Objective Behavioral Data
Objective Behavioral Data - Related Videos
08:28
Novel Object Exploration as a Potential Assay for Higher Order Repetitive Behaviors in Mice
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Cited by 10 •
2016
Higher order restricted, repetitive behaviors (RRBs) disrupt the lives of affected individuals. These behaviors are challenging to model in rodents, making basic biomedical research into potential treatments or interventions for RRBs difficult. Here we describe novel object exploration as a potential assay for higher order RRBs in mice.
05:57
Novel Object Recognition and Object Location Behavioral Testing in Mice on a Budget
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Cited by 251 •
2018
Here we provide a protocol which includes comprehensive instructions for the economical establishment of murine object location and novel object recognition behavioral testing, including the design, cost, and construction of required equipment as well as execution of behavioral testing, data collection, and analysis.
14:38
Creating Objects and Object Categories for Studying Perception and Perceptual Learning
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Cited by 12 •
2012
We describe a novel methodology for creating naturalistic 3-D objects and object categories with precisely defined feature variations. We use simulations of the biological processes of morphogenesis and phylogenesis to create novel, naturalistic virtual 3-D objects and object categories that can then be rendered as visual images or haptic objects.
10:14
Object Substitution Masking
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2023
Source: Laboratory of Jonathan Flombaum—Johns Hopkins University Visual masking is a term used by perceptual scientists to refer to a wide range of phenomena in which in an image is presented but not perceived by an observer because of the presentation of a second image. There are several different kinds of masking, many of them relatively intuitive and unsurprising. But one surprising and important type of masking is called Object Substitution Masking. It has been a focus of research in vision...
15:25
Tomato Analyzer: A Useful Software Application to Collect Accurate and Detailed Morphological and Colorimetric Data from Two-dimensional Objects
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Cited by 152 •
2010
Tomato Analyzer (TA) quantifies attributes of two dimensional shapes and color in a reproducible and accurate manner. A step-by-step procedure for obtaining high quality digitalized images of tomato fruit, morphological and color analyses of these images and several applications using the data generated through this software are described.
FAQs
Operational definitions translate a broad behavior into observable criteria that researchers can apply consistently. This reduces the influence of personal interpretation and makes it possible to record the same type of event across participants or experimental conditions. Clear definitions also support reproducible analysis, allowing researchers to evaluate whether measured behavior changes in response to learning, environmental conditions, or an intervention.
The appropriate measurement depends on the behavioral question. Frequency indicates how often an event occurs, duration shows how long it continues, latency measures the delay before it begins, and intensity captures its strength. Selecting among these dimensions helps researchers represent behavior more precisely and compare patterns across individuals, groups, or conditions without relying on a single summary measure.
Consistent observation, coding, or automated tracking allows measurements to be compared across participants and conditions. When researchers apply the same operational criteria and recording approach throughout a study, differences in the data are more likely to reflect actual behavioral variation rather than changes in measurement. This consistency strengthens reproducibility and supports more reliable evaluation of research hypotheses.
Objective measures focus on observable indicators of what individuals or groups do, whereas self-report represents participants’ descriptions or interpretations of their own behavior. Using observable records can provide a quantifiable basis for comparison and can complement self-report rather than simply replace it. This distinction is especially useful when researchers need to evaluate behavior across conditions or assess changes during an intervention.
A basic workflow begins by defining the target behavior in operational terms and choosing whether frequency, duration, latency, or intensity best addresses the research question. Researchers then record the behavior through structured observation, coding, or automated tracking, applying the same procedure across participants and conditions. The resulting measurements can be organized for comparison and analysis.
Researchers use measurable behavioral records to examine learning, decision-making, social interactions, and responses to environmental changes or interventions. The data can reveal patterns, test hypotheses, compare conditions, and help assess treatment outcomes. Because the measurements are quantifiable, they also provide a basis for evaluating whether observed behavioral changes correspond with the conditions or intervention being studied.