AIMC Topic: Behavior, Animal
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Skilled reach training enhances robotic gait training to restore overground locomotion following spinal cord injury in rats.
Behavioural brain research
Aug 3, 2021
Rehabilitative training has been shown to improve motor function following spinal cord injury (SCI). Unfortunately, these gains are primarily task specific; where reach training only improves reaching, step training only improves stepping and stand t...
Quantifying finer-scale behaviours using self-organising maps (SOMs) to link accelerometery signatures with behavioural patterns in free-roaming terrestrial animals.
Scientific reports
Jun 30, 2021
Collecting quantitative information on animal behaviours is difficult, especially from cryptic species or species that alter natural behaviours under observation. Using harness-mounted tri-axial accelerometers free-roaming domestic cats (Felis Catus)...
Zebrafish behavior feature recognition using three-dimensional tracking and machine learning.
Scientific reports
Jun 29, 2021
In this work, we aim to construct a new behavior analysis method by using machine learning. We used two cameras to capture three-dimensional (3D) tracking data of zebrafish, which were analyzed using fuzzy adaptive resonance theory (FuzzyART), a type...
Multi-View Mouse Social Behaviour Recognition With Deep Graphic Model.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jun 11, 2021
Home-cage social behaviour analysis of mice is an invaluable tool to assess therapeutic efficacy of neurodegenerative diseases. Despite tremendous efforts made within the research community, single-camera video recordings are mainly used for such ana...
Low-dimensional learned feature spaces quantify individual and group differences in vocal repertoires.
eLife
May 14, 2021
Increases in the scale and complexity of behavioral data pose an increasing challenge for data analysis. A common strategy involves replacing entire behaviors with small numbers of handpicked, domain-specific features, but this approach suffers from ...
Real-Time Closed-Loop Feedback in Behavioral Time Scales Using DeepLabCut.
eNeuro
Apr 16, 2021
Computer vision approaches have made significant inroads into offline tracking of behavior and estimating animal poses. In particular, because of their versatility, deep-learning approaches have been gaining attention in behavioral tracking without a...
Action detection using a neural network elucidates the genetics of mouse grooming behavior.
eLife
Mar 17, 2021
Automated detection of complex animal behaviors remains a challenging problem in neuroscience, particularly for behaviors that consist of disparate sequential motions. Grooming is a prototypical stereotyped behavior that is often used as an endopheno...
Opposite valence social information provided by bio-robotic demonstrators shapes selection processes in the green bottle fly.
Journal of the Royal Society, Interface
Mar 17, 2021
Social learning represents a high-level complex process to acquire information about the environment, which is increasingly reported in invertebrates. The animal-robot interaction paradigm turned out to be an encouraging strategy to unveil social lea...
Automation of training and testing motor and related tasks in pre-clinical behavioural and rehabilitative neuroscience.
Experimental neurology
Feb 15, 2021
Testing and training animals in motor and related tasks is a cornerstone of pre-clinical behavioural and rehabilitative neuroscience. Yet manually testing and training animals in these tasks is time consuming and analyses are often subjective. Conseq...
Unsupervised manifold learning of collective behavior.
PLoS computational biology
Feb 12, 2021
Collective behavior is an emergent property of numerous complex systems, from financial markets to cancer cells to predator-prey ecological systems. Characterizing modes of collective behavior is often done through human observation, training generat...
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