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

Hierarchy of Motor Control01:18

Hierarchy of Motor Control

6.5K
The hierarchy of motor control refers to the different levels of organization and processing involved in controlling movement in the body. These levels range from higher cortical areas involved in planning and decision-making to lower spinal cord reflexes that respond automatically to external stimuli.
6.5K
Storage01:23

Storage

452
A schema is a mental framework that helps individuals organize and interpret information. Schemata, formed from previous experiences, influence how we process new information: how we encode it, the inferences we make, and how we retrieve it. For instance, a schema for what a typical classroom looks like might include desks, a teacher's desk, a whiteboard, and students in such an environment. This expectation helps us quickly understand and navigate new classrooms without needing to analyze...
452
Neural Circuits01:25

Neural Circuits

3.1K
Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
3.1K
Real-World Application of Classical Conditioning01:15

Real-World Application of Classical Conditioning

1.8K
Classical conditioning not only includes the initial pairing of stimuli but also extends to more complex forms, such as higher-order conditioning. Higher-order conditioning involves creating associations beyond the primary conditioned stimulus, resulting in a chain of conditioned responses.
Higher-order, or second-order, conditioning occurs when a neutral stimulus becomes associated with an already established conditioned stimulus through repeated pairings. For instance, if a dog has been...
1.8K
Impact of Schemas01:30

Impact of Schemas

242
Schemas are cognitive structures that provide a framework for interpreting and organizing social information. They help individuals navigate complex environments by offering expectations about people, events, and behaviors. Schemas influence attention, encoding, and retrieval processes, thereby shaping the entire trajectory of information processing in social contexts.Attention and Cognitive LoadDuring initial attention, schemas function as filters that prioritize schema-consistent information,...
242
The Nativist Approach01:21

The Nativist Approach

529
The nativist approach to infant cognitive development proposes that infants are born with inherent knowledge structures that allow them to interpret the world almost immediately. This perspective contrasts with earlier developmental theories, such as those proposed by Jean Piaget, which emphasized a more gradual acquisition of cognitive abilities through interaction with the environment. One key concept in this approach is object permanence — the understanding that objects continue to...
529

You might also read

Related Articles

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

Sort by
Same author

Wordsworth: A generative word dataset for comparison of speech representations in humans and neural networks.

Scientific data·2025
Same author

Multimodal AI needs active human interaction.

Nature human behaviour·2024
Same author

Probing the Structure and Functional Properties of the Dropout-Induced Correlated Variability in Convolutional Neural Networks.

Neural computation·2024
Same author

Generalizing biological surround suppression based on center surround similarity via deep neural network models.

PLoS computational biology·2023
Same author

SymbiQuant: A Machine Learning Object Detection Tool for Polyploid Independent Estimates of Endosymbiont Population Size.

Frontiers in microbiology·2022
Same author

Inference via sparse coding in a hierarchical vision model.

Journal of vision·2022

Related Experiment Video

Updated: Mar 6, 2026

Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

794

Behavioral and neural constraints on hierarchical representations.

Odelia Schwartz1, Luis Gonzalo Sanchez Giraldo2

  • 1Department of Computer Science, University of Miami, Miami, FL, USAodelia@cs.miami.edu.

Journal of Vision
|March 21, 2017
PubMed
Summary

The brain represents sensory stimuli using hierarchical structures, particularly for images. Understanding these neural representations can inform artificial intelligence and computer vision through better experimental design and modeling.

More Related Videos

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
09:01

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

10.6K
Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
07:34

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

18.0K

Related Experiment Videos

Last Updated: Mar 6, 2026

Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

794
A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
09:01

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

10.6K
Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
07:34

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

18.0K

Area of Science:

  • Neuroscience
  • Cognitive Science
  • Computer Vision

Background:

  • Neural systems represent sensory stimuli, but how the brain exploits environmental structure is unknown.
  • Hierarchical structures are prevalent in sensory data, especially images.
  • Understanding these structures is key to behavior and cognition.

Purpose of the Study:

  • Investigate how the brain captures and utilizes hierarchical structures in sensory representations.
  • Explore the role of hierarchies in image representation within neural systems.
  • Bridge the gap between neuroscience and machine learning for improved models.

Main Methods:

  • Review experimental approaches from inference, memory recall, and visual adaptation.
  • Analyze hierarchical models of image representation.
  • Discuss the integration of machine learning and computer vision.

Main Results:

  • Hierarchical representations are constrained by various experimental approaches.
  • Hierarchical models offer insights into how the world's structure is reflected biologically.
  • Current methods can be enhanced by incorporating natural scene statistics and synthetic stimuli.

Conclusions:

  • A deeper integration of machine learning and computer vision is needed for experimental design and interpretation.
  • Utilizing knowledge of natural scene structure and creating hierarchical synthetic stimuli can advance research.
  • This approach can clarify how biological systems represent hierarchical environmental regularities.