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

False Memories01:18

False Memories

333
False memories represent a cognitive distortion in which individuals recall events that did not happen, or remember them in an altered form. This phenomenon highlights the brain's constructive nature in processing and recalling memories, emphasizing that memory is not a perfect representation of past events but rather a dynamic reconstruction influenced by various factors.
One primary source of false memories is misattribution, where individuals incorrectly associate external information...
333
Understanding Deception01:14

Understanding Deception

130
Deception is a pervasive aspect of human communication. Empirical studies have shown that most individuals engage in some form of deceit on a daily basis, with approximately 20% of social exchanges involving deceptive elements. Lying follows a developmental trajectory, peaking during adolescence and declining with age, possibly due to the maturation of cognitive control and social accountability.Cognitive and Social Factors in Deception DetectionDespite its prevalence, accurately detecting...
130
Self-Discrepancy Theory02:45

Self-Discrepancy Theory

18.8K
One influential perspective on what motivates people's behavior is detailed in Tory Higgin's self-discrepancy theory (Higgins, 1987). He proposed that people hold disagreeing internal representations of themselves that lead to different emotional states.  
18.8K
Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

6.8K
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
6.8K
Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

9.3K
Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
9.3K
Difference from Background: Limit of Detection01:05

Difference from Background: Limit of Detection

8.0K
The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...
8.0K

You might also read

Related Articles

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

Sort by
Same author

The role of goals and outcomes in young children's memory for actions.

Cognitive processing·2020
Same author

Kindergarten children's event memory: the role of action prediction in remembering.

Cognitive processing·2019
Same author

Reflecting on how we remember the personal past: missing components in the study of memory appraisal and theoretical implications.

Memory (Hove, England)·2017
Same author

False memories and the DRM paradigm: effects of imagery, list, and test type.

The Journal of general psychology·2016
Same author

Source misattributions and false recognition errors: examining the role of perceptual resemblance and imagery generation processes.

Memory (Hove, England)·2014
Same author

Collaborative encoding and memory accuracy: examining the effects of interactive components of co-construction processes.

Journal of experimental psychology. Learning, memory, and cognition·2013

Related Experiment Video

Updated: Dec 31, 2025

The Deese-Roediger-McDermott DRM Task: A Simple Cognitive Paradigm to Investigate False Memories in the Laboratory
07:26

The Deese-Roediger-McDermott DRM Task: A Simple Cognitive Paradigm to Investigate False Memories in the Laboratory

Published on: January 31, 2017

39.5K

Is it all in the details? Description content and false recognition errors.

Rebecca Brooke Bays1, Mary Ann Foley2, Annelise Cohen2

  • 1Department of Psychology, Oglethorpe University, 4484 Peachtree Road, Atlanta, GA, 30319, USA. rbays@Oglethorpe.edu.

Cognitive Processing
|January 6, 2020
PubMed
Summary

Detailed scene descriptions increase memory errors, particularly false recognition, by enhancing vivid imagination. This suggests encoding vividness influences memory accuracy for related items.

Keywords:
Description contentFalse recognitionImagerySource monitoring

More Related Videos

Using a Classroom-Based Deese Roediger McDermott Paradigm to Assess the Effects of Imagery on False Memories
08:53

Using a Classroom-Based Deese Roediger McDermott Paradigm to Assess the Effects of Imagery on False Memories

Published on: November 14, 2018

10.1K
Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
07:34

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

17.8K

Related Experiment Videos

Last Updated: Dec 31, 2025

The Deese-Roediger-McDermott DRM Task: A Simple Cognitive Paradigm to Investigate False Memories in the Laboratory
07:26

The Deese-Roediger-McDermott DRM Task: A Simple Cognitive Paradigm to Investigate False Memories in the Laboratory

Published on: January 31, 2017

39.5K
Using a Classroom-Based Deese Roediger McDermott Paradigm to Assess the Effects of Imagery on False Memories
08:53

Using a Classroom-Based Deese Roediger McDermott Paradigm to Assess the Effects of Imagery on False Memories

Published on: November 14, 2018

10.1K
Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
07:34

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

17.8K

Area of Science:

  • Cognitive Psychology
  • Memory Research

Background:

  • The Deese-Roediger-McDermott (DRM) paradigm is a standard tool for studying false memory.
  • Embellished content may influence memory recall and recognition accuracy.

Purpose of the Study:

  • To investigate how embellished content in scene descriptions affects memory errors.
  • To determine if visualization instructions impact these memory errors.

Main Methods:

  • Participants listened to DRM items embedded in either detailed or general scene descriptions.
  • A modified DRM paradigm was employed across three experiments.
  • Visualization instructions were used as an encoding manipulation.

Main Results:

  • Detailed scene descriptions led to higher false recognition errors compared to general references.
  • Varying description details within an encoding series did not significantly alter false recognition.
  • More detailed content correlated with more vivid imagination, potentially explaining increased false recognition.

Conclusions:

  • Embellished encoding, particularly detailed scene descriptions, can increase false recognition errors.
  • Vivid imagination may mediate the relationship between detailed content and memory errors.
  • Encoding task details significantly influence the occurrence of memory distortions.