You really have to make a model of it and figure out how you think it’s going to behave.”Ībbott, Freeman, and other theoretical and computational neuroscientists at Janelia are working to build lifeboats and lighthouses for other scientists to help them navigate the swirling storms of data. “When you have a population of neurons, and they’re all interacting, it’s almost impossible to have that intuition. With a single neuron, an experimentalist could use his or her intuition and, in fact, people are quite good at that,” says Larry Abbott, a Janelia senior fellow and a theoretical neuroscientist at Columbia University. “It’s really a big change from thinking about what single neurons do to thinking about what large populations of neurons do. To stay afloat in the deluge of data, scientists need to develop an entirely new way of thinking about experiments – and making sense of the resulting torrent of information. Simultaneous increases in computing power mean researchers can perform more sophisticated analyses, studying relationships between groups of neurons instead of analyzing one neuron at a time. A single set of experiments can generate terabytes of information. Neuroscientists can record the activity of nearly all the neurons in the brains of zebrafish larvae, and in ever increasing portions of mouse and Drosophila fruit fly brains. Now, the pendulum has swung in the opposite direction. “What you would do, back in the day, is maybe look at a couple of neurons in one part of the brain during simple sensory stimulation – a very focused study,” says Jeremy Freeman, a neuroscientist and group leader at HHMI’s Janelia Research Campus. To utilize this information about the billions of neurons that spit and sputter and make us, well, human, researchers have to cope with an exponential growth in data. Since the 1950s, the number of neurons that scientists can record simultaneously has grown at an exponential pace, doubling roughly every seven years.

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