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

Association Areas of the Cortex01:21

Association Areas of the Cortex

Association areas are regions of the cerebral cortex that do not have a specific sensory or motor function. Instead, they integrate and interpret information from various sources to enable higher cognitive processes such as memory, learning, and decision-making. Some key association areas include the following:
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...
Centroid of a Body: Problem Solving01:03

Centroid of a Body: Problem Solving

The centroid of a body is a crucial concept in engineering and physics. Finding the centroid of a body can help determine its stability, its balance point, and even its design. In this context, consider a thin wire bent in the form of a quarter circular arc. Polar coordinates are used to calculate the centroid. The wire is first divided into small differential elements of a length equal to the radius multiplied by the differential angle.
The x-coordinates and y-coordinates of each element's...
Force Classification01:22

Force Classification

Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
Structural Classification of Joints01:20

Structural Classification of Joints

Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
Constraints and Statical Determinacy01:26

Constraints and Statical Determinacy

In structural engineering, the equilibrium of a system is not only determined by its equations of equilibrium but also with the help of constraints. Constraints refer to restrictions on the motion of a system. The proper combinations of constraints can minimize the total number of constraints needed to maintain a system in mechanical equilibrium. When this happens, the system is said to be statically determinate. For such systems, the unknown reaction supports can be estimated using equilibrium...
Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...

You might also read

Related Articles

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

Sort by
Same author

Development of Crowding Distance in Children Is Faster and Later Than Visual Acuity and Better Predicts Reading Performance.

Investigative ophthalmology & visual science·2026
Same author

An increasingly efficient narrowband object-recognition channel along the ventral stream.

bioRxiv : the preprint server for biology·2026
Same author

EasyEyes: Crowded dynamic fixation for online psychophysics.

Journal of vision·2026
Same author

Human V4 size predicts crowding distance.

Nature communications·2025
Same author

EasyEyes: Crowded Dynamic Fixation for Online Psychophysics.

bioRxiv : the preprint server for biology·2025
Same author

Benchmarking the speed-accuracy tradeoff in object recognition by humans and neural networks.

Journal of vision·2025
Same journal

Cichlid fish as a model for understanding social dysfunction.

Current opinion in neurobiology·2026
Same journal

On aims and methods in field neuroethology: Investigating neural mechanisms of behavior in semi-natural and natural contexts.

Current opinion in neurobiology·2026
Same journal

Neurobiological interfaces connecting environmental change to monarch butterfly migration.

Current opinion in neurobiology·2026
Same journal

Learning how to experience the world: From circuits to cell types to genes.

Current opinion in neurobiology·2026
Same journal

Editorial overview for neurobiology of disease 2026.

Current opinion in neurobiology·2026
Same journal

Optical voltage imaging: ready to spark systems neuroscience.

Current opinion in neurobiology·2026
See all related articles

Related Experiment Video

Updated: Jun 29, 2026

Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings
07:08

Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings

Published on: August 1, 2018

Crowding: a cortical constraint on object recognition.

Denis G Pelli1

  • 1Psychology and Neural Science, New York University, New York, NY 10003, USA. denis.pelli@nyu.edu

Current Opinion in Neurobiology
|October 7, 2008
PubMed
Summary
This summary is machine-generated.

Object recognition requires sufficient separation in the visual cortex (V1). Crowding occurs when objects are too close, limiting visual processing like reading and searching speed.

More Related Videos

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

Related Experiment Videos

Last Updated: Jun 29, 2026

Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings
07:08

Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings

Published on: August 1, 2018

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

Area of Science:

  • Neuroscience
  • Visual Perception
  • Computational Neuroscience

Background:

  • The external world is mapped retinotopically onto the primary visual cortex (V1).
  • Visual crowding, where objects closer than a critical spacing are unrecognizable, severely limits visual processing.
  • Understanding the spatial constraints of object recognition in V1 is crucial for visual neuroscience.

Purpose of the Study:

  • To determine the critical spacing requirements for object recognition in the primary visual cortex (V1).
  • To investigate the relationship between visual field eccentricity and cortical spacing.
  • To explore the neural basis of visual crowding.

Main Methods:

  • Psychophysical measurements of critical spacing in the visual field.
  • Anatomical analysis of the retinotopic map in V1.
  • Computational modeling of 'combining fields' implemented by cortical neurons.

Main Results:

  • Critical spacing in V1 is proportional to object eccentricity (radial) and fixed at equal eccentricity (circumferential).
  • Critical spacing is independent of object size and type.
  • The cortical representation of the visual field is logarithmic with eccentricity, aligning with observed spacing.
  • A fixed number of cortical neurons can account for the measured 'combining fields'.

Conclusions:

  • Object recognition in V1 depends on specific spatial separations, with crowding occurring below critical thresholds.
  • The logarithmic cortical map explains the eccentricity-dependent spacing observed.
  • Visual crowding is a fundamental limitation explained by the neural implementation of visual processing in V1.