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ZENODO
Dataset . 2023
License: CC BY NC
Data sources: ZENODO
ZENODO
Dataset . 2023
License: CC BY NC
Data sources: Datacite
ZENODO
Dataset . 2023
License: CC BY NC
Data sources: Datacite
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Connectivity matrix of the internal connectivity of a SSCX model

Authors: Reimann, Michael;

Connectivity matrix of the internal connectivity of a SSCX model

Abstract

This is a simplified view of the internal synaptic connectivity of the model deposited under https://zenodo.org/records/8026353. While in this view a lot of data is lost compared to the detailed representation linked above (such as the pre- and postsynaptic locations of synaptic contacts and their physiology), it can still be used for structural connectomics analyses. The data is in a format that can be loaded using our Connectome_Utilities package. We have converted the internal connectivity of the MICrONS dataset into the same format (found here), allowing researchers to easily run the same analysis scripts on both datasets.

Keywords

Computational model, Connectomics, Neuroscience

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average