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

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 System01:26

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...
Parallel Processing01:20

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
The Retina01:32

The Retina

The retina is a layer of nervous tissue at the back of the eye that transduces light into neural signals. This process, called phototransduction, is carried out by rod and cone photoreceptor cells in the back of the retina.
Photoreceptors and Visual Pathways01:22

Photoreceptors and Visual Pathways

At the molecular level, visual signals trigger transformations in photopigment molecules, resulting in changes in the photoreceptor cell's membrane potential. The photon's energy level is denoted by its wavelength, with each specific wavelength of visible light associated with a distinct color. The spectral range of visible light, classified as electromagnetic radiation, spans from 380 to 720 nm. Electromagnetic radiation wavelengths exceeding 720 nm fall under the infrared category, whereas...
Motor and Sensory Areas of the Cortex01:14

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.

You might also read

Related Articles

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

Sort by
Same author

The Cooperative Network Architecture: Learning Structured Networks as Representation of Sensory Patterns.

Neural computation·2026
Same author

How are segmentation and binding computed and represented in the brain?

Cognitive processing·2024
Same author

Toward understanding the neural code of the brain.

Biological cybernetics·2021
Same author

An applet for the Gabor similarity scaling of the differences between complex stimuli.

Attention, perception & psychophysics·2016
Same author

Self-organization of control circuits for invariant fiber projections.

Neural computation·2015
Same author

Predicting the psychophysical similarity of faces and non-face complex shapes by image-based measures.

Vision research·2012

Related Experiment Video

Updated: Jul 10, 2026

DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions
10:05

DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions

Published on: August 26, 2014

What is the optimal architecture for visual information routing?

Philipp Wolfrum1, Christoph von der Malsburg

  • 1Frankfurt Institute for Advanced Studies, D-60438 Frankfurt am Main, Germany. wolfrum@fias.uni-frankfurt.de

Neural Computation
|November 1, 2007
PubMed
Summary

This study proposes optimality criteria for visual information routing networks. The findings reveal optimal fanout and layer scaling that align with primate visual system data.

More Related Videos

Functional Magnetic Resonance Imaging (fMRI) of the Visual Cortex with Wide-View Retinotopic Stimulation
07:11

Functional Magnetic Resonance Imaging (fMRI) of the Visual Cortex with Wide-View Retinotopic Stimulation

Published on: December 8, 2023

Related Experiment Videos

Last Updated: Jul 10, 2026

DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions
10:05

DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions

Published on: August 26, 2014

Functional Magnetic Resonance Imaging (fMRI) of the Visual Cortex with Wide-View Retinotopic Stimulation
07:11

Functional Magnetic Resonance Imaging (fMRI) of the Visual Cortex with Wide-View Retinotopic Stimulation

Published on: December 8, 2023

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Systems Neuroscience

Background:

  • Designing visual information routing networks is complex due to limited anatomical and physiological data.
  • Existing models often lack clear principles for network architecture optimization.

Discussion:

  • This research introduces novel optimality criteria to address the underconstrained problem of visual routing network design.
  • The study derives generalizable principles for network architecture, focusing on minimizing neural circuitry.

Key Insights:

  • Optimal fanout (l) for routing networks is independent of network size.
  • The number of routing layers (k) scales logarithmically with the number of visual units (n), with a prefactor less than 1.
  • Derived network design principles align with observed data from the primate visual system.

Outlook:

  • These findings provide a theoretical framework for understanding and designing efficient neural information processing systems.
  • Further research can explore the application of these criteria to other biological or artificial neural networks.
  • Experimental validation of these derived principles in biological systems is a potential future direction.