Map scale

A new brain map represents every component of the biological universe

Neurons make up less than half of the brain. Yet when it comes to brain mapping, they get all the limelight.

It’s easy to see why: as surprisingly powerful mini-processors, neurons and their connections – collectively called the connectome – hold the secret to highly efficient and flexible computation. Tucked inside the wiring diagrams of the brain are the keys to consciousness, memories and emotions. For connectomics, mapping the brain is not just an academic exercise to better understand us, it could lead to more efficient AI that thinks like us.

But the brain’s supporting characters are often overlooked: astrocytes, star-shaped brain cells, and microglia, specialized immune cells. Previously thought of as “wallflowers,” these cells feed neurons and refine their connections, ultimately shaping the connectome. Without this long-forgotten half, the brain would not be the computer assistant we strive to emulate with machines.

In a stunning new brain map published in Cell, these cells finally have their time in the spotlight. Led by Princeton University’s Dr. H. Sebastian Seung, the original prophet of the connectome, the map captures a tiny piece of the mouse’s visual cortex, less than 1,000 times smaller than a pea. However, inside the map, there are not only neurons; in a technical tour de force, the team mapped all brain cells, their connections, blood vessels and even the compartments inside cells that house DNA and produce energy.

All the data is freely available here for neuroscientists (and you!) to explore.

“A groundbreaking large-scale dataset and a shining star of open science, which will support breakthroughs in understanding the neocortex for years to come,” remarked Dr. Eilif Muller of the University of Montreal, who n did not participate in the study.

“It’s impossible to overstate the impact that functional connectomics will have on neuroscience,” said Dr. David Markowitz, program manager at the Intelligence Advanced Research Projects Activity (IARPA), which funded the study.

MICrONS on Steroids

The new board is part of MICrONS, a highly ambitious project under IARPA and the BRAIN initiative that pursues the high-risk, high-reward perspective of our times: machines that think like humans.

Launched in 2016 with an initial budget of $100 million, the project – Machine Intelligence from Cortical Networks – is betting on reverse engineering algorithms in our brains to power the next generation of AI. Their first goal may seem rather mundane: to distill sensory computations, that is, how the brain handles visual data, to amplify a machine’s ability to process, analyze and label images and video. In a world of ever-increasing digital content (and deepfakes), more efficient visual processing could mean billions.

There have already been significant victories. In 2021, the project published the largest ever map of neural activity and synapses in the mammalian brain. The map covered 75,000 neurons and over 500 million synaptic connections. It’s a jaw-dropping scale, and the treasure trove of data is still being mined today, as scientists study how the shape, i.e. the location of neurons and synapses, impacts on the functioning of the visual cortex.

A triumph of automation

With the new map, Seung has expanded the effort and made it much more detailed.

It starts with a healthy young male mouse. Using a dye that lights up when neurons fire, the team recorded hours of activity from his visual cortex, gaining insight into activated neural networks in real time.

The brain was then carefully sliced ​​into ultra-thin slices at freezing temperatures to preserve all biological components. At the same time, the team imaged each slice with an electron microscope, a very powerful tool with resolution at a fraction of the nanoscale and 4,000,000 times more powerful than our eyes. At this resolution, the team was able to clearly see organelles – small nuclei inside cells – such as the nucleus that houses DNA or the mitochondria that generate energy.

In total, the images yielded around eight million objects, including neurons, other brain cells and fragments.

Then came the hard part: putting everything back in place. The team used a semi-automated method, drawing on previous algorithms to identify different cell types. They further tweaked existing programs to better capture cells and their components, working for over a thousand hours per person.

It paid off. Overall, the team reconstructed more than 350 neurons, each with its tightly intertwined branches, and more than 3.5 million synapses. They further mapped dozens of supporting brain cells, including those that protect the brain’s blood supply and immune cells and those that arm neurons with a nonconductive protective sheath for faster signal transduction. Add to that more than 2.4 million mapped mitochondria – the powerhouse of the cell – and the team has constructed a never-before-seen map of the brain.

After proofreading, the team said they had a “very precise map of the connectivity” between neurons, with almost 2,000 synapses that “can be used to analyze the properties of cortical circuits”.

Why care?

A card is just boring data if it is not used. In several short proof-of-concept experiments, the team dug into the ultimate question: why is the brain so energy efficient?

The first thumbnail went deep. A neuron, often dubbed the computing unit in the brain, is much more complex. Each section of a neuron has its own algorithms, supported by local energy producers, the mitochondria. Looking at the new map, the team realized that not all mitochondria are the same, with much longer shapes in the input wires of neurons – also nanocomputers themselves – than those of exit.

By analyzing the map, the team found that the number of mitochondria increased with the number of synapses (where neurons connect to each other), providing support that neurons use to route more energy factories to their connectivity hubs. In other words, neurons have a built-in supply chain to deliver energy to the most consuming regions.

In another analysis, the team took a peek into the new board’s connectome. To their surprise, for a subset of more than 100 nearby neurons, the cells connected to just over eight percent of them, much sparser connections than previously thought. When neurons connected, they went both ways, with inputs and outputs going both ways. This type of circuit wiring had a huge impact on the calculation. When the team overlaid neural network activity on the map, they found that cells with more connections to their neighbors also tended to respond more strongly to visual cues.

They found both “chorister” and “soloist” cells. But from the map, it’s clear that a higher density of connections for one cell – a “chorister” – enhances its response to visual stimuli.

This is just a first look at how the new map provides insight into our neural computations. Analyzing these connecting “patterns” can help us better understand why and how the visual cortex shows strong and reliable responses in an ever-changing world, which we can then program into machines.

For now, the team is happy with their massive data dump and the tools they have to help analyze the dataset. Their detailed reconstruction of part of the brain, including all the details, will no doubt intrigue experts specializing in non-neuronal brain cells and their function. The map comes at a time of growing evidence that the brain’s immune system is involved in normal neural processing and dementia.

Overall, the study is an introduction to a new era of brain mapping. “This paper from the IARPA MICrONS Consortium lays the groundwork for making these studies routine network-wide,” Markowitz said. “Really awesome stuff.”

Image Credit: H. Sebastian Seung/Princeton Neuroscience Institute