Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Steps in the Modeling Process

Steps in the Modeling Process

Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Safety of long-term use of contezolid for TB and non-TB mycobacteria infections.

The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease·2026

Same author

[miR-488-5p promotes osteogenic and neurogenic differentiation of rat bone marrow mesenchymal stem cells and enhances neuralized bone regeneration].

Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences·2026

Same author

Chlorogenic acid supplementation regulates redox status, hepatic inflammation, and mitochondrial function in weaned piglets with intrauterine growth retardation.

Polish journal of veterinary sciences·2025

Same author

Anti-HBs Immune Complex Levels: A Novel Marker of Hepatitis Flare Following Nucleos(t)ide Analog Withdrawal in HBeAg-negative Chronic Hepatitis B.

The Journal of infectious diseases·2025

Same author

Corrigendum to 'Round Window Membrane Extracellular Vesicles Facilitate Inner Ear Drug Delivery' [Journal of Controlled Release 387 (2025) 114153].

Journal of controlled release : official journal of the Controlled Release Society·2025

Same author

Psychometric properties of the Chinese version of 21-item Fall Risk Index for community-dwelling older adults with stroke.

European journal of physical and rehabilitation medicine·2025

Same journal

Behavioral and physiological changes during the estrous cycle of socially housed female guinea pigs.

Behavioural processes·2026

Same journal

Flexible time-series analysis: A dynamically aware method for inferring directed dependencies in behavioral data.

Behavioural processes·2026

Same journal

Effects of group size and landmarks on escape behavior of three fish species.

Behavioural processes·2026

Same journal

Vocal individuality in two sympatric seabird species: The role of developmental strategy, analytical approach and sample size.

Behavioural processes·2026

Same journal

No evidence of sex-specific responses to chemosensory risk assessment cues in Harts rivulus.

Behavioural processes·2026

Same journal

Exploratory responses of rats to cage-mates and conspecifics from another cage in a habituation-dishabituation paradigm with multiple habituation stimuli.

Behavioural processes·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Apr 28, 2026

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Published on: May 10, 2019

Modelling timing performance on the peak procedure.

K Cheng¹, P Miceli²

¹School of Behavioural Sciences, Macquarie University, Sydney, NSW 2109, Australia.

Behavioural Processes

|June 5, 2014

Summary

This summary is machine-generated.

Scalar Expectancy Theory (SET) models accurately predicted response patterns in the peak procedure. Connectionist models, however, failed to match the observed data, highlighting SET

More Related Videos

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

Postural Organization of Gait Initiation for Biomechanical Analysis Using Force Platform Recordings

Postural Organization of Gait Initiation for Biomechanical Analysis Using Force Platform Recordings

Published on: July 26, 2022

Related Experiment Videos

Last Updated: Apr 28, 2026

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Published on: May 10, 2019

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

Postural Organization of Gait Initiation for Biomechanical Analysis Using Force Platform Recordings

Postural Organization of Gait Initiation for Biomechanical Analysis Using Force Platform Recordings

Published on: July 26, 2022

Area of Science:

Behavioral neuroscience
Computational psychology
Animal behavior

Background:

The peak procedure is a behavioral paradigm used to study timing and learning.
It involves fixed interval reinforcement schedules with occasional extinction probes.
This procedure elicits a characteristic pattern of responding, known as the 'run'.

Purpose of the Study:

To compare the efficacy of two computational models in explaining behavior in the peak procedure.
To assess the Scalar Expectancy Theory (SET) against a connectionist model.
To determine which model best accounts for the statistical properties of the response run.

Main Methods:

Computer simulations of the Scalar Expectancy Theory (SET) and a connectionist model.
Models were configured to match empirical data from the peak procedure.
Key parameters analyzed included the start, end, duration, and correlations within the response run.

Main Results:

SET models, particularly those with two thresholds and both difference and ratio comparison rules, demonstrated a good fit to the data.
Connectionist models, utilizing vector autocorrelations and angular thresholds, did not perform well.
The SET models successfully replicated the means and standard deviations of the response run characteristics.

Conclusions:

The Scalar Expectancy Theory provides a robust framework for understanding timing in behavioral tasks like the peak procedure.
Connectionist approaches, in their current form, are less effective at modeling these specific timing phenomena.
Computational modeling is crucial for testing and refining theories of learning and timing.