The supply of blood to brain tissue is thought to depend on the overall neural activity in that tissue, and this dependence is thought to differ across brain regions and across brain states. However, studies supporting these views have measured neural activity as a bulk quantity and related it to blood supply following disparate events in different regions. Here we measure fluctuations in neuronal activity and blood volume across the mouse brain, and find that their relationship is consistent across brain states and brain regions but differs in two opposing brainwide neural populations. Functional ultrasound imaging (fUSI) revealed that whisking, a marker of arousal, is associated with brainwide fluctuations in blood volume. Simultaneous fUSI and Neuropixels recordings showed that neurons that increase activity with whisking have distinct haemodynamic response functions compared with those that decrease activity. Their summed contributions predicted blood volume across states.Brainwide Neuropixels recordings revealed that these opposing populations coexist in the entire brain. Their differing contributions to blood volume largely explain the apparent differences in blood volume fluctuations across regions. The mouse brain thus contains two neural populations with opposite relations to brain state and distinct relationships to blood supply, which together account for brainwide fluctuations in blood volume.

How does blood flow relate to brain activity? We discovered that it reflects two neural populations affected oppositely by arousal. Together, they explain neurovascular coupling in all brain regions and brain states!

Out today in Nature: rdcu.be/fdC2A

@uclbrainscience.bsky.social

Arousal neuron activity explains brain blood flow in mice The findings could impact how researchers interpret signals from techniques that use blood flow as a surrogate for neural activity.

When it comes to blood flow in the brain, not all neurons are created equal. Rather, only a subset of neurons may be driving vascular changes, a new study finds.

By @claudia-lopez.bsky.social

#neuroskyence

www.thetransmitter.org/neurovascula...

Major effort from Samuel and the rest of the authors! Looking forward to seeing these strategies available and applied in future fUSI papers :)

New paper out 🎉

Awake fUSI is powerful, but motion can strongly bias the data, even in head-fixed experiments.

In this paper, we tried to systematically characterize those artifacts, benchmark denoising strategies, and turn that into practical recommendations for awake fUSI of mouse brains.

1/12

𝗞𝗶𝗰𝗸𝗶𝗻𝗴 𝗼𝗳𝗳 𝟮𝟬𝟮𝟲 𝘄𝗶𝘁𝗵 𝗮 𝗻𝗲𝘄 𝗽𝘂𝗯𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗶𝗻 𝗖𝗲𝗹𝗹 𝗥𝗲𝗽𝗼𝗿𝘁𝘀
@felipecybis.bsky.social, postdoct in our lab, is the first author of the study "A vascular code for speed in the spatial navigation system", now published in Cell Reports: doi.org/10.1016/j.celrep.2025.116791

#Ultrasound #fUS #Research

Data is (hopefully) fUSI-BIDS friendly, btw :)

A vascular code for speed in the spatial navigation system During free exploration, cerebral blood volume in the entorhinal-hippocampal navigation system closely tracked locomotion speed, revealing hierarchical thalamic-to-hippocampal flow and exposing a vasc...

Thanks to all my co-authors and to all the effort put into this paper: @sdiebolt.bsky.social @sebastian-castedo.bsky.social Jeremy Ferrier, Nathalie Ialy-Radio, Bruno Osmanski, Remi Monasson, Simona Cocco @sophiepezet.bsky.social @mickaeltanter.bsky.social. 10/10

Full paper here: tiny.cc/a48x001

To conclude, we think that this richness of speed representation in the vasculature of the spatial navigation system is due to the unidimensionality of this signal (in contrast to the N-dimensionality of HD/grid/place cells), offering a vascular perspective on spatial navigation representation. 9/10

Analyzing ultra-slow activity, we found minute scale CBV oscillations in the same spatial navigation regions we see speed-responsiveness and we show that this minute scale oscillations are present in the speed signal itself, derived from the animal's exploratory behavior. 8/10

Also, in collaboration with @qbio-ens.bsky.social folks, a link between energy expenditure, animal speed and a CAN model of path integration was proposed and could be modeled with experimental data. 7/10

We could train a decoder in one animal to decode speed from another animal using ROI-based signals, showing regional stability and universality of this vascular response to animal speed. 6/10

Decoding animal speed from functional ultrasound imaging data gave us accuracies that matched decoders from previous papers using speed cells. Decoders for positional data was also possible. Interestingly, proximity to edges cannot be modeled by animal speed and can be modeled by CBV data! 5/10

We saw similar correlations when head angular speed was the signal of interest, but now peak activations are seen in dorsal thalamic nuclei (and parahippocampus for some animals) and not in the hippocampus, supporting the metabolic demands of this "angular coding" region. 4/10

Across all animals and sessions, we found robust correlation between animal speed and CBV in spatial navigation regions in a wave of activation propagating from MEC -> parahippocampus -> hippocampus proper. We see well-delineated "speed-responsive" regions. (full videos in the full text link) 3/10

This is the main (neuro) output of my PhD project under the supervision of @mickaeltanter.bsky.social and @sophiepezet.bsky.social in collaboration with @iconeus.bsky.social. We recorded 7 SD rats across ~60 imaging sessions. Using pose estimation we compared CBV dynamics and navigational data. 2/10

A vascular code for speed in the spatial navigation system During free exploration, cerebral blood volume in the entorhinal-hippocampal navigation system closely tracked locomotion speed, revealing hierarchical thalamic-to-hippocampal flow and exposing a vasc...

🚨 New paper alert: fUS and free exploration 🚨

Happy to share this end-of-year publication ("A vascular code for speed in the spatial navigation system") just out in Cell Reports a few days ago.

Functional ultrasound imaging in rats during free exploration! 1/10
Full paper: tiny.cc/a48x001

Sleep-dependent infraslow rhythms are evolutionarily conserved across reptiles and mammals Nature Neuroscience - Bergel et al. show that an infraslow rhythm connecting the brain and body during sleep is shared by lizards, mammals and birds, revealing an ancestral process and reshaping...

⚠️ New paper alert and what a way to end 2025! 🎉
Happy to share our story “Sleep-dependent infraslow rhythms are evolutionarily conserved across reptiles and mammals.” published today in Nature Neuroscience.

Sleeping dragons 🦎 and functional ultrasound!
Read the full paper here: rdcu.be/eWJHb 1/8

“Leave the lab! Escape the ivory tower!” they said.
Hold our EEGs!

@dreamteamicm.bsky.social is teaming up with Alexia Barrier and The Famous Project, the first all-female crew racing the Trophée Jules Verne!

We’ll track their brain activity across 40 days at sea!

@institutducerveau.bsky.social

fUSI-BIDS extension proposal v0.0.11 BIDS Extension Proposal 40 (BEP040): fUSI-BIDS version 0.0.11 Available under the CC-BY 4.0 International license. Extension moderators/leads: Jean-Charles Mariani <jean-charles.mariani@cri-paris.org...

Long-awaited #fUSI - #BIDS meeting scheduled! 🧠

📅 Nov 27, 5PM Paris time
🎯 Finalizing BEP for BIDS maintainer discussions

Implemented fUSI-BIDS or planning to? We need your input to strengthen the spec. Join us!

Details on the specification GDoc (docs.google.com/document/d/1...)

🚨𝗛𝗼𝘁 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗽𝗿𝗲𝘀𝘀 – 𝗠𝗮𝗷𝗼𝗿 𝗯𝗿𝗲𝗮𝗸𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝗶𝗻 𝗺𝗲𝗱𝗶𝗰𝗮𝗹 𝗶𝗺𝗮𝗴𝗶𝗻𝗴 𝗷𝘂𝘀𝘁 𝗽𝘂𝗯𝗹𝗶𝘀𝗵𝗲𝗱 𝗶𝗻 𝗡𝗮𝘁𝘂𝗿𝗲 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀!
For the first time, whole-organ blood flow dynamics can be mapped at micrometric resolution using an ultrasound multi-lens probe.
🔗 Find out more: physicsformedicine.espci.fr/major-breakt...

This looks pretty cool: ultrasound can now see through the skull! 🧠🔊

The skull has long been a barrier to ultrasound. This reprint shows how to make it quickly transparent → enabling full-depth, high-res fUSI in mice (& humans! 🤯🤯)
Huge congrats to the authors!!!

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

Our didactic review on machine learning for causal inference, now open access:
• identifiability (theory of when the data can answer a causal question)
• machine-learning estimators
• study design (asking well-framed questions + loopholes, eg with timewise data)
www.annualreviews.org/content/jour...

Thanks to @physmedparis.bsky.social @iconeus.bsky.social @mickaeltanter.bsky.social and Sophie Pezet as well as all my other incredible co-authors!

We tackle energy consumption modeling for path integration using fUSI data and, finally, fUS minute-scale oscillations vs. minute-scale behavior.

Other behavioral correlates do appear, but not as striking as animal speed.

Metrics for decoding continuous locomotion speed with fUSI data match decoding results using standard ephys methods (for speed cells or theta freq, for example).

We show that robust spatiotemporal correlation patterns appear when comparing relative cerebral blood volume with continuous animal speed. These patterns start from dorso-thalamic nuclei than go to parahippocampal regions (MEC, PaS, PrS…) to finally peak in the hippocampus proper (CA1, CA3).

🚨 Preprint alert 🚨
The main results of my PhD are online and I only now could find some time to post about it!

We explored the neurovascular activations of spatial navigation by using functional ultrasound imaging (fUSI) in freely moving rats during open field.

We need your help!!! 🧠🧪💤

If you are human, you fall asleep at least once a day! What happens in your mind then?

Scientists know actually very little about this private moment.

We propose a 20-min survey to get as much data as possible!

Here is the link:
redcap.link/DriftingMinds

Enormous amount of work put into it by @sdiebolt.bsky.social! Glad to be part of it :)

🚨 New preprint alert!

We benchmarked 792 denoising pipelines for #fUSI in awake mice 🐭🧠

Our results show how they reduce motion artifacts and impact seed-based connectivity analyses.

Check it out on @biorxivpreprint.bsky.social 👇
🔗 www.biorxiv.org/content/10.1...