September 2018
Volume 18, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2018
Rapid learning of meaningful image interpretation
Author Affiliations
  • Gabriel Kreiman
    Harvard University
Journal of Vision September 2018, Vol.18, 1362. doi:10.1167/18.10.1362
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      Gabriel Kreiman; Rapid learning of meaningful image interpretation. Journal of Vision 2018;18(10):1362. doi: 10.1167/18.10.1362.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

A single event of visual exposure to new information may be sufficient for interpreting and remembering an image. This rapid form of visual learning stands in stark contrast with modern state-of-the-art deep convolutional networks for vision. Such models thrive in object classification after supervised learning with a large number of training examples. The neural mechanisms subserving rapid visual learning remain largely unknown. I will discuss efforts towards unraveling the neural circuits involved in rapid learning of meaningful image interpretation in the human brain. We studied single neuron responses in human epilepsy patients to instances of single shot learning using Mooney images. Mooney images render objects in binary black and white in such a way that they can be difficult to recognize. After exposure to the corresponding grayscale image (and without any type of supervision), it becomes easier to recognize the objects in the original Mooney image. We will demonstrate a single unit signature of rapid learning in the human medial temporal lobe and provide initial steps to understand the mechanisms by which top-down inputs can rapidly orchestrate plastic changes in neuronal circuitry.

Meeting abstract presented at VSS 2018

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