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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.

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,...

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...

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.

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.

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Related Experiment Video

Updated: Jul 14, 2026

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

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

Published on: December 8, 2023

Object recognition by artificial cortical maps.

Alessio Plebe¹, Rosaria Grazia Domenella

¹Department of Cognitive Science, University of Messina, V. Concezione 8, Messina, Italy. aplebe@unime.it

Neural Networks : the Official Journal of the International Neural Network Society

|July 3, 2007

Summary

This study presents a novel model for object recognition development, suggesting it emerges from epigenetic factors and neural plasticity, not genetic programming. The model demonstrates how artificial cortical networks can develop recognition abilities from visual input alone.

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Area of Science:

Neuroscience
Computational Neuroscience
Artificial Intelligence

Background:

Object recognition is a key function of the human visual system, yet remains poorly understood.
While some visual processing functions like orientation discrimination are well-studied, the development of recognition is less clear.

Purpose of the Study:

To propose a computational model for the developmental trajectory of object recognition.
To investigate the roles of epigenetic influences and neural plasticity in developing recognition capabilities.
To demonstrate that recognition can emerge without geometric reconstruction, relying solely on retinal 2D views.

Main Methods:

Development of a modular model inspired by biological visual areas.
Implementation using the LISSOM (Large-scale Integrated Self-Organizing Map) architecture.
Simulation of intercortical lateral connections and exposure to natural images.

Main Results:

The model successfully develops object recognition capabilities.
The emergent abilities mirror those observed in the ventral visual areas of the brain.
Spontaneous development of recognition was achieved through interaction with visual data.

Conclusions:

Object recognition development is driven by epigenetic factors and neural plasticity, not solely by genetic pre-wiring.
A 2D retinal view is sufficient for recognition, negating the need for complex geometrical reconstruction.
Artificial neural network models, like LISSOM, can replicate biological visual recognition development through self-organization and environmental interaction.