Neural circuit mechanisms underlying context-specific halting in Drosophila.

Walking is a complex motor programme involving coordinated and distributed activity across the brain and the spinal cord. Halting appropriately at the correct time is a critical component of walking control. Despite progress in identifying neurons driving halting1-6, the underlying neural circuit mechanisms responsible for overruling the competing walking state remain unclear. Here, using connectome-informed models7-9 and functional studies, we explain two fundamental mechanisms by which Drosophila implement context-appropriate halting. The first mechanism ('walk-OFF') relies on GABAergic neurons that inhibit specific descending walking commands in the brain, whereas the second mechanism ('brake') relies on excitatory cholinergic neurons in the nerve cord that lead to an active arrest of stepping movements. We show that two neurons that deploy the walk-OFF mechanism inhibit distinct populations of walking-promotion neurons, leading to differential halting of forward walking or turning. The brake neurons, by constrast, override all walking commands by simultaneously inhibiting descending walking-promotion neurons and increasing the resistance at the leg joints. We characterized two behavioural contexts in which the distinct halting mechanisms were used by the animal in a mutually exclusive manner: the walk-OFF mechanism was engaged for halting during feeding and the brake mechanism was engaged for halting and stability during grooming.

The fly connectome reveals a path to the effectome.

A goal of neuroscience is to obtain a causal model of the nervous system. The recently reported whole-brain fly connectome1-3 specifies the synaptic paths by which neurons can affect each other, but not how strongly they do affect each other in vivo. To overcome this limitation, we introduce a combined experimental and statistical strategy for efficiently learning a causal model of the fly brain, which we refer to as the 'effectome'. Specifically, we propose an estimator for a linear dynamical model of the fly brain that uses stochastic optogenetic perturbation data to estimate causal effects and the connectome as a prior to greatly improve estimation efficiency. We validate our estimator in connectome-based linear simulations and show that it recovers a linear approximation to the nonlinear dynamics of more biophysically realistic simulations. We then analyse the connectome to propose circuits that dominate the dynamics of the fly nervous system. We discover that the dominant circuits involve only relatively small populations of neurons-thus, neuron-level imaging, stimulation and identification are feasible. This approach also re-discovers known circuits and generates testable hypotheses about their dynamics. Overall, we provide evidence that fly whole-brain dynamics are generated by a large collection of small circuits that operate largely independently of each other. This implies that a causal model of a brain can be feasibly obtained in the fly.

Synaptic architecture of leg and wing premotor control networks in Drosophila.

Animal movement is controlled by motor neurons (MNs), which project out of the central nervous system to activate muscles1. MN activity is coordinated by complex premotor networks that facilitate the contribution of individual muscles to many different behaviours2-6. Here we use connectomics7 to analyse the wiring logic of premotor circuits controlling the Drosophila leg and wing. We find that both premotor networks cluster into modules that link MNs innervating muscles with related functions. Within most leg motor modules, the synaptic weights of each premotor neuron are proportional to the size of their target MNs, establishing a circuit basis for hierarchical MN recruitment. By contrast, wing premotor networks lack proportional synaptic connectivity, which may enable more flexible recruitment of wing steering muscles. Through comparison of the architecture of distinct motor control systems within the same animal, we identify common principles of premotor network organization and specializations that reflect the unique biomechanical constraints and evolutionary origins of leg and wing motor control.

Neuronal wiring diagram of an adult brain.

Connections between neurons can be mapped by acquiring and analysing electron microscopic brain images. In recent years, this approach has been applied to chunks of brains to reconstruct local connectivity maps that are highly informative1-6, but nevertheless inadequate for understanding brain function more globally. Here we present a neuronal wiring diagram of a whole brain containing 5 × 107 chemical synapses7 between 139,255 neurons reconstructed from an adult female Drosophila melanogaster8,9. The resource also incorporates annotations of cell classes and types, nerves, hemilineages and predictions of neurotransmitter identities10-12. Data products are available for download, programmatic access and interactive browsing and have been made interoperable with other fly data resources. We derive a projectome-a map of projections between regions-from the connectome and report on tracing of synaptic pathways and the analysis of information flow from inputs (sensory and ascending neurons) to outputs (motor, endocrine and descending neurons) across both hemispheres and between the central brain and the optic lobes. Tracing from a subset of photoreceptors to descending motor pathways illustrates how structure can uncover putative circuit mechanisms underlying sensorimotor behaviours. The technologies and open ecosystem reported here set the stage for future large-scale connectome projects in other species.

Connectomic reconstruction of a female Drosophila ventral nerve cord.

A deep understanding of how the brain controls behaviour requires mapping neural circuits down to the muscles that they control. Here, we apply automated tools to segment neurons and identify synapses in an electron microscopy dataset of an adult female Drosophila melanogaster ventral nerve cord (VNC)1, which functions like the vertebrate spinal cord to sense and control the body. We find that the fly VNC contains roughly 45 million synapses and 14,600 neuronal cell bodies. To interpret the output of the connectome, we mapped the muscle targets of leg and wing motor neurons using genetic driver lines2 and X-ray holographic nanotomography3. With this motor neuron atlas, we identified neural circuits that coordinate leg and wing movements during take-off. We provide the reconstruction of VNC circuits, the motor neuron atlas and tools for programmatic and interactive access as resources to support experimental and theoretical studies of how the nervous system controls behaviour.

Network statistics of the whole-brain connectome of Drosophila.

Brains comprise complex networks of neurons and connections, similar to the nodes and edges of artificial networks. Network analysis applied to the wiring diagrams of brains can offer insights into how they support computations and regulate the flow of information underlying perception and behaviour. The completion of the first whole-brain connectome of an adult fly, containing over 130,000 neurons and millions of synaptic connections1-3, offers an opportunity to analyse the statistical properties and topological features of a complete brain. Here we computed the prevalence of two- and three-node motifs, examined their strengths, related this information to both neurotransmitter composition and cell type annotations4,5, and compared these metrics with wiring diagrams of other animals. We found that the network of the fly brain displays rich-club organization, with a large population (30% of the connectome) of highly connected neurons. We identified subsets of rich-club neurons that may serve as integrators or broadcasters of signals. Finally, we examined subnetworks based on 78 anatomically defined brain regions or neuropils. These data products are shared within the FlyWire Codex ( https://codex.flywire.ai ) and should serve as a foundation for models and experiments exploring the relationship between neural activity and anatomical structure.

A Drosophila computational brain model reveals sensorimotor processing.

The recent assembly of the adult Drosophila melanogaster central brain connectome, containing more than 125,000 neurons and 50 million synaptic connections, provides a template for examining sensory processing throughout the brain1,2. Here we create a leaky integrate-and-fire computational model of the entire Drosophila brain, on the basis of neural connectivity and neurotransmitter identity3, to study circuit properties of feeding and grooming behaviours. We show that activation of sugar-sensing or water-sensing gustatory neurons in the computational model accurately predicts neurons that respond to tastes and are required for feeding initiation4. In addition, using the model to activate neurons in the feeding region of the Drosophila brain predicts those that elicit motor neuron firing5-a testable hypothesis that we validate by optogenetic activation and behavioural studies. Activating different classes of gustatory neurons in the model makes accurate predictions of how several taste modalities interact, providing circuit-level insight into aversive and appetitive taste processing. Additionally, we applied this model to mechanosensory circuits and found that computational activation of mechanosensory neurons predicts activation of a small set of neurons comprising the antennal grooming circuit, and accurately describes the circuit response upon activation of different mechanosensory subtypes6-10. Our results demonstrate that modelling brain circuits using only synapse-level connectivity and predicted neurotransmitter identity generates experimentally testable hypotheses and can describe complete sensorimotor transformations.

Brain-wide correspondence of neuronal epigenomics and distant projections.

Single-cell analyses parse the brain's billions of neurons into thousands of 'cell-type' clusters residing in different brain structures1. Many cell types mediate their functions through targeted long-distance projections allowing interactions between specific cell types. Here we used epi-retro-seq2 to link single-cell epigenomes and cell types to long-distance projections for 33,034 neurons dissected from 32 different regions projecting to 24 different targets (225 source-to-target combinations) across the whole mouse brain. We highlight uses of these data for interrogating principles relating projection types to transcriptomics and epigenomics, and for addressing hypotheses about cell types and connections related to genetics. We provide an overall synthesis with 926 statistical comparisons of discriminability of neurons projecting to each target for every source. We integrate this dataset into the larger BRAIN Initiative Cell Census Network atlas, composed of millions of neurons, to link projection cell types to consensus clusters. Integration with spatial transcriptomics further assigns projection-enriched clusters to smaller source regions than the original dissections. We exemplify this by presenting in-depth analyses of projection neurons from the hypothalamus, thalamus, hindbrain, amygdala and midbrain to provide insights into properties of those cell types, including differentially expressed genes, their associated cis-regulatory elements and transcription-factor-binding motifs, and neurotransmitter use.

Sequential appetite suppression by oral and visceral feedback to the brainstem.

The termination of a meal is controlled by dedicated neural circuits in the caudal brainstem. A key challenge is to understand how these circuits transform the sensory signals generated during feeding into dynamic control of behaviour. The caudal nucleus of the solitary tract (cNTS) is the first site in the brain where many meal-related signals are sensed and integrated1-4, but how the cNTS processes ingestive feedback during behaviour is unknown. Here we describe how prolactin-releasing hormone (PRLH) and GCG neurons, two principal cNTS cell types that promote non-aversive satiety, are regulated during ingestion. PRLH neurons showed sustained activation by visceral feedback when nutrients were infused into the stomach, but these sustained responses were substantially reduced during oral consumption. Instead, PRLH neurons shifted to a phasic activity pattern that was time-locked to ingestion and linked to the taste of food. Optogenetic manipulations revealed that PRLH neurons control the duration of seconds-timescale feeding bursts, revealing a mechanism by which orosensory signals feed back to restrain the pace of ingestion. By contrast, GCG neurons were activated by mechanical feedback from the gut, tracked the amount of food consumed and promoted satiety that lasted for tens of minutes. These findings reveal that sequential negative feedback signals from the mouth and gut engage distinct circuits in the caudal brainstem, which in turn control elements of feeding behaviour operating on short and long timescales.

Action suppression reveals opponent parallel control via striatal circuits.

The direct and indirect pathways of the basal ganglia are classically thought to promote and suppress action, respectively1. However, the observed co-activation of striatal direct and indirect medium spiny neurons2 (dMSNs and iMSNs, respectively) has challenged this view. Here we study these circuits in mice performing an interval categorization task that requires a series of self-initiated and cued actions and, critically, a sustained period of dynamic action suppression. Although movement produced the co-activation of iMSNs and dMSNs in the sensorimotor, dorsolateral striatum (DLS), fibre photometry and photo-identified electrophysiological recordings revealed signatures of functional opponency between the two pathways during action suppression. Notably, optogenetic inhibition showed that DLS circuits were largely engaged to suppress-and not promote-action. Specifically, iMSNs on a given hemisphere were dynamically engaged to suppress tempting contralateral action. To understand how such regionally specific circuit function arose, we constructed a computational reinforcement learning model that reproduced key features of behaviour, neural activity and optogenetic inhibition. The model predicted that parallel striatal circuits outside the DLS learned the action-promoting functions, generating the temptation to act. Consistent with this, optogenetic inhibition experiments revealed that dMSNs in the associative, dorsomedial striatum, in contrast to those in the DLS, promote contralateral actions. These data highlight how opponent interactions between multiple circuit- and region-specific basal ganglia processes can lead to behavioural control, and establish a critical role for the sensorimotor indirect pathway in the proactive suppression of tempting actions.

Neural circuit mechanisms of sexual receptivity in Drosophila females.

Choosing a mate is one of the most consequential decisions a female will make during her lifetime. A female fly signals her willingness to mate by opening her vaginal plates, allowing a courting male to copulate1,2. Vaginal plate opening (VPO) occurs in response to the male courtship song and is dependent on the mating status of the female. How these exteroceptive (song) and interoceptive (mating status) inputs are integrated to regulate VPO remains unknown. Here we characterize the neural circuitry that implements mating decisions in the brain of female Drosophila melanogaster. We show that VPO is controlled by a pair of female-specific descending neurons (vpoDNs). The vpoDNs receive excitatory input from auditory neurons (vpoENs), which are tuned to specific features of the D. melanogaster song, and from pC1 neurons, which encode the mating status of the female3,4. The song responses of vpoDNs, but not vpoENs, are attenuated upon mating, accounting for the reduced receptivity of mated females. This modulation is mediated by pC1 neurons. The vpoDNs thus directly integrate the external and internal signals that control the mating decisions of Drosophila females.

A discrete neuronal circuit induces a hibernation-like state in rodents.

Hibernating mammals actively lower their body temperature to reduce energy expenditure when facing food scarcity1. This ability to induce a hypometabolic state has evoked great interest owing to its potential medical benefits2,3. Here we show that a hypothalamic neuronal circuit in rodents induces a long-lasting hypothermic and hypometabolic state similar to hibernation. In this state, although body temperature and levels of oxygen consumption are kept very low, the ability to regulate metabolism still remains functional, as in hibernation4. There was no obvious damage to tissues and organs or abnormalities in behaviour after recovery from this state. Our findings could enable the development of a method to induce a hibernation-like state, which would have potential applications in non-hibernating mammalian species including humans.

Hierarchical organization of cortical and thalamic connectivity.

The mammalian cortex is a laminar structure containing many areas and cell types that are densely interconnected in complex ways, and for which generalizable principles of organization remain mostly unknown. Here we describe a major expansion of the Allen Mouse Brain Connectivity Atlas resource1, involving around a thousand new tracer experiments in the cortex and its main satellite structure, the thalamus. We used Cre driver lines (mice expressing Cre recombinase) to comprehensively and selectively label brain-wide connections by layer and class of projection neuron. Through observations of axon termination patterns, we have derived a set of generalized anatomical rules to describe corticocortical, thalamocortical and corticothalamic projections. We have built a model to assign connection patterns between areas as either feedforward or feedback, and generated testable predictions of hierarchical positions for individual cortical and thalamic areas and for cortical network modules. Our results show that cell-class-specific connections are organized in a shallow hierarchy within the mouse corticothalamic network.

Chemosensory modulation of neural circuits for sodium appetite.

Sodium is the main cation in the extracellular fluid and it regulates various physiological functions. Depletion of sodium in the body increases the hedonic value of sodium taste, which drives animals towards sodium consumption1,2. By contrast, oral sodium detection rapidly quenches sodium appetite3,4, suggesting that taste signals have a central role in sodium appetite and its satiation. Nevertheless, the neural mechanisms of chemosensory-based appetite regulation remain poorly understood. Here we identify genetically defined neural circuits in mice that control sodium intake by integrating chemosensory and internal depletion signals. We show that a subset of excitatory neurons in the pre-locus coeruleus express prodynorphin, and that these neurons are a critical neural substrate for sodium-intake behaviour. Acute stimulation of this population triggered robust ingestion of sodium even from rock salt, while evoking aversive signals. Inhibition of the same neurons reduced sodium consumption selectively. We further demonstrate that the oral detection of sodium rapidly suppresses these sodium-appetite neurons. Simultaneous in vivo optical recording and gastric infusion revealed that sodium taste-but not sodium ingestion per se-is required for the acute modulation of neurons in the pre-locus coeruleus that express prodynorphin, and for satiation of sodium appetite. Moreover, retrograde-virus tracing showed that sensory modulation is in part mediated by specific GABA (γ-aminobutyric acid)-producing neurons in the bed nucleus of the stria terminalis. This inhibitory neural population is activated by sodium ingestion, and sends rapid inhibitory signals to sodium-appetite neurons. Together, this study reveals a neural architecture that integrates chemosensory signals and the internal need to maintain sodium balance.

Electrophysiological and morphological properties of prefrontal pyramidal neurons innervated by mediodorsal thalamus.

The high-order cognitive and executive functions are necessary for an individual to survive. The densely bidirectional innervations between the medial prefrontal cortex (mPFC) and the mediodorsal thalamus (MD) play a vital role in regulating high-order functions. Pyramidal neurons in mPFC have been classified into several subclasses according to their morphological and electrophysiological properties, but the properties of the input-specific pyramidal neurons in mPFC remain poorly understood. The present study aimed to profile the morphological and electrophysiological properties of mPFC pyramidal neurons innervated by MD. In the past, the studies for characterizing the morphological and electrophysiological properties of neurons mainly relied on the electrophysiological recording of a large number of neurons and their morphologic reconstructions. But, it is a low efficient method for characterizing the circuit-specific neurons. The present study combined the advantages of traditional morphological and electrophysiological methods with machine learning to address the shortcomings of the past method, to establish a classification model for the morphological and electrophysiological properties of mPFC pyramidal neurons, and to achieve more accurate and efficient identification of the properties from a small size sample of neurons. We labeled MD-innervated pyramidal neurons of mPFC using the trans-synaptic neural circuitry tracing method and obtained their morphological properties using whole-cell patch-clamp recording and morphologic reconstructions. The results showed that the classification model established in the present study could predict the electrophysiological properties of MD-innervated pyramidal neurons based on their morphology. MD-innervated pyramidal neurons exhibit larger basal dendritic length but lower apical dendrite complexity compared to non-MD-innervated neurons in the mPFC. The morphological characteristics of the two subtypes (ET-1 and ET-2) of mPFC pyramidal neurons innervated by MD are different, with the apical dendrites of ET-1 neurons being longer and more complex than those of ET-2 neurons. These results suggest that the electrophysiological properties of MD- innervated pyramidal neurons within mPFC correlate with their morphological properties, indicating that the different roles of these two subclasses in local circuits within PFC, as well as in PFC-cortical/subcortical brain region circuits.

Pathways for Memory, Cognition and Emotional Context: Hippocampal, Subgenual Area 25, and Amygdalar Axons Show Unique Interactions in the Primate Thalamic Reuniens Nucleus.

The reuniens nucleus (RE) is situated at the most ventral position of the midline thalamus. In rats and mice RE is distinguished by bidirectional connections with the hippocampus and medial prefrontal cortex (mPFC) and a role in memory and cognition. In primates, many foundational questions pertaining to RE remain unresolved. We addressed these issues by investigating the composition of the rhesus monkey RE in both sexes by labeling for GABA, a marker of inhibitory neurons, and for the calcium-binding proteins parvalbumin (PV), calbindin (CB), and calretinin (CR), which label thalamic excitatory neurons that project to cortex. As in rats and mice, the macaque RE was mostly populated by CB and CR neurons, characteristic of matrix-dominant nuclei, and had bidirectional connections with hippocampus and mPFC area 25 (A25). Unlike rodents, we found GABAergic neurons in the monkey RE and a sparser but consistent population of core-associated thalamocortical PV neurons. RE had stronger connections with the basal amygdalar complex than in rats or mice. Amygdalar terminations were enriched with mitochondria and frequently formed successive synapses with the same postsynaptic structures, suggesting an active and robust pathway to RE. Significantly, hippocampal pathways formed multisynaptic complexes that uniquely involved excitatory projection neurons and dendrites of local inhibitory neurons in RE, extending this synaptic principle beyond sensory to high-order thalamic nuclei. Convergent pathways from hippocampus, A25, and amygdala in RE position it to flexibly coordinate activity for memory, cognition, and emotional context, which are disrupted in several psychiatric and neurologic diseases in humans.SIGNIFICANCE STATEMENT The primate RE is a central node for memory and cognition through connections with the hippocampus and mPFC. As in rats or mice, the primate RE is a matrix-dominant thalamic nucleus, suggesting signal traffic to the upper cortical layers. Unlike rats or mice, the primate RE contains inhibitory neurons, synaptic specializations with the hippocampal pathway, and robust connections with the amygdala, suggesting unique adaptations. Convergence of hippocampal, mPFC, and amygdalar pathways in RE may help unravel a circuit basis for binding diverse signals for conscious flexible behaviors and the synthesis of memory with affective significance in primates, whereas disruption of distinct circuit nodes may occur in psychiatric disorders in humans.

Involvement of Denervated Midbrain-Derived Factors in the Formation of Ectopic Cortico-Mesencephalic Projection after Hemispherectomy.

Neuronal remodeling after brain injury is essential for functional recovery. After unilateral cortical lesion, axons from the intact cortex ectopically project to the denervated midbrain, but the molecular mechanisms remain largely unknown. To address this issue, we examined gene expression profiles in denervated and intact mouse midbrains after hemispherectomy at early developmental stages using mice of either sex, when ectopic contralateral projection occurs robustly. The analysis showed that various axon growth-related genes were upregulated in the denervated midbrain, and most of these genes are reportedly expressed by glial cells. To identify the underlying molecules, the receptors for candidate upregulated molecules were knocked out in layer 5 projection neurons in the intact cortex, using the CRISPR/Cas9-mediated method, and axonal projection from the knocked-out cortical neurons was examined after hemispherectomy. We found that the ectopic projection was significantly reduced when integrin subunit ß three or neurotrophic receptor tyrosine kinase 2 (also known as TrkB) was knocked out. Overall, the present study suggests that denervated midbrain-derived glial factors contribute to lesion-induced remodeling of the cortico-mesencephalic projection via these receptors.SIGNIFICANCE STATEMENT After brain injury, compensatory neural circuits are established that contribute to functional recovery. However, little is known about the intrinsic mechanism that underlies the injury-induced remodeling. We found that after unilateral cortical ablation expression of axon-growth promoting factors is elevated in the denervated midbrain and is involved in the formation of ectopic axonal projection from the intact cortex. Evidence further demonstrated that these factors are expressed by astrocytes and microglia, which are activated in the denervated midbrain. Thus, our present study provides a new insight into the mechanism of lesion-induced axonal remodeling and further therapeutic strategies after brain injury.

Axonal synapse sorting in medial entorhinal cortex.

Research on neuronal connectivity in the cerebral cortex has focused on the existence and strength of synapses between neurons, and their location on the cell bodies and dendrites of postsynaptic neurons. The synaptic architecture of individual presynaptic axonal trees, however, remains largely unknown. Here we used dense reconstructions from three-dimensional electron microscopy in rats to study the synaptic organization of local presynaptic axons in layer 2 of the medial entorhinal cortex, the site of grid-like spatial representations. We observe path-length-dependent axonal synapse sorting, such that axons of excitatory neurons sequentially target inhibitory neurons followed by excitatory neurons. Connectivity analysis revealed a cellular feedforward inhibition circuit involving wide, myelinated inhibitory axons and dendritic synapse clustering. Simulations show that this high-precision circuit can control the propagation of synchronized activity in the medial entorhinal cortex, which is known for temporally precise discharges.

Cell diversity and network dynamics in photosensitive human brain organoids.

In vitro models of the developing brain such as three-dimensional brain organoids offer an unprecedented opportunity to study aspects of human brain development and disease. However, the cells generated within organoids and the extent to which they recapitulate the regional complexity, cellular diversity and circuit functionality of the brain remain undefined. Here we analyse gene expression in over 80,000 individual cells isolated from 31 human brain organoids. We find that organoids can generate a broad diversity of cells, which are related to endogenous classes, including cells from the cerebral cortex and the retina. Organoids could be developed over extended periods (more than 9 months), allowing for the establishment of relatively mature features, including the formation of dendritic spines and spontaneously active neuronal networks. Finally, neuronal activity within organoids could be controlled using light stimulation of photosensitive cells, which may offer a way to probe the functionality of human neuronal circuits using physiological sensory stimuli.