EPFL: Breakdown and repair of the aging brain metabolic system

The study presented explores the complex relationship between the aging brain, energy metabolism, blood flow and neuronal activity by introducing a comprehensive, data-driven molecular model of the neuro-glial vascular system, including all key enzymes, transporters, metabolites, and blood flow vital for neuronal electrical activity with 16’800 interaction pathways. We find significant alterations in metabolite concentrations and differential effects on ATP supply in neurons and astrocytes and within subcellular compartments within aged brains, and identify reduced Na⁺/K⁺-ATPase as the leading cause of impaired neuronal action potentials. The model predicts that the metabolic pathways cluster more closely in the aged brain, suggesting a loss of robustness and adaptability. Additionally, the aged metabolic system displays reduced flexibility, undermining its capacity to efficiently respond to stimuli and recover from damage. Through transcription factor analysis, the estrogen-related receptor alpha (ESRRA) emerged as a central target connected to these aging-related changes. An unguided optimization search pinpointed potential interventions capable of restoring the brain’s metabolic flexibility and restoring action potential generation. These strategies include increasing the NADH cytosol-mitochondria shuttle, NAD+ pool, ketone β-hydroxybutyrate, lactate and Na⁺/K⁺-ATPase and reducing blood glucose levels. The model is open-sourced to help guide further research in brain metabolism.

Publication: https://www.biorxiv.org/content/10.1101/2023.08.30.555341v2 

Scientific Collaborator: Polina Shichkova, Ph. D

Data visualization tool: Blue Brain BioExplorer

EPFL: Neuromodulation of neocortical microcircuitry: a multi-scale framework to model the effects of cholinergic release

Neuromodulation of neocortical microcircuits is one of the most fascinating
and mysterious aspects of brain physiology. Despite over a century of research,
the neuroscientific community has yet to uncover the fundamental biological organizing principles underlying neuromodulatory release.

Phylogenetically, Acetylcholine (ACh) is perhaps the oldest neuromodulator, and one of the most well-studied. ACh regulates the physiology of neurons and synapses, and modulates neural microcircuits to bring about a reconfiguration of global network states. ACh is known to support cognitive processes such as learning and memory, and is involved in the regulation of arousal, attention and sensory processing. While the effects of ACh in the neocortex have been characterized extensively, integrated knowledge of its mechanisms of action is lacking.

Furthermore, the ways in which ACh is released from en-passant axons originating in subcortical nuclei are still debatable. Simulation-based paradigms play an important role in testing scientific hypotheses, and provide a useful framework to integrate what is already known and systematically explore previously uncharted territory.

Importantly, data-driven computational approaches highlight gaps in current knowledge and guide experimental research. To this end, I developed a multi-scale model of cholinergic innervation of rodent somatosensory cortex comprising two distinct sets of ascending projections implementing either synaptic (ST) or volumetric transmission (VT). The model enables the projection types to be combined in arbitrary proportions, thus permitting investigations of the relative contributions of these two transmission modalities.

Using our ACh model, we find that the two modes of cholinergic release act in concert and have powerful desynchronizing effects on microcircuit activity. Furthermore we show that this modeling framework can be extended to other neuromodulators, such as dopamine and serotonin, with minimal constraining data. In summary, our results suggest a more nuanced view of neuromodulation in which multiple modes of transmitter release - ST vs VT - are required to produce synergistic functional effects.

Publication: https://infoscience.epfl.ch/entities/publication/0a69c342-ac83-4fa3-bc08-44b886969d60

Scientific Collaborator: Cristina Colangelo, Ph.D

Data visualization tool: Blue Brain BioExplorer 

NVIDIA: Wanted! Business Card on a Mission

Wanted: one ambitious business card, last seen in 2012, lounging on a bench in front of NVIDIA’s former US offices.

Picture it: 2012, bright-eyed me, full of dreams, standing at the gates of NVIDIA, the tech giant of my fantasies. Armed with nothing but a neatly printed business card and an overabundance of optimism, I did what any sensible person would do: I left my card on a bench. The strategy? Genius. The logic? Questionable. But hey, in my head, it was the ultimate mic drop. Someone would find it? get intrigued?

Instead, life had other plans, steering me toward EPFL's Blue Brain Project, where I spent a decade on the wildest, most rewarding ride of my career. From unraveling neural mysteries to building tools that merged science and creativity.

Still, every now and then, I wonder—what happened to that card? Is it still there, weathered and waiting? If you find it, congratulations! And guess what? It’s still valid, and I’d love to hear from you.

NVIDIA: Bringing Brain Simulations to Life with NVIDIA Omniverse

In computational neuroscience, visualizing the brain is crucial to understanding its complex behavior. NVIDIA Omniverse is revolutionizing this process by turning neuron simulations into vibrant, dynamic visualizations—bridging the gap between data and discovery.

 

Using Omniverse, we can map electrical currents in neurons to vivid colors, creating real-time, interactive displays of brain activity. Researchers can zoom into individual neurons, explore neural networks, and observe dynamic changes in activity—all in stunning 3D.

Omniverse empowers researchers to build digital twins of brain regions. These twins enable the simulation of diseases, testing of interventions, and real-time collaboration. Its USD-based scalability and Python integration make it an unparalleled tool for neuroscience visualization.

From advancing research on neurological disorders to immersive education tools, Omniverse empowers neuroscientists to transform raw data into actionable insights. 

Data sources:

- BluePyOpt: https://github.com/BlueBrain/BluePyOpt

- Neuromorpho.org: https://neuromorpho.org/

NVIDIA: Blood flow visualization with Omniverse

Today, I explored the incredible flexibility of NVIDIA's fully scriptable Omniverse platform by developing an interactive blood flow visualization. The dataset, originally generated using AstroVascPy (https://lnkd.in/d3dxN6yJ), was initially in SONATA format and later converted into OpenUSD for compatibility. The simulation data was integrated as custom attributes directly tied to the streamline geometry, allowing for a dynamic, frame-based rendering.

With each simulation frame, the radius and color of the streamlines update automatically, reflecting changes in the dataset in real time. This approach combines the power of Python scripting with the robust visualization capabilities of Omniverse, making it effortless to bring complex, multi-dimensional simulation data to life.

Omniverse's fully scriptable architecture played a critical role in streamlining this process, enabling custom workflows tailored to specific datasets and visualization requirements. This project highlights how the platform can bridge scientific simulation and interactive visualization, offering researchers powerful tools to analyze and present intricate biological processes with unprecedented clarity.

- AstroVascPy: https://github.com/BlueBrain/AstroVascPy

NVIDIA: Playing with Omniverse and Exploring Brain Digital Twins in High-Quality 3D

I’ve been having a blast experimenting with NVIDIA Omniverse, using neuroscience data to delve into the concept of brain digital twins. While it’s not a finished solution (yet), it’s an incredible sandbox for interactive visualization and testing the limits of what’s possible in rendering complex neural structures.

Bringing brain models to life in immersive, high-quality 3D is both captivating and full of promise. Omniverse provides a glimpse into a future where neuroscience can be explored in entirely new ways, making it an exciting platform to experiment with.

This is just the beginning, but the potential is huge.

Data sources:
- EPFL Blue Brain Project: https://lnkd.in/gH3cgPAs
- Tractome Dataset: https://lnkd.in/dGwgsv5z
- Flywire: https://flywire.ai

EPFL: Modeling of blood flow dynamics in the rat somatosensory cortex

I'm very proud of this publication, where I contributed to the visualization of a comprehensive simulation framework to study neurovascular coupling in the rat somatosensory cortex. This study sheds light on the fascinating interplay between astrocytic activity and cerebral microvasculature, revealing how astrocytic endfeet drive localized vessel diameter changes, particularly in capillaries, to regulate blood flow. A huge congratulations to Stéphanie Battini for her outstanding work and for being such a fantastic collaborator—it’s been an absolute pleasure to work alongside you!

Publication: https://www.biorxiv.org/content/10.1101/2024.11.14.623572v1

Model: https://github.com/BlueBrain/AstroVascPy

Gource: A Tool for Validating Project Quality

Gource is an open-source visualization tool that animates your project's history, making it invaluable for assessing development quality, refactoring efforts, and overall contributions.

Validating Code Quality Through Visualizations

Gource visualizes refactoring by animating file changes, showing how files move, split, or consolidate over time. This helps developers and stakeholders quickly understand improvements in code quality, reduction of technical debt, and the effectiveness of refactoring efforts.

Assessing Project Structure and Stability

Gource illustrates the evolution of project structure as a dynamic tree, with commits visually highlighted. This allows teams to track development focus, identify potential problem areas, and validate the stability of critical components, ensuring the quality of the evolving codebase.

Recognizing Contributor Impact

Gource highlights individual contributions, bringing visibility to crucial but often-overlooked work like testing, infrastructure, and maintenance. By summarizing contributions, Gource helps validate each team member’s impact on the project's quality.

Demonstrating Project Health and Progress

Gource’s animations transform complex commit histories into clear, engaging visuals, allowing stakeholders to easily understand project health, growth, and quality improvements over time.

Conclusion

Gource is a powerful tool for validating and communicating project quality. It provides an engaging way to understand development progress, refactoring outcomes, and individual contributions, turning commit history into a meaningful story of continuous improvement.

Links

Gource: https://github.com/acaudwell/Gource

Demo Project: https://github.com/BlueBrain/BioExplorer/

AI: The Fourth Industrial Revolution explained simply

The 21st century's tech revolution evolved by decade: the 2000s brought massive data through the internet, the 2010s saw GPU-powered computing take off, and the 2020s combined data and compute into transformative AI. Each decade set the stage, driving us into an AI-centric Fourth Industrial Revolution.

Looking forward to 2030! 😀

EPFL: An extended and improved CCFv3 annotation and Nissl atlas of the entire mouse brain

Huge congrats to Sebastien Piluso!

It was a pleasure and a real learning experience working for the inspiring science of finaly completing the truncated version of the mouse brain atlas.

The Blue Brain Project presents the first comprehensive mouse brain atlas based on the Allen Institute’s Common Coordinate Framework version 3. This atlas includes anatomical Nissl reference data that has been precisely aligned within this reference space, providing the scientific community with a crucial tool for automated and accurate mapping of a wide range of histological slices or volumes of the mouse brain. We have also integrated additional layers, such as the spinal cord, barrel columns, as well as the granular and molecular layers in the cerebellum. This allowed us to create an enhanced version of our cell atlas, mapping every cell in the mouse brain by location, region, and type. From this data, properties such as neuron soma and morphology can be derived, paving the way for increasingly accurate simulation models.

So proud of that movie!

Link to the publication: https://www.biorxiv.org/content/10.1101/2024.11.06.622212v1

Neuroscience: VR Tractome Dataset Diffusion Tensor Imaging as a point cloud

Hey tech enthusiasts,

I'm thrilled to announce that I've just deployed a virtual reality experience that takes Diffusion Tensor Imaging (DTI) to the next level. Imagine walking through the intricate neural pathways of the human brain, visualized as a mesmerizing network of point clouds—now possible in full VR.

Try it here: https://diffusion-tensor-imaging.netlify.app

The experience is based on DTI data from the Tractome project, which you can explore right here:

- Tractome Dataset: https://github.com/FBK-NILab/tractome

Grab your favorite VR headset—like the Meta Quest—and get ready for an immersive adventure that lets you journey through the brain in a completely new way. Whether you’re a neuroscientist, a VR enthusiast, or just someone curious about the inner workings of the mind, this is your chance to dive deep into brain connectivity, like never before.

For those who want to dive under the hood, I've shared the source code to create the point cloud LAS dataset, which you can find here:

- MetaBrain DTI Point Cloud: https://github.com/favreau/MetaBrain/tree/main/DTI

This repository provides everything you need to generate these beautiful visualizations and bring them into VR.

So, put on that headset, fire up the point cloud, and get ready to be amazed by the beauty of the brain.

Happy exploring!

Science: Rendering the Beautiful FlyWire Dataset In Just 2 Hours

When tasked with rendering a dataset as intricate and breathtaking as the one I recently worked on, the tools at my disposal had to be cutting-edge. Fortunately, I had the privilege of developing and utilizing the open-source Blue Brain BioExplorer. With this powerful software, I was able to render a stunning, complex dataset in just two hours, starting from scratch.

The dataset in question showcased neural circuits and synaptic connections, which demanded precise visualization. Standard off-the-shelf tools wouldn’t have been up to the task, but the BioExplorer—specifically designed for handling massive neural data—allowed me to create high-quality images quickly and efficiently.

What might have taken days using generic software took only two hours with the BioExplorer, demonstrating the importance of having the right tools for the job. This custom solution, optimized for large-scale data and high-performance environments, allowed me to bring the dataset to life, offering a detailed, clear, and beautiful view of neural structures.

The ability to achieve such results in record time speaks volumes about the power of specialized software. The Blue Brain BioExplorer not only makes working with complex data manageable, but it transforms the data into something visually inspiring, informing, educating, and sparking curiosity along the way.

We thank the Princeton FlyWire team and members of the Murthy and Seung labs, as well as members of the Allen Institute for Brain Science, for development and maintenance of FlyWire (supported by BRAIN Initiative grants MH117815 and NS126935 to Murthy and Seung). We also acknowledge members of the Princeton FlyWire team and the FlyWire consortium for neuron proofreading and annotation.

Flywire: https://flywire.ai

Blue Brain BioExplorer: https://github.com/BlueBrain/BioExplorer

Dataset: https://codex.flywire.ai/api/download

Just for fun: Online open-source online SWC neuron visualizer

With SfN coming up, I’ve put together a small neuron visualizer for SWC files. It's nothing too fancy, just a fun, simple base for anyone who wants to interactively visualize neurons. Best part? It’s open source and super easy to tweak

You can also hook it up to http://www.neuromorpho.org if you need access to a broader neuron database. Feel free to play around, modify the code, and let me know what you think. It’s all about making things simpler and more accessible.

Try it live: https://single-neuron.scientific-visualization.org

Visualize a morphology from neuromorpho using the swc url parameter:

https://single-neuron.scientific-visualization.org/?swc=https://neuromorpho.org/dableFiles/tarusawa/CNG%20version/WT-iPS-derived-cell-14L.CNG.swc

Source code: https://github.com/favreau/MetaBrain