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Of course you can, use the ocdi/before_widgets_import action. You can also target different predefined demo imports like in the example above. Here is a simple example code of the ocdi/before_widgets_import
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How to fill out a unified connectomic target
How to fill out a unified connectomic target
01
Gather all necessary information such as neuron types, synapse locations, and connection strengths.
02
Create a comprehensive map of the neural network by documenting each neuron and its connections.
03
Use specialized software or tools to visualize and analyze the connectome data.
04
Double-check the accuracy of the data and make any necessary corrections.
05
Share the unified connectomic target with researchers and scientists for further study and analysis.
Who needs a unified connectomic target?
01
Researchers studying brain structure and function
02
Neuroscientists investigating neural circuits and network dynamics
03
Medical professionals researching neurological disorders and treatments
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What is a unified connectomic target?
A unified connectomic target is a specific goal or objective that combines different connectomic datasets to create a comprehensive map of neural connections in the brain.
Who is required to file a unified connectomic target?
Researchers, neuroscientists, and institutions studying brain connectivity are required to file a unified connectomic target.
How to fill out a unified connectomic target?
To fill out a unified connectomic target, researchers need to input data from various connectomic studies and integrate them to create a unified map of neural connections.
What is the purpose of a unified connectomic target?
The purpose of a unified connectomic target is to better understand the complex network of connections in the brain and to identify patterns that may contribute to neurological disorders or brain function.
What information must be reported on a unified connectomic target?
A unified connectomic target must include data on neuron locations, synaptic connections, and connectivity patterns between different brain regions.
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