Despite recent advances in optogenetics, it remains challenging to manipulate gene expression in specific populations of neurons. We present a dual-protein switch system, Cal-Light, that translates neuronal-activity-mediated calcium signaling into gene expression in a light-dependent manner. In cultured neurons and brain slices, we show that Cal-Light drives expression of the reporter EGFP with high spatiotemporal resolution only in the presence of both blue light and calcium. Delivery of the Cal-Light components to the motor cortex of mice by viral vectors labels a subset of excitatory and inhibitory neurons related to learned lever-pressing behavior. By using Cal-Light to drive expression of the inhibitory receptor halorhodopsin (eNpHR), which responds to yellow light, we temporarily inhibit the lever-pressing behavior, confirming that the labeled neurons mediate the behavior. Thus, Cal-Light enables dissection of neural circuits underlying complex mammalian behaviors with high spatiotemporal precision.

Few tools exist to visualize and manipulate neurons that are targets of neuromodulators. We present iTango, a light- and ligand-gated gene expression system based on a light-inducible split tobacco etch virus protease. Cells expressing the iTango system exhibit increased expression of a marker gene in the presence of dopamine and blue-light exposure, both in vitro and in vivo. We demonstrated the iTango system in a behaviorally relevant context, by inducing expression of optogenetic tools in neurons under dopaminergic control during a behavior of interest. We thereby gained optogenetic control of these behaviorally relevant neurons. We applied the iTango system to decipher the roles of two classes of dopaminergic neurons in the mouse nucleus accumbens in a sensitized locomotor response to cocaine. Thus, the iTango platform allows for control of neuromodulatory circuits in a genetically and functionally defined manner with spatial and temporal precision.

Ras and Rho small GTPases are critical for numerous cellular processes including cell division, migration, and intercellular communication. Despite extensive efforts to visualize the spatiotemporal activity of these proteins, achieving the sensitivity and dynamic range necessary for in vivo application has been challenging. Here, we present highly sensitive intensiometric small GTPase biosensors visualizing the activity of multiple small GTPases in single cells in vivo. Red-shifted sensors combined with blue light-controllable optogenetic modules achieved simultaneous monitoring and manipulation of protein activities in a highly spatiotemporal manner. Our biosensors revealed spatial dynamics of Cdc42 and Ras activities upon structural plasticity of single dendritic spines, as well as a broad range of subcellular Ras activities in the brains of freely behaving mice. Thus, these intensiometric small GTPase sensors enable the spatiotemporal dissection of complex protein signaling networks in live animals.

SummaryOxytocin is a neuropeptide important for maternal physiology and childcare, including parturition and milk ejection during nursing. Suckling triggers oxytocin release, but other sensory cues- specifically infant cries- can elevate oxytocin levels in new human mothers, indicating that cries can activate hypothalamic oxytocin neurons. Here we describe a neural circuit routing auditory information about infant vocalizations to the oxytocin system of the mouse brain. We performed in vivo electrophysiological recordings and photometry from identified oxytocin neurons in awake maternal mice presented with pup calls. We found that oxytocin neurons responded to pup vocalizations via input from the posterior intralaminar thalamus, and repetitive thalamic stimulation induced lasting disinhibition of oxytocin neurons. Suppression of this pathway impaired maternal behavior and playing pup calls led to central oxytocin release in vivo. This circuit provides a mechanism for transforming acoustic input into hormonal output to ensure modulation of brain state required for successful parenting.

Oxytocin (OXT) is a neuropeptide originating in the paraventricular nucleus (PVN) of the hypothalamus, with a role in influencing various social behaviors. However, pinpointing its actions only during the time animals are performing specific behaviors has been difficult to study. Here we developed an optogenetic gene expression system designed to selectively label neuronal populations activated by OXT in the presence of blue-light, named OXTR-iTango2. The OXTR-iTango2 was capable of inducing gene expression of a reporter gene in both human embryonic kidney (HEK) cells and neurons in a quantitative manner. In vivo expression of OXTR-iTango2 selectively labeled OXT-sensitive neurons in a blue-light dependent manner. Furthermore, we were able to detect a subset of dopamine (DA) neurons in the ventral tegmental area (VTA) that receive OXT activation during social interaction. Thus, we provide a genetically-encoded, scalable optogenetic toolset to target neural circuits activated by OXT in behaving animals with a high temporal resolution.

A fundamental understanding of behavior requires predicting when and what an individual will choose. However, the actual temporal and sequential dynamics of successive choices made among multiple alternatives remain unclear. In the current study, we tested the hypothesis that there is a general bursting property in both the timing and sequential patterns of foraging decisions. We conducted a foraging experiment in which rats chose among four different foods over a continuous two-week time period. Regarding when choices were made, we found bursts of rapidly occurring actions, separated by time-varying inactive periods, partially based on a circadian rhythm. Regarding what was chosen, we found sequential dynamics in affective choices characterized by two key features: (a) a highly biased choice distribution; and (b) preferential attachment, in which the animals were more likely to choose what they had previously chosen. To capture the temporal dynamics, we propose a dual-state model consisting of active and inactive states. We also introduce a satiation-attainment process for bursty activity, and a non-homogeneous Poisson process for longer inactivity between bursts. For the sequential dynamics, we propose a dual-control model consisting of goal-directed and habit systems, based on outcome valuation and choice history, respectively. This study provides insights into how the bursty nature of behavior emerges from the interaction of different underlying systems, leading to heavy tails in the distribution of behavior over time and choices.

Animals typically must make a number of successive choices to achieve a goal: e.g., eating multiple food items before becoming satiated. However, it is unclear whether choosing the best first or saving the best for last represents the best choice strategy to maximize overall reward. Specifically, since outcomes can be evaluated prospectively (with future rewards discounted and more immediate rewards preferred) or retrospectively (with prior rewards discounted and more recent rewards preferred), the conditions under which each are used remains unclear. On the one hand, humans and non-human animals clearly discount future reward, preferring immediate rewards to delayed ones, suggesting prospective evaluation; on the other hand, it has also been shown that a sequence that ends well, i.e., with the best event or item last, is often preferred, suggesting retrospective evaluation. Here we hypothesized that when individuals are allowed to build the sequence themselves they are more likely to evaluate each item individually and therefore build a sequence using prospective evaluation. We examined the relationship between self-generated choice order and preference in rhesus monkeys in two experiments in which the distinctiveness of options were relatively high and low, respectively. We observed a positive linear relationship between choice order and preference among highly distinct options, indicating that the rhesus monkeys chose their preferred food first: i.e., a peak-first order preference. Overall, choice order depended on the degree of relative preference among alternatives and a peak-first bias, providing evidence for prospective evaluation when choice order is self-generated.

Genetically defined subgroups of inhibitory interneurons are thought to play distinct roles in learning, but heterogeneity within these subgroups has limited our understanding of the scope and nature of their specific contributions. Here we reveal that the chandelier cell (ChC), an interneuron type that specializes in inhibiting the axon-initial segment (AIS) of pyramidal neurons, establishes cortical microcircuits for organizing neural coding through selective axo-axonic synaptic plasticity. We found that organized motor control is mediated by enhanced population coding of direction-tuned premotor neurons, with tuning refined through suppression of irrelevant neuronal activity. ChCs contribute to learning-dependent refinements by providing selective inhibitory control over individual pyramidal neurons rather than global suppression. Quantitative analysis of structural plasticity across axo-axonic synapses revealed that ChCs redistributed inhibitory weights to individual pyramidal neurons during learning. These results demonstrate an adaptive logic of the inhibitory circuit motif responsible for organizing distributed neural representations. Thus, ChCs permit efficient cortical computation in a targeted cell-specific manner.