TY - JOUR
T1 - Dissociable neural mechanisms for determining the perceived heaviness of objects and the predicted weight of objects during lifting
T2 - An fMRI investigation of the size-weight illusion
AU - Chouinard, Philippe A.
AU - Large, Mary Ellen
AU - Chang, Erik C.
AU - Goodale, Melvyn A.
N1 - Funding Information:
We thank Mrs. Joy Williams and Dr. Haitao Yang for providing us with technical support. This work was supported by the Canadian Institutes of Health Research.
PY - 2009/1/1
Y1 - 2009/1/1
N2 - In size-weight (SW) illusions, people learn to scale their fingertip forces for lifting small and big objects of equal weight even though they fail to learn perceptually that both objects have the same weight. The question then arises as to what the separate neural mechanisms are for determining the perceived heaviness of objects and the predicted weight of these objects during lifting. To answer this question, we used fMRI to first identify areas that code for the size, weight, and density of objects using an adaptation paradigm. We then contrasted BOLD in the SW illusion condition in which subjects falsely perceived the smaller of two equally weighted objects as heavier versus a condition in which size and weight did not differ between objects. Sensory areas in the parietal and temporal cortex adapted to the size of objects and the primary motor area (M1) contralateral to the lifting hand adapted to the weight of objects. The ventral premotor area (PMv), which did not adapt to either the size or the weight of objects, adapted instead to the density of objects, and responded more when subjects falsely perceived differences in weight between objects in the SW illusion condition. Taken together, we conclude that the real-world properties of objects, such as size and weight, are computed by sensory areas and by M1 respectively, whereas the perceived heaviness of objects, presumably based on their apparent density, is computed by PMv, a higher-order area well placed to integrate sensory information about the size of objects and the weight of objects.
AB - In size-weight (SW) illusions, people learn to scale their fingertip forces for lifting small and big objects of equal weight even though they fail to learn perceptually that both objects have the same weight. The question then arises as to what the separate neural mechanisms are for determining the perceived heaviness of objects and the predicted weight of these objects during lifting. To answer this question, we used fMRI to first identify areas that code for the size, weight, and density of objects using an adaptation paradigm. We then contrasted BOLD in the SW illusion condition in which subjects falsely perceived the smaller of two equally weighted objects as heavier versus a condition in which size and weight did not differ between objects. Sensory areas in the parietal and temporal cortex adapted to the size of objects and the primary motor area (M1) contralateral to the lifting hand adapted to the weight of objects. The ventral premotor area (PMv), which did not adapt to either the size or the weight of objects, adapted instead to the density of objects, and responded more when subjects falsely perceived differences in weight between objects in the SW illusion condition. Taken together, we conclude that the real-world properties of objects, such as size and weight, are computed by sensory areas and by M1 respectively, whereas the perceived heaviness of objects, presumably based on their apparent density, is computed by PMv, a higher-order area well placed to integrate sensory information about the size of objects and the weight of objects.
KW - Functional magnetic-resonance imaging
KW - Object lifting
KW - Sensorimotor areas
KW - Size-weight illusion
KW - Ventral premotor area
KW - Weight perception
UR - http://www.scopus.com/inward/record.url?scp=55349146906&partnerID=8YFLogxK
U2 - 10.1016/j.neuroimage.2008.08.023
DO - 10.1016/j.neuroimage.2008.08.023
M3 - 期刊論文
C2 - 18801445
AN - SCOPUS:55349146906
SN - 1053-8119
VL - 44
SP - 200
EP - 212
JO - NeuroImage
JF - NeuroImage
IS - 1
ER -