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

Schemas01:42

Schemas

12.2K
A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.
12.2K
Fixed Action Patterns01:06

Fixed Action Patterns

17.0K
A fixed action pattern (FAP) is a specific, hard-wired sequence of behaviors that occurs in response to an external stimulus, called a sign stimulus. The behavior is “fixed” because it is essentially unchangeable—proceeding similarly across individuals of a species every time it occurs.
17.0K
End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

909
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
909

You might also read

Related Articles

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

Sort by
Same author

Competition Between Memory Updating and Differentiation Emerges From Intrinsic Network Dynamics.

Neural computation·2026
Same author

PriMAT: Robust multi-animal tracking of primates in the wild.

PloS one·2026
Same author

Kinematic modulation across the ontogenetic transition to active social engagement.

Early human development·2026
Same author

To update or to separate: Neural signatures and consequences of latent cause inference in episodic memory.

NeuroImage·2026
Same author

InFoRM: a unified inverse and forward model for sensorimotor control.

Scientific reports·2026
Same author

Self-serving biases shape the relationship between future thinking and remembering of elections.

Communications psychology·2026

Related Experiment Video

Updated: Nov 24, 2025

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

9.3K

Using enriched semantic event chains to model human action prediction based on (minimal) spatial information.

Fatemeh Ziaeetabar1, Jennifer Pomp2, Stefan Pfeiffer1

  • 1Institute for Physics 3 - Biophysics and Bernstein Center for Computational Neuroscience (BCCN), University of Göttingen, Göttingen, Germany.

Plos One
|December 28, 2020
PubMed
Summary
This summary is machine-generated.

Humans can predict actions using only spatial relationships between abstract objects, relying on a mixed-cue strategy. This understanding aids in developing robots for better human-robot cooperation.

More Related Videos

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

4.8K

Related Experiment Videos

Last Updated: Nov 24, 2025

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

9.3K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

4.8K

Area of Science:

  • Cognitive Science
  • Human-Computer Interaction
  • Robotics

Background:

  • Predicting actions is crucial for social interaction.
  • Previous research identified object, movement, and identity cues for action prediction.
  • The role of changing spatial relations between objects was less understood.

Purpose of the Study:

  • To investigate how humans use static and dynamic inter-object spatial relations to predict actions.
  • To compare human action prediction strategies with a computational model (enriched Semantic Event Chain - eSEC).

Main Methods:

  • Developed a virtual reality (VR) setup with abstract cube objects to isolate spatial relation cues.
  • Tested human recognition speed for ten manipulation actions based solely on spatial changes.
  • Utilized information-theoretical analysis and the eSEC model to analyze prediction strategies.

Main Results:

  • Participants predicted actions within 64% of the action's duration, relying only on spatial cues.
  • Information-theoretical analysis indicated humans employ a mixed-cue strategy for action prediction.
  • The enriched Semantic Event Chain (eSEC) model demonstrated machine-based prediction can be faster using individual cues.

Conclusions:

  • Human action prediction, while slower than machine-based, effectively integrates multiple spatial cues.
  • This mixed-cue strategy may be advantageous for complex, naturalistic actions with variable information.
  • Findings advance the understanding of action goal inference and inform robot design for human-robot cooperation.