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

Neural Circuits

Neural Circuits

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...

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...

Depth Perception and Spatial Vision

Depth Perception and Spatial Vision

Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.

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...

You might also read

Related Articles

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

Sort by

Same author

Investigating the mechanisms underlying saccade generation in the frontal eye fields using multi-site microstimulation.

Journal of neurophysiology·2026

Same author

State-switching navigation strategies in <i>Caenorhabditis elegans</i> are beneficial for chemotaxis.

Proceedings of the National Academy of Sciences of the United States of America·2026

Same author

Brain-wide arousal signals are segregated from movement planning in the superior colliculus of the macaque.

eLife·2026

Same author

Interactions across hemispheres in prefrontal cortex reflect global cognitive processing.

Nature communications·2026

Same author

Linking reaction time variability to physiological markers of arousal across timescales.

bioRxiv : the preprint server for biology·2026

Same author

From Breath to Behavior: Respiratory Features Predict Visual Detection Performance.

bioRxiv : the preprint server for biology·2026

Same journal

Author Correction: cBAF complex components and MYC cooperate early in CD8<sup>+</sup> T cell fate.

Nature·2026

Same journal

Addendum: Transmission of MPXV from fire-footed rope squirrels to sooty mangabeys.

Nature·2026

Same journal

Dietary cholesterol activates a Ral-dependent pathway driving LDLR turnover.

Nature·2026

Same journal

An ECG biomarker for sudden cardiac death discovered with deep learning.

Nature·2026

Same journal

Role of methanesulfonic acid in atmospheric particle nucleation and growth.

Nature·2026

Same journal

Ductile alloys offering 100 MPa tensile strength at 2,400 °C.

Nature·2026

See all related articles

Search research articles

Home
Compact Deep Neural Network Models Of The Visual Cortex.

Home
Compact Deep Neural Network Models Of The Visual Cortex.

Related Experiment Video

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

Compact deep neural network models of the visual cortex.

Benjamin R Cowley^1,2, Patricia L Stan^3,4,5, Jonathan W Pillow⁶

¹Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. cowley@cshl.edu.

|February 25, 2026

View abstract on PubMed

Summary

This summary is machine-generated.

Researchers developed compact deep neural network (DNN) models to understand the primate visual cortex. These smaller models accurately predict neural responses, revealing how visual information is processed and specialized.

More Related Videos

Deep Neural Networks for Image-Based Dietary Assessment

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

Related Experiment Videos

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

Deep Neural Networks for Image-Based Dietary Assessment

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

Area of Science:

Computational neuroscience
Machine learning
Primate visual system

Background:

Deep neural networks (DNNs) are powerful tools for modeling neural responses but are often large and complex.
Understanding the computations within the primate visual cortex requires predictive models.

Purpose of the Study:

To develop predictive and parsimonious DNN models of the primate visual cortex.
To investigate the internal workings of compressed DNN models.

Main Methods:

Adaptive closed-loop experiments combining data collection and DNN model training.
Compression of a large DNN model (60 million parameters) to identify compact models (5,000x fewer parameters).
Analysis of compact models to uncover computational motifs and mechanisms.

Main Results:

Achieved highly predictive DNN models for macaque visual area V4.
Successfully compressed a large DNN model, retaining high accuracy with significantly fewer parameters.
Discovered a computational motif of shared early filters followed by specialized feature selectivity consolidation.
Identified a circuit hypothesis for dot-selective V4 neurons.
Demonstrated strong model compression for visual areas V1 and IT, suggesting a general principle.

Conclusions:

Large DNNs are not always necessary for predicting individual neuron responses.
A modeling framework balancing prediction and parsimony is established.
A general computational principle of feature selectivity consolidation exists in the visual cortex.