Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Prevalence and Incidence01:08

Prevalence and Incidence

1.9K
In statistical epidemiology and health sciences, two essential metrics—prevalence and incidence—are fundamental for understanding disease dynamics within a population. These measures enable public health officials, epidemiologists, and researchers to assess the burden of diseases, allocate resources effectively, and design impactful public health policies and interventions.
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
1.9K
Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

2.6K
Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
2.6K
Associative Learning01:27

Associative Learning

1.5K
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
1.5K
Purposive Learning01:22

Purposive Learning

518
E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
518
Observational Learning01:12

Observational Learning

1.0K
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
1.0K
Learning Disabilities01:25

Learning Disabilities

634
Learning disabilities are cognitive disorders caused by neurological impairments that affect cognitive functions like language and reading, without indicating overall intellectual or developmental challenges. These disabilities differ from global intellectual or developmental disabilities as they are limited to distinct cognitive functions. Common learning disabilities include dysgraphia, dyslexia, and dyscalculia, each of which impacts unique aspects of learning.
Dyslexia
Dyslexia is a...
634

You might also read

Related Articles

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

Sort by
Same author

The salience of an agency experience influences its ability to improve memory.

Psychological research·2024
Same author

Predicting cognitive scores from wearable-based digital physiological features using machine learning: data from a clinical trial in mild cognitive impairment.

BMC medicine·2024
Same author

Probabilistic and rich individual working memories revealed by a betting game.

Scientific reports·2023
Same author

Attention and expectation likely underlie temporal binding measured using the Libet Clock.

Quarterly journal of experimental psychology (2006)·2022
Same author

Perception is rich and probabilistic.

Scientific reports·2022
Same author

How do expectations change behavior? Investigating the contributions at encoding versus decision-making.

Journal of experimental psychology. Learning, memory, and cognition·2022
Same journal

Predictive models and parameter analysis for multiple tactile perceptions in skin-wet fabrics interface.

Perception·2026
Same journal

High-resolution kitsch by AI: Why society needs art, not more AI content.

Perception·2026
Same journal

Benchmarking spatial discrimination thresholds of two-frame motion defined forms compared to luminance and stereoscopic defined forms.

Perception·2026
Same journal

The effect of face masks on the perception of trustworthiness and competence in individuals with autistic traits.

Perception·2026
Same journal

The importance of external features for categorizing ethnicity: can Koreans identify Korean, Japanese, and Chinese faces?

Perception·2026
Same journal

Interoception, alexithymia, and motor congruency: Psychological drivers of body ownership in virtual reality.

Perception·2026
See all related articles

Related Experiment Video

Updated: Feb 11, 2026

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task
11:18

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task

Published on: June 1, 2015

11.2K

Learning in the Target Prevalence Effect.

Nicholas Hon1, Syaheed B Jabar2

  • 1Department of Psychology, National University of Singapore, Singapore.

Perception
|April 28, 2018
PubMed
Summary
This summary is machine-generated.

Learning target probabilities requires consistent experience, regardless of the probability value. This study shows that acquiring knowledge about target occurrence probability is similar across different values, impacting mental task representations and attention.

Keywords:
attentioncognitiontarget detectiontarget probability

More Related Videos

Evaluation of Colorectal Cancer Risk and Prevalence by Stool DNA Integrity Detection
07:35

Evaluation of Colorectal Cancer Risk and Prevalence by Stool DNA Integrity Detection

Published on: June 8, 2020

7.5K
Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
12:06

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

4.8K

Related Experiment Videos

Last Updated: Feb 11, 2026

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task
11:18

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task

Published on: June 1, 2015

11.2K
Evaluation of Colorectal Cancer Risk and Prevalence by Stool DNA Integrity Detection
07:35

Evaluation of Colorectal Cancer Risk and Prevalence by Stool DNA Integrity Detection

Published on: June 8, 2020

7.5K
Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
12:06

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

4.8K

Area of Science:

  • Cognitive Psychology
  • Human Factors
  • Perception

Background:

  • Detection of rare targets is often less accurate than high-prevalence targets.
  • Understanding target probability is crucial before performance deficits emerge.

Purpose of the Study:

  • To determine the amount of target experience needed to fully learn target probabilities.
  • To investigate how target probabilities are integrated into mental task representations.

Main Methods:

  • Experiment 1: Learning target probabilities from a naive starting point.
  • Experiment 2: Recalibrating existing knowledge of target probabilities.
  • Quantifying the target sampling required for probability acquisition.

Main Results:

  • The amount of target experience needed to learn probabilities was similar across different probability values.
  • This learning rate held true for both initial learning and recalibration scenarios.
  • Findings suggest a consistent learning mechanism for target probabilities.

Conclusions:

  • Mental task representations adapt to new information, including target probabilities.
  • The acquisition of target probability information influences attentional processes.
  • Consistent target sampling is key for updating internal probability models.