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Description (provided by applicant): Visual object recognition is crucial for most everyday tasks including face identification, reading and navigation. In spite of the massive increase in computational power over the last two decades, a 3-year-old still outperforms the most sophisticated algorithms even in simple recognition tasks. Understanding the computations performed by the human visual system to recognize objects will have profound implications not only to understand the functions (and malfunction) of the cerebral cortex but also for developing visual prosthetic devices for the visually impaired. We combine neurophysiology, electrical stimulation and tools from machine learning to further our understanding of the neuronal circuits, algorithms and computations performed by the human visual system to perform visual pattern recognition. In the vast majority of visually impaired or blind people, the problems originate at the level of the retina while the visual cortex remains unimpaired. Our proposal constitutes a proof- of-principle approach towards developing visual prosthetic devices that rely on electrical stimulation of visual cortex. The specific aims of this proposal are designed to test the possibility of decoding and recoding information in visual cortex: (1) Read-out of visual information from human visual cortex on line (2) Write-in of visual information in human visual cortex. We take advantage of a rare opportunity to study the human brain at high spatial and temporal resolution by studying patients who have electrodes implanted for clinical reasons. Our electrophysiological recordings provide us with a unique view of the human temporal lobe circuitry and allow us to test the feasibility of cortical visual prosthetics in behaving human subjects. PUBLIC HEALTH RELEVANCE: Towards cortical visual prosthetics one of the key challenges for the visually impaired and blind people is the lack of visual object recognition capabilities. Visual recognition is crucial for most everyday tasks including navigation and face identification. Our proposal is a proof-of-principle approach towards the development of visual prosthetics devices based on electrical stimulation in visual cortex.
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Neural circuits for action perception: An integrative approach
  • 批准号:
    10301963
  • 项目类别:
  • 资助金额:
    $26.01万
  • 财政年份:
    2021
  • 负责人:
    Gabriel Kreiman
  • 依托单位:
Neural circuits for action perception: An integrative approach
  • 批准号:
    10475153
  • 项目类别:
  • 资助金额:
    $21.46万
  • 财政年份:
    2021
  • 负责人:
    Gabriel Kreiman
  • 依托单位:
Neural circuits for cognitive control
  • 批准号:
    9243760
  • 项目类别:
  • 资助金额:
    $26.55万
  • 财政年份:
    2017
  • 负责人:
    Gabriel Kreiman
  • 依托单位:
Neural circuits for cognitive control
  • 批准号:
    9693540
  • 项目类别:
  • 资助金额:
    $0.95万
  • 财政年份:
    2017
  • 负责人:
    Gabriel Kreiman
  • 依托单位:
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