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Related Experiment Video

Updated: Jul 2, 2025

Large-scale Three-dimensional Imaging of Cellular Organization in the Mouse Neocortex

Large-scale Three-dimensional Imaging of Cellular Organization in the Mouse Neocortex

Published on: September 5, 2018

Multimodal cortical neuronal cell type classification.

Xiaoyi Mao¹, Jochen F Staiger²

¹Institute for Neuroanatomy, University Medical Center Göttingen, Georg-August-University, Kreuzbergring 36, 37075, Göttingen, Germany.

Pflugers Archiv : European Journal of Physiology

|February 20, 2024

Summary

Neuroscientists classify cortical neurons using single-cell transcriptomics, identifying distinct excitatory and inhibitory cell types. Future research will link these transcriptomic types to multimodal features for functional understanding.

Keywords:

Cerebral cortex Excitatory neurons Inhibitory neurons Multimodal classification Neuronal cell types Transcriptomics

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Last Updated: Jul 2, 2025

Large-scale Three-dimensional Imaging of Cellular Organization in the Mouse Neocortex

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Published on: September 5, 2018

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Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

Area of Science:

Neuroscience
Genomics
Cell Biology

Background:

Cortical neurons traditionally classified by morphology, electrophysiology, and neurochemistry.
Distinction between excitatory (glutamatergic) and inhibitory (GABAergic) neurons with differing projection patterns.
Layer-dependent schemes established for principal and inhibitory cortical neurons.

Purpose of the Study:

To integrate recent insights from single-cell transcriptomics for cortical cell type classification.
To identify reliably identifiable cortical cell types across established differences.
To establish a foundation for linking transcriptomic cell types to multimodal features and functions.

Main Methods:

Single-cell transcriptomics as the primary method for cell type classification.
Analysis of transcriptomic data to identify distinct excitatory and inhibitory neuronal subpopulations.
Comparison of transcriptomic data with existing morphological, electrophysiological, and neurochemical classifications.

Main Results:

Identification of approximately 56 transcriptomic cell types (t-types) for excitatory neurons, including intratelencephalic (IT), extratelencephalic (ET), and corticothalamic (CT) categories.
Subdivision of inhibitory neurons into approximately 60 t-types, including parvalbumin (PV), somatostatin (SST), vasoactive intestinal polypeptide (VIP), and Lamp5/Sncg populations.
Confirmation of distinct transcriptomic profiles for cortical cell types, despite known layer- and area-dependent variations.

Conclusions:

Single-cell transcriptomics provides a powerful tool for refining cortical cell type classification.
A significant number of transcriptomic cell types have been identified within both excitatory and inhibitory neuronal populations.
Future research is needed to validate these transcriptomic types by correlating them with multimodal features (physiology, morphology, connectivity, function).