Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Vision

Vision

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.

Visual System

Visual System

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...

Anatomy of the Eyeball

Anatomy of the Eyeball

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...

Motor and Sensory Areas of the Cortex

Motor and Sensory Areas of the Cortex

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....

Association Areas of the Cortex

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,...

Color Vision

Color Vision

Color perception begins in the retina, the light-sensitive layer at the back of the eye. Two main theories explain how colors are seen: the trichromatic theory and the opponent-process theory. The trichromatic theory, proposed by Thomas Young in 1802 and extended by Hermann von Helmholtz in 1852, suggests that color vision is based on three types of cone receptors in the retina. These cones are sensitive to different but overlapping ranges of wavelengths corresponding to red, blue, and green.

You might also read

Related Articles

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

Sort by

Same author

Nasal and oral breathing modes reconfigure brain network dynamics between stabilizing integration and promoting fragmentation.

Scientific reports·2026

Same author

Breathing mode selectively modulates brain-wide functional connectivity.

PloS one·2025

Same author

Generation of synthetic CT from MRI for MRI-based attenuation correction of brain PET images using radiomics and machine learning.

Medical physics·2025

Same author

Classification of female MDD patients with and without suicidal ideation using resting-state functional magnetic resonance imaging and machine learning.

Frontiers in human neuroscience·2025

Same author

Attention modulates human visual responses to objects by tuning sharpening.

eLife·2024

Same author

Two "What" Networks in the Human Brain.

Journal of cognitive neuroscience·2024

Same journal

Non-canonical amino acid incorporation enables minimally disruptive labeling of stress granule and TDP-43 proteinopathy.

eLife·2026

Same journal

Analysis of dendritic input currents during place field dynamics.

eLife·2026

Same journal

TopoMetry systematically learns and evaluates the latent geometry of single-cell data.

eLife·2026

Same journal

Navigating the path: Advice to physician-scientists on choosing a clinical specialty.

eLife·2026

Same journal

Neural activity profiles reveal overlapping, intermingled subpopulations spanning area borders in mouse sensorimotor cortex.

eLife·2026

Same journal

The exquisite mechanics of a tsetse bite.

eLife·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 31, 2025

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

The normalization model predicts responses in the human visual cortex during object-based attention.

Narges Doostani¹, Gholam-Ali Hossein-Zadeh^1,2, Maryam Vaziri-Pashkam³

¹School of Cognitive Sciences, Institute for Research in Fundamental Sciences, Tehran, Iran.

|May 10, 2023

Summary

This summary is machine-generated.

Divisive normalization, a neural processing model, is supported by new human brain imaging. This fundamental operation predicts visual responses and attention effects in the human visual cortex.

Keywords:

divisive normalization fMRI human human visual cortex neuroscience object-based attention

More Related Videos

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Published on: March 18, 2019

How to Build a Dichoptic Presentation System That Includes an Eye Tracker

How to Build a Dichoptic Presentation System That Includes an Eye Tracker

Published on: September 6, 2017

Related Experiment Videos

Last Updated: Jul 31, 2025

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Published on: March 18, 2019

How to Build a Dichoptic Presentation System That Includes an Eye Tracker

How to Build a Dichoptic Presentation System That Includes an Eye Tracker

Published on: September 6, 2017

Area of Science:

Neuroscience
Cognitive Neuroscience
Visual Neuroscience

Background:

Divisive normalization is a computational model proposed to explain neural responses.
It has been successful in predicting neural activity in primate studies.
However, experimental evidence in the human brain remains limited.

Purpose of the Study:

To investigate the role of divisive normalization in the human visual cortex.
To test whether normalization explains neural responses to visual stimuli and attention.
To examine normalization across different visual areas, including V1, LO, pFs, EBA, and PPA.

Main Methods:

Functional magnetic resonance imaging (fMRI) was used to measure brain activity.
Participants viewed stimuli from categories like bodies and houses, presented in isolation or clutter.
Single-voxel responses were modeled using weighted sum, weighted average, and normalization models.
The effects of visual attention on cortical responses were analyzed.

Main Results:

The normalization model provided a better prediction of responses to multiple stimuli compared to weighted sum or average models.
Attention effects on cortical responses were accurately predicted by the normalization model.
Weighted sum and average models failed to predict attention effects.

Conclusions:

The findings provide evidence for divisive normalization as a fundamental operation in the human brain.
The normalization model successfully predicts neural responses to objects under attentional shifts.
This suggests normalization plays a crucial role in visual processing and attention in humans.