The Grain of Sand That Disproved Francis Crick: The Largest Brain Map Ever Made Broke a Science Prophecy
- Lidi Garcia
- 5 days ago
- 4 min read
A consortium of scientists has managed, for the first time, to map in extremely high detail both the structure and functioning of a tiny piece of a mouse brain, the size of a grain of sand. They used advanced technologies to record how around 75,000 neurons respond to images and then reconstructed in 3D more than 200,000 cells and half a billion connections between them. This allows us to better understand how the brain processes information and may help reveal the "algorithms" it uses to think and perceive the world. It is a huge step towards a deeper understanding of the brain.
In 1979, scientist Francis Crick (one of the discoverers of the structure of DNA) said that it would be impossible to obtain a complete "wiring diagram" of even a tiny piece of the brain, such as a cubic millimeter of tissue. He was referring to the challenge of mapping all the connections between neurons, because this is precisely what defines how they work.
Dr. Francis Crick
For decades, scientists studied these connections using laborious methods, analyzing neurons individually or measuring their electrical activity. Later, they began using other techniques, such as calcium imaging (to see neurons working), laboratory recordings, and even viral tracking.
While these approaches were very useful, they still provided partial information, as if we were seeing only pieces of a giant jigsaw puzzle.
Today, thanks to technological advances, Crick’s vision is becoming a reality. By combining calcium imaging with high-resolution electron microscopy (EM), scientists were able to study in detail a cubic millimeter of a mouse’s visual cortex, a region of the brain responsible for processing visual information.
They did this by recording the activity of thousands of neurons while the animal viewed images, and then analyzed this same tissue with electron microscopy to see the exact structure of the cells and their connections.
Calcium Image
The result was a complete 3D reconstruction, created using artificial intelligence and then manually reviewed to ensure accuracy. Finally, they linked the functional responses of the neurons to their respective connections.
This database is impressive: it includes neurons of various types (such as pyramidal and inhibitory), supporting cells such as astrocytes and microglia, and even blood vessels. Through an online platform, anyone can explore these structures, see input and output synapses, and even download the data to perform their own analyses.
This initiative has enabled new ways of identifying neuron types, showing that in many cases, the way they connect reveals more about their type than their shape. They have also begun to connect these types to genetic data, bridging different areas of science.
Another important result was the discovery of connectivity patterns between neurons that respond to similar stimuli, indicating that the brain may follow more complex organizational rules than previously thought.
Pyramidal cells reconstructed from EM images (inset)
To do this, the scientists used an artificial intelligence trained to predict neuron activity based on the images the mouse saw. This helped them better understand how the brain processes visual information, including aspects such as context and perceptual constancy, and pointed the way for further studies.
But the impact goes beyond these initial findings. The project, called MICrONS, has made this data public, with tools for analysis and visualization. It has also developed technologies that are being used in other massive efforts, such as the complete reconstruction of the fruit fly brain, something comparable to the first neural “map” ever made, that of the worm C. elegans.
It may seem small, but a cubic millimeter of brain contains tens of thousands of neurons and hundreds of millions of synapses. For a long time, it was impossible to study all of these at once.
Scientists focused on pairs of neurons or small groups. But with advances in imaging and artificial intelligence, as well as much more powerful computers, this has finally become feasible. Reconstructing this volume generated about 1 petabyte of data (a thousand times a terabyte!) and was only possible with automated methods to review errors and extract specific parts of neurons, such as axons and dendrites.
Another challenge was to deal with this enormous amount of information collaboratively. For this reason, the project also created its own version control system (as if it were the "GitHub" of the brain), ensuring that the data was organized and that no one did duplicate work. Thus, MICrONS is not only a database, but also a model for how to deal with large scientific projects in an integrated and efficient way. (https://www.microns-explorer.org/)
With all this data, the researchers created a “digital twin” of the mouse brain studied. This model can be used to simulate experiments and test theories about how the brain works, all in a virtual way. This type of approach is already helping to reveal computational principles about the processing of visual information and promises to revolutionize the way we study the brain.
In short, the MICrONS dataset is a milestone in the history of neuroscience. It combines structure and function, includes hundreds of thousands of cells and millions of connections, and is openly available to the scientific community. The project shows how it is possible, for the first time, to study the brain on a scale and with a level of detail previously unimaginable, and we are only at the beginning.
READ MORE:
Functional connectomics spanning multiple areas of mouse visual cortex
The MICrONS Consortium
Nature, volume 640, pages 435 – 447 (2025)
Abstract
Understanding the brain requires understanding neurons’ functional responses to the circuit architecture shaping them. Here we introduce the MICrONS functional connectomics dataset with dense calcium imaging of around 75,000 neurons in primary visual cortex (VISp) and higher visual areas (VISrl, VISal and VISlm) in an awake mouse that is viewing natural and synthetic stimuli. These data are co-registered with an electron microscopy reconstruction containing more than 200,000 cells and 0.5 billion synapses. Proofreading of a subset of neurons yielded reconstructions that include complete dendritic trees as well the local and inter-areal axonal projections that map up to thousands of cell-to-cell connections per neuron. Released as an open-access resource, this dataset includes the tools for data retrieval and analysis1,2. Accompanying studies describe its use for comprehensive characterization of cell types3,4,5,6, a synaptic level connectivity diagram of a cortical column4, and uncovering cell-type-specific inhibitory connectivity that can be linked to gene expression data4,7. Functionally, we identify new computational principles of how information is integrated across visual space8, characterize novel types of neuronal invariances9 and bring structure and function together to uncover a general principle for connectivity between excitatory neurons within and across areas10,11.
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