Opening a whole new interface between nanotechnology and neuroscience, scientists at Harvard University have used slender silicon nanowires to detect, stimulate, and inhibit nerve signals along the axons and dendrites of live mammalian neurons.
Harvard chemist Charles M. Lieber and colleagues report on this marriage of nanowires and neurons this week in the journal Science.
“We describe the first artificial synapses between nanoelectronic devices and individual mammalian neurons, and also the first linking of a solid-state device — a nanowire transistor — to the neuronal projections that interconnect and carry information in the brain,” says Lieber, the Mark Hyman, Jr., Professor of Chemistry in Harvard’s Faculty of Arts and Sciences and Division of Engineering and Applied Sciences. “These extremely local devices can detect, stimulate, and inhibit propagation of neuronal signals with a spa-tial resolution unmatched by existing techniques.”
Because the nanowires are so slight — their contact with a neuron is no more than 20 millionths of a meter in length — Lieber and colleagues were able to measure and manipulate electrical conductance at as many as 50 locations along a single axon.
The current work involves measurement of signals only within single mammalian neurons; the researchers are now working toward monitoring signaling among larger networks of nerve cells. Lieber says the devices could also eventually be configured to measure or detect neurotransmitters, the chemicals that leap synapses to carry electrical impulses from one neuron to another.
“This work could have a revolutionary impact on science and technology,” Lieber says. “It provides a powerful new approach for neuroscience to study and manipulate signal propagation in neuronal networks at a level unmatched by other techniques; it provides a new paradigm for building sophisticated interfaces between the brain and external neural prosthetics; it represents a new, powerful, and flexible approach for real-time cellular assays useful for drug discovery and other applications; and it opens the possibility for hybrid circuits that couple the strengths of digital nanoelectronic and biological computing components.”
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