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Neuroglancer Views

Using Neuroglancer

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Unfamiliar with Neuroglancer? More detail is available here.

Cell inputs

Neuroglancer view of a layer 6 CT cell with annotated input synapses

Layer 6 CT cell with annotated input synapses

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Neuroglancer view of a layer 5 ET cell with annotated input synapses

Layer 5 ET cell with annotated input synapses

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Neuroglancer view of a basket cell with annotated input synapses

Basket cell with annotated input synapses

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Cell outputs

Neuroglancer view of a layer 4 pyramidal cell with annotated output synapses

Layer 4 pyramidal cell with annotated output synapses

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Neuroglancer view of a layer 5 IT pyramidal cell with annotated output synapses

Layer 5 IT pyramidal cell with annotated output synapses

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Neuroglancer view of a basket cell with annotated output synapses

Basket cell with annotated output synapses

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Neuroglancer’s segment propoerties allow you to quickly select cells via a table of properties attached to each cell. Here, we’ve generated a segment properties table which includes information about cell type and some summary statistics about subcellular targeting for each cell in the curated “column” described in the paper. This allows you to quickly navigate to cells of interest based on their predicted properties.

Example selections using segment properties

Neuroglancer view of a basket cells with annotated output synapses

Selection of two basket cells with the highest soma-targeting output fraction.

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Neuroglancer view of a basket cells with annotated output synapses

Selection of two Layer 2/3 pyramidal cells with the rate of multi-input spines on their dendrites.

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Using segment properties

To generate your own selection, access the segment properties view. Ctrl or right-click on the seg tab:

Neuroglancer segment properties view

Type the name of a cell type to filter by type:

Neuroglancer segment properties view

Use the sliders or type an expression to filter by cell properties. Available properties include a sample of the cell-level statistics available for curated cells as described in the paper. For instance, the selection above filters for the Layer 6 CT cells which most target spines:

Neuroglancer segment properties view with selection

Available properties

Numerical properties:

NameDescription
pre_p_spine_synapseProportion of output synapses to spines
pre_p_shaft_synapseProportion of outputs synapses to shaft
pre_p_soma_synapseProportion of output synapses to soma
pre_p_spine_site_is_multiProportion of contacted spines which are multi-input
pre_to_exc_p_spine_synapseProportion of output synapses to excitatory neurons which are to spines
pre_to_exc_p_shaft_synapseProportion of output synapses to excitatory neurons which are to shafts
pre_to_exc_p_soma_synapseProportion of output synapses to excitatory neurons which are to somas
pre_to_exc_p_spine_site_is_multiProportion of contacted spines on excitatory neuron spines which are to multi-input
post_p_spine_synapseProportion of input synapses to spines
post_p_shaft_synapseProportion of input synapses to shaft
post_p_soma_synapseProportion of input synapses to soma
post_p_spine_site_is_multiProportion of input spines which are multi-input

Cell types:

NameDescription
23PLayer 2/3 intratelencephalic pyramidal neuron
4PLayer 4 intratelencephalic pyramidal neuron
5P-ITLayer 5 intratelencephalic pyramidal neuron
5P-ETLayer 5 extratelencephalic pyramidal neuron
5P-NPLayer 5 near-projecting pyramidal neuron
6P-ITLayer 6 intratelencephalic pyramidal neuron
6P-CTLayer 6 corticothalamic pyramidal neuron
BCBasket cell
BPCBipolar cell
MCMartinotti cell
NGCNeurogliaform cell