Deep learning networks reflect cytoarchitectonic features used in brain mapping
Abstract The distribution of neurons in the cortex (cytoarchitecture) differs between cortical areas and constitutes the basis for structural maps of the human brain. Deep learning approaches provide a promising alternative to overcome throughput limitations of currently used cytoarchitectonic mappi...
Saved in:
Main Authors: | Kai Kiwitz, Christian Schiffer, Hannah Spitzer, Timo Dickscheid, Katrin Amunts |
---|---|
Format: | article |
Language: | EN |
Published: |
Nature Portfolio
2020
|
Subjects: | |
Online Access: | https://doaj.org/article/67bde2c876a64ebc9c7c1c47d04d06a8 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
High-throughput dual-colour precision imaging for brain-wide connectome with cytoarchitectonic landmarks at the cellular level
by: Hui Gong, et al.
Published: (2016) -
Beyond cytoarchitectonics: the internal and external connectivity structure of the caudate nucleus.
by: Sonja A Kotz, et al.
Published: (2013) -
Comparative mapping of crawling-cell morphodynamics in deep learning-based feature space.
by: Daisuke Imoto, et al.
Published: (2021) -
Electrophysiological dynamics of antagonistic brain networks reflect attentional fluctuations
by: Aaron Kucyi, et al.
Published: (2020) -
The BigBrainWarp toolbox for integration of BigBrain 3D histology with multimodal neuroimaging
by: Casey Paquola, et al.
Published: (2021)