ArticleGigaScience2018
An open-source high-speed infrared videography database to study the principles of active sensing in freely navigating rodents.
Article in GigaScience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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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.
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Who cites it
9 citing papers in PubMed.
- Peri-head distance coding in the mouse brainstem.Neuron · 2026Article
- NeuroCarta: An automated and quantitative approach to mapping cellular networks in the mouse brain.Network neuroscience (Cambridge, Mass.) · 2025Article
- Restoration of mitochondrial energy metabolism by electroconvulsive therapy in adolescent and juvenile mice.Frontiers in psychiatry · 2025Article
- Integrated software for multi-dimensional analysis of motion using tracking, electrophysiology, and sensor signals.Frontiers in bioengineering and biotechnology · 2023Article
- Article
- Cortical Representation of Touch in Silico.Neuroinformatics · 2022Article
- WhiskEras: A New Algorithm for Accurate Whisker Tracking.Frontiers in cellular neuroscience · 2020Article
- An open-source high-speed infrared videography database to study the principles of active sensing in freely navigating rodents.GigaScience · 2018Article
- A databank for intracellular electrophysiological mapping of the adult somatosensory cortex.GigaScience · 2018Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Active sensing is crucial for navigation. It is characterized by self-generated motor action controlling the accessibility and processing of sensory information. In rodents, active sensing is commonly studied in the whisker system. As rats and mice modulate their whisking contextually, they employ frequency and amplitude modulation. Understanding the development, mechanisms, and plasticity of adaptive motor control will require precise behavioral measurements of whisker position. Findings: Advances in high-speed videography and analytical methods now permit collection and systematic analysis of large datasets. Here, we provide 6,642 videos as freely moving juvenile (third to fourth postnatal week) and adult rodents explore a stationary object on the gap-crossing task. The dataset includes sensory exploration with single- or multi-whiskers in wild-type animals, serotonin transporter knockout rats, rats received pharmacological intervention targeting serotonergic signaling. The dataset includes varying background illumination conditions and signal-to-noise ratios (SNRs), ranging from homogenous/high contrast to non-homogenous/low contrast. A subset of videos has been whisker and nose tracked and are provided as reference for image processing algorithms. Conclusions: The recorded behavioral data can be directly used to study development of sensorimotor computation, top-down mechanisms that control sensory navigation and whisker position, and cross-species comparison of active sensing. It could also help to address contextual modulation of active sensing during touch-induced whisking in head-fixed vs freely behaving animals. Finally, it provides the necessary data for machine learning approaches for automated analysis of sensory and motion parameters across a wide variety of signal-to-noise ratios with accompanying human observer-determined ground-truth.
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Registered trials
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.