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Related Concept Videos

Behavior Modification01:21

Behavior Modification

482
Behavioral approaches have often been criticized for ignoring mental processes and focusing solely on observable behavior. However, these approaches provide an optimistic perspective for individuals seeking to change their behaviors. Rather than concentrating on intrinsic personality traits, behavioral approaches suggest that even longstanding habits can be modified by changing the reward contingencies that maintain them.
A real-world application of operant conditioning principles is applied...
482

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A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
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A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis.

Sanjay Shukla1, Ahmet Arac2

  • 1Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles.

Journal of Visualized Experiments : Jove
|February 25, 2020
PubMed
Summary

DeepBehavior utilizes deep learning and convolutional neural networks to analyze animal behavior videos, offering a robust and precise automated method for detailed behavioral insights.

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Area of Science:

  • Neuroscience
  • Behavioral Science
  • Computer Science

Background:

  • Traditional behavioral analysis methods lack the richness of natural behaviors.
  • Understanding neural mechanisms requires detailed behavioral data.

Purpose of the Study:

  • Introduce DeepBehavior, a novel deep learning toolbox for advanced behavioral video analysis.
  • Provide a detailed protocol for implementing DeepBehavior's frameworks.

Main Methods:

  • Utilized deep learning frameworks with convolutional neural networks for video processing.
  • Implemented frameworks for single and multiple object detection.
  • Developed a framework for 3D human joint pose tracking.

Main Results:

  • DeepBehavior rapidly processes and analyzes behavioral videos.
  • Frameworks return precise Cartesian coordinates for objects of interest.
  • Generated detailed insights into behavior dynamics, surpassing traditional methods.

Conclusions:

  • DeepBehavior offers a robust, automated, and precise method for quantifying behavior.
  • The toolbox enables deeper understanding of behavior-driven neural mechanisms.
  • Provided post-processing code for extracting further insights and visualizations.