ArticleFrontiers in neural circuits2013
Beyond the frontiers of neuronal types.
Article in Frontiers in neural circuits, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 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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Who cites it
32 citing papers in PubMed.
- Hippocampal GABAergic interneurons and memory.Neuron · 2023Review
- Introducing the Software CASE (Cluster and Analyze Sound Events) by Comparing Different Clustering Methods and Audio Transformation Techniques Using Animal Vocalizations.Animals : an open access journal from MDPI · 2022Article
- Cerebellar connectivity maps embody individual adaptive behavior in mice.Nature communications · 2022Article
- Cell types as species: Exploring a metaphor.Frontiers in plant science · 2022Review
- How Many Gammas? Redefining Hippocampal Theta-Gamma Dynamic During Spatial Learning.Frontiers in behavioral neuroscience · 2022Review
- Excitatory cholecystokinin neurons of the midbrain integrate diverse temporal responses and drive auditory thalamic subdomains.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Molecular expression profiles of morphologically defined hippocampal neuron types: Empirical evidence and relational inferences.Hippocampus · 2020Article
- Dynamic core-periphery structure of information sharing networks in entorhinal cortex and hippocampus.Network neuroscience (Cambridge, Mass.) · 2020Article
- Synaptic Plasticity in Cortical Inhibitory Neurons: What Mechanisms May Help to Balance Synaptic Weight Changes?Frontiers in cellular neuroscience · 2020Review
- Alternative classifications of neurons based on physiological properties and synaptic responses, a computational study.Scientific reports · 2019Article
- Distinct Heterosynaptic Plasticity in Fast Spiking and Non-Fast-Spiking Inhibitory Neurons in Rat Visual Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2019Article
- Diversity and Function of Somatostatin-Expressing Interneurons in the Cerebral Cortex.International journal of molecular sciences · 2019Review
- Single Cell Multiplex Reverse Transcription Polymerase Chain Reaction After Patch-clamp.Journal of visualized experiments : JoVE · 2018Article
- Morphological and Functional Characterization of Non-fast-Spiking GABAergic Interneurons in Layer 4 Microcircuitry of Rat Barrel Cortex.Cerebral cortex (New York, N.Y. : 1991) · 2018Article
- Electrophysiological Profiling of Neocortical Neural Subtypes: A Semi-Supervised Method Applied toFrontiers in neuroscience · 2018Article
- Mining Big Neuron Morphological Data.Computational intelligence and neuroscience · 2018Review
- Dissociation between sustained single-neuron spiking and transient β-LFP oscillations in primate motor cortex.Journal of neurophysiology · 2017Article
- Name-calling in the hippocampus (and beyond): coming to terms with neuron types and properties.Brain informatics · 2017Article
- Does Epileptiform Activity Represent a Failure of Neuromodulation to Control Central Pattern Generator-Like Neocortical Behavior?Frontiers in neural circuits · 2017Article
- Gene-environment interactions in cortical interneuron development and dysfunction: A review of preclinical studies.Neurotoxicology · 2017Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cortical neurons and, particularly, inhibitory interneurons display a large diversity of morphological, synaptic, electrophysiological, and molecular properties, as well as diverse embryonic origins. Various authors have proposed alternative classification schemes that rely on the concomitant observation of several multimodal features. However, a broad variability is generally observed even among cells that are grouped into a same class. Furthermore, the attribution of specific neurons to a single defined class is often difficult, because individual properties vary in a highly graded fashion, suggestive of continua of features between types. Going beyond the description of representative traits of distinct classes, we focus here on the analysis of atypical cells. We introduce a novel paradigm for neuronal type classification, assuming explicitly the existence of a structured continuum of diversity. Our approach, grounded on the theory of fuzzy sets, identifies a small optimal number of model archetypes. At the same time, it quantifies the degree of similarity between these archetypes and each considered neuron. This allows highlighting archetypal cells, which bear a clear similarity to a single model archetype, and edge cells, which manifest a convergence of traits from multiple archetypes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.