In the field of behavioral neuroscience, a need exists for an automated method of tracking neuronal activity in model organisms with rapid high-throughput screening. Current imaging methods are designed to only examine a single animal at a time, limiting the understanding of the range and variability of response to stimuli. Examining multiple animals can eliminate this problem. However, the bottleneck now shifts from the experiment to the data analysis as neural experiments become accelerated by 100 fold. The current software used for data analysis requires intense user supervision as moving neurons exhibit brief patterns of ambiguity. We present NeuroTracker 2.0, an improved software used to automatically track neuronal activity in C. elegans.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Cupido, Paul N.
• Hess, Justin Peter
• Feng, Ellva

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-050114-152350

Advisor

• Albrecht, Dirk
• Duffy, Joseph B.
• Ward, Matthew O.

Year

• 2014

Date created

• 2014-05-01

Resource type

• Major Qualifying Project

Major

• Bioinformatics & Computational Biology
• Biomedical Engineering
• Interdisciplinary

Rights statement

• In Copyright

Last modified

• 2020-12-29