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Published December 26, 2007 | Published + Supplemental Material
Journal Article Open

Targeting and Readout Strategies for Fast Optical Neural Control In Vitro and In Vivo


Major obstacles faced by neuroscientists in attempting to unravel the complexity of brain function include both the heterogeneity of brain tissue (with a multitude of cell types present in vivo) and the high speed of brain information processing (with behaviorally relevant millisecond-scale electrical activity patterns). To address different aspects of these technical constraints, genetically targetable neural modulation tools have been developed by a number of groups (Zemelman et al., 2002; Banghart et al., 2004; Karpova et al., 2005; Lima and Miesenbock, 2005; Thompson et al., 2005; Chambers et al., 2006; Tan et al., 2006; Gorostiza et al., 2007; Lerchner et al., 2007; Szobota et al., 2007). One approach recently brought to neurobiology, combining both high speed and genetic targeting, is based on a family of fast light-responsive microbial opsins including halorhodopsins (e.g., NpHR) and channelrhodopsins (e.g., ChR2) (for review, see Zhang et al., 2007b). These microbial opsins are single-component transmembrane conductance regulators encompassing light sensitivity and fast membrane potential control within a single open reading frame, which can be used to achieve fast bidirectional control of specific cell types even in freely moving animals (Adamantidis et al., 2007; Zhang et al., 2007a). Although the basic functioning of these tools has been reviewed previously (Zhang et al., 2007b), here we describe a collection of targeting and readout strategies designed for rapid and flexible application of the microbial opsin system, and provide pointers to the relevant literature. Combinations of these multiple levels of targeting and readout define an evolving toolbox that may open up new possibilities for basic neuroscience investigation.

Additional Information

© 2007 Society for Neuroscience. Beginning six months after publication the Work will be made freely available to the public on SfN's website to copy, distribute, or display under a Creative Commons Attribution 4.0 International (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/). Received Aug. 7, 2007; revised Nov. 21, 2007; accepted Nov. 21, 2007. K.D. is supported by National Alliance for Research on Schizophrenia and Depression, American Psychiatric Institute for Research and Education, and the Snyder, Culpeper, Coulter, Klingenstein, Whitehall, McKnight, Kinetics, and Albert Yu and Mary Bechmann Foundations, as well as by National Institute of Mental Health, National Institute on Drug Abuse, the National Institutes of Health (NIH) Director's Pioneer Award Program, and the National Science Foundation. V.G. is supported by a Stanford Graduate Fellowship. F.Z. is supported by an NIH National Research Service Award. Special thanks to the Deisseroth laboratory, Russ Altman, Matthew Scott, Dan Tracey, Peter Hegemann, Georg Nagel, Alexander Gottschalk, Guoping Feng, George Augustine, and Jaimie Henderson for discussions. The materials and methods described herein are freely distributed and supported by the authors (www.stanford.edu/group/dlab).

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