SipperViz
Developed by Creed and Kravitz Labs at Washington University in St. Louis, Sippers is a 3D-printed, open-source device for behavioral analysis of measuring liquid ingestion in rodents. This is a great tool for neuroscientists in fields studying topics such as reward, metabolism, and circadian biology. It has been shown to be effective in procedures such as two-bottle choice tasks to measure preferences of different liquids. Sippers has been integrated into other device setups for reward delivery such as fiber photometry to display liquid ingestion data alongside neural activity in studies of ingestive behavior. To learn more about Sippers and the documentation behind it, click here.
As an extension to the Sippers hardware, SipperViz was developed. The main idea behind SipperViz is to process data produced by this open-source device. A SipperViz video tutorial series made by Tom Earnest, the creator of SipperViz, is available on YouTube as a walkthrough tutorial. SipperViz is a Python-based GUI for graphing data produced by Sippers. SipperViz can be used to create plots visualizing drink frequency and duration, label and assign liquids associated with Sipper recordings, average data from different recordings based on the bottle, liquid, or experimental group, concatenate data from different recordings, and return the data and code used to create plots.
This research tool was created by your colleagues. Please acknowledge the Principal Investigator, cite the article in which the tool was described, and include an RRID in the Materials and Methods of your future publications. Sippers Hardware: RRID:SCR_021445; SipperViz Software: RRID:SCR_022463
Read the Sippers Paper
The full paper including extensive examples of the data the program has been able to identify can be found here!
SipperViz Github site
Get access to the software, docs, and tutorials from the Github page!
Thanks, Robby!
This post was brought to you by Robby Jones. This project summary is a part of the collection from neuroscience undergraduate and graduate students in the Computational Methods course at American University.