bioRxiv Science⌕ Search

bioRxiv · 10.1101/2024.10.02.616213

Chemoarchitectural studies of the rat hypothalamus and zona incerta.Chemopleth 1.0, a downloadable interactive Brain Maps spatial database of five co-visualizable neurochemical systems, with novel feature- and grid-based mapping tools

Abstract

The hypothalamus and zona incerta of the brown rat (Rattus norvegicus), a model organism important for translational neuroscience research, contain diverse neuronal populations essential for survival, but how these populations are structurally organized as systems remains elusive. With the advent of novel gene-editing technologies and artificial intelligence, there is an apparent research need for high-spatial-resolution maps of rat hypothalamic neurochemical cell types to aid in their gene-directed targeting, to validate their expression in transgenic lines, or to supply precious ground-truth training data for machine learning algorithms. Here, we present Chemopleth 1.0 [available at: https://doi.org/10.5281/zenodo.15788189], a chemoarchitecture database for the rat hypothalamus (HY) and zona incerta (ZI), which features downloadable interactive maps featuring the census distributions of five immunoreactive neurochemical systems: (1) vasopressin (as detected from its gene co-product, copeptin); (2) neuronal nitric oxide synthase (EC 1.14.13.39); (3) hypocretin 1/orexin A; (4) melanin-concentrating hormone; and (5) alpha-melanocyte-stimulating hormone. These maps are formatted for the widely used Brain Maps 4.0 (BM4.0) open-access rat brain atlas (RRID:SCR_017314). Importantly, this dataset retains atlas stereotaxic coordinates that facilitate the precise targeting of the cell bodies and/or axonal fibers of these neurochemical systems, thereby potentially serving to streamline delivery of viral vectors for gene-directed manipulations. The maps are presented together with novel open-access tools to visualize the data, including a new workflow to quantify cell positions and fiber densities for BM4.0. The workflow produces "heat maps" of neurochemical distributions from multiple subjects: 1) isopleth maps that represent consensus distributions independent of underlying atlas boundary conditions, and 2) choropleth maps that provide distribution differences based on cytoarchitectonic boundaries. The database files, generated using the Adobe(R) Illustrator(R) vector graphics environment, can also be opened using the free vector graphics editor, Inkscape. We also introduce a refined grid-based coordinate system for this dataset, register it with previously published spatial data for the HY and ZI, and introduce novel grid-based annotation of experimental observations. This database provides critical spatial targeting information for these neurochemical systems unavailable from mRNA-based maps and allows readers to place their own datasets in register with them. It also provides a space for the continued buildout of a community-driven atlas-based spatial model of rat hypothalamic chemoarchitecture, allowing experimental observations from multiple laboratories to be registered to a common spatial framework.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Navarro, V. I., Arnal, A., Peru, E., Balivada, S., Toccoli, A. R., Sotelo, D., Fuentes, O., Khan, A. M.. 2024-10-03. Chemoarchitectural studies of the rat hypothalamus and zona incerta.Chemopleth 1.0, a downloadable interactive Brain Maps spatial database of five co-visualizable neurochemical systems, with novel feature- and grid-based mapping tools. https://doi.org/10.1101/2024.10.02.616213

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Same Movements, Different Skills: How Context Shapes Learning in Humans and Neural Networks

What determines whether experiences are integrated into shared representations or split? Motor skill learning offers a revealing test: when two tasks require an identical sequence of movements, both intuition and theory suggest that practice in one should generalize to the other. Yet we find that changing context can make identical movements different skills. In simple recurrent networks trained on the same sequence across contexts, splitting was greatest when strong contextual inputs coincided with a high initial weight scale; neither alone sufficed. Greater representational separation coincided with separate context-specific learning curves. Humans practicing the same finger sequence while alternating between two performance-irrelevant contexts likewise exhibited context-specific curves, rather than the single continuous trajectory observed when practicing in a single context. State-space modeling favored split learning states in humans and very weakly coupled states in the most context-dependent networks. These findings have broader implications for understanding how learning generalizes across contexts.

neuroscience↗

Postpartum resource scarcity reshapes maternal care, offspring prioritization, and the steroid-sensitive medial preoptic area

Parental care requires balancing offspring needs with environmental constraints, yet how resource scarcity alters the organization of maternal responses remains poorly understood. Here, we examined maternal behavior, offspring prioritization, and steroid receptor-associated extracellular matrix organization in postpartum rats exposed to limited bedding and nesting (LBN) or control conditions with ample nesting materials. LBN increased pup-directed and reduced self-directed behaviors but also increased behavioral entropy, a measure of behavioral fragmentation, indicating less predictable caregiving sequences. LBN dams preferentially retrieved male pups first, whereas control dams preferentially retrieved females first. LBN also increased the proportion of pup-investigation time directed toward males compared with controls. In offspring on postnatal day 10, corticosterone was elevated in female but not male LBN pups, a pattern that paralleled the maternal male bias. To identify associated neurobiological changes, we assessed steroid receptors and extracellular matrix organization in the medial preoptic area (mPOA), a key region for maternal behavior. LBN increased numbers of estrogen receptor (ER)- and androgen receptor (AR)-immunoreactive cells, reduced perineuronal net (PNN) abundance, and decreased receptor-positive cell enwrapment. Because PNNs constrain structural plasticity, these findings suggest that the postpartum environment alters the organization of steroid receptor-associated extracellular matrix, potentially modulating experience-dependent plasticity in neurosteroid-sensitive circuits. In sum, LBN increases the levels of maternal engagement while reshaping its temporal organization and allocation, accompanied by selective remodeling of steroid-sensitive preoptic architecture. Therefore, maternal adaptation to adversity may be better understood as changes in caregiving allocation strategies rather than a simple gain or loss of maternal care.

neuroscience↗

The Computational Grammar of Human Behaviour in a Biological Environment

Human behaviour unfolds as an extended stream of spontaneous actions shaped by environmental demands and the agent's goals. The organisation of these actions, situated between setting abstract goals and concrete movement execution, remains poorly characterised. Here, we introduce DynaClade, an unsupervised temporal action segmentation algorithm for human full-body motion capture data, and apply it to freely moving participants navigating ecologically realistic risky foraging environments in virtual reality. DynaClade identifies discrete actions whose kinematic characteristics and spatial distributions correspond to environmental affordances, supporting the validity of the approach. Among these actions, we discovered a hitherto undescribed movement pattern defined by increased body sway without locomotion. Action sequences were highly non-random and showed clear history dependence beyond first-order Markov structure, most of which was explained by a second-order prediction. This higher-order structure was well captured in a hidden Markov model, in which some of the observed actions were associated with more than one latent state. Each of these latent states corresponded to the same action in a distinct action context. These findings suggest that spontaneous human actions are predominantly selected based on the current action and context, rather than following pre-planned or habitually assembled sequences.

neuroscience↗