ReviewBrain research reviews2009
Comparing histological data from different brains: sources of error and strategies for minimizing them.
Review in Brain research reviews, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
31 citing papers in PubMed.
- Cancer Neuroscience: Linking Neuronal Plasticity with Brain Tumor Growth and Resistance.Biology · 2026Review
- Chemoarchitectural studies of the rat hypothalamus and zona incerta.bioRxiv : the preprint server for biology · 2025Article
- Article
- Elaborating the connections of a closed-loop forebrain circuit in the rat: Circumscribed evidence for novel topography within a cortico-striato-pallidal triple descending projection, with thalamic feedback, to the anterior lateral hypothalamic area.bioRxiv : the preprint server for biology · 2025Article
- Topographic organization of bidirectional connections between the cingulate region (infralimbic area and anterior cingulate area, dorsal part) and the interbrain (diencephalon) of the adult male rat.bioRxiv : the preprint server for biology · 2024Article
- Comparison of basal ganglia regions across murine brain atlases using metadata models and the Waxholm Space.Scientific data · 2024Article
- Review
- Glycemic Challenge Is Associated with the Rapid Cellular Activation of the Locus Ceruleus and Nucleus of Solitary Tract: Circumscribed Spatial Analysis of Phosphorylated MAP Kinase Immunoreactivity.Journal of clinical medicine · 2023Article
- Article
- A neuroscientist's guide to using murine brain atlases for efficient analysis and transparent reporting.Frontiers in neuroinformatics · 2023Article
- Potential of the zebrafish (Danio rerio) embryo test to discriminate between chemicals of similar molecular structure-a study with valproic acid and 14 of its analogues.Archives of toxicology · 2022Article
- Constructing the rodent stereotaxic brain atlas: a survey.Science China. Life sciences · 2022Review
- Article
- Article
- Use of computational fluid dynamics for 3D fiber tract visualization on human high-thickness histological slices: histological mesh tractography.Brain structure & function · 2021Article
- A qualitative solution with quantitative potential for the mouse hippocampal cortex flatmap problem.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- QUINT: Workflow for Quantification and Spatial Analysis of Features in Histological Images From Rodent Brain.Frontiers in neuroinformatics · 2019Article
- Cognitive and Non-Cognitive Outcomes Associated with Student Engagement in a Novel Brain Chemoarchitecture Mapping Course-Based Undergraduate Research Experience.Journal of undergraduate neuroscience education : JUNE : a publication of FUN, Faculty for Undergraduate Neuroscience · 2019Article
- Brain maps 4.0-Structure of the rat brain: An open access atlas with global nervous system nomenclature ontology and flatmaps.The Journal of comparative neurology · 2018Article
- High thickness histological sections as alternative to study the three-dimensional microscopic human sub-cortical neuroanatomy.Brain structure & function · 2018Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
The recent development of brain atlases with computer graphics templates, and of huge databases of neurohistochemical data on the internet, has forced a systematic re-examination of errors associated with comparing histological features between adjacent sections of the same brain, between brains treated in the same way, and between brains from groups treated in different ways. The long-term goal is to compare as accurately as possible a broad array of data from experimental brains within the framework of reference atlases. Main sources of error, each of which ideally should be measured and minimized, include intrinsic biological variation, linear and nonlinear distortion of histological sections, plane of section differences between each brain, section alignment problems, and sampling errors. These variables are discussed, along with approaches to error estimation and minimization in terms of a specific example-the distribution of neuroendocrine neurons in the rat paraventricular nucleus. Based on the strategy developed here, the main conclusion is that the best long-term solution is a high-resolution 3D computer graphics model of the brain that can be sliced in any plane and used as the framework for quantitative neuroanatomy, databases, knowledge management systems, and structure-function modeling. However, any approach to the automatic annotation of neuroanatomical data-relating its spatial distribution to a reference atlas-should deal systematically with these sources of error, which reduce localization reliability.
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Registered trials
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