There are 70 million neurons in the mouse brain, and Moritz Helmstaedter wants to map them all. He was a medical student at Heidelberg University in Germany when psychiatrists there suggested that some aspects of the human psyche lack a biological explanation. “I was totally appalled,” recalls Helmstaedter, who is now a director at the Max Planck Institute for Brain Research in Frankfurt, Germany.

Although the brain remains a mystery, Helmstaedter was convinced that what goes on there “must be a mechanistic phenomenon in the end, as complex as it may be”. He has dedicated the past two decades to working those mechanisms out — and he and other neuroscientists are finally starting to scratch the surface, one cubic micrometre at a time.

Starting in the 1970s, it took more than a decade to unravel the neural circuitry of the one-millimetre worm, Caenorhabditis elegans. Probing the relationship between genes and behaviour, biologist Sydney Brenner and his colleagues at the MRC Laboratory of Molecular Biology in Cambridge, UK, laboriously traced the fine branches and synaptic connections of each nerve cell, colour-coding them by hand on thousands of electron-micrograph prints. That wiring map — the first and only complete set of synaptic connections in an animal’s nervous system — was stored on a room-sized computer and published1 as the first full animal ‘connectome’ in a 340-page opus in 1986.

Caenorhabditis elegans has fewer than 400 neurons; human brains have 86 billion. So for now, scientists are eyeing an intermediate milestone: mapping the fine-scale neural circuitry of the mouse2.

Even with about 1,000-fold fewer cells, the mouse brain poses a formidable challenge, says Jeff Lichtman, a neuroscientist at Harvard University in Cambridge, Massachusetts, who is one of the leaders of a global consortium that aims to reconstruct the neural wiring of a mouse brain over the next decade. “We’re dealing with a data set that will be on the scale of an exabyte.” An exabyte is one billion gigabytes; the entire human genome can be represented in about 1.5 gigabytes. In terms of data size, mapping the mouse brain connectome will be “enormous compared to anything that’s been done as a single project”, he says. “Connectomes are just magnificently complicated.”

Yet the technology to make such an undertaking possible is nearly there. With advances in microscopy and artificial intelligence (AI), and crowdsourced help from human gamers, researchers are beginning to map neural networks and their connections at ever-higher resolution and scale. Over the past several years, small bits of brain, including pieces of the mammalian retina and cerebral cortex, have come into focus. And in September, researchers working on Drosophila fruit flies reported3 the largest reconstruction so far: 25,000 neurons in the hemibrain, a cube of tissue measuring 250 micrometres on a side and representing 40% of the fly’s brain.

These are not mere exercises in big biology. As connectomics pushes the technological and computational limits, researchers hope to tap these data sets to learn how experiences are stored in the brain, with potential insights into autism, schizophrenia and other ‘connectopathies’.

Early developments

After the C. elegans neural-wiring diagram launched connectomics in 1986, the field went silent, says Helmstaedter. It was an issue of technology: researchers had no way, beyond what Brenner’s team had done, to probe neural circuits at connectome scales.

As a doctoral student in the early 2000s, Helmstaedter stuck electrodes into nerve cells to figure out which ones were electrically connected, an approach that might allow the simultaneous recording of four or five neurons. Yet networks have hundreds or thousands of nerve cells and millions of connections. “To really map the circuits, we needed something else,” he says.

That came in 2004. Winfried Denk, then at the Max Planck Institute for Medical Research in Heidelberg, and his colleagues installed a precision-cutting tool called a microtome in the vacuum chamber of an electron microscope (EM), making it possible to automate nanoscale imaging. It revitalized the field4.

Called serial block-face scanning electron microscopy (SBEM), Denk’s method involves loading a block of tissue into the machine, which then automatically images the exposed face, scrapes off the top layer of tissue and repeats, for days or weeks at a time. In 2013, Denk’s team, led by Helmstaedter, a former postdoc in the lab, used SBEM to map a complete set of synaptic connections for 950 neurons in the mouse retina5. This was a significant undertaking: the cost, including equipment, salaries and some €300,000 (US$350,000) in fees paid to undergraduate students to trace circuits throughout the EM data sets, totalled around €2 million. And it revealed new cell subtypes. But beyond that, the work provided a comprehensive map for researchers to identify interaction partners for cells of interest, Helmstaedter says — “l(fā)ike using a street map for navigation versus trial and error”.

Worm maths

The students who traced those neural circuits did so using computers. That shift began in the early 2000s, when researchers began adopting a computational approach to mapping the connectome. This wasn’t machine learning; humans still did the work. But rather than tracing neurons on paper with coloured pencils as Brenner’s team had, they mouse-clicked through stacks of digitized images.

Biologist Scott Emmons at the Albert Einstein College of Medicine in New York City and his team, for instance, digitized Brenner’s original images and used a computational approach to map the circuits that regulate mating behaviours in the tail of a male C. elegans. (The 1986 effort focused on the other C. elegans sex, the hermaphrodite.)