Optogenetics seminars

Karl Deisseroth explains how light-sensitive microbial proteins became tools for investigating brain circuits in living, freely moving animals. By controlling selected classes of neurons, and sometimes individual cells, optogenetics allows researchers to ask how cellular activity contributes to behaviour and mental experience. The lecture connects the discovery and development of these tools with questions about emotions, the neural pathways that generate our inner experience, and processes disrupted in psychiatric illness. It considers both basic research and clinical possibilities, including the importance of neuronal and social connections for emotional well-being.

The ability to keep track of one’s location in space is a critical behavior for animals navigating to and from a salient location, and its computational basis is now beginning to be unraveled. Here, we tracked flies in a ring-shaped channel as they executed bouts of search triggered by optogenetic activation of sugar receptors. Unlike experiments in open field arenas, which produce highly tortuous search trajectories, our geometrically constrained paradigm enabled us to monitor flies’ decisions to move toward or away from the fictive food. Our results suggest that flies use path integration to remember the location of a food site even after it has disappeared, and flies can remember the location of a former food site even after walking around the arena one or more times. To determine the behavioral algorithms underlying Drosophila search, we developed multiple state transition models and found that flies likely accomplish path integration by combining odometry and compass navigation to keep track of their position relative to the fictive food. Our results indicate that whereas flies re-zero their path integrator at food when only one feeding site is present, they adjust their path integrator to a central location between sites when experiencing food at two or more locations. Together, this work provides a simple experimental paradigm and theoretical framework to advance investigations of the neural basis of path integration.

PiVR is a system that allows experimenters to immerse small animals into virtual realities. The system tracks the position of the animal and presents light stimulation according to predefined rules, thus creating a virtual landscape in which the animal can behave. By using optogenetics, we have used PiVR to present fruit fly larvae with virtual olfactory realities, adult fruit flies with a virtual gustatory reality and zebrafish larvae with a virtual light gradient. PiVR operates at high temporal resolution (70Hz) with low latencies (<30 milliseconds) while being affordable (<US$500) and easy to build (<6 hours). Through extensive documentation (www.PiVR.org), this tool was designed to be accessible to a wide public, from high school students to professional researchers studying systems neuroscience in academia.

Tracking heading within an environment is a fundamental requirement for flexible, goal-directed navigation. In insects, a head-direction representation that guides the animal’s movements is maintained in a conserved brain region called the central complex. Two-photon calcium imaging of genetically targeted neural populations in the central complex of tethered fruit flies behaving in virtual reality (VR) environments has shown that the head-direction representation is updated based on self-motion cues and external sensory information, such as visual features and wind direction. Thus far, the head direction representation has mainly been studied in VR settings that only give flies control of the angular rotation of simple sensory cues. How the fly’s head direction circuitry enables the animal to navigate in dynamic, immersive and naturalistic environments is largely unexplored. I have developed a novel setup that permits imaging in complex VR environments that also accommodate flies’ translational movements. I have previously demonstrated that flies perform visually-guided navigation in such an immersive VR setting, and also that they learn to associate aversive optogenetically-generated heat stimuli with specific visual landmarks. A stable head direction representation is likely necessary to support such behaviors, but the underlying neural mechanisms are unclear. Based on a connectomic analysis of the central complex, I identified likely circuit mechanisms for prioritizing and combining different sensory cues to generate a stable head direction representation in complex, multimodal environments. I am now testing these predictions using calcium imaging in genetically targeted cell types in flies performing 2D navigation in immersive VR.

Motivational drives are internal states that can be different even in similar interactions with external stimuli. Curiosity as the motivational drive for novelty-seeking and investigating the surrounding environment is for survival as essential and intrinsic as hunger. Curiosity, hunger, and appetitive aggression drive three different goal-directed behaviors—novelty seeking, food eating, and hunting— but these behaviors are composed of similar actions in animals. This similarity of actions has made it challenging to study novelty seeking and distinguish it from eating and hunting in nonarticulating animals. The brain mechanisms underlying this basic survival drive, curiosity, and novelty-seeking behavior have remained unclear. In spite of having well-developed techniques to study mouse brain circuits, there are many controversial and different results in the field of motivational behavior. This has left the functions of motivational brain regions such as the zona incerta (ZI) still uncertain. Not having a transparent, nonreinforced, and easily replicable paradigm is one of the main causes of this uncertainty. Therefore, we chose a simple solution to conduct our research: giving the mouse freedom to choose what it wants—double freeaccess choice. By examining mice in an experimental battery of object free-access double-choice (FADC) and social interaction tests—using optogenetics, chemogenetics, calcium fiber photometry, multichannel recording electrophysiology, and multicolor mRNA in situ hybridization—we uncovered a cell type–specific cortico-subcortical brain circuit of the curiosity and novelty-seeking behavior. We found in mice that inhibitory neurons in the medial ZI (ZIm) are essential for the decision to investigate an object or a conspecific. These neurons receive excitatory input from the prelimbic cortex to signal the initiation of exploration. This signal is modulated in the ZIm by the level of investigatory motivation. Increased activity in the ZIm instigates deep investigative action by inhibiting the periaqueductal gray region. A subpopulation of inhibitory ZIm neurons expressing tachykinin 1 (TAC1) modulates the investigatory behavior.

Coping with threatening situations requires both identifying stimuli predicting danger and selecting adaptive behavioral responses in order to survive. The dorso medial prefrontal cortex (dmPFC) is a critical structure involved in the regulation of threat-related behaviour, yet it is still largely unclear how threat-predicting stimuli and defensive behaviours are associated within prefrontal networks in order to successfully drive adaptive responses. To address these questions, we used a combination of extracellular recordings, neuronal decoding approaches, and optogenetic manipulations to show that threat representations and the initiation of avoidance behaviour are dynamically encoded in the overall population activity of dmPFC neurons. These data indicate that although dmPFC population activity at stimulus onset encodes sustained threat representations and discriminates threat- from non-threat cues, it does not predict action outcome. In contrast, transient dmPFC population activity prior to action initiation reliably predicts avoided from non-avoided trials. Accordingly, optogenetic inhibition of prefrontal activity critically constrained the selection of adaptive defensive responses in a time-dependent manner. These results reveal that the adaptive selection of active fear responses relies on a dynamic process of information linking threats with defensive actions unfolding within prefrontal networks.

Dysregulation of emotional processing and its integration with cognitive functions are central features of many mental/emotional disorders associated both with externalizing problems (aggressive, antisocial behaviors) and internalizing problems (anxiety, depression). As Dr. Joseph LeDoux, our invited speaker of this program, wrote in his famous book “Synaptic self: How Our Brains Become Who We Are”—the brain’s synapses—are the channels through which we think, act, imagine, feel, and remember. Synapses encode the essence of personality, enabling each of us to function as a distinctive, integrated individual from moment to moment. Thus, exploring the functioning of synapses leads to the understanding of the mechanism of (patho)physiological function of our brain. In this context, we have investigated the pathophysiology of psychiatric disorders, with particular emphasis on the synaptic function of model mice of various psychiatric disorders such as schizophrenia, autism, depression, and PTSD. Our current interest is how synaptic inputs are integrated to generate the action potential. Because the spatiotemporal organization of neuronal firing is crucial for information processing, but how thousands of inputs to the dendritic spines drive the firing remains a central question in neuroscience. We identified a distinct pattern of synaptic integration in the disease-related models, in which extra-large (XL) spines generate NMDA spikes within these spines, which was sufficient to drive neuronal firing. We experimentally and theoretically observed that XL spines negatively correlated with working memory. Our work offers a whole new concept for dendritic computation and network dynamics, and the understanding of psychiatric research will be greatly reconsidered. The second half of my talk is the development of a novel synaptic tool. Because, no matter how beautifully we can illuminate the spine morphology and how accurately we can quantify the synaptic integration, the links between synapse and brain function remain correlational. In order to challenge the causal relationship between synapse and brain function, we established AS-PaRac1, which is unique not only because it can specifically label and manipulate the recently potentiated dendritic spine (Hayashi-Takagi et al, 2015, Nature). With use of AS-PaRac1, we developed an activity-dependent simultaneous labeling of the presynaptic bouton and the potentiated spines to establish “functional connectomics” in a synaptic resolution. When we apply this new imaging method for PTSD model mice, we identified a completely new functional neural circuit of brain region A→B→C with a very strong S/N in the PTSD model mice. This novel tool of “functional connectomics” and its photo-manipulation could open up new areas of emotional/psychiatric research, and by extension, shed light on the neural networks that determine who we are.

Transient changes in dopamine activity in response to reward and punishment have been known to regulate reward-related learning. However, the cellular basis that detects the transient dopamine signaling has long been unclear. Using two-photon microscopy and optogenetics, I have shown that transient increases and decreases of dopamine modulate plasticity of dopamine D1 and D2 receptor-expressing cells in the nucleus accumbens, respectively. At the behavioral level, I characterized that these D1 and D2 cells cooperatively tune learning by generalization and discrimination learning. Interestingly, disturbance of the dopamine signaling impaired D2 cell plasticity and discrimination learning, which was analogous to salience misattribution seen in subjects with schizophrenia.

Coordinated activity across networks of neurons is a hallmark of both resting and active behavioral states in many species, including worms, flies, fish, mice and humans. These global patterns alter energy metabolism in the brain over seconds to hours, making oxygen consumption and glucose uptake widely used proxies of neural activity. However, whether changes in neural activity are causally related to changes in metabolic flux in intact circuits on the sub-second timescales associated with behavior, is unclear. Moreover, it is unclear whether differences between rest and action are associated with spatiotemporally structured changes in neuronal energy metabolism at the subcellular level. My work combines two-photon microscopy across the fruit fly brain with sensors that allow simultaneous measurements of neural activity and metabolic flux, across both resting and active behavioral states. It demonstrates that neural activity drives changes in metabolic flux, creating a tight coupling between these signals that can be measured across large-scale brain networks. Further, using local optogenetic perturbation, I show that even transient increases in neural activity result in rapid and persistent increases in cytosolic ATP, suggesting that neuronal metabolism predictively allocates resources to meet the energy demands of future neural activity. Finally, these studies reveal that the initiation of even minimal behavioral movements causes large-scale changes in the pattern of neural activity and energy metabolism, revealing unexpectedly widespread engagement of the central brain.

The main pillars of social behaviors involve (1) mating, where males copulate with female partners to reproduce, and (2) aggression, where males fight conspecific male competitors in territory guarding. Decades of study have identified two key regions in the hypothalamus, the medial preoptic nucleus (MPN) and the ventrolateral part of ventromedial hypothalamus (VMHvl) , that are essential for male sexual and aggressive behaviors, respectively. However, it remains ambiguous what area directs excitatory control of the hypothalamic activity and generates the initiation signal for social behaviors. Through neural tracing, in vivo optical recording and functional manipulations, we identified the estrogen receptor alpha (Esr1)-expressing cells in the posterior amygdala (PA) as a main source of excitatory inputs to the MPN and VMHvl, and key hubs in mating and fighting circuits in males. Importantly, two spatially-distinct populations in the PA regulate male sexual and aggressive behaviors, respectively. Moreover, these two subpopulations in the PA display differential molecular phenotypes, projection patterns and in vivo neural responses. Our work also observed the parallels between these social behavior circuits and basal ganglia circuits to control motivated behaviors, which Larry Swanson (2000) originally proposed based on extensive developmental and anatomical evidence.

Social interactions such as mating and fighting are driven by internal emotional states. How can we study internal states of an animal when it cannot tell us its subjective feelings? Especially when the meaning of the animal’s behavior is not clear to us, can we understand the underlying internal states of the animal? In this talk, I will introduce our recent work in which we used male mounting behavior in mice as an example to understand the underlying internal state of the animals. In many animal species, males exhibit mounting behavior toward females as part of the mating behavior repertoire. Interestingly, males also frequently show mounting behavior toward other males of the same species. It is not clear what the underlying motivation is - whether it is reproductive in nature or something distinct. Through detailed analysis of video and audio recordings during social interactions, we found that while male-directed and female-directed mounting behaviors are motorically similar, they can be distinguished by both the presence of ultrasonic vocalization during female-directed mounting (reproductive mounting) and the display of aggression following male-directed mounting (aggressive mounting). Using optogenetics, we further identified genetically defined neural populations in the medial preoptic area (MPOA) that mediate reproductive mounting and the ventrolateral ventromedial hypothalamus (VMHvl) that mediate aggressive mounting. In vivo microendocsopic imaging in MPOA and VMHvl revealed distinct neural ensembles that mainly encode either a reproductive or an aggressive state during which male or female directed mounting occurs. Together, these findings demonstrate that internal states are represented in the hypothalamus and that motorically similar behaviors exhibited under different contexts may reflect distinct internal states.

Animals constantly modify their behavior through experience. Flexible behavior is key to our ability to adapt to the ever-changing environment. My laboratory is interested in studying the activity of neuronal ensembles in behaving animals, and how it changes with learning. We have recently set up a paradigm where mice learn to associate sensory information (two different odors) to motor outputs (lick vs no-lick) under head-fixation. We combined this with two-photon calcium imaging, which can monitor the activity of a microcircuit of many tens of neurons simultaneously from a small area of the brain. Imaging the motor cortex during the learning of this task revealed neurons with diverse task-related response types. Intriguingly, different response types were spatially intermingled; even immediately adjacent neurons often had very different response types. As the mouse learned the task under the microscope, the activity coupling of neurons with similar response types specifically increased, even though they are intermingled with neurons with dissimilar response types. This suggests that intermingled subnetworks of functionally-related neurons form in a learning-related way, an observation that became possible with our cutting-edge technique combining imaging and behavior. We are working to extend this study. How plastic are neuronal microcircuits during other forms of learning? How plastic are they in other parts of the brain? What are the cellular and molecular mechanisms of the microcircuit plasticity? Are the observed activity and plasticity required for learning? How does the activity of identified individual neurons change over days to weeks? We are asking these questions, combining a variety of techniques including in vivo two-photon imaging, optogenetics, electrophysiology, genetics and behavior.

Over 60 years of research has established that medial temporal lobe structures, including the hippocampus and entorhinal cortex, are necessary for the formation of episodic memories (i.e. memories of specific personal events that occur in spatial and temporal context). While prior work to establish the neural mechanisms underlying episodic memory has largely focused on questions related spatial context, recently we have begun to investigate how these brain structures could be involved in encoding aspects of temporal context. In particular, we have focused on how medial entorhinal cortex, a structure well known for its role in spatial memory, may also be involved in encoding interval time. To answer this question we have developed an instrumental paradigm for head-fixed mice that requires both immobile interval timing and locomotion-dependent navigation behavior. By combining this behavioral paradigm with large-scale cellular resolution functional imaging and optogenetic-mediated inactivation, our results suggest that MEC is required for learning of interval timing behavior and that interval timing could be mediated through regular, sequential neural activity of a distinct subpopulation of neurons in MEC that encode elapsed time during periods of immobility (Heys and Dombeck, 2018; Heys et al, 2020; Issa et al., 2020). In this talk, I will discuss these findings and discuss our on-going work to investigate the principles underlying the role of medial temporal lobe structures in timing behavior and episodic memory.

Broadly, the Mauro Costa-Mattioli laboratory (The MCM Lab) encompasses two complementary lines of research. The first one, more traditional but very important, aims at unraveling the molecular mechanisms underlying memory formation (e.g., using state-of-the-art molecular and cell-specific genetic approaches). Learning and memory disorders can strike the brain during development (e.g., Autism Spectrum Disorders and Down Syndrome), as well as during adulthood (e.g., Alzheimer’s disease). We are interested in understanding the specific circuits and molecular pathways that are primarily targeted in these disorders and how they can be restored. To tackle these questions, we use a multidisciplinary, convergent and cross-species approach that combines mouse and fly genetics, molecular biology, electrophysiology, stem cell biology, optogenetics and behavioral techniques. The second line of research, more recent and relatively unexplored, is focused on understanding how gut microbes control CNS driven-behavior and brain function. Our recent discoveries, that microbes in the gut could modulate brain function and behavior in a very powerful way, have added a whole new dimension to the classic view of how complex behaviors are controlled. The unexpected findings have opened new avenues of study for us and are currently driving my lab to answer a host of new and very interesting questions: - What are the gut microbes (and metabolites) that regulate CNS-driven behaviors? Would it be possible to develop an unbiased screening method to identify specific microbes that regulate different behaviors? - If this is the case, can we identify how members of the gut microbiome (and their metabolites) mechanistically influence brain function? - What is the communication channel between the gut microbiota and the brain? Do different gut microbes use different ways to interact with the brain? - Could disruption of the gut microbial ecology cause neurodevelopmental dysfunction? If so, what is the impact of disruption in young and adult animals? - More importantly, could specific restoration of selected bacterial strains (new generation probiotics) represent a novel therapeutic approach for the targeted treatment of neurodevelopmental disorders? - Finally, can we develop microbiota-directed therapeutic foods to repair brain dysfunction in a variety of neurological disorders?

Team work makes sensory streams work: our senses work together, learn from each other, and stand in for one another, the result of which is perception and understanding. Learned associations between stimuli in different sensory modalities can shape the way we perceive these stimuli (Mcgurk and Macdonald, 1976). During audio-visual associative learning, auditory cortex is thought to underlie multi-modal plasticity in visual cortex (McIntosh et al., 1998; Mishra et al., 2007; Zangenehpour and Zatorre, 2010). However, it is not well understood how processing in visual cortex is altered by an auditory stimulus that is predictive of a visual stimulus and what the mechanisms are that mediate such experience-dependent, audio-visual associations in sensory cortex. Here we describe a neural mechanism by which an auditory input can shape visual representations of behaviorally relevant stimuli through direct interactions between auditory and visual cortices. We show that the association of an auditory stimulus with a visual stimulus in a behaviorally relevant context leads to an experience-dependent suppression of visual responses in primary visual cortex (V1). Auditory cortex axons carry a mixture of auditory and retinotopically-matched visual input to V1, and optogenetic stimulation of these axons selectively suppresses V1 neurons responsive to the associated visual stimulus after, but not before, learning. Our results suggest that cross-modal associations can be stored in long-range cortical connections and that with learning these cross-modal connections function to suppress the responses to predictable input.

Sequential temporal ordering and patterning are key features of natural signals, used by the brain to decode stimuli and perceive them as sensory objects. Touch is one sensory modality where temporal patterning carries key information, and the rodent whisker system is a prominent model for understanding neuronal coding and plasticity underlying touch sensation. Neurons in this system are precise encoders of fluctuations in whisker dynamics down to a timescale of milliseconds, but it is not clear whether they can refine their encoding abilities as a result of learning patterned stimuli. For example, can they enhance temporal integration to become better at distinguishing sequences? To explore how cortical coding plasticity underpins sequence discrimination, we developed a task in which mice distinguished between tactile ‘word’ sequences constructed from distinct vibrations delivered to the whiskers, assembled in different orders. Animals licked to report the presence of the target sequence. Optogenetic inactivation showed that the somatosensory cortex was necessary for sequence discrimination. Two-photon imaging in layer 2/3 of the primary somatosensory “barrel” cortex (S1bf) revealed that, in well-trained animals, neurons had heterogeneous selectivity to multiple task variables including not just sensory input but also the animal’s action decision and the trial outcome (presence or absence of the predicted reward). Many neurons were activated preceding goal-directed licking, thus reflecting the animal’s learnt action in response to the target sequence; these neurons were found as soon as mice learned to associate the rewarded sequence with licking. In contrast, learning evoked smaller changes in sensory response tuning: neurons responding to stimulus features were already found in naïve mice, and training did not generate neurons with enhanced temporal integration or categorical responses. Therefore, in S1bf sequence learning results in neurons whose activity reflects the learnt association between target sequence and licking, rather than a refined representation of sensory features. Taken together with results from other laboratories, our findings suggest that neurons in sensory cortex are involved in task-specific processing and that an animal does not sense the world independently of what it needs to feel in order to guide behaviour.

Neural responses in the visual system are usually not purely visual but depend on behavioural and internal states such as arousal. This dependence is seen both in primary visual cortex (V1) and in subcortical brain structures receiving direct retinal input. In this talk, I will show that modulation by behavioural state arises as early as in the output of the retina.To measure retinal activity in the awake, intact brain, we imaged the synaptic boutons of retinal axons in the superficial superior colliculus (sSC) of mice. The activity of about half of the boutons depended not only on vision but also on running speed and pupil size, regardless of retinal illumination. Arousal typically reduced the boutons’ visual responses to preferred direction and their selectivity for direction and orientation.Arousal may affect activity in retinal boutons by presynaptic neuromodulation. To test whether the effects of arousal occur already in the retina, we recorded from retinal axons in the optic tract. We found that, in darkness, more than one third of the recorded axons was significantly correlated with running speed. Arousal had similar effects postsynaptically, in sSC neurons, independent of activity in V1, the other main source of visual inputs to colliculus. Optogenetic inactivation of V1 generally decreased activity in collicular neurons but did not diminish the effects of arousal. These results indicate that arousal modulates activity at every stage of the visual system. In the future, we will study the purpose and the underlying mechanisms of behavioural modulation in the early visual system

My lab seeks to understand how the mammalian brain performs the computations that underlie cognitive functions, including decision-making, short-term memory, and spatial navigation, at the level of the building blocks of the nervous system, cell types and neural populations organized into circuits. We have developed methods to measure, manipulate, and analyze neural circuits across various spatial and temporal scales, including technology for virtual reality, optical imaging, optogenetics, intracellular electrophysiology, molecular sensors, and computational modeling. I will present recent work that uses large scale calcium imaging to reveal the functional organization of the mouse posterior cortex for flexible decision-making during spatial navigation in virtual reality. I will also discuss work that uses optogenetics and calcium imaging during a variety of decision-making tasks to highlight how cognitive experience and context greatly alter the cortical circuits necessary for navigation decisions.

Coping with threatening situations requires both identifying stimuli predicting danger and selecting adaptive behavioral responses in order to survive. The dorso medial prefrontal cortex (dmPFC) is a critical structure involved in the regulation of threat-related behaviour, yet it is still largely unclear how threat-predicting stimuli and defensive behaviours are associated within prefrontal networks in order to successfully drive adaptive responses. To address these questions, we used a combination of extracellular recordings, neuronal decoding approaches, and optogenetic manipulations to show that threat representations and the initiation of avoidance behaviour are dynamically encoded in the overall population activity of dmPFC neurons. These data indicate that although dmPFC population activity at stimulus onset encodes sustained threat representations and discriminates threat- from non-threat cues, it does not predict action outcome. In contrast, transient dmPFC population activity prior to action initiation reliably predicts avoided from non-avoided trials. Accordingly, optogenetic inhibition of prefrontal activity critically constrained the selection of adaptive defensive responses in a time-dependent manner. These results reveal that the adaptive selection of active fear responses relies on a dynamic process of information linking threats with defensive actions unfolding within prefrontal networks.