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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.

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 the...

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,...

Somatosensation

Somatosensation

The somatosensory system relays sensory information from the skin, mucous membranes, limbs, and joints. Somatosensation is more familiarly known as the sense of touch. A typical somatosensory pathway includes three types of long neurons: primary, secondary, and tertiary. Primary neurons have cell bodies located near the spinal cord in groups of neurons called dorsal root ganglia. The sensory neurons of ganglia innervate designated areas of skin called dermatomes.

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Related Experiment Video

Updated: Jun 7, 2026

Cortical Source Analysis of High-Density EEG Recordings in Children

Cortical Source Analysis of High-Density EEG Recordings in Children

Published on: June 30, 2014

Demixing population activity in higher cortical areas.

Christian K Machens¹

¹Group for Neural Theory, INSERM Unité 960, Département d'Etudes Cognitives, École Normale Supérieure Paris, France.

Frontiers in Computational Neuroscience

|October 30, 2010

Summary

This study introduces a new coordinate transformation method to untangle complex neural responses in the brain. It effectively separates different sources of neural activity, improving our understanding of higher cortical areas.

Keywords:

blind source separation multi-electrode recordings population code prefrontal cortex principal component analysis

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

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

Published on: October 24, 2012

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Last Updated: Jun 7, 2026

Cortical Source Analysis of High-Density EEG Recordings in Children

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Published on: June 30, 2014

Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software

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Published on: October 30, 2018

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

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 Neuroscience

Background:

Neural responses in higher cortical areas are complex, with single neurons encoding multiple parameters simultaneously.
Conventional methods for classifying neural responses often fail to capture the distributed nature of representations.

Purpose of the Study:

To develop a novel method for demixing heterogeneous neural responses.
To address the limitations of traditional statistical tools and principal component analysis (PCA) in analyzing complex neural data.

Main Methods:

A coordinate transformation method is proposed to orthogonally separate variance from different sources of neural firing rates.
The method maximizes variance within these orthogonal subspaces.

Main Results:

Simulated examples demonstrate the effectiveness of the proposed approach in demixing heterogeneous neural responses.
The method successfully separates variance originating from different sources, such as stimuli, rewards, and time.

Conclusions:

The new coordinate transformation method offers an improved way to analyze complex neural data from higher cortical areas.
This approach has the potential to clarify response heterogeneity and enhance understanding of neural representations.