Computational Neuroscientist; Francis Crick Professor, the Salk Institute; Investigator, Howard Hughes Medical Institute; Co-author (with Patricia Churchland), The Computational Brain

Scientific ideas change when new instruments are developed that detect something new about nature. Electron microscopes, radio telescopes, and patch recordings from single ion channels have all led to game-changing discoveries.

We are in the midst of a technological revolution in computing that has been unfolding since 1950 and is having a profound impact on all areas of science and technology. As computing power doubles every 18 months according to Moore's Law, unprecedented levels of data collection, storage and analysis have revolutionized many areas of science.

For example, optical microscopy is undergoing a renaissance as computers have made it possible to localize single molecules with nanometer precision and image the extraordinary complex molecular organization inside cells. This has become possible because computers allow beams to be formed and photons collected over long stretches of time, perfectly preserved and processed into synthetic pictures. High resolution movies are revealing the dynamics of macromolecular structures and molecular interactions for the first time.

In trying to understand brain function we have until recently relied on microelectrode technology that limited us to recording from one neuron at a time. Coupled with advances in molecular labels and reporters, new two-photon microscopes guided by computers will soon make it possible to image the electrical activity and chemical reactions occurring inside millions of neurons simultaneously. This will realize Sherrington's dream of seeing brain activity as an "enchanted loom where millions of flashing shuttles weave a dissolving pattern, always a meaningful pattern though never an abiding one; a shifting harmony of subpatterns."

By 2015 computer power will begin to approach the neural computation that occurs in brains. This does not mean we will be able to understand it, only that we can begin to approach the complexity of a brain on its own terms. Coupled with advances in large-scale recordings from neurons we should by then be in a position to crack many of the brain's mysteries, such as how we learn and where memories reside. However, I would not expect a computer model of human level intelligence to emerge from these studies without other breakthroughs that cannot be predicted.

Computers have become the new microscopes, allowing us to see behind the curtains. Without computers none of this would be possible, at least not in my lifetime.