Chronotate: An open-source tool for manual timestamping and quantification of animal behavior

Paul A. Philipsberg, Zoé Christenson Wick, Keziah S. Diego, Nick Vaughan, Angelina Galas, Albert Jurkowski, Yu Feng, Lauren M. Vetere, Lingxuan Chen, Iván Soler, Denise J. Cai, Tristan Shuman

Research output: Contribution to journalArticlepeer-review


A core necessity to behavioral neuroscience research is the ability to accurately measure performance on behavioral assays, such as the novel object location and novel object recognition tasks. These tasks are widely used in neuroscience research and measure a rodent's instinct for investigating novel features as a proxy to test their memory of a previous experience. Automated tools for scoring behavioral videos can be cost prohibitive and often have difficulty distinguishing between active investigation of an object and simply being in close proximity to an object. As such, many experimenters continue to rely on hand scoring interactions using stopwatches, which makes it difficult to review scoring after-the-fact and results in the loss of temporal information. Here, we introduce Chronotate, a free, open-source tool to aid in manually scoring novel object behavior videos. The software consists of an interactive video player with keyboard integration for marking timestamps of behavioral events during video playback, making it simple to quickly score and review bouts of rodent-object interaction. In addition, Chronotate outputs detailed interaction bout data, allowing for nuanced behavioral performance analyses. Using this detailed temporal information, we demonstrate that novel object location performance peaks within the first 3 s of interaction time and preference for the novel location becomes reduced across the test session. Thus, Chronotate can be used to determine the temporal structure of interactions on this task and can provide new insight into the memory processes that drive this behavior. Chronotate is available for download at:

Original languageEnglish
Article number137461
JournalNeuroscience Letters
StatePublished - 25 Sep 2023


  • Novel object location
  • Novel object recognition
  • Open-source
  • Rodent behavior


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