Evidence map›Paper›PMID 37619698›Full record

ArticleNeuroscience letters2023

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 and 2 more

Abstract read
In one paragraph

Article in Neuroscience letters, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
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  7. Progressive Excitability Changes in the Medial Entorhinal Cortex in the 3xTg Mouse Model of Alzheimer's Disease Pathology.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Paul A PhilipsbergIcahn School of Medicine at Mount Sinai, New York NY, United States.
Zoé Christenson WickIcahn School of Medicine at Mount Sinai, New York NY, United States.
Keziah S DiegoIcahn School of Medicine at Mount Sinai, New York NY, United States.
Nick VaughanIcahn School of Medicine at Mount Sinai, New York NY, United States.
Angelina GalasIcahn School of Medicine at Mount Sinai, New York NY, United States; New York University, New York NY, United States.
Albert JurkowskiIcahn School of Medicine at Mount Sinai, New York NY, United States; CUNY Hunter College, New York NY, United States.
Yu FengIcahn School of Medicine at Mount Sinai, New York NY, United States.
Lauren M VetereIcahn School of Medicine at Mount Sinai, New York NY, United States.
Lingxuan ChenIcahn School of Medicine at Mount Sinai, New York NY, United States.
Iván SolerIcahn School of Medicine at Mount Sinai, New York NY, United States.
Denise J CaiIcahn School of Medicine at Mount Sinai, New York NY, United States.
Tristan ShumanIcahn School of Medicine at Mount Sinai, New York NY, United States. Electronic address: tristan.shuman@mssm.edu.

Funding

Circuit Mechanisms of Retrospective Memory-LinkingR01MH120162 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Denise Jade Cai · 2020 to 2026
$3.9M
Research Training in the Neuroscience of AgingT32AG049688 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Joseph Michael Castellano, PATRICK R HOF · 2015 to 2026
$3.0M
Circuits Driving Spatial Coding Deficits in EpilepsyR01NS116357 · NINDS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI SHUMAN, TRISTAN · 2021 to 2025
$2.8M
How does the brain maximize storage capacity?DP2MH122399 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI CAI, DENISE JADE · 2019 to 2020
$2.6M
Entorhinal-hippocampal interactions during progressive memory impairments in mouse models of Alzheimer's disease pathologyRF1AG072497 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI SHUMAN, TRISTAN · 2022 to 2024
$2.4M
Fear and anxiety circuit mechanisms in anterior hypothalamic nucleusR56MH132959 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI CAI, DENISE JADE · 2023 to 2024
$1.3M
Closed-Loop Control of Dentate Inhibitory Timing in Healthy and Epileptic MiceF32NS116416 · NINDS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI CHRISTENSON WICK, ZOÉ · 2020 to 2023
$206k
Interneuron and Network Dysfunction in a Mouse Model of Alzheimer's DiseaseF31AG069496 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI VETERE, LAUREN · 2020 to 2022
$134k
NIA NIH HHS F31 AG069496NIA NIH HHS RF1 AG072497NIA NIH HHS T32 AG049688NIMH NIH HHS DP2 MH122399NIMH NIH HHS R01 MH120162NIMH NIH HHS R56 MH132959NINDS NIH HHS F32 NS116416NINDS NIH HHS R01 NS116357
6 · The paper itself

Abstract

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.

Indexed as

MemoryRecognition, PsychologyAnimalsBehavior, AnimalVisual PerceptionNovel object locationNovel object recognitionOpen-sourceRodent behavior

Identifiers

PMID37619698
PMCPMC10529615

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.