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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....

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Related Experiment Video

Updated: May 1, 2026

Non-Invasive Modulation and Robotic Mapping of Motor Cortex in the Developing Brain

Non-Invasive Modulation and Robotic Mapping of Motor Cortex in the Developing Brain

Published on: July 1, 2019

Motor cortex microcircuit simulation based on brain activity mapping.

George L Chadderdon¹, Ashutosh Mohan, Benjamin A Suter

¹Department of Physiology and Pharmacology, SUNY Downstate, Brooklyn, NY 11203 gchadder3@gmail.com.

Neural Computation

|April 9, 2014

Summary

This summary is machine-generated.

We created a computational model of the mouse neocortex, revealing the corticostriatal population acts as a network hub. Dynamic analysis showed layer-specific activation thresholds and oscillations, highlighting the link between brain structure and function.

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Published on: October 24, 2012

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Last Updated: May 1, 2026

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Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

Area of Science:

Neuroscience
Computational Biology
Systems Neuroscience

Background:

The neocortex's laminar structure is complex, with intricate intra- and interlaminar connectivity.
Understanding this connectivity is crucial for deciphering brain function.

Purpose of the Study:

To develop a computational model of mouse M1 (primary motor cortex) to analyze neocortical connectivity.
To investigate the relationship between static connectivity maps and dynamic brain activity.

Main Methods:

Developed a computational model with 775 spiking neurons across 10 cell types.
Utilized graph-theoretic tools for static connectivity analysis.
Performed dynamical analysis to observe network behavior under stimulation.

Main Results:

Identified the corticostriatal population as a network hub with strong centrality.
Revealed layer-specific activation thresholds for sustained network oscillations (Layer 2/3: 13%, Layer 5A: 54%, Layer 5B: 25%, Layer 6: 17%).
Demonstrated that oscillation frequency and phase depend on the stimulated cortical layer.

Conclusions:

Combined static and dynamic analyses effectively link brain structure to activity.
The corticostriatal population plays a key role as a network hub.
Neocortical network dynamics are complex and not fully predictable from wiring diagrams alone.