Event Title

Analysis of Circadian Neuro-Networks in Mouse Brains

Presenter Information

Audrey Lyman, Colby CollegeFollow

Location

Diamond 344

Start Date

1-5-2014 1:00 PM

End Date

1-5-2014 3:00 PM

Project Type

Presentation

Description

While the circadian rhythm has been extensively studied in many organisms, the specific cell-to-cell communication that confers this rhythm is not as well understood, especially in the brain. Despite a significant amount of data, circadian neural cell networks have not yet been mapped, primarily due to a gap in neurological knowledge. In this study, we have begun analyzing the patterns of individual cells from mouse brains, specifically cells in the suprachiastmatic nucleus, observing how activity levels in individual cells change over several days after a given treatment. Using computational tools to study the phase velocity and peaks and troughs of per gene expression in the cells, we have visualized and studied the data in various ways in an attempt to better understand how the cells communicate with each other and thus form these advanced networks. These visualizations and analyses have provided insight into some of the basic ways neural cells form a network by illuminating the relative significance that certain key cells play in the system as a whole.

Faculty Sponsor

Dale Skrien

Sponsoring Department

Colby College. Computer Science Dept.

CLAS Field of Study

Natural Sciences

Event Website

http://www.colby.edu/clas

ID

832

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May 1st, 1:00 PM May 1st, 3:00 PM

Analysis of Circadian Neuro-Networks in Mouse Brains

Diamond 344

While the circadian rhythm has been extensively studied in many organisms, the specific cell-to-cell communication that confers this rhythm is not as well understood, especially in the brain. Despite a significant amount of data, circadian neural cell networks have not yet been mapped, primarily due to a gap in neurological knowledge. In this study, we have begun analyzing the patterns of individual cells from mouse brains, specifically cells in the suprachiastmatic nucleus, observing how activity levels in individual cells change over several days after a given treatment. Using computational tools to study the phase velocity and peaks and troughs of per gene expression in the cells, we have visualized and studied the data in various ways in an attempt to better understand how the cells communicate with each other and thus form these advanced networks. These visualizations and analyses have provided insight into some of the basic ways neural cells form a network by illuminating the relative significance that certain key cells play in the system as a whole.

http://digitalcommons.colby.edu/clas/2014/program/21