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It’s a long, <\/span>hard road to understanding the human brain, and one of the first milestones in that journey is building a \u2026 database.<\/p>\n In the past few years, neuroscientists have embarked on several ambitious projects to make sense of the tangle of neurons that makes the human experience human, and an experience. In the UK, Henry Markram\u00a0–\u00a0the Helen Cho to Elon Musk\u2019s Tony Stark\u00a0–\u00a0is leading the Human Brain Project<\/a>, a $1.3 billion plan to build a computer model of the brain. In the US, the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative hopes to, in its own nebulous way, map the dynamic activity of the noggin\u2019s 86 billion neurons.<\/p>\n Now, the Allen Institute for Brain Science<\/a>, a key player in the BRAIN Initiative, has launched a database of neuronal cell types that serves as a first step toward\u00a0a complete\u00a0understanding of the brain. It\u2019s the first milestone in the Institute\u2019s 10-year MindScope<\/a> plan, which aims to nail down how\u00a0the visual system of a mouse works, starting by developing a functional taxonomy of all the different types of neurons in the brain.<\/p>\n \u201cThe big plan is to try to understand how the brain works,\u201d says Lydia Ng<\/a>, director of technology for the database. \u201cCell types are one of the building blocks of the brain, and by making\u00a0a big model of how they\u2019re put together, we can understand all the activity that goes into perceiving something and creating an action based on that perception.\u201d<\/p>\n The Allen Cell Types Database<\/a>, on its surface, doesn\u2019t look like much. The first release includes information on just 240 neurons out of hundreds of thousands\u00a0in the mouse visual cortex, with a focus on the electrophysiology of those individual cells: the electrical pulses that tell a neuron to fire, initiating a pattern of neural activation that results in perception and action. But understanding those single cells well enough to put\u00a0them into larger categories will be crucial to understanding the brain as a whole\u00a0–\u00a0much like the periodic table was necessary\u00a0to establish\u00a0basic chemical principles.<\/p>\n Though researchers have come a long way in studying\u00a0the brain, most of the information they have is big-picture, in the form of functional scans that show activity in brain areas, or small-scale, like the expression of neurotransmitters and their receptors in individual neurons. But the connection between those two scales\u00a0–\u00a0how billions of neurons firing together results in patterns of activation and behavior\u00a0–\u00a0is still unclear. Neuroscientists don\u2019t even have a clear idea of just how many different cell types exist, which is crucial to understanding how they work together. \u201cThere was a lot of fundamental information that was missing,\u201d CEO Allan Jones says\u00a0in a video<\/a>\u00a0about the database project. \u201cSo when we got started, we focused on what we call a reductionist approach, really trying to understand the parts.\u201d<\/p>\n When it\u2019s complete, the database will be the first in the world to collect information from individual cells along\u00a0four basic but crucial\u00a0variables: cell shape, gene expression, position in the brain, and electrical activity.\u00a0So far, the Institute has tracked three of those variables, taking high-resolution images of dozens of electrically-stimulated neurons with a light microscope, while carefully noting their position in the mouse\u2019s cortex. \u201cThe important early findings are that there are indeed a finite number of classes,\u201d says Jones. \u201cWe can logically bend them into classes of cells.\u201d<\/p>\n Next up, the Institute will accumulate\u00a0gene expression data in individual cells by sequencing their RNA, and the\u00a0overlap of all four\u00a0variables ultimately will result in the complete cell type taxonomy.\u00a0That classification system will help\u00a0anatomists, physicists, and neuroscientists direct their study of neurons more efficiently and build more accurate models of cortical function. But it\u2019s important to point out that the database isn\u2019t merely important for its contents. How those contents were measured and aggregated also is crucial to the future of these big-picture brain mapping initiatives.<\/p>\n To create a unified model of the brain, neuroscientists must collect millions of individual data points from neurons in the brain. To start, they take electrical readings from living neurons by stabbing them with tiny, micron-wide pipettes. Those pipettes deliver current to the cells\u2014enough to get them to fire\u2014and record the cell\u2019s electrical output. But there are many ways to set up those electrical readings, and to understand the neural system as a whole, neuroscientists need to use the same technique every time to make sure that the electrical traces can be compared from neuron to neuron.<\/p>\n