September 2021
Volume 21, Issue 9
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2021
Neural representation of multiple visual stimuli moving transparently at different depths in cortical area MT
Author Affiliations & Notes
  • Anjani Chakrala
    Department of Neuroscience, University of Wisconsin-Madison
    Neurosciene Training Program
  • Jianbo Xiao
    Department of Neuroscience, University of Wisconsin-Madison
    Neurosciene Training Program
    Physiology Graduate Training Program
  • Xin Huang
    Department of Neuroscience, University of Wisconsin-Madison
    Neurosciene Training Program
    Physiology Graduate Training Program
    McPherson Eye Research Institute
  • Footnotes
    Acknowledgements  NIH grant R01EY022443, I want to acknowledge McPherson Eye Research Institute for their support for the membership fee.
Journal of Vision September 2021, Vol.21, 2918. doi:https://doi.org/10.1167/jov.21.9.2918
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      Anjani Chakrala, Jianbo Xiao, Xin Huang; Neural representation of multiple visual stimuli moving transparently at different depths in cortical area MT. Journal of Vision 2021;21(9):2918. https://doi.org/10.1167/jov.21.9.2918.

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

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Abstract

Visual motion and depth provide important cues for image segmentation. We characterized how neurons in the middle-temporal (MT) cortex represent multiple moving stimuli and how depth cue contributes to segmentation. We recorded from neurons in area MT of two macaques. The visual stimuli were overlapping random-dot patches moving in two directions separated by 60° or 120°. One patch was presented at a near disparity (-0.1°) and the other at a far disparity (0.1°). We varied the vector-averaged direction of the two patches to characterize response tuning to the bi-directional stimuli. We also measured the direction tuning to the individual patch. The animals performed a direction discrimination task to report the direction of one of two patches at a cued depth. The first animal performed slightly but significantly better for discriminating the direction of the near-surface, whereas the second performed equally well for discriminating the direction of either surface. The neuronal responses to the bi-directional stimuli were markedly different between the two animals. The response tuning of the first animal showed a significant bias toward the near-surface (p<10-11), regardless of whether a neuron preferred a near or far disparity, or which surface the animal was cued to attend. In contrast, the response tuning of a neuron in the second animal tended to bias toward the surface that the neuron preferred when presented alone. We found a significant correlation between the response bias and a neuron’s preference for the individual surface (Pearson’s r>0.43, p<10-9). For both animals, attending to one of the two surfaces pulled the response tuning to the bi-directional stimuli toward the attended surface. We are currently investigating why the neural tuning properties differ between the two animals. In either case, the depth cue caused a biased neural representation toward the individual stimulus component(s) and therefore can facilitate image segmentation.

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