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Neurology Enlightenment Optogenetic Tools for Understanding the Brain Hannah Payne ‘11 N euroscientists are scrambling to play with the new toys of optogenetic technology, but with the explosion of popular science articles and even videos of light-controlled dancing mice (1), it is important to step back and evaluate how this technology can be most effectively used to solve meaningful problems in neuroscience. Optogenetics serve as a remote control of neural activity. Groups of cells are genetically encoded to produce light-sensitive proteins, allowing high levels of control of neural activity in specific populations of neurons. This review will focus on optogenetic actuators, which drive activity using light, as opposed to sensors, which report activity, beginning with a brief overview of optogenetic technology. The review will then synthesize recent progress that optogenetics has allowed in teasing apart the role of specific subpopulations and patterns of activity in network dynamics and ultimately how complex behaviors emerge from these elements. Finally, future applications for both neuroscientific research and human disease will be discussed. The Optogenetic Toolbox The capabilities of optogenetic technology for controlling activity have expanded tremendously since Karl Deisseroth’s group first demonstrated the efficacy of channelrhodopsin-2 (ChR2) in 2005 (2). ChR2 was taken from the green algae Clamydomonas reinhardtii and successfully used to drive activity in mammalian neurons, and is still the most commonly used optogenetic tool, although improved engineered versions such as ChETA and ChIEF will likely replace it in the future (3,4). Similar to opsins found in the retina, ChR2 responds to light in the presence of the commonly occurring cofactor, all-trans retinal. However, instead of triggering a G-protein coupled signaling cascade as do opsins in mammalian Winter 2011 retinas, ChR2 responds to 460 nm blue light by opening the ion channel at the core of its seven transmembrane domains, allowing positive ions to pass through (Fig. 1). The result is a sensitive and rapid depolarization of the cell in response to light, allowing neuronal spiking to be reliably elicited (2). Furthermore, some optogenetic tools can decrease neuronal activity, which is not easily controlled with conventional stimulating electrodes. For example, halorhodopsin (Halo) is a light-activated chloride pump isolated from the archaebacterium Natronomas pharaonis (5). Upon exposure to yellow light (560 nm), the influx of chloride ions hyperpolarizes the cell and prevents action potentials. Due to the different wavelengths of activation for ChR2 and halorhodopsin, it is possible to express both proteins in the same neuron, allowing for bidirectional control of activity at the millisecond timescale (6). The main labs involved in pioneering optogenetic technology, those of Karl Deisseroth at Stanford University and Ed Boyden at Massachusetts Institute of Technology, are attempting to make the process as transparent as possible by providing detailed protocols and genetic sequences freely online (openoptogenetics.org, optogenetics. org, and syntheticneurobiology.org). Together they have distributed plasmids containing the ChR2 gene to hundreds of other laboratories. Overall, the process can be divided into three steps: expressing the gene in desired cells, delivering light to control activity, and recording output (behavioral and/or electrophysiological) (7). Gene expression is a well-established problem, and is acheived using transgenic animals, viral infection, or electroporation (7). Light is typically delivered using fiber optic cables which in rodents or monkeys are attached to the head, while smaller organisms (nematodes, xenopus, or drosophila) are simply exposed to full-field light. Behavioral output can be observed with the use of flexible fiber optic cables and has resulted in dramatic demonstrations of the direct link between neural activity and behavior (8). Multielectrode arrays or single electrodes can record extracellular signals from both single cells and population activity (local field potentials); patch clamping methods are used to record with great precision from single neurons; and optogenetic voltage or calcium sensors that can report activity are an ongoing area of development. Pros and Cons Light-years ahead Optogenetics has several key advantages over previous methods of controlling neuronal activity, such as electrical stimulation or neurotransmitter uncaging. Optogenetics is less invasive than electrical stimulation, since light can penetrate several millimeters into brain tissue (7). Neurotransmitter uncaging, in which special caged particles containing glutamate or other neurotransmitters are injected into the brain, also requires invasive injection procedures, which may be avoided by using transgenic optogenetic lines (7). Compared to both methods, the optogenetic response time is faster and spikes are more reliable (2). Additionally, the specificity of genetic encoding via promoters for specific cell types makes this technique extremely powerful for distinguishing functions of different neural populations. Limitations A main limitation of optogenetic probes is their low sensitivity— compared to human photoreceptors, light-activated proteins are nearly blind. In a photoreceptor-lacking retina expressing ChR2, about 1015 photons cm-2 s-1 are needed to produce a response, compared to only 106 photons cm-2 s-1 for rod photoreceptors, a billion-fold increase (9). For most 19 experimental applications this is not a problem as bright light sources are readily available; however one must consider that the visual system might be inadvertently activated in small organisms such as fruit flies and tadpoles. However, the most salient limitation may the difficulty in translating the power of optogenetics into therapeutic approaches to human disease. There are many technical and ethical difficulties faced in introducing a foreign gene to human cells, let alone into the brain. Virus particles may cause adverse reactions, and precise expression of the gene may be hard to control. Also, fiber optics would have to be permanently affixed to the head, potentially causing infection, discomfort, and the need to carry heavy batteries. Finally, the ethical considerations of having such direct control over human neural activity must be very carefully considered. At present, optogenetics remains extremely powerful for purposes of scientific research. Illuminating Neural Networks Currently, optogenetic technology is being applied somewhat haphazardly to a great variety of problems (1, 8). While these “proof-of-principle” demonstrations are useful, they do not necessarily constitute experiments. Overall, neuroscience seeks to understand the brain from the most basic molecular level up through complex human behavior, and optogenetics holds the most promise for understanding the brain at the intermediate level of neural networks. First, optogenetics can be used to manipulate activity of individual neurons, or small subpopulations of neurons, and one can then observe the effects on the activity of the entire local circuit. Second, optogenetics can be used to manipulate activity with extreme temporal precision, allowing the function of patterns of activity to be studied. Third, these elements can then be combined to connect neuronal activity to complex brain functions such as perception and learning and memory. Subpopulation contributions to network dynamics A main strength of optogenetics is 20 that it allows detailed genetic specificity. Different promoters can target very specific types of neurons. Furthermore, electroporation of DNA by applying a brief electric current to open temporary pores in a cell membrane allows for labeling of just one or a few cells. These techniques allow for an understanding of neural network activity at the most basic functional level. For example, researchers led by Michael Hausser at the University College in London recently used ChR2 to investigate the role of individual somatostatin interneurons in visual processing. Somatostatin inhibitory neurons make up roughly 15% of the interneurons in the cortex and synapse primarily on pyramidal cell apical dendrites, but their function is unknown (10). The researchers expressed ChR2 in two to five somatostatin neurons in mouse visual cortex. They then recorded from neighboring pyramidal cells while stimulating the visual system with a series of moving visual stimuli. As expected, activation of the inhibitory somatostatin neurons reduced the response of some neighboring pyramidal cells, but surprisingly some pyramidal cells actually increased firing when the somatostatin neurons were activated. Although the mechanism for the paradoxical enhancement of some pyramidal cells is not known, it could be due either to inhibition of other neighboring interneurons, or by direct integration properties on the pyramidal cell dendrites (10). It is tempting to think that interneurons might be wired to affect pyramidal cells differently depending on whether they convey information from the center or surround of the pyramidal cell’s receptive field. The role of patterned activity in network dynamics In addition to genetic specificity, the temporal precision of optogentics is also invaluable. The ability to control exactly when a neuron fires or does not fire with millisecond precision is beginning to allow researchers to dissect the role that a specific observed pattern of activity, such as oscillation at a specific frequency, has on the overall performance of the network. The experiment described above used a regular train of light pulses at 40 Hz to drive the somatostatin inhibi- tory neurons, but no other frequency was tested (10). This frequency was likely chosen because oscillations between 30-60 Hz, known as the gamma frequency band, have been commonly observed in the cortex, especially during activity and memory retrieval (11). The Hausser lab examined the effect of changing the oscillation frequency of both excitatory and inhibitory neuron populations in V1 cortex in another recent abstract (12). Interestingly, regardless of the frequency enforced in either subpopulation by ChR2 activation (5, 25, 40, and 75 Hz), local field potentials from layer 2/3 recorded enhanced oscillations around the intrinsic frequency of the network (20-35 Hz). Oscillations were increased more when the animals were under anesthesia than when they were awake and moving on a treadmill, which is somewhat puzzling since gamma oscillations are typically linked with active behavior (11). A final interesting finding from this study was that when optogenetic stimulation was applied in concert with visual stimulation, oscillation power was enhanced in an additive manner (12). Overall, this study demonstrates the power of ChR2 to reveal a new wealth of information about the effects of patterned activity on network dynamics. However, there is still disagreement about exactly how these gamma oscillations arise. In a study published in Nature last year, both fast-spiking interneurons and excitatory pyramidal cells were controlled with ChR2 in the mouse somatosensory barrel cortex (13). Like Havenith et al., the group found that regardless of the imposed frequency of fast-spiking interneurons, local field potentials were enhanced within the gamma range. However, activation of pyramidal cells only increased lower frequency oscillations (Fig. 2). This cell-type specific dissociation in network oscillatory activity is an interesting property that may be important in brain disorders with deficits in gamma oscillation, and optogenetics will be instrumental in working out the details. Dartmouth Undergraduate Journal of Science a. b. c. Image retrieved from http://www.nature.com/nature/journal/v459/n7247/images/nature08002-f3.2.jpg (Accessed 29 Jan 2011). Fig. 2: a. Example of natural gamma oscillations phase shifted by blue light pulse. b,c. Local field potential enhancement at 40 Hz was only driven by fast-spiking (FS) interneuron oscillation, not regular-spiking (RS) pyramidal cells. Connecting Neuronal Activity to Brain Function shifted responses towards the preferred octave of the activated region in a behavioral tone discrimination task (18). While the above studies begin to reveal the precise connection of individual neurons and activity patterns to the dynamics of the surrounding network, optogenetics can also link network elements directly to higher-order brain function. Learning and memory Perception Gamma oscillations driven by inhibitory neurons have been theorized to control the gain of sensory input, to act as an attentional mechanism (14), and to influence working memory (11). Failure of gamma oscillation is associated with brain disorders such as autism (15) and schizophrenia (16, 17). Cardin et al. therefore investigated the role of the precise timing of oscillatory activity on neural coding of whisker stimulation (13). Using a mouse expressing ChR2 in fast-spiking interneurons, they applied blue light at 40 Hz to induce gamma oscillations phase-locked to the light pulses. They then stimulated a whisker at various time points (Fig. 3a). Remarkably, precision of pyramidal cell responses increased when the whisker was stimulated at specific phases of the oscillation (Fig. 3b-f). The authors conclude that sensory transmission is decreased during the peak of the interneuron inhibitory neurotransmitter release, leading to temporal sharpening of the response during inhibitory neuron oscillation(14). Optogenetics have also been used in simpler experiments to link neuronal activity to perception. For example, stimulation of auditory cortex using nonspecifically expressed ChR2 Winter 2011 Optogenetics is also beginning to reveal novel aspects of learning and memory. For example, a recent optogenetic study found intriguingly different results when using a light-activated activity block compared to a pharmocological block (19). When tetrodotoxin (TTX) was injected to inactivate the CA1 region of the hippocampus, a timedependent affect on memory retrieval in a contextual fear conditioning task was found: when injected before training, or right before testing one day after training, TTX blocked memory of the feared context. But when TTX was injected just prior to testing after 28 days, both control and TTX-injected rats still froze in response to the context, corroborating the generally accepted hypothesis that CA1 of the hippocampus is involved in the formation and consolidation of memories, but not long term storage. However, injection of pharmacological agents necessarily takes time on the order of 30-60 minutes, a relatively long time when one considers that new memories can be formed on the scale of minutes and even seconds. Therefore, the researchers employed the light-activated chloride pump halorhodopsin (Halo) to rapidly and reversibly block activity in CA1 (19). Halo was expressed in excitatory neurons in CA1 and effectively blocked activity when activated by light. Turning the light on during training or during testing one day after training impaired recall of the context. However, unlike TTX, activation of Halo during testing 28 days later also significantly blocked the fear response. Activating Halo 30 minutes before the 28-day testing phase did not cause any impairments in memory recall, and auditory cued-fear responses were not affected by light activation in CA1 at any stage of testing or training. Together, these novel results may indicate that the hippocampus does in fact store long-term memories, but may not be necessary for long-term memory recall if the brain has sufficient time to recruit alternate mechanisms (19). Future Experimental Directions Overall, the sampling of findings above, although incomplete, provides a broad picture of how optogenetics are beginning to reveal the neural mechanisms underlying complex brain functions. By linking individual neurons and specific patterns of activity to network dynamics, and then linking these elements to complex tasks such as perception or learning and memory, optogenetics should make it possible to understand the brain in unprecedented detail. Many other brain functions are promising candidates for optogenetic research. In particular, Robert Wurtz has suggested that optogenetic perturbation of neuronal activity will be useful in correlating neural activity to behavior in order to dissect the mechanisms of visual attention and suppression during saccades (20). Similarly, studies of motivation have thus far relied on recording neural activity in different brain regions in response to behavior (21); by expressing optogenetic controls in dopaminergic or seratoninergic systems and directly stimulating or inactivating those neurons, the reverse experiment could be conducted in which neural activity might be shown to cause the specific motivational behaviors. The genetic specificity of lightcontrolled neurons is especially promising for studying the balance of excitation and inhibition. Excitatory/ Inhibitory (E/I) balance changes drastically during development, from mainly excitatory in childhood to roughly equal in adulthood. This shift in E/I balance is essential for proper timing of the “critical period” during which 21 Image retrieved from http://www.nature.com/nature/journal/v459/n7247/images/ nature08002-f4.2.jpg (Accessed 29 Jan 2011). Fig. 3: a. A whisker was stimulated at five different points during the light-induced oscillation. b. Baseline response histogram. c. Responses with gamma oscillation d. Spike count was reduced for some stimulation phases e. Some spike latencies increased f. Spike precision was increased in a phase dependent manner. experience-dependent plasticity can shape the developing nervous system (22). Monocular deprivation during this critical period causes a cortical bias towards the contralateral eye which is normally irreversible. However, some manipulations such as demyelination or decreasing cortical inhibition using pharmacology can return the brain to a plastic state (22). Optogenetics would allow more precise investigation of how E/I balance regulates the boundaries of the critical period. Treatment of Disease Since optogenetics has already been used to selectively activate or suppress specific populations of excitatory or inhibitory neurons, it could conceivably be used to correct E/I balance in certain brain disorders. For example, schizophrenics have decreased myelin and too much excitatory activity—in a way the brain is developmentally immature (22). Increasing activity in in22 hibitory neurons, or alternatively suppressing activity in excitatory neurons, might help correct the balance. Increasing inhibition may also help restore normal gamma oscillations, which are dysfunctional in schizophrenics (16, 17). Conversely, if the critical period has passed without the opportunity for normal experience, as it has for patients who only gain sight after childhood (23), a shift in the excitatory direction might aid the development of a functional visual system even late in life. Other potential therapeutic approaches include cell-type specific versions of deep-brain stimulation with potential for treating Parkinson’s, epilepsy, severe depression and mood disorders, sleep disorders, and phobias. Additionally, some groups have begun engineering retinas with ChR2 to replace damaged photoreceptors (24,25). Perhaps if multiple opsins were expressed, such as ChR2 plus a red-shifted version, or ChR2 plus Halo (6), then functionally distinct populations of neurons in the retina could be activated differentially to provide more biologically realistic inputs. However, although the possibilities for therapeutic approaches are limited only by the imagination, any use of optogenetics in humans is light-years away due to the difficulty of introducing genes into the human brain and the ethics of directly controlling neural activity. Conclusion In a way, the timing of optogenetic’s entrance on the stage of neuroscience is ideal. Other techniques have shown how environmental stimuli and behavioral outputs correlate with patterns of neuronal activity; the next step is to directly manipulate activity with genetic and temporal precision to elucidate the neural basis of perception, behavior, and everything in between. References 4. L. A. Gunaydin et al., Nature Neuroscience. 13, 387–392 (2010). 5. B. Schobert and J. K. Lanyi, The Journal of Biological Chemistry, 257, 10306-10313 (1982). 6. X. Han, E. S. Boyden, PLoS ONE 2, 299 (2007). 7. F. Zhang, et al. Nature Protocols, 5(3):439-456. (2010). 8. M. Rizzi et al., Program No. 388.8. 2009 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience. Online. (2009). 9. E. Ivanova, Z. H. Pan, Mol Vis. 15, 1680–1689 (2009). 10. J. C. Cottam, S. L. Smith, M. Hausser, Program No. 450.21. 2010 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience. Online. (2010). 11. M. W. Howard et al., Cereb. Cortex. 13, 1369-1374 (2003). 12. M. N. Havenith, H. Langeslag, J. Cottam, M. Hausser, Program No. 673.13. 2010 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience. Online. (2010). 13. J. A. Cardin et al., Nature. 459, 663-667 (2009). 14. U. Knoblich, C. I. Moore, Program No. 673.14. 2010 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience. Online. (2010). 15. E. V. Orekhova et al., Biol. Psychiatry 62: 1022–1029. (2007). 16. K. M. Spencer, M. A. Niznikiewicz, M. E. Shenton, R. W. McCarley, Biol. Psychiatry 63, 744–747 (2008). 17. P. J. Uhlhaas, C. Haenschel, D. Nikolic, W. Singer, Schizophr. Bull. 34, 927–943 (2008). 18. P. Znamenskiyi, A. M. Zador. Program No. 805.13. 2010 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience. Online. (2010). 19. I. Goshen et al., Program No. 412.3. 2010 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience. Online. (2010). 20. Wurtz, Peter and Patricia Gruber Lecture: Brain Circuits for Active Vision. 2010 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience. Online. (2010). 21. O. Hikosaka, Program No. 218: Presidential Special Lecture. 2010 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience. Online. (2010). 22. T. Hensch, Program No. 213.2. Molecular brakes on plasticity. 2010 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience. Online. (2010). 23. P. Sinha, Program No. 422. Presidential Special Lecture. 2010 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience. Online. (2010). 24. P. S. Lagali, et al., Nature Neuroscience. 11, 667 – 675 (2008). 25. S. Thyagarajan et al., The Journal of Neuroscience, 30(26): 8745-8758 (2010). 1. Anonymous. “Optogenetics and mouse (with music)” 25 May, 2010. YouTube. Accessed Dec 5, 2010. http://www.youtube.com/ watch?v=obJjXRyDcYE (2010). 2. E. S. Boyden, F. Zhang, E. Bamberg, E. Nagel, L. Deisseroth, Nature Neuroscience. 8, 1263-8 (2005). 3. J. Lin, Program No. 314.4. 2010 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience, 2010. Online. (2010). Dartmouth Undergraduate Journal of Science