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Open AccessJournal ArticleDOI

Classification of electrophysiological and morphological neuron types in the mouse visual cortex.

TLDR
A single-cell characterization pipeline is established using standardized patch-clamp recordings in brain slices and biocytin-based neuronal reconstructions to establish a morpho-electrical taxonomy of cell types for the mouse visual cortex via unsupervised clustering analysis of multiple quantitative features.
Abstract
Understanding the diversity of cell types in the brain has been an enduring challenge and requires detailed characterization of individual neurons in multiple dimensions. To systematically profile morpho-electric properties of mammalian neurons, we established a single-cell characterization pipeline using standardized patch-clamp recordings in brain slices and biocytin-based neuronal reconstructions. We built a publicly accessible online database, the Allen Cell Types Database, to display these datasets. Intrinsic physiological properties were measured from 1,938 neurons from the adult laboratory mouse visual cortex, morphological properties were measured from 461 reconstructed neurons, and 452 neurons had both measurements available. Quantitative features were used to classify neurons into distinct types using unsupervised methods. We established a taxonomy of morphologically and electrophysiologically defined cell types for this region of the cortex, with 17 electrophysiological types, 38 morphological types and 46 morpho-electric types. There was good correspondence with previously defined transcriptomic cell types and subclasses using the same transgenic mouse lines.

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Citations
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Journal ArticleDOI

Integrated Morphoelectric and Transcriptomic Classification of Cortical GABAergic Cells.

TL;DR: 28 met- types are defined that have congruent morphological, electrophysiological, and transcriptomic properties and robust mutual predictability, and layer-specific axon innervation pattern is identified as a defining feature distinguishing different met-types.
Journal ArticleDOI

Comparative cellular analysis of motor cortex in human, marmoset and mouse

Trygve E. Bakken, +121 more
- 01 Oct 2021 - 
TL;DR: The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals using high-throughput transcriptomic and epigenomic profiling of more than 450k single nuclei in humans, marmoset monkeys and mice as mentioned in this paper.
Journal ArticleDOI

Development and Arealization of the Cerebral Cortex.

TL;DR: This work proposes an integrated model of serial homology whereby intrinsic genetic programs and local factors establish early transcriptomic differences between excitatory neurons destined to give rise to broad "proto-regions," and activity-dependent mechanisms lead to progressive refinement and formation of sharp boundaries between functional areas.
Journal ArticleDOI

The diversity of GABAergic neurons and neural communication elements

TL;DR: It is posited that cardinal interneuron types can be defined by their synaptic communication properties, which are encoded in key transcriptional signatures, and a framework in which cell types are transcriptionally defined communication elements with characteristic input–output properties is proposed.
References
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Journal Article

Visualizing Data using t-SNE

TL;DR: A new technique called t-SNE that visualizes high-dimensional data by giving each datapoint a location in a two or three-dimensional map, a variation of Stochastic Neighbor Embedding that is much easier to optimize, and produces significantly better visualizations by reducing the tendency to crowd points together in the center of the map.
Book

Classification and regression trees

Leo Breiman
TL;DR: The methodology used to construct tree structured rules is the focus of a monograph as mentioned in this paper, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.
BookDOI

An introduction to statistical learning

TL;DR: An introduction to statistical learning provides an accessible overview of the essential toolset for making sense of the vast and complex data sets that have emerged in science, industry, and other sectors in the past twenty years.
Journal ArticleDOI

A robust and high-throughput Cre reporting and characterization system for the whole mouse brain

TL;DR: A set of Cre reporter mice with strong, ubiquitous expression of fluorescent proteins of different spectra is generated and enables direct visualization of fine dendritic structures and axonal projections of the labeled neurons, which is useful in mapping neuronal circuitry, imaging and tracking specific cell populations in vivo.
Journal ArticleDOI

Sparse Principal Component Analysis

TL;DR: This work introduces a new method called sparse principal component analysis (SPCA) using the lasso (elastic net) to produce modified principal components with sparse loadings and shows that PCA can be formulated as a regression-type optimization problem.
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