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Allen Cell Types Database

This is the online help for the ALLEN Cell Types Database web application.

The Dataset

The Allen Cell Types dataset is a database of neuronal cell types based on multimodal characterization of single cells to enable data-driven approaches to classification and is fully integrated with the other Allen Brain Atlas resources.

The Allen Cell Types Database currently includes:

Electrophysiology - whole cell current clamp recordings made from identified, fluorescent Cre-positive neurons.
Morphology - reconstruction-quality, 3-D images of the complete structure of neurons filled and recorded from in vitro slice preparations and 3-D reconstructions of the dendrites and the initial part of the axon of each neuron.
Generalized Leaky Integrate-and-Fire (GLIF) models - A series of point neuron models of increasing complexity to reproduce the spiking behaviors of the recorded neurons. Starting with a leaky integrate and fire model, more complex models attempt to model variable spike threshold, afterspike currents, and threshold adaptation.
“Biophysical-Perisomatic” model - compartmental model of neurons that account for the neural morphology and emulates electrophysiological responses by assuming biophysically detailed mechanisms for specific families of ionic conductances.

Key features

• Registration to the mouse CCF, a 3-D anatomical framework with 3-D structural annotations.
• Data traces for the electrophysiology data from each neuron.
• Manually corrected and curated dendritic morphologies with annotation of neuronal compartments and extracted quantitative values for each reconstruction.
• Search and visualization tools for exploring the single cell electrophysiology, morphology, and modeling data.
• Data and models available for download via Allen Brain Atlas API and Allen Software Development Kit (SDK)
• RNA sequencing data derived from single cells isolated from the dorsal part of the lateral geniculate complex (LGd)

For complete details please see the white papers on our Documentation page.

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