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Human perception and recognition of metric changes of part-based dynamic novel objects

Middle Temporal Gyrus (motion). Post. Lat. Occ. Areas (shape). diff motion benefit. Human perception and recognition of metric changes of part-based dynamic novel objects. same motion benefit. Quoc C. Vuong, Johannes Schultz, & Lewis Chuang

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Human perception and recognition of metric changes of part-based dynamic novel objects

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  1. Middle Temporal Gyrus (motion) Post. Lat. Occ. Areas (shape) diff motion benefit Human perception and recognition of metric changes of part-based dynamic novel objects same motion benefit Quoc C. Vuong, Johannes Schultz, & Lewis Chuang Max Planck Institute for Biological Cybernetics, Tübingen, Germany • Parts play an important role in object recognition. One issue is whether observers encode parts in a qualitative or quantitative fashion. Both single-cell recording in monkeys and human behavioral experiments show that metric aspects of parts (e.g., the amount of curvature) are encoded in visual memory. Here, using morphing techniques borrowed from Computer Graphics, we tested the following questions: • Are observers sensitive to complex quantitative changes of multi-part novel objects? • Does motion affect how observers encode part information? • We also examined the neural correlates by conducting the experiment in a 3T scanner. Our hypothesis is that both shape-selective and motion-selective brain areas may mediate the effect of both part and motion information. • What neural regions are involved in part and motion interactions? same motion diff motion • The stimuli were multi-part objects. Each part varied along three independent and parametric dimensions: • Bend (straight to curved) • Taper (symmetric ends to tapered ends) • Cross Section (circle to square) • Morphing Technique: For the multi-part object, a single parameter was used to control the three dimensions of all parts. Thus, the objects could be varied along an “identity” axis between two exemplars. • Task: Same or different shape? • 6 Morph Levels: • 0% (same object), 10%-50% morph difference between the 1st and 2nd stimuli • 10% = hard shape discrimination • 50% = easy shape discrimination • 2 Motion Conditions: • Same or Different directions • N = 15 L R E1 E2 Identity Axis 2000 ms 700 ms L R Taper L R 500 ms [53, -61, -2] Bend Cross Section 700 ms [-39, -55, 6] [48, -61 -4] [-45, -56, -5] PCORR < 0.04 hMT+/V5 Post. Lat. Occ. Areas • Each point • represents a subject PCORR < 0.04 Parametric Stimuli and Task Individual Differences in Motion Effect Morph Effect • Observers were more likely to respond “different” for larger Morph Levels in which shapes are more dissimilar from each other. Thus with morphing techniques, we can make complex shape changes in a parametric manner (i.e., along an identity axis). • There was no overall effect of same or different motion, and no interaction between shape and motion. • Motion had different effects on individual observers’ 75% same motion and different motion thresholds. This effect is shown as a difference of the two thresholds. A benefit means that observers need a smaller morph difference for 75% performance. • This effect implies that different observers integrate shape and motion by different amounts. • Whole brain analysis showed significant unilateral activation in posterior lateral occipital areas and the middle temporal gyrus. • We focused on these regions because they are sensitive to shape and motion information. • The mean difference in activation of voxels in these regions for same motion and different motion correlated with observers behavioral difference in same motion and different motion thresholds. • Whole brain analysis showed significant bilateral activation in posterior lateral occipital areas (Talaraich coordinates provided) • We focused on these regions because they are sensitive to shape (i.e., part) information. • Activation of voxels in these regions showed a similar dependence on Morph Level as the behavioral data. same motion diff motion Conclusions fMRI Details • Observers encode metric properties of parts: They are sensitive to complex metric differences between parts of objects • Individual difference for motion: The overall motion of the two test objects (same or different direction of rotation) had different effects on individual observers • For 6/15 observers, there was an advantage in shape discrimination if both objects rotated in the same direction. • Sequence • 3T Siemens magnet • 140 measurements (~7 min) • Whole brain coverage • 36 slices per volume • 3.0 x 3.0 x 2.5 mm voxel with 0.5 mm gap • TR = 3 sec (Repetition Time) • TE = 40 msec (Echo Time) • Analysis • Standard preprocessing in SPM2 (motion correction, normalization, smoothing with 8 FWHM Gaussian) • Event-related analysis with single-subject models • 2nd level group statistics with corrections at the cluster-level • Responses of shape-selective regions are correlated to perceptual difficulty of shape discrimination (i.e., complex metric changes). • Both shape-selective and motion-selective regions are involved in the discrimination of dynamic novel objects

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