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

Expected Value01:15

Expected Value

7.8K
The expected value is known as the "long-term" average or mean. This means that over the long term of experimenting over and over, you would expect this average. The expected average is represented by the symbol μ. It is calculated as follows:
7.8K
Testing a Claim about Mean: Unknown Population SD01:21

Testing a Claim about Mean: Unknown Population SD

6.3K
A complete procedure of testing a hypothesis about a population mean when the population standard deviation is unknown is explained here.
Estimating a population mean requires the samples to be approximately normally distributed. The data should be collected from the randomly selected samples having no sampling bias. There is no specific requirement for sample size. But if the sample size is less than 30, and we don't know the population standard deviation, a different approach is used;...
6.3K
Determination of Expected Frequency01:08

Determination of Expected Frequency

2.6K
Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
2.6K
Predicting Molecular Geometry02:27

Predicting Molecular Geometry

46.1K
VSEPR Theory for Determination of Electron Pair Geometries
46.1K
Estimating Population Mean with Unknown Standard Deviation01:22

Estimating Population Mean with Unknown Standard Deviation

8.9K
In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the...
8.9K
Frequency-dependent Selection01:21

Frequency-dependent Selection

24.2K
When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
24.2K

You might also read

Related Articles

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

Sort by
Same author

The ins and outs of unpacking the black box: Understanding motivation using a multi-level approach.

The Behavioral and brain sciences·2025
Same author

Challenge or threat? A Q-methodological study into nursing students' perceptions on learning to collaborate under stress.

Nurse education today·2024
Same author

Food-related exploration across the menstrual cycle.

Appetite·2024
Same author

When routine becomes stressful: A qualitative study into resuscitation team members' perception of stress and performance.

Journal of interprofessional care·2023
Same author

Novelty-induced memory boosts in humans: The when and how.

Heliyon·2023
Same author

Novelty processing depends on medial temporal lobe structures.

Neurobiology of learning and memory·2021
Same journal

IGFBP3 and UBE2C are associated with protein modification pathways and serve as prognostic markers in glioma.

Brain research·2026
Same journal

Targeting neurodevelopmental miR132-3p promotes neuroprotection and axon regeneration after optic nerve injury in mice.

Brain research·2026
Same journal

Variability in acoustic startle response and prepulse inhibition across adulthood in Fragile X messenger ribonucleoprotein 1 knockout mice.

Brain research·2026
Same journal

Transcriptome-guided modeling reveals insulin-related metabolic dysfunction in SCA3 mouse cerebellum.

Brain research·2026
Same journal

Intranasal stromal cell-derived factor-1α mitigates parkinsonian deficits via dual modulation of neuroinflammation and gut microbiota in MPTP-induced models.

Brain research·2026
Same journal

Emotions, the amygdala, and the right hemisphere.

Brain research·2026
See all related articles

Related Experiment Video

Updated: Feb 10, 2026

Sucrose Preference and Novelty-Induced Hypophagia Tests in Rats using an Automated Food Intake Monitoring System
07:33

Sucrose Preference and Novelty-Induced Hypophagia Tests in Rats using an Automated Food Intake Monitoring System

Published on: May 8, 2020

11.4K

Predicting the unknown: Novelty processing depends on expectations.

J Schomaker1, M Meeter2

  • 1Department of Psychology, Justus Liebig University Giessen, Germany.

Brain Research
|May 15, 2018
PubMed
Summary
This summary is machine-generated.

Expectations significantly influence how the brain processes novel stimuli. Anticipating novelty enhances its initial detection but reduces the orienting response, demonstrating the impact of prediction on novelty processing.

Keywords:
Event-related potentialsExpectationsNoveltyNovelty P3Repetition

More Related Videos

In Vivo Two-photon Imaging Of Experience-dependent Molecular Changes In Cortical Neurons
10:07

In Vivo Two-photon Imaging Of Experience-dependent Molecular Changes In Cortical Neurons

Published on: January 5, 2013

22.3K
Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

7.7K

Related Experiment Videos

Last Updated: Feb 10, 2026

Sucrose Preference and Novelty-Induced Hypophagia Tests in Rats using an Automated Food Intake Monitoring System
07:33

Sucrose Preference and Novelty-Induced Hypophagia Tests in Rats using an Automated Food Intake Monitoring System

Published on: May 8, 2020

11.4K
In Vivo Two-photon Imaging Of Experience-dependent Molecular Changes In Cortical Neurons
10:07

In Vivo Two-photon Imaging Of Experience-dependent Molecular Changes In Cortical Neurons

Published on: January 5, 2013

22.3K
Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

7.7K

Area of Science:

  • Cognitive Neuroscience
  • Neuroscience
  • Psychology

Background:

  • Repetition suppression demonstrates neural adaptation to familiar stimuli.
  • The generalization of these effects to broader categories and the processing of novelty remain less understood.

Purpose of the Study:

  • To investigate how expectations influence the neural processing of novel stimuli.
  • To differentiate the effects of violated expectations from stimulus repetition on novelty detection.

Main Methods:

  • Utilized event-related potentials (ERPs) to measure neural responses.
  • Employed a continuous stimulus sequence with predictable cues for standard and novel stimuli.
  • Introduced unexpected novel stimuli and analyzed responses to expected vs. unexpected novelty, and novelty following other novel stimuli.

Main Results:

  • Expected novel stimuli showed enhanced initial detection (larger anterior N2) compared to unexpected novel stimuli.
  • The orienting response (novelty P3) was reduced for expected novels versus unexpected ones.
  • Category repetition of novel stimuli also affected processing, showing an enhanced anterior N2 and reduced novelty P3.

Conclusions:

  • Novelty processing is modulated by prior expectations.
  • Both the anticipation of novelty and the sequential presentation of novel stimuli impact neural responses.