ArticleScientific data2019
Classification of GABAergic interneurons by leading neuroscientists.
Article in Scientific data, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Postnatal development of vasoactive intestinal polypeptide-expressing GABAergic interneurons in mouse somatosensory cortex.Acta physiologica (Oxford, England) · 2025Article
- Bidirectional modulation of somatostatin-expressing interneurons in the basolateral amygdala reduces neuropathic pain perception in mice.Frontiers in pain research (Lausanne, Switzerland) · 2025Article
- Thyroid Hormone Transporters MCT8 and OATP1C1 Are Expressed in Pyramidal Neurons and Interneurons in the Adult Motor Cortex of Human and Macaque Brain.International journal of molecular sciences · 2023Article
- microRNA-dependent regulation of gene expression in GABAergic interneurons.Frontiers in cellular neuroscience · 2023Review
- Multi-scale light microscopy/electron microscopy neuronal imaging from brain to synapse with a tissue clearing method, ScaiScience · 2022Article
- The Role of Inhibitory Interneurons in Circuit Assembly and Refinement Across Sensory Cortices.Frontiers in neural circuits · 2022Review
- Using 2D and 3D pluripotent stem cell models to study neurotropic viruses.Frontiers in virology (Lausanne, Switzerland) · 2022Article
- Optimal responsiveness and information flow in networks of heterogeneous neurons.Scientific reports · 2021Article
- Deep Learning-Based Classification of GAD67-Positive Neurons Without the Immunosignal.Frontiers in neuroanatomy · 2021Article
- Comparing the Electrophysiology and Morphology of Human and Mouse Layer 2/3 Pyramidal Neurons With Bayesian Networks.Frontiers in neuroinformatics · 2021Article
- Classification of GABAergic interneurons by leading neuroscientists.Scientific data · 2019Article
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Authors and funding
5 authors.
Funding
Abstract
There is currently no unique catalog of cortical GABAergic interneuron types. In 2013, we asked 48 leading neuroscientists to classify 320 interneurons by inspecting images of their morphology. That study was the first to quantify the degree of agreement among neuroscientists in morphology-based interneuron classification, showing high agreement for the chandelier and Martinotti types, yet low agreement for most of the remaining types considered. Here we present the dataset containing the classification choices by the neuroscientists according to interneuron type as well as to five prominent morphological features. These data can be used as crisp or soft training labels for learning supervised machine learning interneuron classifiers, while further analyses can try to pinpoint anatomical characteristics that make an interneuron especially difficult or especially easy to classify.
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