Human depth sensitivity is affected by object plausibility

NHL Wong, H Ban, DHF Chang - Journal of Cognitive Neuroscience, 2020 - direct.mit.edu
NHL Wong, H Ban, DHF Chang
Journal of Cognitive Neuroscience, 2020direct.mit.edu
Using behavioral and fMRI paradigms, we asked how the physical plausibility of complex 3-
D objects, as defined by the object's congruence with 3-D Euclidean geometry, affects
behavioral thresholds and neural responses to depth information. Stimuli were disparity-
defined geometric objects rendered as random dot stereograms, presented in plausible and
implausible variations. In the behavior experiment, observers were asked to complete (1) a
noise-based depth task that involved judging the depth position of a target embedded in …
Abstract
Using behavioral and fMRI paradigms, we asked how the physical plausibility of complex 3-D objects, as defined by the object's congruence with 3-D Euclidean geometry, affects behavioral thresholds and neural responses to depth information. Stimuli were disparity-defined geometric objects rendered as random dot stereograms, presented in plausible and implausible variations. In the behavior experiment, observers were asked to complete (1) a noise-based depth task that involved judging the depth position of a target embedded in noise and (2) a fine depth judgment task that involved discriminating the nearer of two consecutively presented targets. Interestingly, results indicated greater behavioral sensitivities of depth judgments for implausible versus plausible objects across both tasks. In the fMRI experiment, we measured fMRI responses concurrently with behavioral depth responses. Although univariate responses for depth judgments were largely similar across cortex regardless of object plausibility, multivariate representations for plausible and implausible objects were notably distinguishable along depth-relevant intermediate regions V3 and V3A, in addition to object-relevant LOC. Our data indicate significant modulations of both behavioral judgments of and neural responses to depth by object context. We conjecture that disparity mechanisms interact dynamically with the object recognition problem in the visual system such that disparity computations are adjusted based on object familiarity.
MIT Press
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