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Related Concept Videos

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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:
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In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint...
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Motor and Sensory Areas of the Cortex01:14

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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
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Somatosensory, Motor, and Association Cortex01:23

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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...
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Role of Cerebellum and Prefrontal Cortex in Memory01:14

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The cerebellum, while traditionally associated with motor control, also plays a crucial role in memory, particularly in procedural memory, which involves learning motor tasks that become automatic through repetition. For example, studies have shown that when the cerebellum is damaged, individuals or animals lose the ability to learn conditioned motor responses, such as the conditioned eye-blink response in classical conditioning experiments with rabbits. This study demonstrates the...
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Visual System01:26

Visual System

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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.
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Chronic Imaging of Mouse Visual Cortex Using a Thinned-skull Preparation
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A Transparent Photonic Artificial Visual Cortex.

Mohit Kumar1, Tapobrata Som2,3, Joondong Kim1

  • 1Photoelectric and Energy Device Application Lab (PEDAL), Multidisciplinary Core Institute for Future Energies (MCIFE) and Department of Electrical Engineering, Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea.

Advanced Materials (Deerfield Beach, Fla.)
|August 15, 2019
PubMed
Summary
This summary is machine-generated.

Researchers developed a transparent electronic device mimicking the brain's visual cortex. This self-powered, oxide-based heterostructure demonstrates energy-efficient neuromorphic computing capabilities for future AI applications.

Keywords:
neuromorphic computingphotonic devicesself-biasingtransparent materialsvisual cortex

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Area of Science:

  • Materials Science
  • Neuroscience
  • Electronics

Background:

  • Mimicking brain functionality in electronic devices is crucial for advanced artificial vision and memory.
  • Neuromorphic computing aims to create energy-efficient systems inspired by the brain's structure and function.

Purpose of the Study:

  • To propose and demonstrate a proof-of-concept all-oxide heterostructure mimicking primitive visual cortex functions.
  • To showcase an energy-efficient, self-biased approach for neuromorphic computing using optical stimuli.

Main Methods:

  • Fabrication of a highly transparent (54%) NiO/TiO2 heterostructure.
  • Utilizing direct optical stimuli and the photovoltaic effect for device operation.
  • Employing Kelvin probe force measurements to analyze the underlying physical mechanisms.

Main Results:

  • The device successfully mimicked orientation selectivity and spatiotemporal processing of the visual cortex.
  • Photocurrent modulation from 0 to 80 µA was achieved by rotating a slit by 90°.
  • Fast response times (3 ms rise, 6 ms fall) were observed, attributed to the lateral photovoltaic effect.

Conclusions:

  • The developed NiO/TiO2 heterostructure offers a transparent, self-biased, and optically triggered platform for neuromorphic computing.
  • This technology advances energy-efficient solutions for artificial intelligence and brain-inspired computing.
  • The device demonstrates a promising pathway toward next-generation electronic systems with brain-like capabilities.