Chronotate: An open-source tool for manual timestamping and quantification of animal behavior
Neuroscience Letters, ISSN: 0304-3940, Vol: 814, Page: 137461
2023
- 2Citations
- 1Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations2
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- Readers1
Article Description
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: https://github.com/ShumanLab/Chronotate.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0304394023004202; http://dx.doi.org/10.1016/j.neulet.2023.137461; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85168852967&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/37619698; https://linkinghub.elsevier.com/retrieve/pii/S0304394023004202; https://dx.doi.org/10.1016/j.neulet.2023.137461
Elsevier BV
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