AI Article Synopsis
- A deep understanding of neuron connectivity and cell types across different brain regions is essential for revealing how emotions and memory function, as well as for developing treatments for brain impairments.
- Brain-wide imaging with single-cell resolution has led to significant discoveries in animal models, but there is an urgent need for high-throughput systems to study neural structures at a larger scale, especially for non-human primates and human brains.
- Advances in AI and computational resources present opportunities to enhance imaging systems, allowing for automation and optimization, which is crucial for smart imaging techniques in brain-wide studies at single-cell resolution.
Article Abstract
A deep understanding of the neuronal connectivity and networks with detailed cell typing across brain regions is necessary to unravel the mechanisms behind the emotional and memorial functions as well as to find the treatment of brain impairment. Brain-wide imaging with single-cell resolution provides unique advantages to access morphological features of a neuron and to investigate the connectivity of neuron networks, which has led to exciting discoveries over the past years based on animal models, such as rodents. Nonetheless, high-throughput systems are in urgent demand to support studies of neural morphologies at larger scale and more detailed level, as well as to enable research on non-human primates (NHP) and human brains. The advances in artificial intelligence (AI) and computational resources bring great opportunity to 'smart' imaging systems, i.e., to automate, speed up, optimize and upgrade the imaging systems with AI and computational strategies. In this light, we review the important computational techniques that can support smart systems in brain-wide imaging at single-cell resolution.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9095808 | PMC |
| http://dx.doi.org/10.1186/s40708-022-00158-4 | DOI Listing |
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