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The Journal of Neuroscience, November 4, 2009, 29(44):14026-14038; doi:10.1523/JNEUROSCI.3070-09.2009
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Behavioral/Systems/Cognitive
Visual Learning Shapes the Processing of Complex Movement Stimuli in the Human Brain
Jan Jastorff,1,2 Zoe Kourtzi,3,4 andMartin A. Giese1 1Section for Computational Sensomotorics, Department of Cognitive Neurology, Hertie Institute of Clinical Brain Research and Center for Integrative Neurosciences, University Clinic Tübingen, 72074 Tübingen, Germany, 2Laboratorium voor Neuro- en Psychophysiologie, Katholieke Universiteit Leuven Medical School, 3000 Leuven, Belgium, 3Max Planck Institute for Biological Cybernetics, 72026 Tübingen, Germany, and 4School of Psychology, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
Correspondence should be addressed to Martin A. Giese, Section for Computational Sensomotorics, Department of Cognitive Neurology, Hertie Institute of Clinical Brain Research and Center for Integrative Neurosciences, University Clinic Tübingen, Frondsbergstrasse 23, 72074 Tübingen, Germany. Email: martin.giese{at}uni-tuebingen.de
Recognition of actions and complex movements is fundamental for social interactions and action understanding. While the relationship between motor expertise and visual recognition of body movements has received a vast amount of interest, the role of visual learning remains largely unexplored. Combining psychophysics and functional magnetic resonance imaging (fMRI) experiments, we investigated neural correlates of visual learning of complex movements. Subjects were trained to visually discriminate between very similar complex movement stimuli generated by motion morphing that were either compatible (experiments 1 and 2) or incompatible (experiment 3) with human movement execution. Employing an fMRI adaptation paradigm as index of discriminability, we scanned human subjects before and after discrimination training. The results of experiment 1 revealed three different effects as a consequence of training: (1) Emerging fMRI-selective adaptation in general motion-related areas (hMT/V5+, KO/V3b) for the differences between human-like movements. (2) Enhanced of fMRI-selective adaptation already present before training in biological motion-related areas (pSTS, FBA). (3) Changes covarying with task difficulty in frontal areas. Moreover, the observed activity changes were specific to the trained movement patterns (experiment 2). The results of experiment 3, testing artificial movement stimuli, were strikingly similar to the results obtained for human movements. General and biological motion-related areas showed movement-specific changes in fMRI-selective adaptation for the differences between the stimuli after training. These results support the existence of a powerful visual machinery for the learning of complex motion patterns that is independent of motor execution. We thus propose a key role of visual learning in action recognition.
Received June 29, 2009; revised Sept. 11, 2009; accepted Sept. 21, 2009.
Correspondence should be addressed to Martin A. Giese, Section for Computational Sensomotorics, Department of Cognitive Neurology, Hertie Institute of Clinical Brain Research and Center for Integrative Neurosciences, University Clinic Tübingen, Frondsbergstrasse 23, 72074 Tübingen, Germany. Email: martin.giese{at}uni-tuebingen.de
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