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Poster

Neural Correlates of the Learning of Biological Motion: An fMRI Adaptation Experiment

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84832

Jastorff,  J
Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84787

Giese,  MA
Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84023

Kourtzi,  Z
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Jastorff, J., Giese, M., & Kourtzi, Z. (2004). Neural Correlates of the Learning of Biological Motion: An fMRI Adaptation Experiment. Poster presented at 7th Tübingen Perception Conference (TWK 2004), Tübingen, Germany.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-D9FD-6
Zusammenfassung
Introduction: Previous experimental work indicates that biological motion recognition is dependent on learning. In order to determine neural correlates of this learning process we conducted an fMRI adaptation experiment (cf. [1]). Compared to previous studies using a classical block design, adaptation experiments have the advantage that they allow to distinguish multiple functionally distinct neural subpopulations within the same voxel, exploiting the fact that the BOLD signal decays if the same stimulus is presented repeatedly. Methods: Pairs of unfamiliar motion stimuli for a discrimination task were generated by motion morphing between triples of prototypical trajectories of human movements. The morphs were generated by linear combination of the prototypical trajectories in space-time [2]. Subjects had to discriminate between two successive stimuli presented as Johansson point light walkers with same or different linear weights of the prototypes. By choosing appropriate weight vectors the difculty of the discrimination task can be precisely controlled. This was used to generate four conditions with identical (SAME), very similar (SIMILAR), moderately similar (DISSIMILAR), and completely different (DIFFERENT) stimulus pairs. Subjects reported whether they perceived the successive stimuli as same or different. The subjects were scanned before and after a training period. Areas relevant for the processing of biological motion (early visual areas, MT+ , KO, FFA, and STS) were localized using standard techniques. Results: Before the training subjects could discriminate the stimuli in the DISSIMILAR and in the DIFFERENT condition. After training they could also discriminate the stimulus pairs in the SIMILAR condition. Comparing the BOLD signal before and after the training period we found a signicant reduction of the signal in all localized regions of interest. Before training, we obtained signicant adaptation effects for the SAME and the SIMILAR condition only in area FFA and the STS. The other areas did not show selective adaptation. After training, however, no adaptation effect was observed for the SIMILAR condition any more. This result is consistent with an increased discrimination capability after training. Conclusion: We have successfully established the fMRI adaptation paradigm for biological motion experiments. The adaptation effects in area FFA and the STS are consistent with the discrimination performance of the subjects before and after training. Conforming with earlier studies, the STS and area FFA seem to be critical for biological motion recognition. The general decrease in BOLD signal observed after training might be related to a more efcient encoding of the stimuli after learning.