CellExplorer: A framework for visualizing and characterizing single neurons
| Autor: | Joshua H. Siegel, Sara Mahallati, Peter C. Peterson, György Buzsáki, Nicholas A. Steinmetz |
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| Rok vydání: | 2021 |
| Předmět: |
Neurons
Cortical circuits Computer science business.industry Process (engineering) General Neuroscience Process (computing) Pattern recognition Data structure computer.software_genre Neuron types Set (abstract data type) Afferent Artificial intelligence Data mining business MATLAB computer Graphical user interface computer.programming_language |
| Zdroj: | Neuron. 109:3594-3608.e2 |
| ISSN: | 0896-6273 |
| Popis: | The large diversity of neuron types of the brain, provides the means by which cortical circuits perform complex operations. Neuron types can be described by a broad set of electrophysiological characteristics, afferent inputs, neuron targets and molecular features. To quantify, visualize, and standardize these features, we developed the open-source Matlab-based framework, CellExplorer. It consists of three components: a processing module, a flexible data structure, and a powerful graphical interface. The processing module calculates standardized physiological metrics, performs neuron type classification from electrophysiological features, finds putative monosynaptic connections and saves it to a standardized yet flexible machine-readable format. The graphical interface makes it possible to explore any combination of computed features at the speed of a mouse click. The framework allows users to process, curate and relate their data to a growing publicly available collection of neurons. In addition to data mining, CellExplorer can link genetically identified cell types to physiological properties of tens of thousands of single neurons collected across laboratories, potentially leading to interlaboratory standards of single cell metrics. |
| Databáze: | OpenAIRE |
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