Cell-type-specific population dynamics of diverse reward computations.

Computational analysis of cellular activity has developed largely independently of modern transcriptomic cell typology, but integrating these approaches may be essential for full insight into cellular-level mechanisms underlying brain function and dysfunction. Applying this approach to the habenula (a structure with diverse, intermingled molecular, anatomical, and computational features), we identified encoding of reward-predictive cues and reward outcomes in distinct genetically defined neural populations, including TH+ cells and Tac1+ cells. Data from genetically targeted recordings were used to train an optimized nonlinear dynamical systems model and revealed activity dynamics consistent with a line attractor. High-density, cell-type-specific electrophysiological recordings and optogenetic perturbation provided supporting evidence for this model. Reverse-engineering predicted how Tac1+ cells might integrate reward history, which was complemented by in vivo experimentation. This integrated approach describes a process by which data-driven computational models of population activity can generate and frame actionable hypotheses for cell-type-specific investigation in biological systems.

Dominant Malignant Clones Leverage Lineage Restricted Epigenomic Programs to Drive Ependymoma Development.

ZFTA-RELA is the most recurrent genetic alteration seen in pediatric supratentorial ependymoma (EPN) and is sufficient to initiate tumors in mice. Despite ZFTA-RELA's potent oncogenic potential, ZFTA-RELA gene fusions are observed exclusively in childhood EPN, with tumors located distinctly in the supratentorial region of the central nervous system (CNS). We hypothesized that specific chromatin modules accessible during brain development would render distinct cell lineage programs at direct risk of transformation by ZFTA-RELA. To this end, we performed combined single cell ATAC and RNA-seq analysis (scMultiome) of the developing mouse forebrain as compared to ZR-driven mouse and human EPN. We demonstrate that specific developmental lineage programs present in radial glial cells and regulated by Plagl family transcription factors are at risk of neoplastic transformation. Binding of this chromatin network by ZFTA-RELA or other PLAGL family motif targeting fusion proteins leads to persistent chromatin accessibility at oncogenic loci and oncogene expression. Cross-species analysis of mouse and human EPN reveals significant cell type heterogeneity mirroring incomplete neurogenic and gliogenic differentiation, with a small percentage of cycling intermediate progenitor-like cells that establish a putative tumor cell hierarchy. In vivo lineage tracing studies reveal single neoplastic clones that aggressively dominate tumor growth and establish the entire EPN cellular hierarchy. These findings unravel developmental epigenomic states critical for fusion oncoprotein driven transformation and elucidate how these states continue to shape tumor progression. HIGHLIGHTS: 1. Specific chromatin modules accessible during brain development render distinct cell lineage programs at risk of transformation by pediatric fusion oncoproteins.2. Cross-species single cell ATAC and RNA (scMultiome) of mouse and human ependymoma (EPN) reveals diverse patterns of lineage differentiation programs that restrain oncogenic transformation.3. Early intermediate progenitor-like EPN cells establish a tumor cell hierarchy that mirrors neural differentiation programs.4. ZFTA-RELA transformation is compatible with distinct developmental epigenetic states requiring precise 'goldilocks' levels of fusion oncoprotein expression.5. Dominant tumor clones establish the entire EPN cellular hierarchy that reflects normal gliogenic and neurogenic differentiation programs.

Sniff-synchronized, gradient-guided olfactory search by freely moving mice.

For many organisms, searching for relevant targets such as food or mates entails active, strategic sampling of the environment. Finding odorous targets may be the most ancient search problem that motile organisms evolved to solve. While chemosensory navigation has been well characterized in microorganisms and invertebrates, spatial olfaction in vertebrates is poorly understood. We have established an olfactory search assay in which freely moving mice navigate noisy concentration gradients of airborne odor. Mice solve this task using concentration gradient cues and do not require stereo olfaction for performance. During task performance, respiration and nose movement are synchronized with tens of milliseconds precision. This synchrony is present during trials and largely absent during inter-trial intervals, suggesting that sniff-synchronized nose movement is a strategic behavioral state rather than simply a constant accompaniment to fast breathing. To reveal the spatiotemporal structure of these active sensing movements, we used machine learning methods to parse motion trajectories into elementary movement motifs. Motifs fall into two clusters, which correspond to investigation and approach states. Investigation motifs lock precisely to sniffing, such that the individual motifs preferentially occur at specific phases of the sniff cycle. The allocentric structure of investigation and approach indicates an advantage to sampling both sides of the sharpest part of the odor gradient, consistent with a serial-sniff strategy for gradient sensing. This work clarifies sensorimotor strategies for mouse olfactory search and guides ongoing work into the underlying neural mechanisms.