time to expand your neuroimaging toolkit 🧠🚀

Structural and dynamic embedding of the mouse functional connectome revealed by functional ultrasound imaging (fUSI) https://www.biorxiv.org/content/10.64898/2026.02.05.704055v1

So sorry...