Navigating the Murine Brain: Toward Best Practices for Determining and Documenting Neuroanatomical Locations in Experimental Studies

The Locare workflow: representing neuroscience data locations as geometric objects in 3D brain atlases

Neuroscientists employ a range of methods and generate increasing amounts of data describing brain structure and function. The anatomical locations from which observations or measurements originate represent a common context for data interpretation, and a starting point for identifying data of interest. However, the multimodality and abundance of brain data pose a challenge for efforts to organize, integrate, and analyze data based on anatomical locations. While structured metadata allow faceted data queries, different types of data are not easily represented in a standardized and machine-readable way that allow comparison, analysis, and queries related to anatomical relevance. To this end, three-dimensional (3D) digital brain atlases provide frameworks in which disparate multimodal and multilevel neuroscience data can be spatially represented. We propose to represent the locations of different neuroscience data as geometric objects in 3D brain atlases. Such geometric objects can be specified in a standardized file format and stored as location metadata for use with different computational tools. We here present the Locare workflow developed for defining the anatomical location of data elements from rodent brains as geometric objects. We demonstrate how the workflow can be used to define geometric objects representing multimodal and multilevel experimental neuroscience in rat or mouse brain atlases. We further propose a collection of JSON schemas (LocareJSON) for specifying geometric objects by atlas coordinates, suitable as a starting point for co-visualization of different data in an anatomical context and for enabling spatial data queries.

Emotion in action: When emotions meet motor circuits

The brain is a remarkably complex organ responsible for a wide range of functions, including the modulation of emotional states and movement. Neuronal circuits are believed to play a crucial role in integrating sensory, cognitive, and emotional information to ultimately guide motor behavior. Over the years, numerous studies employing diverse techniques such as electrophysiology, imaging, and optogenetics have revealed a complex network of neural circuits involved in the regulation of emotional or motor processes. Emotions can exert a substantial influence on motor performance, encompassing both everyday activities and pathological conditions. The aim of this review is to explore how emotional states can shape movements by connecting the neural circuits for emotional processing to motor neural circuits. We first provide a comprehensive overview of the impact of different emotional states on motor control in humans and rodents. In line with behavioral studies, we set out to identify emotion-related structures capable of modulating motor output, behaviorally and anatomically. Neuronal circuits involved in emotional processing are extensively connected to the motor system. These circuits can drive emotional behavior, essential for survival, but can also continuously shape ongoing movement. In summary, the investigation of the intricate relationship between emotion and movement offers valuable insights into human behavior, including opportunities to enhance performance, and holds promise for improving mental and physical health. This review integrates findings from multiple scientific approaches, including anatomical tracing, circuit-based dissection, and behavioral studies, conducted in both animal and human subjects. By incorporating these different methodologies, we aim to present a comprehensive overview of the current understanding of the emotional modulation of movement in both physiological and pathological conditions.

Radioprotective potential of probiotics against gastrointestinal and neuronal toxicity: a preclinical study

PURPOSE

Radiotherapy is a critical component of cancer treatment, along with surgery and chemotherapy. Approximately, 90% of cancer patients undergoing pelvic radiotherapy show gastrointestinal (GI) toxicity, including bloody diarrhea, and gastritis, most of which are associated with gut dysbiosis. In addition to the direct effect of radiation on the brain, pelvic irradiation can alter the gut microbiome, leading to inflammation and breakdown of the gut-blood barrier. This allows toxins and bacteria to enter the bloodstream and reach the brain. Probiotics have been proven to prevent GI toxicity by producing short-chain fatty acids and exopolysaccharides beneficial for protecting mucosal integrity and oxidative stress reduction in the intestine and also shown to be beneficial in brain health. Microbiota plays a significant role in maintaining gut and brain health, so it is important to study whether bacterial supplementation will help in maintaining the gut and brain structure after radiation exposure.

METHODS

In the present study, male C57BL/6 mice were divided into control, radiation, probiotics, and probiotics + radiation groups. On the 7th day, animals in the radiation and probiotics + radiation groups received a single dose of 4 Gy to  whole-body. Posttreatment, mice were sacrificed, and the intestine and brain tissues were excised for histological analysis to assess GI and neuronal damage.

RESULTS

Radiation-induced damage to the villi height and mucosal thickness was mitigated by the probiotic treatment significantly (p < 0.01). Further, radiation-induced pyknotic cell numbers in the DG, CA2, and CA3 areas were substantially reduced with bacterial supplementation (p < 0.001). Similarly, probiotics reduced neuronal inflammation induced by radiation in the cortex, CA2, and DG region (p < 0.01). Altogether, the probiotics treatment helps mitigate radiation-induced intestinal and neuronal damage.

CONCLUSION

In conclusion, the probiotic formulation could attenuate the number of pyknotic cells in the hippocampal brain region and decrease neuroinflammation by reducing the number of microglial cells.

Scaling up cell-counting efforts in neuroscience through semi-automated methods

Quantifying how the cellular composition of brain regions vary across development, aging, sex, and disease, is crucial in experimental neuroscience, and the accuracy of different counting methods is continuously debated. Due to the tedious nature of most counting procedures, studies are often restricted to one or a few brain regions. Recently, there have been considerable methodological advances in combining semi-automated feature extraction with brain atlases for cell quantification. Such methods hold great promise for scaling up cell-counting efforts. However, little focus has been paid to how these methods should be implemented and reported to support reproducibility. Here, we provide an overview of practices for conducting and reporting cell counting in mouse and rat brains, showing that critical details for interpretation are typically lacking. We go on to discuss how novel methods may increase efficiency and reproducibility of cell counting studies. Lastly, we provide practical recommendations for researchers planning cell counting.

AtOM, an ontology model to standardize use of brain atlases in tools, workflows, and data infrastructures

Brain atlases are important reference resources for accurate anatomical description of neuroscience data. Open access, three-dimensional atlases serve as spatial frameworks for integrating experimental data and defining regions-of-interest in analytic workflows. However, naming conventions, parcellation criteria, area definitions, and underlying mapping methodologies differ considerably between atlases and across atlas versions. This lack of standardized description impedes use of atlases in analytic tools and registration of data to different atlases. To establish a machine-readable standard for representing brain atlases, we identified four fundamental atlas elements, defined their relations, and created an ontology model. Here we present our Atlas Ontology Model (AtOM) and exemplify its use by applying it to mouse, rat, and human brain atlases. We discuss how AtOM can facilitate atlas interoperability and data integration, thereby increasing compliance with the FAIR guiding principles. AtOM provides a standardized framework for communication and use of brain atlases to create, use, and refer to specific atlas elements and versions. We argue that AtOM will accelerate analysis, sharing, and reuse of neuroscience data.

A Timm-Nissl multiplane microscopic atlas of rat brain zincergic terminal fields and metal-containing glia

The ability of Timm's sulphide silver method to stain zincergic terminal fields has made it a useful neuromorphological marker. Beyond its roles in zinc-signalling and neuromodulation, zinc is involved in the pathophysiology of ischemic stroke, epilepsy, degenerative diseases and neuropsychiatric conditions. In addition to visualising zincergic terminal fields, the method also labels transition metals in neuronal perikarya and glial cells. To provide a benchmark reference for planning and interpretation of experimental investigations of zinc-related phenomena in rat brains, we have established a comprehensive repository of serial microscopic images from a historical collection of coronally, horizontally and sagittally oriented rat brain sections stained with Timm's method. Adjacent Nissl-stained sections showing cytoarchitecture, and customised atlas overlays from a three-dimensional rat brain reference atlas registered to each section image are included for spatial reference and guiding identification of anatomical boundaries. The Timm-Nissl atlas, available from EBRAINS, enables experimental researchers to navigate normal rat brain material in three planes and investigate the spatial distribution and density of zincergic terminal fields across the entire brain.

A neuroscientist's guide to using murine brain atlases for efficient analysis and transparent reporting

Brain atlases are widely used in neuroscience as resources for conducting experimental studies, and for integrating, analyzing, and reporting data from animal models. A variety of atlases are available, and it may be challenging to find the optimal atlas for a given purpose and to perform efficient atlas-based data analyses. Comparing findings reported using different atlases is also not trivial, and represents a barrier to reproducible science. With this perspective article, we provide a guide to how mouse and rat brain atlases can be used for analyzing and reporting data in accordance with the FAIR principles that advocate for data to be findable, accessible, interoperable, and re-usable. We first introduce how atlases can be interpreted and used for navigating to brain locations, before discussing how they can be used for different analytic purposes, including spatial registration and data visualization. We provide guidance on how neuroscientists can compare data mapped to different atlases and ensure transparent reporting of findings. Finally, we summarize key considerations when choosing an atlas and give an outlook on the relevance of increased uptake of atlas-based tools and workflows for FAIR data sharing.

Atlas-based data integration for mapping the connections and architecture of the brain

Detailed knowledge about the neural connections among regions of the brain is key for advancing our understanding of normal brain function and changes that occur with aging and disease. Researchers use a range of experimental techniques to map connections at different levels of granularity in rodent animal models, but the results are often challenging to compare and integrate. Three-dimensional reference atlases of the brain provide new opportunities for cumulating, integrating, and reinterpreting research findings across studies. Here, we review approaches for integrating data describing neural connections and other modalities in rodent brain atlases and discuss how atlas-based workflows can facilitate brainwide analyses of neural network organization in relation to other facets of neuroarchitecture.

Pursuit of precision medicine: Systems biology approaches in Alzheimer's disease mouse models

Alzheimer's disease (AD) is a complex disease that is mediated by numerous factors and manifests in various forms. A systems biology approach to studying AD involves analyses of various body systems, biological scales, environmental elements, and clinical outcomes to understand the genotype to phenotype relationship that potentially drives AD development. Currently, there are many research investigations probing how modifiable and nonmodifiable factors impact AD symptom presentation. This review specifically focuses on how imaging modalities can be integrated into systems biology approaches using model mouse populations to link brain level functional and structural changes to disease onset and progression. Combining imaging and omics data promotes the classification of AD into subtypes and paves the way for precision medicine solutions to prevent and treat AD.

A graph-based approach for representing, integrating and analysing neuroscience data: the case of the murine basal ganglia

Purpose

Neuroscience data are spread across a variety of sources, typically provisioned through ad-hoc and non-standard approaches and formats and often have no connection to the related data sources. These make it difficult for researchers to understand, integrate and reuse brain-related data. The aim of this study is to show that a graph-based approach offers an effective mean for representing, analysing and accessing brain-related data, which is highly interconnected, evolving over time and often needed in combination.

Design/methodology/approach

The authors present an approach for organising brain-related data in a graph model. The approach is exemplified in the case of a unique data set of quantitative neuroanatomical data about the murine basal ganglia––a group of nuclei in the brain essential for processing information related to movement. Specifically, the murine basal ganglia data set is modelled as a graph, integrated with relevant data from third-party repositories, published through a Web-based user interface and API, analysed from exploratory and confirmatory perspectives using popular graph algorithms to extract new insights.

Findings

The evaluation of the graph model and the results of the graph data analysis and usability study of the user interface suggest that graph-based data management in the neuroscience domain is a promising approach, since it enables integration of various disparate data sources and improves understanding and usability of data.

Originality/value

The study provides a practical and generic approach for representing, integrating, analysing and provisioning brain-related data and a set of software tools to support the proposed approach.

Densities and numbers of calbindin and parvalbumin positive neurons across the rat and mouse brain

The calcium-binding proteins parvalbumin and calbindin are expressed in neuronal populations regulating brain networks involved in spatial navigation, memory processes, and social interactions. Information about the numbers of these neurons across brain regions is required to understand their functional roles but is scarcely available. Employing semi-automated image analysis, we performed brain-wide analysis of immunohistochemically stained parvalbumin and calbindin sections and show that these neurons distribute in complementary patterns across the mouse brain. Parvalbumin neurons dominate in areas related to sensorimotor processing and navigation, whereas calbindin neurons prevail in regions reflecting behavioral states. We also find that parvalbumin neurons distribute according to similar principles in the hippocampal region of the rat and mouse brain. We validated our results against manual counts and evaluated variability of results among researchers. Comparison of our results to previous reports showed that neuron numbers vary, whereas patterns of relative densities and numbers are consistent.

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Brain-wide, semi-automatic quantification of parvalbumin and calbindin neurons

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Largely complementary distribution of calbindin and parvalbumin neurons in mice

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Comparison with several previous studies shows variable numbers but similar trends

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Similar distribution of parvalbumin neurons in the rat and mouse hippocampal region

Enhanced and unified anatomical labeling for a common mouse brain atlas

Anatomical atlases in standard coordinates are necessary for the interpretation and integration of research findings in a common spatial context. However, the two most-used mouse brain atlases, the Franklin-Paxinos (FP) and the common coordinate framework (CCF) from the Allen Institute for Brain Science, have accumulated inconsistencies in anatomical delineations and nomenclature, creating confusion among neuroscientists. To overcome these issues, we adopt here the FP labels into the CCF to merge the labels in the single atlas framework. We use cell type-specific transgenic mice and an MRI atlas to adjust and further segment our labels. Moreover, detailed segmentations are added to the dorsal striatum using cortico-striatal connectivity data. Lastly, we digitize our anatomical labels based on the Allen ontology, create a web-interface for visualization, and provide tools for comprehensive comparisons between the CCF and FP labels. Our open-source labels signify a key step towards a unified mouse brain atlas.

Neurons in the Intermediate Reticular Nucleus Coordinate Postinspiratory Activity, Swallowing, and Respiratory-Sympathetic Coupling in the Rat

Breathing results from sequential recruitment of muscles in the expiratory, inspiratory, and postinspiratory (post-I) phases of the respiratory cycle. Here we investigate whether neurons in the medullary intermediate reticular nucleus (IRt) are components of a central pattern generator (CPG) that generates post-I activity in laryngeal adductors and vasomotor sympathetic nerves and interacts with other members of the central respiratory network to terminate inspiration. We first identified the region of the (male) rat IRt that contains the highest density of lightly cholinergic neurons, many of which are glutamatergic, which aligns well with the putative postinspiratory complex in the mouse (Anderson et al., 2016). Acute bilateral inhibition of this region reduced the amplitudes of post-I vagal and sympathetic nerve activities. However, although associated with reduced expiratory duration and increased respiratory frequency, IRt inhibition did not affect inspiratory duration or abolish the recruitment of post-I activity during acute hypoxemia as predicted. Rather than representing an independent CPG for post-I activity, we hypothesized that IRt neurons may instead function as a relay that distributes post-I activity generated elsewhere, and wondered whether they could be a site of integration for para-respiratory CPGs that drive the same outputs. Consistent with this idea, IRt inhibition blocked rhythmic motor and autonomic components of fictive swallow but not swallow-related apnea. Our data support a role for IRt neurons in the transmission of post-I and swallowing activity to motor and sympathetic outputs, but suggest that other mechanisms also contribute to the generation of post-I activity.SIGNIFICANCE STATEMENT Interactions between multiple coupled oscillators underlie a three-part respiratory cycle composed from inspiratory, postinspiratory (post-I), and late-expiratory phases. Central post-I activity terminates inspiration and activates laryngeal motoneurons. We investigate whether neurons in the intermediate reticular nucleus (IRt) form the central pattern generator (CPG) responsible for post-I activity. We confirm that IRt activity contributes to post-I motor and autonomic outputs, and find that IRt neurons are necessary for activation of the same outputs during swallow, but that they are not required for termination of inspiration or recruitment of post-I activity during hypoxemia. We conclude that this population may not represent a distinct CPG, but instead may function as a premotor relay that integrates activity generated by diverse respiratory and nonrespiratory CPGs.