| Electrokinetic confinement of axonal growth for dynamically configurable neural networks. | |
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MedLine Citation:
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PMID: 23314575 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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Axons in the developing nervous system are directed via guidance cues, whose expression varies both spatially and temporally, to create functional neural circuits. Existing methods to create patterns of neural connectivity in vitro use only static geometries, and are unable to dynamically alter the guidance cues imparted on the cells. We introduce the use of AC electrokinetics to dynamically control axonal growth in cultured rat hippocampal neurons. We find that the application of modest voltages at frequencies on the order of 10(5) Hz can cause developing axons to be stopped adjacent to the electrodes while axons away from the electric fields exhibit uninhibited growth. By switching electrodes on or off, we can reversibly inhibit or permit axon passage across the electrodes. Our models suggest that dielectrophoresis is the causative AC electrokinetic effect. We make use of our dynamic control over axon elongation to create an axon-diode via an axon-lock system that consists of a pair of electrode 'gates' that either permit or prevent axons from passing through. Finally, we developed a neural circuit consisting of three populations of neurons, separated by three axon-locks to demonstrate the assembly of a functional, engineered neural network. Action potential recordings demonstrate that the AC electrokinetic effect does not harm axons, and Ca(2+) imaging demonstrated the unidirectional nature of the synaptic connections. AC electrokinetic confinement of axonal growth has potential for creating configurable, directional neural networks. |
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Authors:
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Thibault Honegger; Mark A Scott; Mehmet F Yanik; Joel Voldman |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2013-1-14 |
Journal Detail:
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Title: Lab on a chip Volume: - ISSN: 1473-0189 ISO Abbreviation: Lab Chip Publication Date: 2013 Jan |
Date Detail:
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Created Date: 2013-1-14 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101128948 Medline TA: Lab Chip Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Room 36-824, Cambridge, MA 02139, USA. voldman@mit.edu. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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