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The Journal of Neurophysiology Vol. 83 No. 5 May 2000, pp. 3140-3146
Copyright ©2000 by the American Physiological Society
RAPID COMMUNICATION
1First Department of Physiology, Nihon University, School of Medicine; 2Department of Neuropsychiatry, Nihon University, School of Medicine, Tokyo 173-8610; and 3Japan Society for Promotion of Science (JSPS), Tokyo 102-8471, Japan
Taira, Masato,
Ken-Ichiro Tsutsui,
Min Jiang,
Kazuo Yara, and
Hideo Sakata.
Parietal Neurons Represent Surface Orientation From the Gradient
of Binocular Disparity. J. Neurophysiol. 83: 3140-3146, 2000. In order to elucidate the neural
mechanisms involved in the perception of the three-dimensional (3D)
orientation of a surface, we trained monkeys to discriminate the 3D
orientation of a surface from binocular disparity cues using a Go/No-go
type delayed-matching-to-sample (DMTS) task and examined the properties
of the surface-orientation-selective (SOS) neurons. We recorded 57 SOS
neurons from the caudal part of the lateral bank of the intraparietal
sulcus (area CIP) of three hemispheres of two Japanese monkeys
(Macaca fuscata). We tested 29 of 57 SOS neurons using
the square plate of a solid figure stereogram (SFS) and random-dot
stereogram (RDS) without perspective cues; almost all of the tested
neurons (28/29) showed surface orientation selectivity for the SFS
and/or the RDS without perspective cues. Eight of these 28 neurons
(28.6%) showed selectivity for both the RDS and SFS, 7 (25.0%) were
dominantly selective for the RDS, and 13 (46.4%) were dominantly
selective for the SFS. These results suggest that neurons that show
surface orientation tuning for the RDS without perspective cues compute
surface orientation from the gradient of the binocular disparity given
by the random-dot across the surface. On the other hand, neurons that
show surface orientation tuning for the SFS without perspective cues
may represent surface orientation primarily from the gradient of the
binocular disparity along the contours. In conclusion, the SOS neurons
in the area CIP are likely to operate higher order processing of disparity signals for surface perception by integrating the input signals from many disparity-sensitive neurons with different disparity tuning.
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