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INTRODUCTION: The brains of extant animals have evolved over hundreds of millions of years from simple circuits. Cell types diversified, connections elaborated, and new brain regions emerged. Models for brain region evolution range from duplication of existing regions to splitting of previously multifunctional regions and de novo assembly from existing cell types. These models, however, have not been demonstrated in vertebrate brains at cell-type resolution. RATIONALE: We investigated brain region evolution using the cerebellar nuclei as a model system. The cerebellum is a major hindbrain structure in jawed vertebrates, comprising the cerebellar cortex and cerebellar nuclei. It is thought to act as a feedforward model for motor control and cognitive processes. The cerebellar cortex receives and processes inputs and sends outputs to the cerebellar nuclei, which route the results of cerebellar computations to the rest of the brain. Whereas the cerebellar cortex is well conserved across vertebrates, the cerebellar nuclei vary in number, with none in jawless vertebrates, one pair in cartilaginous fishes and amphibians, two pairs in reptiles and birds, and three pairs in mammals. This pattern suggests that extant cerebellar nuclei evolved from a single ancestral nucleus. Cerebellar nuclei thus provide a good model to interrogate brain region evolution. RESULTS: We characterized the cerebellar nuclei in mice, chickens, and humans using whole-brain and spinal cord projection mapping in cleared samples, single-nucleus RNA sequencing (snRNAseq), and spatially resolved transcript amplicon readout mapping (STARmap) analysis. We first compared the projection patterns of the three cerebellar nuclei of mice. Our data reveal broad projections of all nuclei, which in common target regions are shifted relative to each other. To understand the transcriptomic differences that underlie these shifting projections, we produced a cell-type atlas of the mouse cerebellar nuclei using snRNAseq. We discovered three region-invariant inhibitory cell classes and 15 region-specific excitatory cell types. Excitatory cell types fall into two classes with distinct gene expression and electrophysiological properties. Members of each class are present in every nucleus and are putative sister cell types. STARmap analysis in mice revealed that the organizational unit of the cerebellar nuclei is cytoarchitectonically distinguishable subnuclei, each of which contains the three inhibitory and two excitatory classes. To test whether this archetypal subnucleus is also the evolutionary unit of the cerebellar nuclei, we performed snRNAseq and STARmap on the chicken cerebellar nuclei. We identified four subnuclei, three of which had direct orthologs in mice. Each chicken subnucleus contained the same cell-type set of three inhibitory and two excitatory classes already identified in mice, confirming our hypothesis. Cerebellar nuclei vary in size across vertebrates. In particular, the human lateral nucleus is markedly expanded. To understand this expansion, we performed snRNAseq in humans. We found that the medial and interposed nuclei maintained the archetypal cerebellar nuclei composition. However, the lateral nucleus expanded one excitatory cell class at the expense of the other. Conditional tracing in the mouse lateral nucleus revealed that the cell class expanded in humans preferentially accesses lateral frontal cortices via specific intermediate thalamic nuclei. CONCLUSION: We identified a conserved cell-type set that forms an archetypal cerebellar nucleus as the unit of cerebellar nuclei organization and evolution. We propose that this archetypal nucleus was repeatedly duplicated during evolution, accompanied primarily by transcriptomic divergence of excitatory neurons and shifts in their projection patterns. Our data support a model of duplication-and-divergence of entire cell-type sets for brain region evolution.

Memories of fearful events can last a lifetime. The prelimbic (PL) cortex, a subregion of prefrontal cortex, plays a critical role in fear memory retrieval over time. Most studies have focused on acquisition, consolidation, and retrieval of recent memories, but much less is known about the neural mechanisms of remote memory. Using a new knock-in mouse for activity-dependent genetic labeling (TRAP2), we demonstrate that neuronal ensembles in the PL cortex are dynamic. PL neurons TRAPed during later memory retrievals are more likely to be reactivated and make larger behavioral contributions to remote memory retrieval compared to those TRAPed during learning or early memory retrieval. PL activity during learning is required to initiate this time-dependent reorganization in PL ensembles underlying memory retrieval. Finally, while neurons TRAPed during earlier and later retrievals have similar broad projections throughout the brain, PL neurons TRAPed later have a stronger functional recruitment of cortical targets.

Serotonin neurons of the dorsal and median raphe nuclei (DR, MR) collectively innervate the entire forebrain and midbrain, modulating diverse physiology and behavior. To gain a fundamental understanding of their molecular heterogeneity, we used plate-based single-cell RNA-sequencing to generate a comprehensive dataset comprising eleven transcriptomically distinct serotonin neuron clusters. Systematic in situ hybridization mapped specific clusters to the principal DR, caudal DR, or MR. These transcriptomic clusters differentially express a rich repertoire of neuropeptides, receptors, ion channels, and transcription factors. We generated novel intersectional viral-genetic tools to access specific subpopulations. Whole-brain axonal projection mapping revealed that DR serotonin neurons co-expressing vesicular glutamate transporter-3 preferentially innervate the cortex, whereas those co-expressing thyrotropin-releasing hormone innervate subcortical regions in particular the hypothalamus. Reconstruction of 50 individual DR serotonin neurons revealed diverse and segregated axonal projection patterns at the single-cell level. Together, these results provide a molecular foundation of the heterogenous serotonin neuronal phenotypes.

The projection targets of a neuronal population are a key feature of its anatomical characterization. Historically, tissue sectioning, confocal microscopy, and manual scoring of specific regions of interest have been used to generate coarse summaries of mesoscale projectomes. We present here TrailMap, a 3D convolutional network for extracting axonal projections from intact cleared mouse brains imaged by light-sheet microscopy. TrailMap allows region-based quantification of total axon content in large and complex 3D structures after registration to a standard reference atlas. The identification of axonal structures as thin as one voxel benefits from data augmentation but also requires a loss function that tolerates errors in annotation. A network trained with volumes of serotonergic axons in all major brain regions can be generalized to map and quantify axons from thalamocortical, deep cerebellar, and cortical projection neurons, validating transfer learning as a tool to adapt the model to novel categories of axonal morphology. Speed of training, ease of use, and accuracy improve over existing tools without a need for specialized computing hardware. Given the recent emphasis on genetically and functionally defining cell types in neural circuit analysis, TrailMap will facilitate automated extraction and quantification of axons from these specific cell types at the scale of the entire mouse brain, an essential component of deciphering their connectivity.

Studies of amnesic patients and animal models support a systems consolidation model, which posits that explicit memories formed in hippocampus are transferred to cortex over time1–6. Prelimbic cortex (PL), a subregion of the medial prefrontal cortex, is required for the expression of learned fear memories from hours after learning until weeks later7–12. While some studies suggested that prefrontal cortical neurons active during learning are required for memory retrieval13–15, others provided evidence for ongoing cortical circuit reorganization during memory consolidation10,16,17. It has been difficult to causally relate the activity of cortical neurons during learning or recent memory retrieval to their function in remote memory, in part due to a lack of tools18. Here we show that a new version of ‘targeted recombination in active populations’, TRAP2, has enhanced efficiency over the past version, providing brain-wide access to neurons activated by a particular experience. Using TRAP2, we accessed PL neurons activated during fear conditioning or 1-, 7-, or 14-day memory retrieval, and assessed their contributions to 28-day remote memory. We found that PL neurons TRAPed at later retrieval times were more likely to be reactivated during remote memory retrieval, and more effectively promoted remote memory retrieval. Furthermore, reducing PL activity during learning blunted the ability of TRAPed PL neurons to promote remote memory retrieval. Finally, a series of whole-brain analyses identified a set of cortical regions that were densely innervated by memory-TRAPed PL neurons and preferentially activated by PL neurons TRAPed during 14-day retrieval, and whose activity co-varied with PL and correlated with memory specificity. These findings support a model in which PL ensembles underlying remote memory undergo dynamic changes during the first two weeks after learning, which manifest as increased functional recruitment of cortical targets.

The dorsal raphe (DR) constitutes a major serotonergic input to the forebrain and modulates diverse functions and brain states, including mood, anxiety, and sensory and motor functions. Most functional studies to date have treated DR serotonin neurons as a single population. Using viral-genetic methods, we found that subcortical- and cortical-projecting serotonin neurons have distinct cell-body distributions within the DR and differentially co-express a vesicular glutamate transporter. Further, amygdala- and frontal-cortex-projecting DR serotonin neurons have largely complementary whole-brain collateralization patterns, receive biased inputs from presynaptic partners, and exhibit opposite responses to aversive stimuli. Gain- and loss-of-function experiments suggest that amygdala-projecting DR serotonin neurons promote anxiety-like behavior, whereas frontal-cortex-projecting neurons promote active coping in the face of challenge. These results provide compelling evidence that the DR serotonin system contains parallel sub-systems that differ in input and output connectivity, physiological response properties, and behavioral functions.

Summary Background Developing neural networks display spontaneous and correlated rhythmic bursts of action potentials that are essential for circuit refinement. In the spinal cord, it is poorly understood how correlated activity is acquired and how its emergence relates to the formation of the spinal central pattern generator (CPG), the circuit that mediates rhythmic behaviors like walking and swimming. It is also unknown whether early, uncorrelated activity is necessary for the formation of the coordinated CPG. Results Time-lapse imaging in the intact zebrafish embryo with the genetically encoded calcium indicator GCaMP3 revealed a rapid transition from slow, sporadic activity to fast, ipsilaterally correlated, and contralaterally anticorrelated activity, characteristic of the spinal CPG. Ipsilateral correlations were acquired through the coalescence of local microcircuits. Brief optical manipulation of activity with the light-driven pump halorhodopsin revealed that the transition to correlated activity was associated with a strengthening of ipsilateral connections, likely mediated by gap junctions. Contralateral antagonism increased in strength at the same time. The transition to coordinated activity was disrupted by long-term optical inhibition of sporadic activity in motoneurons and ventral longitudinal descending interneurons and resulted in more neurons exhibiting uncoordinated activity patterns at later time points. Conclusions These findings show that the CPG in the zebrafish spinal cord emerges directly from a sporadically active network as functional connectivity strengthens between local and then more distal neurons. These results also reveal that early, sporadic activity in a subset of ventral spinal neurons is required for the integration of maturing neurons into the coordinated CPG network.