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2024 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology (CIBCB)

Clustering density based gene expression data in the mouse brainstem and comparison to actual neuroanatomy

Colin Buenvenida, Brandon Kong, Shane Jung, Kaiwen Kam, Jacob Furst, Thiruvarangan Ramaraj

Abstract

The medullary reticular formation is a network of brainstem nuclei and neurons in the brain that is composed of circuit pathways from the brain to the spinal cord. It carries out vital roles and orofacial behaviors such as vocalization, swallowing, and breathing. A disruption in these neuronal circuits can be threatening for persons with neurodevelopmental and neurodegenerative disorders, leading to deficits in breathing, swallowing, and communication. However, the neurons associated with orofacial motor controls are not clearly defined or localized within the reticular formation due to the lack of molecular markers and distinct brain tissue cells. This project serves to understand the organization of the reticular formation and define where orofacial motor behaviors are localized. We hypothesize that differences in gene expression and three-dimensional proximities can identify functional subpopulations of the reticular formation that control orofacial motor behaviors. Using gene density measures of the coronal plane in the adult male mouse brain that are attributed to the reticular formation, we computed 13 clusters using K-Means clustering with Euclidean distance measure based on brainstem nuclei that are biologically significant to the control of orofacial behaviors. This clustering pattern has implications for understanding the organization of the reticular formation. By understanding the organization of these brainstem nuclei, neuroscientists can better understand how neurodegenerative disorders work and potentially lead to effective treatments for persons suffering from them.

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