Research
Machine-learning Clustering on Novel Brainstem Nuclei Controlling Orofacial Behaviors
Machine-learning Clustering in the reticular formation, a brain structure that houses important nuclei that controls movements such as breathing, swallowing, and talking, is a novel approach.
Problem
It is currently difficult to identity function-specific Reticular Formation nuclei in the brain due to a lack of distinct, defined cytoarchitectonic boundaries in the brainstem.
Motivations
- Clarifying the function-specific nuclei in the brain can increase understanding of other body tissues and their functions
- Understanding the organization of neurons within the brain can improve treatments for neurodevelopmental and neurodegenerative disorders such as Sudden Infant Death Syndrome (SIDS)
- Leveraging machine-learning technology can further neuroscientific understandings of the human brain
Methodology
# Example Python code
def greet(name):
print("Hello, " + name + "!")
greet("World")
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Figure 1: Caption
Test