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

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...

Somatosensory, Motor, and Association Cortex

Somatosensory, Motor, and Association Cortex

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...

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,...

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.

You might also read

Related Articles

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

Sort by

Same author

A wireless subdural-contained brain-computer interface with 65,536 electrodes and 1,024 channels.

Nature electronics·2026

Same author

Visual uncertainty and task demands shape active sensing strategies in mice.

bioRxiv : the preprint server for biology·2026

Same author

Reply to 'Boundary issues for multidimensional frameworks of representation'.

Nature reviews. Neuroscience·2026

Same author

Connecting single-cell transcriptomes to projectomes in the mouse visual cortex.

Nature·2026

Same author

Visual uncertainty and task demands shape active sensing strategies in mice.

Current biology : CB·2026

Same author

Uncovering Sex Differences in the Drosophila Ventral Nerve Cord Through Connectome Alignment.

bioRxiv : the preprint server for biology·2026

Same journal

Daily briefing: How cooperation built the world.

Nature·2026

Same journal

Deep-sea oddities and boatloads of other new species - June's best science images.

Nature·2026

Same journal

From cloning to gene-editing: the enduring legacy of Dolly the sheep.

Nature·2026

Same journal

Time to give hydration breaks the red card? What science says about keeping cool.

Nature·2026

Same journal

Universities are relying on AI-detection software to catch cheating. How well do the programs work?

Nature·2026

Same journal

Daily briefing: 'Cyborg' cockroaches breathe underwater with printed suit.

Nature·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 15, 2025

Visualization of Cortical Modules in Flattened Mammalian Cortices

Visualization of Cortical Modules in Flattened Mammalian Cortices

Published on: January 22, 2018

Functional connectomics reveals general wiring rule in mouse visual cortex.

Zhuokun Ding^1,2,3,4, Paul G Fahey^1,2,3,4, Stelios Papadopoulos^1,2,3,4

¹Center for Neuroscience and Artificial Intelligence and Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA.

|April 9, 2025

Summary

This summary is machine-generated.

Brain connectivity follows a "like-to-like" rule across layers and areas, with feature tuning, not location, driving synaptic connections. This principle aids sensory processing and learning in both biological and artificial systems.

More Related Videos

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

Author Spotlight: Deciphering Neural Circuit Formation from Two-Photon Microscopy and Single Neuron Imaging

Author Spotlight: Deciphering Neural Circuit Formation from Two-Photon Microscopy and Single Neuron Imaging

Published on: November 21, 2023

Related Experiment Videos

Last Updated: May 15, 2025

Visualization of Cortical Modules in Flattened Mammalian Cortices

Visualization of Cortical Modules in Flattened Mammalian Cortices

Published on: January 22, 2018

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

Author Spotlight: Deciphering Neural Circuit Formation from Two-Photon Microscopy and Single Neuron Imaging

Author Spotlight: Deciphering Neural Circuit Formation from Two-Photon Microscopy and Single Neuron Imaging

Published on: November 21, 2023

Area of Science:

Neuroscience
Computational Neuroscience
Systems Neuroscience

Background:

Understanding neural circuit connectivity is key to deciphering brain computation.
In mouse visual cortex, neurons with similar response properties show preferential synaptic connections.
Broader connectivity rules across cortical layers and areas remain largely unknown.

Purpose of the Study:

To analyze synaptic connectivity and neuronal functional properties across cortical layers and areas using the MICrONS dataset.
To investigate the universality of 'like-to-like' connectivity principles.
To differentiate the roles of feature and spatial tuning in synaptic connections and explore higher-order connectivity rules.

Main Methods:

Analysis of the millimetre-scale MICrONS dataset for synaptic connectivity and functional properties.
Utilizing a digital twin model to separate neuronal tuning into feature and spatial components.
Employing recurrent neural networks (RNNs) to model connectivity rules and performing ablation studies.

Main Results:

Neurons with similar response properties exhibit preferential connectivity within and across layers and areas, including feedback connections.
Neuronal feature tuning, not spatial receptive field location, predicts fine-scale synaptic connections.
A higher-order rule reveals greater functional similarity in downstream postsynaptic neuron cohorts than predicted by pairwise rules.
RNNs trained on classification tasks develop connectivity patterns mirroring biological rules, and disrupting 'like-to-like' connections impairs RNN performance.

Conclusions:

'Like-to-like' connectivity, driven by feature tuning, is a universal principle across the visual hierarchy.
Higher-order connectivity rules contribute to functional similarity in neural circuits.
These connectivity principles are functionally relevant for sensory processing and learning.
Shared principles exist between biological neural networks and artificial recurrent neural networks.