scholarly journals The Extrastriate Body Area and identity processing: An fMRI guided TMS study

2021 ◽  
Vol 9 (8) ◽  
Author(s):  
Alizée Pann ◽  
Mireille Bonnard ◽  
Olivier Felician ◽  
Patricia Romaiguère
2010 ◽  
Vol 206 (1) ◽  
pp. 63-67 ◽  
Author(s):  
Boris Suchan ◽  
Martin Busch ◽  
Dietmar Schulte ◽  
Dietrich Grönermeyer ◽  
Stephan Herpertz ◽  
...  

eNeuro ◽  
2016 ◽  
Vol 3 (2) ◽  
pp. ENEURO.0020-16.2016 ◽  
Author(s):  
Marius Zimmermann ◽  
Lennart Verhagen ◽  
Floris P. de Lange ◽  
Ivan Toni

2013 ◽  
Vol 33 (16) ◽  
pp. 7003-7010 ◽  
Author(s):  
M. G. van Koningsbruggen ◽  
M. V. Peelen ◽  
P. E. Downing

2009 ◽  
Vol 4 (1) ◽  
pp. 40-48 ◽  
Author(s):  
Nicole David ◽  
Marije Jansen ◽  
Michael X. Cohen ◽  
Katja Osswald ◽  
Istvan Molnar-Szakacs ◽  
...  

2020 ◽  
Vol 30 (12) ◽  
pp. 6376-6390
Author(s):  
Marta Poyo Solanas ◽  
Maarten Vaessen ◽  
Beatrice de Gelder

Abstract Humans and other primate species are experts at recognizing body expressions. To understand the underlying perceptual mechanisms, we computed postural and kinematic features from affective whole-body movement videos and related them to brain processes. Using representational similarity and multivoxel pattern analyses, we showed systematic relations between computation-based body features and brain activity. Our results revealed that postural rather than kinematic features reflect the affective category of the body movements. The feature limb contraction showed a central contribution in fearful body expression perception, differentially represented in action observation, motor preparation, and affect coding regions, including the amygdala. The posterior superior temporal sulcus differentiated fearful from other affective categories using limb contraction rather than kinematics. The extrastriate body area and fusiform body area also showed greater tuning to postural features. The discovery of midlevel body feature encoding in the brain moves affective neuroscience beyond research on high-level emotion representations and provides insights in the perceptual features that possibly drive automatic emotion perception.


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