AIMC Topic: Behavioral Research
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A non-parametric effect-size measure capturing changes in central tendency and data distribution shape.
PloS one
Sep 24, 2020
MOTIVATION: Calculating the magnitude of treatment effects or of differences between two groups is a common task in quantitative science. Standard effect size measures based on differences, such as the commonly used Cohen's, fail to capture the treat...
An automatic behavior recognition system classifies animal behaviors using movements and their temporal context.
Journal of neuroscience methods
Aug 12, 2019
Animals can perform complex and purposeful behaviors by executing simpler movements in flexible sequences. It is particularly challenging to analyze behavior sequences when they are highly variable, as is the case in language production, certain type...
Real-time analysis of the behaviour of groups of mice via a depth-sensing camera and machine learning.
Nature biomedical engineering
May 20, 2019
Preclinical studies of psychiatric disorders use animal models to investigate the impact of environmental factors or genetic mutations on complex traits such as decision-making and social interactions. Here, we introduce a method for the real-time an...
Automated gesture tracking in head-fixed mice.
Journal of neuroscience methods
Jul 17, 2017
BACKGROUND: The preparation consisting of a head-fixed mouse on a spherical or cylindrical treadmill offers unique advantages in a variety of experimental contexts. Head fixation provides the mechanical stability necessary for optical and electrophys...
A comparison of machine learning methods for classification using simulation with multiple real data examples from mental health studies.
Statistical methods in medical research
Sep 18, 2013
BACKGROUND: Recent literature on the comparison of machine learning methods has raised questions about the neutrality, unbiasedness and utility of many comparative studies. Reporting of results on favourable datasets and sampling error in the estimat...
Swimming into the future: Machine learning in zebrafish behavioral research.
Progress in neuro-psychopharmacology & biological psychiatry
Jun 20, 2025
The zebrafish (Danio rerio) has emerged as a powerful organism in behavioral neuroscience, offering invaluable insights into the neural circuits and molecular pathways underlying complex behaviors. Although the knowledge of zebrafish behavioral reper...
Feature-based behavior coding for efficient exploratory analysis using pose estimation.
Behavior research methods
May 9, 2025
This paper introduces feature-based behavior coding (FBBC), an efficient method for exploratory analysis in behavioral research using pose estimation techniques. FBBC addresses the challenges of traditional behavioral coding methods, particularly in ...
A framework for language technologies in behavioral research and clinical applications: Ethical challenges, implications, and solutions.
The American psychologist
Jan 1, 2024
Technological advances in the assessment and understanding of speech and language within the domains of automatic speech recognition, natural language processing, and machine learning present a remarkable opportunity for psychologists to learn more a...
Developing Machine Learning Models for Behavioral Coding.
Journal of pediatric psychology
Apr 1, 2019
OBJECTIVE: The goal of this research is to develop a machine learning supervised classification model to automatically code clinical encounter transcripts using a behavioral code scheme.
gazeNet: End-to-end eye-movement event detection with deep neural networks.
Behavior research methods
Apr 1, 2019
Existing event detection algorithms for eye-movement data almost exclusively rely on thresholding one or more hand-crafted signal features, each computed from the stream of raw gaze data. Moreover, this thresholding is largely left for the end user. ...
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