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

Vision01:24

Vision

59.2K
Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
59.2K
Motor and Sensory Areas of the Cortex01:14

Motor and Sensory Areas of the Cortex

6.8K
The cerebral cortex, the brain's outermost layer, is pivotal in processing complex cognitive tasks, emotions, and various sensory inputs and executing voluntary motor activities. This intricate structure is divided into three primary functional areas: the motor areas, sensory areas, and association areas.
Motor Areas
The motor areas located in the frontal lobe are central to controlling voluntary movements. This region is further subdivided into the primary motor cortex and the premotor cortex....
6.8K
Visual System01:26

Visual System

1.6K
Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...
1.6K
Somatosensory, Motor, and Association Cortex01:23

Somatosensory, Motor, and Association Cortex

2.2K
The somatosensory cortex in the parietal lobes is crucial for interpreting sensory data such as touch, temperature, and proprioception. The somatosensory cortex, situated in the parietal lobes, plays a vital role in interpreting sensory information like touch, temperature, and proprioception—awareness of body position. This specialized brain region features an organized structure wherein neurons at the top primarily process sensations originating from the lower body. In contrast, those at...
2.2K
Association Areas of the Cortex01:21

Association Areas of the Cortex

8.7K
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,...
8.7K
Anatomy of the Eyeball01:20

Anatomy of the Eyeball

9.4K
The eye is a spherical, hollow structure composed of three tissue layers. The outer layer — the fibrous tunic, comprises the sclera — a white structure — and the cornea, which is transparent. The sclera encompasses some of the ocular surface, most of which is not visible. However, the 'white of the eye' is distinctively visible in humans compared to other species. The cornea, a clear covering at the front of the eye, enables light penetration. The eye's middle...
9.4K

You might also read

Related Articles

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

Sort by
Same author

Dynamic categorization rules alter representations in human visual cortex.

Nature communications·2025
Same author

Dynamic categorization rules alter representations in human visual cortex.

bioRxiv : the preprint server for biology·2023
Same author

A Texture Statistics Encoding Model Reveals Hierarchical Feature Selectivity across Human Visual Cortex.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2023
Same author

Selectivity for food in human ventral visual cortex.

Communications biology·2023
Same author

Early experience with low-pass filtered images facilitates visual category learning in a neural network model.

PloS one·2023
Same author

Flexible utilization of spatial- and motor-based codes for the storage of visuo-spatial information.

eLife·2022
Same journal

On the clinical anatomy of technological cognition.

Cognitive neuroscience·2026
Same journal

Increasing statistical power in functional MRI through permutation and multivariate statistics.

Cognitive neuroscience·2026
Same journal

fMRI research: do we need statistically better studies, larger studies, or no more studies?

Cognitive neuroscience·2026
Same journal

Catching the drift: EEG microstate dynamics resemble time-on-task changes in mind wandering and sustained attention.

Cognitive neuroscience·2026
Same journal

Toward a cognitive neuroscience of technology.

Cognitive neuroscience·2026
Same journal

What behavioral relevance is (not).

Cognitive neuroscience·2026
See all related articles

Related Experiment Video

Updated: Jan 10, 2026

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping
07:11

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Published on: December 8, 2023

2.3K

Visual input statistics and behavioral relevance jointly constrain higher visual cortex organization.

Margaret M Henderson1,2,3

  • 1Department of Psychology, Carnegie Mellon University, Pittsburgh, PA, USA.

Cognitive Neuroscience
|November 23, 2025
PubMed
Summary
This summary is machine-generated.

The brain's visual cortex organization is shaped by both what's behaviorally relevant and the statistical patterns in visual input. Understanding this interplay is key to visual system function.

Keywords:
Visiondeep neural networkfMRIhigher visual cortexnatural image statisticsobject recognition

More Related Videos

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

8.6K
Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior
09:49

Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior

Published on: April 16, 2014

26.8K

Related Experiment Videos

Last Updated: Jan 10, 2026

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping
07:11

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

Published on: December 8, 2023

2.3K
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

8.6K
Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior
09:49

Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior

Published on: April 16, 2014

26.8K

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Visual System Research

Background:

  • Current theories suggest higher visual cortex organization is driven by category selectivity.
  • Ritchie et al. propose behavioral relevance as a more fitting framework.
  • This work builds upon existing frameworks by incorporating additional constraints.

Purpose of the Study:

  • To propose that statistical structure of visual inputs is a critical constraint on visual cortex organization.
  • To integrate input statistics with behavioral relevance for a comprehensive understanding of the visual system.
  • To use cortical food selectivity as a case study and explore deep neural networks for testing these theories.

Main Methods:

  • Theoretical integration of behavioral relevance and input statistics.
  • Case study analysis of cortical food selectivity.
  • Exploration of deep neural network models for empirical testing.

Main Results:

  • The statistical structure of visual input is proposed as a crucial factor influencing visual cortex organization.
  • A unified framework accounting for both behavioral relevance and input statistics is presented.
  • Deep neural networks offer a viable method for testing hypotheses about visual system organization.

Conclusions:

  • A complete understanding of visual cortex organization requires considering both behavioral relevance and input statistics.
  • The proposed framework offers a more comprehensive view of visual system function.
  • Computational approaches, like deep neural networks, can significantly advance research in this area.