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

Confidence Coefficient01:24

Confidence Coefficient

10.5K
The confidence coefficient is also known as the confidence level or degree of confidence. It is the percent expression for the probability, 1-α, that the confidence interval contains the true population parameter assuming that the confidence interval is obtained after sufficient unbiased sampling; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter. Here α is the area under the curve, distributed equally under...
10.5K
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

100.1K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
100.1K
Confidence Intervals01:21

Confidence Intervals

10.2K
An unbiased point estimate is often insufficient to predict a population estimate, such as population mean or population proportion. In this scenario, a confidence interval is used. A confidence interval is an estimate similar to a  sample proportion. However, unlike the point estimate which is a single value, the confidence interval  contains a range of values. These values have lower and upper limits, known as confidence limits, and can be designated as L1 and L2, respectively.
A...
10.2K
Improving Translational Accuracy02:07

Improving Translational Accuracy

14.1K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
14.1K
Uncertainty: Confidence Intervals00:54

Uncertainty: Confidence Intervals

10.2K
The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...
10.2K
Interpretation of Confidence Intervals01:19

Interpretation of Confidence Intervals

9.4K
A confidence interval is a better estimate of the population than a point estimate, as it uses a range of values from a sample instead of a single value.
Confidence intervals have confidence coefficients that are crucial for their interpretation. The most common confidence coefficients are 0.90, 0.95, and 0.99, which can be written as percentages–90%, 95%, and 99%, respectively.
Suppose a person calculates a confidence interval with a confidence coefficient of 0.95. In that case, they can...
9.4K

You might also read

Related Articles

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

Sort by
Same author

Robust evidence for theta-band rhythmicity in behavior across two dense-sampling datasets.

Communications psychology·2026
Same author

Adaptive variability in humans, pigeons, and rats.

Psychological review·2026
Same author

Investigating the analytical robustness of the social and behavioural sciences.

Nature·2026
Same author

Rhythmic sampling of multiple decision alternatives in the human brain.

Nature communications·2026
Same author

Cognitive flexibility versus stability via activation-based and weight-based adaptations.

Communications psychology·2026
Same author

Cortex-wide Dynamics of Internal Decisions About Behavioral Context.

bioRxiv : the preprint server for biology·2025

Related Experiment Video

Updated: Jan 20, 2026

Importance of Jumping Ability in Handball Throwing Speed and Accuracy
02:43

Importance of Jumping Ability in Handball Throwing Speed and Accuracy

Published on: April 4, 2025

1.3K

Confidence predicts speed-accuracy tradeoff for subsequent decisions.

Kobe Desender1,2, Annika Boldt3, Tom Verguts2

  • 1Department of Neurophysiology and Pathophysiology, University Medical Center, Hamburg, Germany.

Elife
|August 21, 2019
PubMed
Summary

Agents adjust decision-making speed and accuracy using internal decision confidence. Low confidence leads to slower, more accurate choices in subsequent decisions, as shown by EEG signals.

Keywords:
EEGERNPeconfidencedecision makingdrift diffusion modelinghumanneuroscience

More Related Videos

A Task for Assessing the Impact of a Partner on the Speed and Accuracy of Motor Performance in Rats
06:17

A Task for Assessing the Impact of a Partner on the Speed and Accuracy of Motor Performance in Rats

Published on: October 17, 2019

5.2K
A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

69.7K

Related Experiment Videos

Last Updated: Jan 20, 2026

Importance of Jumping Ability in Handball Throwing Speed and Accuracy
02:43

Importance of Jumping Ability in Handball Throwing Speed and Accuracy

Published on: April 4, 2025

1.3K
A Task for Assessing the Impact of a Partner on the Speed and Accuracy of Motor Performance in Rats
06:17

A Task for Assessing the Impact of a Partner on the Speed and Accuracy of Motor Performance in Rats

Published on: October 17, 2019

5.2K
A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

69.7K

Area of Science:

  • Cognitive Neuroscience
  • Decision Science
  • Computational Neuroscience

Background:

  • Agents often make decisions without external feedback, necessitating internal mechanisms to guide policy adaptation.
  • Decision confidence, an internal estimate of choice correctness, is crucial for adapting decision-making strategies.

Purpose of the Study:

  • To investigate how decision confidence influences the speed-accuracy tradeoff in decision-making.
  • To determine if confidence signals predict adjustments in decision policies.

Main Methods:

  • Fitting a bounded accumulation decision model to behavioral data from three perceptual choice tasks.
  • Analyzing electroencephalography (EEG) data, specifically a centro-parietal component sensitive to confidence.
  • Correlating reported confidence from previous trials with decision bounds in subsequent trials.

Main Results:

  • Decision bounds were significantly influenced by previous trial confidence, irrespective of objective accuracy.
  • Increased decision bounds, indicating slower and potentially more accurate decisions, were predicted by confidence-sensitive EEG signals.
  • Behavioral data supported the hypothesis that confidence modulates the speed-accuracy tradeoff.

Conclusions:

  • Internally generated neural signals of decision confidence play a key role in dynamically adjusting decision policies.
  • Confidence serves as a critical internal signal for optimizing the balance between decision speed and accuracy.
  • The findings provide neural evidence for confidence-based adaptation of decision-making strategies.