English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In the brain, the structure of a network of neurons defines how these neuronsimplement the computations that underlie the mind and the behavior of animalsand humans. Provided that we can describe the network of neurons as a graph, wecan employ methods from graph theory to investigate its structure or usecellular automata to mathematically assess its function. Although, software forthe analysis of graphs and cellular automata are widely available. Graphextraction from the image of networks of brain cells remains difficult. Nervoustissue is heterogeneous, and differences in anatomy may reflect relevantdifferences in function. Here we introduce a deep learning based toolbox toextracts graphs from images of brain tissue. This toolbox provides aneasy-to-use framework allowing system neuroscientists to generate graphs basedon images of brain tissue by combining methods from image processing, deeplearning, and graph theory. The goals are to simplify the training and usage ofdeep learning methods for computer vision and facilitate its integration intograph extraction pipelines. In this way, the toolbox provides an alternative tothe required laborious manual process of tracing, sorting and classifying. Weexpect to democratize the machine learning methods to a wider community ofusers beyond the computer vision experts and improve the time-efficiency ofgraph extraction from large brain image datasets, which may lead to furtherunderstanding of the human mind.

DeepTEGINN: Deep Learning Based Tools to Extract Graphs from Images of Neural Networks