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

Types of Errors: Detection and Minimization

Types of Errors: Detection and Minimization

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...

Propagation of Uncertainty from Random Error

Propagation of Uncertainty from Random Error

An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...

Propagation of Uncertainty from Systematic Error

Propagation of Uncertainty from Systematic Error

The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...

Accuracy and Errors in Hypothesis Testing

Accuracy and Errors in Hypothesis Testing

Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...

Random and Systematic Errors

Random and Systematic Errors

Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...

Cognitive Learning

Cognitive Learning

Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...

You might also read

Related Articles

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

Sort by

Same author

From Sensory Details to Verbal Codes: Visual Memory Reinstatement of Location and Color Features.

bioRxiv : the preprint server for biology·2026

Same author

Insight predicts subsequent memory via cortical representational change and hippocampal activity.

Nature communications·2025

Same author

Surprise!-Clarifying the link between insight and prediction error.

Psychonomic bulletin & review·2024

Same author

Cognitive enhancement: Effects of methylphenidate, modafinil, and caffeine on latent memory and resting state functional connectivity in healthy adults.

Human brain mapping·2022

Same author

Assessing creativity independently of language: A language-independent remote associate task (LI-RAT).

Behavior research methods·2022

Same author

Between automatic and control processes: How relationships between problem elements interact to facilitate or impede insight.

Memory & cognition·2022

Search research articles

Related Experiment Video

Updated: Jun 25, 2025

Errors as a Means of Reducing Impulsive Food Choice

Errors as a Means of Reducing Impulsive Food Choice

Published on: June 5, 2016

Prediction error minimization as a common computational principle for curiosity and creativity.

Maxi Becker¹, Roberto Cabeza^1,2

¹Department of Psychology, Humboldt University Berlin, Berlin, Germany maxi.becker@gmx.net; maxi.becker@hu-berlin.de.

The Behavioral and Brain Sciences

|May 21, 2024

Summary

This study proposes that minimizing prediction errors, the mismatch between expectations and reality, drives both curiosity and creativity. Curiosity anticipates future error reduction, while creative insights achieve it with novel information.

More Related Videos

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities

Published on: September 11, 2021

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

Published on: January 5, 2018

Related Experiment Videos

Last Updated: Jun 25, 2025

Errors as a Means of Reducing Impulsive Food Choice

Errors as a Means of Reducing Impulsive Food Choice

Published on: June 5, 2016

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities

Published on: September 11, 2021

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

Published on: January 5, 2018

Area of Science:

Cognitive Science
Computational Neuroscience
Psychology

Background:

Creativity and curiosity are often linked to novelty-seeking behaviors.
The underlying computational mechanisms driving these phenomena remain incompletely understood.

Purpose of the Study:

To propose a unified computational principle underlying both curiosity and creativity.
To link novelty-seeking to the minimization of prediction errors.

Main Methods:

Theoretical framework development.
Conceptual analysis linking prediction error minimization to curiosity and creative insight.

Main Results:

Novelty-seeking in creativity and curiosity can be computationally explained by minimizing prediction errors.
Curiosity is associated with the anticipation of future prediction error reduction.
Creative "AHA" moments are linked to the successful minimization of prediction errors with novel information.

Conclusions:

Minimizing prediction errors provides a unifying computational basis for understanding curiosity and creativity.
This framework offers new avenues for investigating the cognitive and neural underpinnings of insight and exploration.