Joint representation of depth from motion parallax and binocular disparity cues in macaque area MT

Jacob W. Nadler, Daniel Barbash, Hyung Goo R. Kim, Swati Shimpi, Dora E. Angelaki, Gregory C. DeAngelis

Research output: Contribution to journalArticlepeer-review


Perception of depth is based on a variety of cues, with binocular disparity and motion parallax generally providing more precise depth information than pictorial cues. Much is known about how neurons in visual cortex represent depth from binocular disparity or motion parallax, but little is known about the joint neural representation of these depth cues. We recently described neurons in the middle temporal (MT) area that signal depth sign (near vs far) from motion parallax; here,weexamine whether andhowthese neurons also signal depth from binocular disparity.Wefind that mostMTneurons in rhesus monkeys (Macaca Mulatta) are selective for depth sign based on both disparity and motion parallax cues. However, the depth-sign preferences (near or far) are not always aligned: 56% of MT neurons have matched depth-sign preferences ("congruent" cells) whereas the remaining 44% of neurons prefer near depth from motion parallax and far depth from disparity, or vice versa ("opposite" cells). For congruent cells, depth-sign selectivity increases when disparity cues are added to motion parallax, but this enhancement does not occur for opposite cells. This suggests that congruent cells might contribute to perceptual integration of depth cues. We also found that neurons are clustered in MT according to their depth tuning based on motion parallax, similar to the known clustering ofMTneurons for binocular disparity. Together, these findings suggest that areaMTis involved in constructing a representation of 3D scene structure that takes advantage of multiple depth cues available to mobile observers.

Original languageEnglish (US)
Pages (from-to)14061-14074
Number of pages14
JournalJournal of Neuroscience
Issue number35
StatePublished - 2013

ASJC Scopus subject areas

  • General Neuroscience


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