Reference projects such as GenBank and the HapMap, which catalog gene sequences, have ushered in a new era of discovery in many avenues of biomedicine. But the burgeoning field of neuroimaging still lacks such scientific tools. This is in part because data from one of the most commonly used tools for studying human cognition—functional magnetic resonance imaging (fMRI) on subjects performing a specific task—cannot easily be compared across study sites. As a result, there's a growing need for a large database to serve as a reference of activity patterns within the human brain.

Last month, a team led by Michael Milham, a neuroscientist at New York University (NYU) Child Study Center, published the first analysis from the 1,000 Functional Connectomes Project, a collection of fMRI data sets donated by researchers from 35 centers around the world. This freely available resource includes data from more than 1,400 healthy subjects who underwent fMRI scans that assessed their brain activity when their minds were at rest (Proc. Natl. Acad. Sci. USA 107, 4734–4739, 2010). The study showed that resting-state fMRI data—long thought of as nothing more than random, background noise—can be reliably pooled across scanners to unveil a universal architecture of activity connections within the brain.

Unlike task-based fMRI, which can be highly specific to the study site, the 1,000 Functional Connectomes resource allows for systematic explorations of healthy and diseased brains to discover hitherto unknown underlying differences. “We're moving in the direction of being able to have objective measures of neurological and psychiatric illness,” Milham says. “It's all stepping in the direction of being a clinical tool.”

The effort takes its name from the Human Connectome Project, a $30 million initiative launched by the US National Institutes of Health last year to map the entire physical circuitry of the healthy adult human brain. But functional connectivity and structural connectivity are not the same thing. Functional connections, for example, can span more than one synapse and can be modulated by emotion or sleep, whereas anatomical circuits are more or less fixed over the short term.

“Having this much data in one place is a real treasure trove that is free to anybody who wants to play with it,” says Marcus Raichle, a pioneer of resting-state fMRI at Washington University in St. Louis, Missouri who was not involved with the study.

“The connectomes project has the power to ask more questions,” adds Craig Bennett, a cognitive neuroscientist at the University of California–Santa Barbara who published a review this month questioning the reliability and repeatability of fMRI scans in most typical neuroimaging studies (Ann. N.Y. Acad. Sci. 1191, 133–155, 2010). “You're not just looking across one study, you're drawing from such a large body of research that you really say things with authority.”

Since having been posted online last December, the data set has been downloaded more than 4,500 times from researchers across 54 countries, according to Milham. One person who has explored the resource is Nora Volkow, director of the US National Institute on Drug Abuse in Bethesda, Maryland. Volkow is now developing quantitative methods to measure functional connectivity in her lab to follow up on preliminary observations of systemic differences between males and females.

“What's striking is how terribly consistent [the data] are—it's mindboggling,” Volkow says. “I could use that data set to assess whether the connectivity patterns that I'm seeing in my patient actually differ in any significant way from this data set, which I can use as reference.”