Real-time visualization of structural dynamics of synapses in live cells in vivo.

The structural plasticity of synapses is crucial for regulating brain functions. However, currently available methods for studying synapse organization based on split fluorescent proteins (FPs) have been limited in assessing synaptic dynamics in vivo due to the irreversible binding of split FPs. Here, we develop 'SynapShot', a method for visualizing the structural dynamics of intact synapses by combining dimerization-dependent FPs (ddFPs) with engineered synaptic adhesion molecules. SynapShot allows real-time monitoring of reversible and bidirectional changes of synaptic contacts under physiological stimulation. The application of green and red ddFPs in SynapShot enables simultaneous visualization of two distinct populations of synapses. Notably, the red-shifted SynapShot is highly compatible with blue light-based optogenetic techniques, allowing for visualization of synaptic dynamics while precisely controlling specific signaling pathways. Furthermore, we demonstrate that SynapShot enables real-time monitoring of structural changes in synaptic contacts in the mouse brain during both primitive and higher-order behaviors.

Neural circuitry for maternal oxytocin release induced by infant cries.

Oxytocin is a neuropeptide that is important for maternal physiology and childcare, including parturition and milk ejection during nursing1-6. Suckling triggers the release of oxytocin, but other sensory cues-specifically, infant cries-can increase the levels of oxytocin in new human mothers7, which indicates that cries can activate hypothalamic oxytocin neurons. Here we describe a neural circuit that routes auditory information about infant vocalizations to mouse oxytocin neurons. We performed in vivo electrophysiological recordings and photometry from identified oxytocin neurons in awake maternal mice that were presented with pup calls. We found that oxytocin neurons responded to pup vocalizations, but not to pure tones, through input from the posterior intralaminar thalamus, and that repetitive thalamic stimulation induced lasting disinhibition of oxytocin neurons. This circuit gates central oxytocin release and maternal behaviour in response to calls, providing a mechanism for the integration of sensory cues from the offspring in maternal endocrine networks to ensure modulation of brain state for efficient parenting.

An adaptive behavioral control motif mediated by cortical axo-axonic inhibition.

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.

An adaptive behavioral control motif mediated by cortical axo-axonic inhibition.

Neural circuits are reorganized with specificity during learning. 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 to learning. 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 find that organized motor control is mediated by enhanced population coding of direction-tuned premotor neurons, whose tuning is refined through suppression of irrelevant neuronal activity. ChCs are required for learning-dependent refinements via providing selective inhibitory control over pyramidal neurons rather than global suppression. Quantitative analysis on structural plasticity of 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 target cell specific manner, which highlights the significance of interneuron diversity.

Cortical control of chandelier cells in neural codes.

Various cortical functions arise from the dynamic interplay of excitation and inhibition. GABAergic interneurons that mediate synaptic inhibition display significant diversity in cell morphology, electrophysiology, plasticity rule, and connectivity. These heterogeneous features are thought to underlie their functional diversity. Emerging attention on specific properties of the various interneuron types has emphasized the crucial role of cell-type specific inhibition in cortical neural processing. However, knowledge is still limited on how each interneuron type forms distinct neural circuits and regulates network activity in health and disease. To dissect interneuron heterogeneity at single cell-type precision, we focus on the chandelier cell (ChC), one of the most distinctive GABAergic interneuron types that exclusively innervate the axon initial segments (AIS) of excitatory pyramidal neurons. Here we review the current understanding of the structural and functional properties of ChCs and their implications in behavioral functions, network activity, and psychiatric disorders. These findings provide insights into the distinctive roles of various single-type interneurons in cortical neural coding and the pathophysiology of cortical dysfunction.

Dysregulation of the mesoprefrontal dopamine circuit mediates an early-life stress-induced synaptic imbalance in the prefrontal cortex.

Stress adversely affects an array of cognitive functions. Although stress-related disorders are often addressed in adulthood, far less is known about how early-life stress (ELS) affects the developing brain in early postnatal periods. Here we show that ELS, induced by maternal separation, leads to synaptic alteration of layer 2/3 pyramidal neurons in the prefrontal cortex (PFC) of mice. We find that layer 2/3 neurons show increased excitatory synapse numbers following ELS and that this is accompanied by hyperexcitability of PFC-projecting dopamine (DA) neurons in the ventral tegmental area. Notably, excitatory synaptic change requires local signaling through DA D2 receptors. In vivo pharmacological treatment with a D2 receptor agonist in the PFC of control mice mimics the effects of ELS on synaptic alterations. Our findings reveal a neuromodulatory mechanism underlying ELS-induced PFC dysfunction, and this mechanism may facilitate a more comprehensive understanding of how ELS leads to mental disorders.

A Computational Model of Attention Control in Multi-Attribute, Context-Dependent Decision Making.

Real-life decisions often require a comparison of multi-attribute options with various benefits and costs, and the evaluation of each option depends partly on the others in the choice set (i.e., the choice context). Although reinforcement learning models have successfully described choice behavior, how to account for multi-attribute information when making a context-dependent decision remains unclear. Here we develop a computational model of attention control that includes context effects on multi-attribute decisions, linking a context-dependent choice model with a reinforcement learning model. The overall model suggests that the distinctiveness of attributes guides an individual's preferences among multi-attribute options via an attention-control mechanism that determines whether choices are selectively biased toward the most distinctive attribute (selective attention) or proportionally distributed based on the relative distinctiveness of attributes (divided attention). To test the model, we conducted a behavioral experiment in rhesus monkeys, in which they made simple multi-attribute decisions over three conditions that manipulated the degree of distinctiveness between alternatives: (1) four foods of different size and calorie; (2) four pieces of the same food in different colors; and (3) four identical pieces of food. The model simulation of the choice behavior captured the preference bias (i.e., overall preference structure) and the choice persistence (repeated choices) in the empirical data, providing evidence for the respective influences of attention and memory on preference bias and choice persistence. Our study provides insights into computations underlying multi-attribute decisions, linking attentional control to decision-making processes.

Intensiometric biosensors visualize the activity of multiple small GTPases in vivo.

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.

Nucleus accumbens shell moderates preference bias during voluntary choice behavior.

The nucleus accumbens (NAc) shell lies anatomically at a critical intersection within the brain's reward system circuitry, however, its role in voluntary choice behavior remains unclear. Rats with electrolytic lesions in the NAc shell were tested in a novel foraging paradigm. Over a continuous two-week period they freely chose among four nutritionally identical but differently flavored food pellets by pressing corresponding levers. We examined the lesion's effects on three behavioral dynamics components: motivation (when to eat), preference bias (what to choose) and persistence (how long to repeat the same choice). The lesion led to a marked increase in the preference bias: i.e., increased selection of the most-preferred choice option, and decreased selection of the others. We found no effects on any other behavioral measures, suggesting no effect on motivation or choice persistence. The results implicate the NAc shell in moderating the instrumental valuation process by inhibiting excessive bias toward preferred choice options.

A calcium- and light-gated switch to induce gene expression in activated neurons.

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.

Temporally precise labeling and control of neuromodulatory circuits in the mammalian brain.

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.

Bursts and heavy tails in temporal and sequential dynamics of foraging decisions.

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.

Get it while it's hot: a peak-first bias in self-generated choice order in rhesus macaques.

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.