Key Points
-
'Optogenetic' approaches (the use of light-sensitive genetically encodable tools to manipulate cellular activity) in neuroscience have matured beyond the proof-of-principle phase and have grown into a widely used set of techniques for dissecting the circuits underlying behaviour.
-
Recent technological advances include the integration of optogenetics with established techniques in electrophysiology and pharmacology, as well as the expansion of the optogenetic toolbox to include new opsin variants and new transgenic rodent lines.
-
Optogenetic approaches provide new advantages such as precise cellular targeting and greater temporal control, but also bring new limitations that are important to consider, such as heating artefacts and problems with light delivery and overexpression toxicity.
-
Optogenetic approaches have led to the dissection of microcircuits in the amygdala underlying fear and anxiety and to the discovery of unexpectedly broad temporal regimes in which the hippocampus is involved in recalling remote memories.
-
The use of optogenetics to target a specific projection or specific cell type in transgenic Cre recombinase rodents has advanced our understanding of the circuits underlying reward-related learning relevant to addiction.
-
Manipulating parvalbumin neurons, rhythmic oscillations and the balance of excitation and inhibition in neocortex using optogenetic tools has advanced our understanding of schizophrenia- and autism-related phenomena.
-
The use of optogenetic methods has advanced our understanding of neurological disorders and treatments, clarifying our understanding of deep brain stimulation and striatal circuits in the context of Parkinson's disease.
Abstract
Optogenetic tools have provided a new way to establish causal relationships between brain activity and behaviour in health and disease. Although no animal model captures human disease precisely, behaviours that recapitulate disease symptoms may be elicited and modulated by optogenetic methods, including behaviours that are relevant to anxiety, fear, depression, addiction, autism and parkinsonism. The rapid proliferation of optogenetic reagents together with the swift advancement of strategies for implementation has created new opportunities for causal and precise dissection of the circuits underlying brain diseases in animal models.
This is a preview of subscription content, access via your institution
Relevant articles
Open Access articles citing this article.
-
AAV-compatible optogenetic tools for activating endogenous calcium channels in vivo
Molecular Brain Open Access 17 October 2023
-
Multifocal skull-compensated transcranial focused ultrasound system for neuromodulation applications based on acoustic holography
Microsystems & Nanoengineering Open Access 10 April 2023
-
Prefrontal engrams of long-term fear memory perpetuate pain perception
Nature Neuroscience Open Access 06 April 2023
Access options
Subscribe to this journal
Receive 12 print issues and online access
$189.00 per year
only $15.75 per issue
Rent or buy this article
Prices vary by article type
from$1.95
to$39.95
Prices may be subject to local taxes which are calculated during checkout





References
Deisseroth, K. Optogenetics. Nature Methods 8, 26–29 (2011).
Deisseroth, K. et al. Next-generation optical technologies for illuminating genetically targeted brain circuits. J. Neurosci. 26, 10380–10386 (2006).
Zhang, F. et al. The microbial opsin family of optogenetic tools. Cell 147, 1446–1457 (2011).
Airan, R. D., Thompson, K. R., Fenno, L. E., Bernstein, H. & Deisseroth, K. Temporally precise in vivo control of intracellular signalling. Nature 458, 1025–1029 (2009). This study developed the OptoXRs (photosensitive G protein-coupled receptors based on vertebrate opsin genes) for mammalian in vivo use and showed that light-activated intracellular signalling cascades could support conditioned place preference.
Boyden, E. S., Zhang, F., Bamberg, E., Nagel, G. & Deisseroth, K. Millisecond-timescale, genetically targeted optical control of neural activity. Nature Neurosci. 8, 1263–1268 (2005). The initial demonstration of single-component optogenetics using a microbial opsin gene (in this case, a channelrhodopsin).
Yizhar, O., Fenno, L. E., Davidson, T. J., Mogri, M. & Deisseroth, K. Optogenetics in neural systems. Neuron 71, 9–34 (2011). A comprehensive practical overview describing the implementation of optogenetic tools in neural systems.
Fenno, L., Yizhar, O. & Deisseroth, K. The development and application of optogenetics. Annu. Rev. Neurosci. 34, 389–412 (2010).
Carter, M. E. & de Lecea, L. Optogenetic investigation of neural circuits in vivo. Trends Mol. Med. 17, 197–206 (2011).
Aravanis, A. M. et al. An optical neural interface: in vivo control of rodent motor cortex with integrated fiberoptic and optogenetic technology. J. Neural Eng. 4, S143–S156 (2007).
Kravitz, A. V. & Kreitzer, A. C. Optogenetic manipulation of neural circuitry in vivo. Curr. Opin. Neurobiol. 21, 433–439 (2011).
Lima, S. Q. & Miesenböck, G. Remote control of behavior through genetically targeted photostimulation of neurons. Cell 121, 141–152 (2005).
Nagel, G. et al. Channelrhodopsin-1: a light-gated proton channel in green algae. Science 296, 2395–2398 (2002).
Nagel, G. et al. Channelrhodopsin-2, a directly light-gated cation-selective membrane channel. Proc. Natl Acad. Sci. USA 100, 13940–13945 (2003).
Zhang, F. et al. Red-shifted optogenetic excitation: a tool for fast neural control derived from Volvox carteri. Nature Neurosci. 11, 631–633 (2008).
Berndt, A. et al. High-efficiency channelrhodopsins for fast neuronal stimulation at low light levels. Proc. Natl Acad. Sci. USA 108, 7595–7600 (2011).
Gradinaru, V. et al. Molecular and cellular approaches for diversifying and extending optogenetics. Cell 141, 154–165 (2010).
Berndt, A., Yizhar, O., Gunaydin, L. A., Hegemann, P. & Deisseroth, K. Bi-stable neural state switches. Nature Neurosci. 12, 229–234 (2009).
Zhang, F. et al. Multimodal fast optical interrogation of neural circuitry. Nature 446, 633–639 (2007). The first behavioural loss-of-function using optogenetics; achieved here with the inhibitory optogenetic tool NpHR.
Chow, B. Y. et al. High-performance genetically targetable optical neural silencing by light-driven proton pumps. Nature 463, 98–102 (2010).
Gunaydin, L. A. et al. Ultrafast optogenetic control. Nature Neurosci. 13, 387–392 (2010).
Mattis, J. et al. Principles for applying optogenetic tools derived from direct comparative analysis of microbial opsins. Nature Methods 9, 159–172 (2011). An empirical comparison of most existing microbial opsin-derived optogenetic tools under matched conditions, including the development of several new opsin variants.
Iwai, Y., Honda, S., Ozeki, H., Hashimoto, M. & Hirase, H. A simple head-mountable LED device for chronic stimulation of optogenetic molecules in freely moving mice. Neurosci. Res. 70, 124–127 (2011).
Schneider, M. B., Gradinaru, V., Zhang, F. & Deisseroth, K. Controlling neuronal activity. Am. J. Psychiatry 165, 562 (2008).
Diester, I. et al. An optogenetic toolbox designed for primates. Nature Neurosci. 14, 387–397 (2011).
Adamantidis, A. R., Zhang, F., Aravanis, A. M., Deisseroth, K. & de Lecea, L. Neural substrates of awakening probed with optogenetic control of hypocretin neurons. Nature 450, 420–424 (2007). The first application of a microbial opsin to show a behavioural change in a mammal (gain of function, using a channelrhodopsin).
Grossman, N. et al. Multi-site optical excitation using ChR2 and micro-LED array. J. Neural Eng. 7, 016004 (2010).
Bernstein, J. G. et al. Prosthetic systems for therapeutic optical activation and silencing of genetically-targeted neurons. Proc. Soc. Photo Opt. Instrum. Eng. 6854, 68540H (2008).
Sparta, D. R. et al. Construction of implantable optical fibers for long-term optogenetic manipulation of neural circuits. Nature Protoc. 7, 68512–68523 (2011).
Atasoy, D., Aponte, Y., Su, H. H. & Sternson, S. M. A FLEX switch targets Channelrhodopsin-2 to multiple cell types for imaging and long-range circuit mapping. J. Neurosci. 28, 7025–7030 (2008).
Kuhlman, S. J. & Huang, Z. J. High-resolution labeling and functional manipulation of specific neuron types in mouse brain by Cre-activated viral gene expression. PLoS ONE 3, e2005 (2008).
Tsai, H.-C. et al. Phasic firing in dopaminergic neurons is sufficient for behavioral conditioning. Science 324, 1080–1084 (2009). The initial behavioural application of the double-floxed inverted open reading frame tool enabling selective opsin expression in neurons positive for Cre recombinase. This is used in the TH::Cre mouse to demonstrate the hedonic properties of phasic dopamine neuron firing.
Arenkiel, B. R. et al. In vivo light-induced activation of neural circuitry in transgenic mice expressing Channelrhodopsin-2. Neuron 54, 205–218 (2007).
Zhao, S. et al. Cell type-specific channelrhodopsin-2 transgenic mice for optogenetic dissection of neural circuitry function. Nature Methods 8, 745–752 (2011).
Taniguchi, H. et al. A resource of cre driver lines for genetic targeting of GABAergic neurons in cerebral cortex. Neuron 71, 995–1013 (2011).
Anikeeva, P. et al. Optetrode: a multichannel readout for optogenetic control in freely moving mice. Nature Neurosci. 15, 163–170 (2012).
Wang, J. et al. Integrated device for combined optical neuromodulation and electrical recording for chronic in vivo applications. J. Neural Eng. 9, 016001 (2012).
Witten, I. B. et al. Recombinase-driver rat lines: tools, techniques, and optogenetic application to dopamine-mediated reinforcement. Neuron 72, 721–733 (2011).
Lee, J. H. et al. Global and local fMRI signals driven by neurons defined optogenetically by type and wiring. Nature 465, 788–792 (2010).
Peterlin, Z. A., Kozloski, J., Mao, B.-Q., Tsiola, A. & Yuste, R. Optical probing of neuronal circuits with calcium indicators. Proc. Natl Acad. Sci. USA 97, 3619–3624 (2000).
Shoham, S. Optogenetics meets optical wavefront shaping. Nature Methods 7, 798–799 (2010).
Petreanu, L., Huber, D., Sobczyk, A. & Svoboda, K. Channelrhodopsin-2-assisted circuit mapping of long-range callosal projections. Nature Neurosci. 10, 663–668 (2007).
Petreanu, L., Mao, T., Sternson, S. M. & Svoboda, K. The subcellular organization of neocortical excitatory connections. Nature 457, 1142–1145 (2009).
Adesnik, H. & Scanziani, M. Lateral competition for cortical space by layer-specific horizontal circuits. Nature 464, 1155–1160 (2010).
Han, X. & Boyden, E. S. Multiple-color optical activation, silencing, and desynchronization of neural activity, with single-spike temporal resolution. PLoS ONE 2, e299 (2007).
Zhao, S. et al. Improved expression of halorhodopsin for light-induced silencing of neuronal activity. Brain Cell Biol. 36, 141–154 (2008).
Gradinaru, V., Thompson, K. R. & Deisseroth, K. eNpHR: a Natronomonas halorhodopsin enhanced for optogenetic applications. Brain Cell Biol. 36, 129–139 (2008).
Lin, J. Y., Lin, M. Z., Steinbach, P. & Tsien, R. Y. Characterization of engineered channelrhodopsin variants with improved properties and kinetics. Biophys. J. 96, 1803–1814 (2009).
Yizhar, O. et al. Neocortical excitation/inhibition balance in information processing and social dysfunction. Nature 477, 171–178 (2011). The introduction of two new opsin variants, C1V1 and SSFO, for combinatorial optogenetic excitation in vivo . The study showed the importance of altered excitation/inhibition ratios to social behaviour and cognition.
Berglund, K., Kuner, T., Feng, G. & Augustine, G. J. Imaging synaptic inhibition with the genetically encoded chloride indicator clomeleon. Cold Spring Harb. Protoc. 2011, 1492–1497 (2011).
Witten, I. B. et al. Cholinergic interneurons control local circuit activity and cocaine conditioning. Science 330, 1677–1681 (2010). The first behavioural loss-of-function in mammals achieved using optogenetics. This study involved the introduction of an inhibitory opsin into cholinergic interneurons using the double-floxed inverted open reading frame tool in a choline acetyltransferase (ChAT)::Cre mouse to demonstrate the role of cholinergic neurons in mediating cocaine-conditioned place preference.
Kravitz, A. V. et al. Regulation of parkinsonian motor behaviours by optogenetic control of basal ganglia circuitry. Nature 466, 622–626 (2010). This study used optogenetics to provide empirical evidence of the long-proposed effects of the direct and indirect pathways in the striatum on movement.
Adamantidis, A. R. et al. Optogenetic interrogation of dopaminergic modulation of the multiple phases of reward-seeking behavior. J. Neurosci. 31, 10829–10835 (2011).
Sohal, V. S., Zhang, F., Yizhar, O. & Deisseroth, K. Parvalbumin neurons and gamma rhythms enhance cortical circuit performance. Nature 459, 698–702 (2009). Together with reference 54, this study used optogenetic tools to link parvalbumin cells to gamma rhythms, information transmission and processing in the neocortex.
Cardin, J. A. et al. Driving fast-spiking cells induces γ rhythm and controls sensory responses. Nature 459, 663–667 (2009).
Gradinaru, V., Mogri, M., Thompson, K. R., Henderson, J. M. & Deisseroth, K. Optical deconstruction of parkinsonian neural circuitry. Science 324, 354–359 (2009). This study provided a mechanistic explanation for how DBS alleviates parkinsonian symptoms using optogenetic techniques in animal models.
Tye, K. M. et al. Amygdala circuitry mediating reversible and bidirectional control of anxiety. Nature 471, 358–362 (2011). The first optogenetic projection-specific targeting study of behaviour, showing that acute activation of neuron axon terminals can produce an opposite effect on anxiety to that produced by activating neuron somata. Itwas also the first study to show axon-terminal specific inhibition using optogenetics in vivo.
Aponte, Y., Atasoy, D. & Sternson, S. M. AGRP neurons are sufficient to orchestrate feeding behavior rapidly and without training. Nature Neurosci. 14, 351–355 (2011).
Hägglund, M., Borgius, L., Dougherty, K. J. & Kiehn, O. Activation of groups of excitatory neurons in the mammalian spinal cord or hindbrain evokes locomotion. Nature Neurosci. 13, 246–252 (2010).
Choi, J., Young, J. A. T. & Callaway, E. M. Selective viral vector transduction of ErbB4 expressing cortical interneurons in vivo with a viral receptor-ligand bridge protein. Proc. Natl Acad. Sci. USA 107, 16703–16708 (2010).
Li, F., Ryu, B. Y., Krueger, R. L., Heldt, S. A. & Albritton, L. M. Targeted entry via somatostatin receptors using a novel modified retrovirus glycoprotein that delivers genes at levels comparable to wild type viral glycoproteins. J. Virol. 86, 373–381 (2011).
Stuber, G. D. et al. Excitatory transmission from the amygdala to nucleus accumbens facilitates reward seeking. Nature 475, 377–380 (2011). This study showed that amygdalar projections to the NAc, but not cortical projections, mediate ICSS.
Zorzos, A. N., Boyden, E. S. & Fonstad, C. G. Multiwaveguide implantable probe for light delivery to sets of distributed brain targets. Opt. Lett. 35, 4133–4135 (2010).
Wentz, C. T. et al. A wirelessly powered and controlled device for optical neural control of freely-behaving animals. J. Neural Eng. 8, 046021 (2011).
Kessler, R. C. et al. Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Arch. Gen. Psychiatry 62, 593–602 (2005).
Lieb, R. Anxiety disorders: clinical presentation and epidemiology. Handb. Exp. Pharmacol. 405–432 (2005).
Baldwin, D., Woods, R., Lawson, R. & Taylor, D. Efficacy of drug treatments for generalised anxiety disorder: systematic review and meta-analysis. BMJ 342, d1199 (2011).
Beck, A. T., Emery, G. & Greenberg, R. L. Anxiety Disorders and Phobias: A Cognitive Perspective (Basic Books, 2005).
Woods, J. H., Katz, J. L. & Winger, G. Benzodiazepines: use, abuse, and consequences. Pharmacol. Rev. 44, 151–347 (1992).
Johansen, J. P. et al. Optical activation of lateral amygdala pyramidal cells instructs associative fear learning. Proc. Natl Acad. Sci. USA 107, 12692–12697 (2010).
Adolphs, R., Tranel, D., Damasio, H. & Damasio, A. Fear and the human amygdala. J. Neurosci. 15, 5879–5891 (1995).
Davis, M. The role of the amygdala in fear and anxiety. Annu. Rev. Neurosci. 15, 353–375 (1992).
LeDoux, J. E. Emotion: clues from the brain. Annu. Rev. Psychology 46, 209–235 (1995).
Fanselow, M. S. & Gale, G. D. The amygdala, fear, and memory. Ann. NY Acad. Sci. 985, 125–134 (2003).
Maren, S. Synaptic mechanisms of associative memory in the amygdala. Neuron 47, 783–786 (2005).
Jüngling, K. et al. Neuropeptide S-mediated control of fear expression and extinction: role of intercalated GABAergic neurons in the amygdala. Neuron 59, 298–310 (2008).
LeDoux, J., Cicchetti, P., Xagoraris, A. & Romanski, L. The lateral amygdaloid nucleus: sensory interface of the amygdala in fear conditioning. J. Neurosci. 10, 1062–1069 (1990).
Miserendino, M. J. D., Sananes, C. B., Melia, K. R. & Davis, M. Blocking of acquisition but not expression of conditioned fear-potentiated startle by NMDA antagonists in the amygdala. Nature 345, 716–718 (1990).
Paré, D., Quirk, G. J. & Ledoux, J. E. New vistas on amygdala networks in conditioned fear. J. Neurophysiol. 92, 1–9 (2004).
Rodrigues, S. M., Schafe, G. E. & LeDoux, J. E. Intra-amygdala blockade of the NR2B subunit of the NMDA receptor disrupts the acquisition but not the expression of fear conditioning. J. Neurosci. 21, 6889–6896 (2001).
Wilensky, A. E., Schafe, G. E., Kristensen, M. P. & LeDoux, J. E. Rethinking the fear circuit: the central nucleus of the amygdala is required for the acquisition, consolidation, and expression of pavlovian fear conditioning. J. Neurosci. 26, 12387–12396 (2006).
Han, J.-H. et al. Selective erasure of a fear memory. Science 323, 1492–1496 (2009).
Haubensak, W. et al. Genetic dissection of an amygdala microcircuit that gates conditioned fear. Nature 468, 270–276 (2010). Together with reference 83, this study identified a new population of neurons, and identified functional specificity in PKCδ-expressing neurons in a multisynaptic circuit in the context of conditioned fear expression.
Ciocchi, S. et al. Encoding of conditioned fear in central amygdala inhibitory circuits. Nature 468, 277–282 (2010).
Yehuda, R. Post-traumatic stress disorder. N. Engl. J. Med. 346, 108–114 (2002).
Charney, D. S., Deutch, A. Y., Krystal, J. H., Southwick, S. M. & Davis, M. Psychobiologic mechanisms of posttraumatic stress disorder. Arch. Gen. Psychiatry 50, 295–305 (1993).
Rauch, S. L., Shin, L. M. & Phelps, E. A. Neurocircuitry models of posttraumatic stress disorder and extinction: human neuroimaging research–past, present, and future. Biol. Psychiatry 60, 376–382 (2006).
Milad, M. R., Rauch, S. L., Pitman, R. K. & Quirk, G. J. Fear extinction in rats: implications for human brain imaging and anxiety disorders. Biol. Psychology 73, 61–71 (2006).
Rudy, J. W. & O'Reilly, R. C. Contextual fear conditioning, conjunctive representations, pattern completion, and the hippocampus. Behav. Neurosci. 113, 867–880 (1999).
Fanselow, M. S. Contextual fear, gestalt memories, and the hippocampus. Behav. Brain Res. 110, 73–81 (2000).
Phillips, R. & LeDoux, J. Differential contribution of amygdala and hippocampus to cued and contextual fear conditioning. Behav. Neurosci. 106, 274–285 (1992).
Kim, J. J., Rison, R. A. & Fanselow, M. S. Effects of amygdala, hippocampus, and periaqueductal gray lesions on short-and long-term contextual fear. Behav. Neurosci. 107, 1093–1098 (1993).
McGaugh, J. L. Memory—a century of consolidation. Science 287, 248–251 (2000).
Frankland, P. W. et al. Consolidation of CS and US representations in associative fear conditioning. Hippocampus 14, 557–569 (2004).
Frankland, P. W. & Bontempi, B. The organization of recent and remote memories. Nature Rev. Neuroscience 6, 119–130 (2005).
Wiltgen, B. J., Brown, R. A. M., Talton, L. E. & Silva, A. J. New circuits for old memories: the role of the neocortex in consolidation. Neuron 44, 101–108 (2004).
Lee, J. L. C., Everitt, B. J. & Thomas, K. L. Independent cellular processes for hippocampal memory consolidation and reconsolidation. Science 304, 839–843 (2004).
Goshen, I. et al. Dynamics of retrieval strategies for remote memories. Cell 147, 678–689 (2011). This study showed that remote memory recall is dependent on hippocampal activity, using fast-acting optogenetic methods.
Koob, G. F. Drugs of abuse: anatomy, pharmacology and function of reward pathways. Trends Pharmacol. Sci. 13, 177–184 (1992).
Wise, R. A. Drug-activation of brain reward pathways. Drug Alcohol Depend. 51, 13–22 (1998).
Everitt, B. J. & Robbins, T. W. Neural systems of reinforcement for drug addiction: from actions to habits to compulsion. Nature Neurosci. 8, 1481 (2005).
Robinson, T. E. & Berridge, K. C. The neural basis of drug craving: an incentive-sensitization theory of addiction. Brain Res. Rev. 18, 247–291 (1993).
Kelley, A. E. & Berridge, K. C. The neuroscience of natural rewards: relevance to addictive drugs. J. Neurosci. 22, 3306–3311 (2002).
Schultz, W., Dayan, P. & Montague, P. R. A neural substrate of prediction and reward. Science 275, 1593–1599 (1997).
Spanagel, R. & Weiss, F. The dopamine hypothesis of reward: past and current status. Trends Neurosci. 22, 521–527 (1999).
Berridge, K. C. & Robinson, T. E. What is the role of dopamine in reward: hedonic impact, reward learning, or incentive salience? Brain Res. Rev. 28, 309–369 (1998).
Ikemoto, S. & Panksepp, J. The role of nucleus accumbens dopamine in motivated behavior: a unifying interpretation with special reference to reward-seeking. Brain Res. Rev. 31, 6–41 (1999).
Kalivas, P. W. & Stewart, J. Dopamine transmission in the initiation and expression of drug-and stress-induced sensitization of motor activity. Brain Res. Rev. 16, 223–244 (1991).
Ambroggi, F., Ishikawa, A., Fields, H. L. & Nicola, S. M. Basolateral amygdala neurons facilitate reward-seeking behavior by exciting nucleus accumbens neurons. Neuron 59, 648–661 (2008).
Cardinal, R. N., Parkinson, J. A., Hall, J. & Everitt, B. J. Emotion and motivation: the role of the amygdala, ventral striatum, and prefrontal cortex. Neurosci. Biobehav. Rev. 26, 321–352 (2002).
Nicola, S. M., Yun, I. A., Wakabayashi, K. T. & Fields, H. L. Firing of nucleus accumbens neurons during the consummatory phase of a discriminative stimulus task depends on previous reward predictive cues. J. Neurophysiol. 91, 1866–1882 (2004).
Carr, G. D., Fibiger, H. C. & Phillips, A. G. Conditioned place preference as a measure of drug reward. in The Neuropharmacological Basis of Reward (Topics in Experimental Psychopharmacology) Vol. 1 (eds Liebman, J. M. & Cooper, S. J.) 264–319 (Oxford Univ. Press, 1989).
Tzschentke, T. M. Measuring reward with the conditioned place preference paradigm: a comprehensive review of drug effects, recent progress and new issues. Prog. Neurobiol. 56, 613–672 (1998).
Lobo, M. K. et al. Cell type-specific loss of BDNF signaling mimics optogenetic control of cocaine reward. Science 330, 385–390 (2010). This study showed that D1 and D2 neurons in the NAc have distinctly different effects on cocaine-conditioned place preference.
Olds, J. & Milner, P. Positive reinforcement produced by electrical stimulation of septal area and other regions of rat brain. J. Comp. Physiol. Psychol. 47, 419–427 (1954).
Lüscher, C. & Malenka, R. C. Drug-evoked synaptic plasticity in addiction: from molecular changes to circuit remodeling. Neuron 69, 650–663 (2011).
Schoenbaum, G., Chiba, A. A. & Gallagher, M. Orbitofrontal cortex and basolateral amygdala encode expected outcomes during learning. Nature Neurosci. 1, 155–159 (1998).
Schoenbaum, G. & Roesch, M. Orbitofrontal cortex, associative learning, and expectancies. Neuron 47, 633–636 (2005).
Tye, K. M., Stuber, G. D., de Ridder, B., Bonci, A. & Janak, P. H. Rapid strengthening of thalamo-amygdala synapses mediates cue-reward learning. Nature 453, 1253–1257 (2008).
Tye, K. M. et al. Methylphenidate facilitates learning-induced amygdala plasticity. Nature Neurosci. 13, 475–481 (2010).
Carelli, R. M. & Deadwyler, S. A comparison of nucleus accumbens neuronal firing patterns during cocaine self-administration and water reinforcement in rats. J. Neurosci. 14, 7735–4776 (1994).
Carelli, R. M., Ijames, S. G. & Crumling, A. J. Evidence that separate neural circuits in the nucleus accumbens encode cocaine versus “natural” (water and food) reward. J. Neurosci. 20, 4255–4266 (2000).
Wakabayashi, K. T., Fields, H. L. & Nicola, S. M. Dissociation of the role of nucleus accumbens dopamine in responding to reward-predictive cues and waiting for reward. Behav. Brain Res. 154, 19–30 (2004).
Peters, Y. M., O'Donnell, P. & Carelli, R. M. Prefrontal cortical cell firing during maintenance, extinction, and reinstatement of goal-directed behavior for natural reward. Synapse 56, 74–83 (2005).
Tye, K. M., Cone, J. J., Schairer, W. W. & Janak, P. H. Amygdala neural encoding of the absence of reward during extinction. J. Neurosci. 30, 116–125 (2010).
Tye, K. M. & Janak, P. H. Amygdala neurons differentially encode motivation and reinforcement. J. Neurosci. 27, 3937–3945 (2007).
Phillips, P. E. M., Stuber, G. D., Heien, M., Wightman, R. M. & Carelli, R. M. Subsecond dopamine release promotes cocaine seeking. Nature 422, 614–618 (2003).
Alsiö, J. et al. Enhanced sucrose and cocaine self-administration and cue-induced drug seeking after loss of VGLUT2 in midbrain dopamine neurons in mice. J. Neurosci. 31, 12593–12603 (2011).
Blazer, D., Kessler, R., McGonagle, K. & Swartz, M. The prevalence and distribution of major depression in a national community sample: the National Comorbidity Survey. Am. J. Psychiatry 151, 979–986 (1994).
Nierenberg, A. A. & Dececco, L. M. Definitions of antidepressant treatment response, remission, nonresponse, partial response, and other relevant outcomes: a focus on treatment-resistant depression. J. Clin. Psychiatry 62 (Suppl. 16), 5–9 (2001).
Dailly, E., Chenu, F., Renard, C. E. & Bourin, M. Dopamine, depression and antidepressants. Fundam. Clin. Pharmacol. 18, 601–607 (2004).
Maddox, J. C., Levi, M. & Thompson, C. The compliance with antidepressants in general practice. J. Psychopharmacol. 8, 48–52 (1994).
Melfi, C. A. et al. The effects of adherence to antidepressant treatment guidelines on relapse and recurrence of depression. Arch. Gen. Psychiatry 55, 1128–1132 (1998).
Mayberg, H. S. et al. Deep brain stimulation for treatment-resistant depression. Neuron 45, 651–660 (2005). A seminal study showing that DBS can show acute and long-lasting antidepressant effects, inviting reverse translational studies using optogenetics to provide a mechanistic explanation.
Mayberg, H. Modulating limbic-cortical circuits in depression: targets of antidepressant treatments. Semin. Clin. Neuropsychiatry 7, 255–268 (2002).
Covington, H. E. et al. Antidepressant effect of optogenetic stimulation of the medial prefrontal cortex. J. Neurosci. 30, 16082–16090 (2010).
Bach-Mizrachi, H. et al. Neuronal tryptophan hydroxylase mRNA expression in the human dorsal and median raphe nuclei: major depression and suicide. Neuropsychopharmacology 31, 814–824 (2005).
Greenwood, B. N. et al. Freewheel running prevents learned helplessness/behavioral depression: role of dorsal raphe serotonergic neurons. J. Neurosci. 23, 2889–2898 (2003).
Lira, A. et al. Altered depression-related behaviors and functional changes in the dorsal raphe nucleus of serotonin transporter-deficient mice. Biol. Psychiatry 54, 960–971 (2003).
Airan, R. D. et al. High-speed imaging reveals neurophysiological links to behavior in an animal model of depression. Science 317, 819–823 (2007).
Bremner, J. D. et al. Hippocampal volume reduction in major depression. Am. J. Psychiatry 157, 115–118 (2000).
Sahay, A. & Hen, R. Adult hippocampal neurogenesis in depression. Nature Neurosci. 10, 1110–1115 (2007).
Sapolsky, R. M. The possibility of neurotoxicity in the hippocampus in major depression: a primer on neuron death. Biol. Psychiatry 48, 755–765 (2000).
Mervaala, E. et al. Quantitative MRI of the hippocampus and amygdala in severe depression. Psychol. Med. 30, 117–125 (2000).
Sheline, Y. I., Gado, M. H. & Price, J. L. Amygdala core nuclei volumes are decreased in recurrent major depression. Neuroreport 9, 2023–2028 (1998).
Sheline, Y. I. et al. Increased amygdala response to masked emotional faces in depressed subjects resolves with antidepressant treatment: an fMRI study. Biol. Psychiatry 50, 651–658 (2001).
Siegle, G. J., Thompson, W., Carter, C. S., Steinhauer, S. R. & Thase, M. E. Increased amygdala and decreased dorsolateral prefrontal BOLD responses in unipolar depression: related and independent features. Biol. Psychiatry 61, 198–209 (2007).
Larisch, R. et al. In vivo evidence for the involvement of dopamine-D2 receptors in striatum and anterior cingulate gyrus in major depression. Neuroimage 5, 251–260 (1997).
Zhu, X., Peng, S., Zhang, S. & Zhang, X. Stress-induced depressive behaviors are correlated with Par-4 and DRD2 expression in rat striatum. Behav. Brain Res. 223, 329–335 (2011).
Meyer, J. H. et al. Lower dopamine transporter binding potential in striatum during depression. Neuroreport 12, 4121–4125 (2001).
Binfaré, R. W., Mantovani, M., Budni, J., Santos, A. R. S. & Rodrigues, A. L. S. Involvement of dopamine receptors in the antidepressant-like effect of melatonin in the tail suspension test. Eur. J. Pharmacol. 638, 78–83 (2010).
Willner, P. Dopamine and depression: a review of recent evidence. II. Theoretical approaches. Brain Res. Rev. 6, 225–236 (1983).
Malone, D. A. Jr et al. Deep brain stimulation of the ventral capsule/ventral striatum for treatment-resistant depression. Biol. Psychiatry 65, 267–275 (2009).
Aghajanian, G. K., Graham, A. W. & Sheard, M. H. Serotonin-containing neurons in brain: depression of firing by monoamine oxidase inhibitors. Science 169, 1100–1102 (1970).
Arango, V., Underwood, M. D. & Mann, J. J. Serotonin brain circuits involved in major depression and suicide. Prog. Brain Res. 136, 443–453 (2002).
Weiss, J. M. et al. Behavioral depression produced by an uncontrollable stressor: relationship to norepinephrine, dopamine, and serotonin levels in various regions of rat brain. Brain Res. Rev. 3, 167–205 (1981).
Swerdlow, N. R. & Koob, G. F. Dopamine, schizophrenia, mania, and depression: toward a unified hypothesis of cortico-striato-pallido-thalamic function. Behav. Brain Sci. 10, 197–245 (1987).
Li, X., Frye, M. A. & Shelton, R. C. Review of pharmacological treatment in mood disorders and future directions for drug development. Neuropsychopharmacology 37, 77–101 (2012).
Gillott, A., Furniss, F. & Walter, A. Anxiety in high-functioning children with autism. Autism 5, 277–286 (2001).
Howlin, P. & Moorf, A. Diagnosis in autism. Autism 1, 135–162 (1997).
Phetrasuwan, S., Miles, M. S., Mesibov, G. B. & Robinson, C. Defining autism spectrum disorders. J. Spec. Pediatr. Nurs. 14, 206–209 (2009).
Crow, T. J. Molecular pathology of schizophrenia: more than one disease process? Br. Med. J. 280, 66–68 (1980).
Endicott, J. & Spitzer, R. L. A diagnostic interview: the schedule for affective disorders and schizophrenia. Arch. Gen. Psychiatry 35, 837–844 (1978).
Kay, S. R., Flszbein, A. & Opfer, L. A. The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophr. Bull. 13, 261–276 (1987).
Kehrer, C., Maziashvili, N., Dugladze, T. & Gloveli, T. Altered excitatory-inhibitory balance in the NMDA-hypofunction model of schizophrenia. Front. Mol. Neurosci. 1, 6 (2008).
Gonzalez-Burgos, G., Hashimoto, T. & Lewis, D. A. Alterations of cortical GABA neurons and network oscillations in schizophrenia. Curr. Psychiatry Rep. 12, 335–344 (2010).
Lewis, D. A. & Gonzalez-Burgos, G. Pathophysiologically based treatment interventions in schizophrenia. Nature Med. 12, 1016–1022 (2006).
Lord, C. & Bishop, S. L. Social Policy Report 24. Autism Spectrum Disorders: Diagnosis, Prevalence, and Services for Children and Families (Society for Research in Child Development, 2010).
Tønnesen, J., Sørensen, A. T., Deisseroth, K., Lundberg, C. & Kokaia, M. Optogenetic control of epileptiform activity. Proc. Natl Acad. Sci. USA 106, 12162–12167 (2009).
Paz, J. T. et al. A new mode of corticothalamic transmission revealed in the Gria4−/− model of absence epilepsy. Nature Neurosci. 14, 1167–1173 (2011).
Kim, J. A., Szatmari, P., Bryson, S. E., Streiner, D. L. & Wilson, F. J. The prevalence of anxiety and mood problems among children with autism and Asperger syndrome. Autism 4, 117–132 (2000).
Markram, K. & Markram, H. The intense world theory—a unifying theory of the neurobiology of autism. Front. Hum. Neurosci. 4, 224 (2010).
Vattikuti, S. & Chow, C. C. A computational model for cerebral cortical dysfunction in autism spectrum disorders. Biol. Psychiatry 67, 672–678 (2010).
Rubenstein, J. & Merzenich, M. Model of autism: increased ratio of excitation/inhibition in key neural systems. Genes Brain Behav. 2, 255–267 (2003).
Orekhova, E. V. et al. Excess of high frequency electroencephalogram oscillations in boys with autism. Biol. Psychiatry 62, 1022–1029 (2007).
Kalivas, P. W. & Volkow, N. D. The neural basis of addiction: a pathology of motivation and choice. Am. J. Psychiatry 162, 1403–1413 (2005).
Batel, P. Addiction and schizophrenia. Eur. Psychiatry 15, 115–122 (2000).
Huppert, J. D., Weiss, K. A., Lim, R., Pratt, S. & Smith, T. E. Quality of life in schizophrenia: contributions of anxiety and depression. Schizophr. Res. 51, 171–180 (2001).
Rasmussen, K. CCK, schizophrenia, and anxiety. Ann. NY Acad. Sci. 713, 300–311 (1994).
Busskamp, V. et al. Genetic reactivation of cone photoreceptors restores visual responses in retinitis pigmentosa. Science 329, 413–417 (2010).
Busskamp, V. & Roska, B. Optogenetic approaches to restoring visual function in retinitis pigmentosa. Curr. Opin. Neurobiol. 21, 942–946 (2011).
Pagliardini, S. et al. Active expiration induced by excitation of ventral medulla in adult anesthetized rats. J. Neurosci. 31, 2895–2905 (2011).
Gourine, A. V. et al. Astrocytes control breathing through pH-dependent release of ATP. Science 329, 571–575 (2010).
Alexander, G. E. & Crutcher, M. D. Functional architecture of basal ganglia circuits: neural substrates of parallel processing. Trends Neurosci. 13, 266–271 (1990).
Gurney, K., Prescott, T. & Redgrave, P. A computational model of action selection in the basal ganglia. I. A new functional anatomy. Biol. Cybern. 84, 401–410 (2001).
Smith, Y., Bevan, M., Shink, E. & Bolam, J. Microcircuitry of the direct and indirect pathways of the basal ganglia. Neuroscience 86, 353–387 (1998).
Hughes, A. J., Daniel, S. E., Kilford, L. & Lees, A. J. Accuracy of clinical diagnosis of idiopathic Parkinson's disease: a clinico-pathological study of 100 cases. J. Neurol. Neurosurg. Psychiatry 55, 181–184 (1992).
Gelb, D. J., Oliver, E. & Gilman, S. Diagnostic criteria for parkinson disease. Arch. Neurol. 56, 33–39 (1999).
Benabid, A. L. Deep brain stimulation for Parkinson's disease. Curr. Opin. Neurobiol. 13, 696–706 (2003).
Deuschl, G. et al. A randomized trial of deep-brain stimulation for Parkinson's disease. N. Engl. J. Med. 355, 896–908 (2006).
Kumar, R. et al. Double-blind evaluation of subthalamic nucleus deep brain stimulation in advanced Parkinson's disease. Neurology 51, 850–855 (1998).
Byers, B. et al. SNCA triplication Parkinson's patient's iPSC-derived DA neurons accumulate α-synuclein and are susceptible to oxidative stress. PLoS ONE 6, e26159 (2011).
Lin, D. et al. Functional identification of an aggression locus in the mouse hypothalamus. Nature 470, 221–226 (2011). This study used optogenetic manipulation of neurons to show the causal role of this subpopulation of neurons in mediating aggressive behaviours.
Lin, S. C., Deisseroth, K. & Henderson, J. M. Optogenetics: background and concepts for neurosurgery. Neurosurgery 69, 1–3 (2011).
Han, X. et al. Millisecond-timescale optical control of neural dynamics in the nonhuman primate brain. Neuron 62, 191–198 (2009).
Berdyyeva, T. K. & Reynolds, J. H. The dawning of primate optogenetics. Neuron 62, 159–160 (2009).
Lewis, T. L., Mao, T., Svoboda, K. & Arnold, D. B. Myosin-dependent targeting of transmembrane proteins to neuronal dendrites. Nature Neurosci. 12, 568–576 (2009).
Kleinlogel, S. et al. Ultra light-sensitive and fast neuronal activation with the Ca2+-permeable channelrhodopsin CatCh. Nature Neurosci. 14, 513–518 (2011).
Kato, H. E. et al. Crystal structure of the channelrhodopsin light-gated cation channel. Nature 482, 369–374 (2012).
Acknowledgements
We would like to acknowledge E. E. Steinberg, P. H. Janak, S.-Y. Kim, L. D. Tye, O. Yizhar, A. Kreitzer, A. Kravitz and L. E. Fenno for helpful comments and discussion. We thank the Deisseroth laboratory for intellectual and scientific support. K.M.T. is supported by the US National Institute of Mental Health (NIMH) (1F32MH088010-01), the Picower Institute of Learning and Memory and the Picower Institute Innovation Funds (PIIF). K.D. is supported by the NIMH, the US National Institute on Drug Abuse, the US National Institute of Neurological Disorders and Stroke, the Howard Hughes Medical Institute, the Defense Advanced Research Projects Agency Reorganization and Plasticity to Accelerate Injury Recovery Program, the Keck Foundation, the Wiegers Family Gift Fund and the Gatsby Charitable Foundation. Full funding support is described at http://www.optogenetics.org/funding. Stanford University has filed for patent protection on technologies invented by K.M.T. and K.D., and K.D. is one of the founders of a company (Circuit Therapeutics) focused on drug screening and optogenetic therapies for bladder dysfunction. K.D. and K.M.T. have no more than 5% interest in any company and receive no research funding, royalties or consultant fees from any company. All optogenetic tools and methods are distributed and supported freely from the laboratory (http://www.optogenetics.org).
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing financial interests.
Related links
Glossary
- Opsins
-
Membrane-bound proteins that can incorporate small organic 'retinal' molecules to become a light receptor.
- fMRI
-
(Functional magnetic resonance imaging). This method can use detection of blood oxygen levels as a proxy for neural activity, and offers a non-invasive method to globally assay brain activity in humans.
- BOLD
-
(Blood oxygen level dependent). The BOLD signal is one kind of signal that fMRI can use to assess neural activity.
- Channelrhodopsin
-
A light-driven cation channel, found in algae, that can be used to depolarize cell membranes.
- Halorhodopsin
-
A light-driven chloride ion pump found in phylogenetically ancient archaea, known as halobacteria, that can be used to hyperpolarize cell membranes.
- UP states
-
Sub-threshold membrane depolarization states that have been observed to spontaneously occur in vivo in some neurons and that may serve to increase the intrinsic excitability of the neuron.
- Cre recombinase
-
DNA recombinase that excises DNA sequences flanked by loxP sequences with the same orientation, or inverts sequences flanked by loxP sites with opposite orientation. It is effective in mammalian cells in vitro and in vivo.
- Vectors
-
Vehicles used to transfer genetic material to a target cell.
- Conditioned place preference
-
(CPP). A behavioural test in which an unconditioned stimulus is paired with one distinctive context and a neutral event is paired with a different context. Preference is determined by allowing the animal to move between the two contexts and measuring the amount of time spent in each context.
- Duty cycle
-
The time that a machine, system or light source spends in an active state as a fraction of the total time under consideration.
- Conditioned fear responses
-
A fear-associated stimulus (such as a shock-predictive tone) that may evoke conditioned responses such as freezing, fear-potentiated startle or increases in blood pressure, perspiration or heart rate.
- Deep brain stimulation
-
(DBS). Continuous therapeutic electric stimulation of subcortical areas at high frequencies (∼ 130 Hz) using chronically implanted electrodes.
Rights and permissions
About this article
Cite this article
Tye, K., Deisseroth, K. Optogenetic investigation of neural circuits underlying brain disease in animal models. Nat Rev Neurosci 13, 251–266 (2012). https://doi.org/10.1038/nrn3171
Published:
Issue Date:
DOI: https://doi.org/10.1038/nrn3171
This article is cited by
-
AAV-compatible optogenetic tools for activating endogenous calcium channels in vivo
Molecular Brain (2023)
-
Optogenetic stimulation of anterior insular cortex neurons in male rats reveals causal mechanisms underlying suppression of the default mode network by the salience network
Nature Communications (2023)
-
Prefrontal engrams of long-term fear memory perpetuate pain perception
Nature Neuroscience (2023)
-
Multifocal skull-compensated transcranial focused ultrasound system for neuromodulation applications based on acoustic holography
Microsystems & Nanoengineering (2023)
-
Thalamus sends information about arousal but not valence to the amygdala
Psychopharmacology (2023)