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

Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

2.1K
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...
2.1K
Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

1.5K
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...
1.5K
Uncertainty: Overview00:59

Uncertainty: Overview

1.8K
In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
1.8K
Random and Systematic Errors01:20

Random and Systematic Errors

15.7K
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...
15.7K
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

112.7K
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. 
112.7K
Uncertainty: Confidence Intervals00:54

Uncertainty: Confidence Intervals

11.9K
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...
11.9K

You might also read

Related Articles

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

Sort by
Same author

Predictive Processing Over the Course of Aging: Multiple Timescales of Effective Connectivity.

The European journal of neuroscience·2026
Same author

Mismatch negativity: A systematic review of the spatiotemporal pattern of adaptation and prediction error in MMN.

Neuroscience and biobehavioral reviews·2026
Same author

Auditory Inference and Long-Term Modulation of Excitation and Inhibition.

Psychophysiology·2025
Same author

Temporal Trajectories of Mismatch Negativity Reveal Dynamics of Auditory Perceptual Learning.

The European journal of neuroscience·2025
Same author

From Näätänen to now: Moving the Mismatch Negativity into the Next 50 Years.

Clinical EEG and neuroscience·2024
Same author

Contextualised Processing of Stimuli Modulates Auditory Mismatch Responses in the Rat.

Clinical EEG and neuroscience·2024

Related Experiment Video

Updated: Mar 8, 2026

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
08:05

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

8.2K

Initial uncertainty impacts statistical learning in sound sequence processing.

Juanita Todd1, Alexander Provost1, Lisa Whitson1

  • 1School of Psychology, University of Newcastle, Newcastle, Australia.

Journal of Physiology, Paris
|January 16, 2017
PubMed
Summary
This summary is machine-generated.

Early learning significantly impacts how the brain processes new sounds. Initial exposure to predictable or unpredictable auditory patterns influences subsequent sound relevance filtering, even during incidental learning.

Keywords:
Auditory evoked potentialsMismatch negativityPredictive codingPrimacy biasSequential learning

More Related Videos

Infant Auditory Processing and Event-related Brain Oscillations
06:34

Infant Auditory Processing and Event-related Brain Oscillations

Published on: July 1, 2015

17.0K
Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

10.8K

Related Experiment Videos

Last Updated: Mar 8, 2026

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
08:05

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

8.2K
Infant Auditory Processing and Event-related Brain Oscillations
06:34

Infant Auditory Processing and Event-related Brain Oscillations

Published on: July 1, 2015

17.0K
Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

10.8K

Area of Science:

  • Neuroscience
  • Auditory Perception
  • Cognitive Psychology

Background:

  • The auditory system forms prediction models based on regular sound patterns.
  • Auditory evoked potentials (AEPs) reflect the strength of these prediction models.
  • Incidental learning can occur even when attention is directed elsewhere.

Purpose of the Study:

  • To investigate the lasting impact of initial auditory learning on subsequent experience.
  • To determine how predictability influences early relevance-filtering processes.
  • To examine the role of probability and predictability in updating auditory prediction models.

Main Methods:

  • Two studies exposed participants to auditory sequences with local and longer-term patterns.
  • Deviating tones (rare or common) were introduced into the sound sequences.
  • Auditory evoked potentials were measured while participants focused on a movie.

Main Results:

  • Auditory evoked potentials showed lasting modulatory influences based on initial tone predictability.
  • The initial status of a tone (rare vs. common) affected how prediction models were updated.
  • These effects were observed for both common and rare tone occurrences.

Conclusions:

  • Initial learning profoundly influences how the brain weights subsequent auditory experiences.
  • Predictability, rather than raw probability, may trigger value-based learning modulations.
  • These findings suggest that uncertainty drives learning even in task-irrelevant contexts.