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Related Concept Videos

Visual System01:26

Visual System

588
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...
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Vision01:24

Vision

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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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Anatomy of the Eyeball01:20

Anatomy of the Eyeball

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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...
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Motor and Sensory Areas of the Cortex01:14

Motor and Sensory Areas of the Cortex

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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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Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

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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.
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Association Areas of the Cortex01:21

Association Areas of the Cortex

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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,...
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Anatomical, physiological, and psychophysical data show that the nature of conscious perception is incompatible with the integrated information theory (IIT).

The Behavioral and brain sciences·2022
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There is a fundamental, unbridgeable gap between DNNs and the visual cortex.

Moshe Gur1

  • 1Department of Biomedical Engineering, Technion, Haifa, Israel mogi@bm.technion.ac.il.

The Behavioral and Brain Sciences
|December 6, 2023
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Summary

Deep neural networks (DNNs) are fundamentally different from the human visual system. Their structure and function are so distinct that they cannot replicate holistic object perception, a capability unique to biological vision.

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Area of Science:

  • Neuroscience
  • Computer Science
  • Artificial Intelligence

Background:

  • Deep neural networks (DNNs) are increasingly used to model brain functions, including visual processing.
  • However, significant differences exist between artificial and biological neural systems.

Purpose of the Study:

  • To analyze the structural and functional discrepancies between DNNs and the human visual system.
  • To evaluate the capability of DNNs in replicating human object perception.

Main Methods:

  • Comparative analysis of DNN architecture and function against biological neural networks.
  • Examination of object recognition processes in both artificial and biological systems.

Main Results:

  • DNN units share minimal commonality with biological neurons.
  • DNNs often feature full connectivity, unlike the sparse connectivity in visual neurons.
  • DNNs excel at input labeling but fail to achieve holistic and detail-preserving object perception.

Conclusions:

  • DNNs are inadequate models of the visual system due to fundamental differences in structure and function.
  • Current computational systems, including DNNs, cannot replicate the holistic and detail-preserving nature of human object perception.