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Did I do that?: Causal Inference of Agency in goal-directed actions

Tobias F. Beck1, 2, 3, 4*, Carlo Wilke5, Barbara Wirxel3, 5, Dominik Endres1, 2, 4, 6, Axel Lindner3, 5 and Martin Giese1, 2, 3, 4, 6
  • 1 University Clinic Tuebingen, Cognitive Neurology, Germany
  • 2 Hertie Institute for Clinical Brain Research, Germany
  • 3 Bernstein Center for Computational Neuroscience Tuebingen, Germany
  • 4 CIN Tuebingen, Germany
  • 5 University Clinic Tuebingen, Cognitive Neurology, Germany
  • 6 Equal Contribution, Germany

The perception of own actions is affected by visual information and internal predictions [1]. Integration of these cues depends on their accuracies [2], including the association of visual signals with one’s own action or with unrelated external changes [3]. This attribution should thus depend on the consistency between predicted and actual visual consequences. The goal of this work is to develop quantitative theories for the influence of the sense of agency on the fusion of perceptual signals and predictions derived from internal forward models.
Our work exploits graphical models as central theoretical framework.

METHODS. We used a virtual-reality setup to manipulate the consistency between pointing movements and their visual consequences and investigated its influence on self-action perception. Participants were seated in front of a horizontal board on which their right hand was placed with the index finger on a haptic marker, representing the starting point for each trial. Participants were instructed to execute straight, fast (quasi-ballistic) pointing movements of fixed amplitude (9 deg visual angle), but without any explicit visual target. The hand was obstructed from the participant’s view and terminal visual feedback was provided veridical or manipulated. Participants were then asked two questions:
1) What direction did you point to? And 2) Did you cause the direction of the visual feedback?
We then asked whether a causal inference model accounts for the empirical data, assuming a latent agency-variable: if the visual stimulus was attributed to one’s own action, visual and internal information should fuse in a Bayesian optimal manner and not if attributed to external influences.

RESULTS & CONCLUSION. The model correctly predicts the data, showing attribution of visual signals to one’s own action for small, and stronger reliance on internal information for large deviations. We discuss the causal inference model’s performance compared to alternative models, applying methods for Bayesian model comparison.

Acknowledgements

This work was supported in part by the Bernstein Center for Computational Neuroscience, Tübingen, funded by the German Federal Ministry of Education and Research (BMBF; FKZ: 01GQ1002), the CIN Tübingen, the EU projects FP7-ICT-215866 SEARISE, FP7-249858-TP3 TANGO, FP7-ICT-248311 AMARSi, the DFG and the Hermann and Lilly Schilling Foundation.

References

[1] Wolpert et al,1995,Science,269,1880-1882].
[2] Burge et al,2008,Journal of Vision,8(4:20),1-19
[3] Körding et al,2007,PLOSOne,2(9)

Keywords: sensory processing

Conference: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011, Freiburg, Germany, 4 Oct - 6 Oct, 2011.

Presentation Type: Poster

Topic: sensory processing (please use "sensory processing" as keyword)

Citation: Beck TF, Wilke C, Wirxel B, Endres D, Lindner A and Giese M (2011). Did I do that?: Causal Inference of Agency in goal-directed actions. Front. Comput. Neurosci. Conference Abstract: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011. doi: 10.3389/conf.fncom.2011.53.00128

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Received: 24 Aug 2011; Published Online: 04 Oct 2011.

* Correspondence: Mr. Tobias F Beck, University Clinic Tuebingen, Cognitive Neurology, Tuebingen, 72072, Germany, tobias.beck@uni-tuebingen.de