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1. 4 Time Series Spectra x 10 0 4 IN#001.JLD Amplitude -100 2 1.4 Hz -200 0 0 5 10 15 20 0 4 1 2 3 4 5 x 10 0 4 IN#002.JLD Amplitude -100 2 0.9 Hz -200 0 0 5 10 15 20 0 4 1 2 3 4 5 x 10 0 4 IN#003.JLD Amplitude -100 2 1 Hz -200 0 0 5 10 15 20 0 4 1 2 3 4 5 x 10 0 4 IN#004.JLD Amplitude -100 2 1.2 Hz -200 0 0 5 10 15 20 0 4 1 2 3 4 5 x 10 0 4 IN#005.JLD Amplitude -100 2 1.35 Hz -200 0 4 0 5 10 15 20 0 1 2 3 4 5 x 10 0 4 IN#006.JLD Amplitude -100 2 1.8 Hz -200 0 0 5 10 15 20 0 4 1 2 3 4 5 x 10 0 4 IN#007.JLD Amplitude -100 2 2.2 Hz S2 – Trial 15 - hdL -200 0 0 5 10 15 20 0 1 2 3 4 5 Time [sec] Frequency [Hz] Effects of biological relevance of the stimulus in mediating spontaneous visual social coordination G.C. De Guzman; E. Tognoli; J. Lagarde; K.J. Jantzen; J.A.S. Kelso Center For Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, FL, USA Analysis Introduction Similarity index The efficacy of the stimulus combinations were assessed using the stimulus-hand relative phase and a similarity index measure of coupling strength (Bhattacharya et al., 2003). Individual trials exhibit phase-locking interspersed with phase drifts indicating tendencies to synchronize. When collapsed across trials, the phase distributions showed no difference between conditions. The similarity index showed that coupling between subject and stimulus was strongest when the latter was an image of a hand driven by real movement data. The weakest coupling occurred when the stimulus was a dot image moving in sinusoidal manner. Q: Is behavioral coupling during spontaneous social coordination facilitated by the perception of biologically relevant stimuli?The effects of a biologically realistic agent and movement are compared to a non-biological stimulus and a synthetic motion. If the perception of a functional homology (putatively producing an embodied response) is not important for promoting spontaneous coordination between agents then all stimuli and motion types should elicit the same behavior. Otherwise, biologically constrained stimuli should produce stronger behavioral entrainment. The similarity index (see e.g. Bhattacharya, Pereda & Petsche, 2003) uses state space reconstruction techniques to assess strength of directional effects. In tightly coupled systems, the N-nearest neighbors of a point x(tk) in X and the N-nearest neighbors of the point y(tk) in Y have similar time indices. For uncoupled systems, there is a high probability that the set of time indices for X is very different from the time indices for Y. The collection of points in X at times corresponding to the Y-time indices is called “mutual neighbors”. An instantaneous measure of the similarity, Sk(X|Y), is then the radius of the cloud of R-nearest neighbors divided by the radius of the cloud of R-mutual neighbors: Sk(X|Y) measures the effect of Y on X. Preliminary results A/D: OPTOTRAK @ 100 Hz Summary These preliminary results suggest that embodiment can occur when coordinating with a virtual partner and the quality of the interaction depends on the biological relevancy of the stimulus presented to the other. Motion variability produces a stronger coupling effect than visual (anatomical) accuracy in this synchronization task.. This is easily evident from the perturbations induced by real hand as compared to synthetic movements. That a realistic hand figure driven by a real movement data elicits strong coupling is consistent with studies that showed mere observation of movement of another person affects motor responses strongly enough to interfere with one’s execution of a similar action (Sebanz, Knoblich, & Prinz, 2003). Additionally, studies showed that with a movement stimulus generated by human-figured robots, the interference is less noticeable (see e.g. Kilner, Paulignan, & Blakemore, 2003). Motion characteristics ● Hand movement data ● Perfect sinusoidal ● ± 10% subject frequency Pilot study: 4 Ss Similarity Index Relative phase Experiment Perturbation effects S2 – Trial 12 - dsL While executing self-paced rhythmic finger flexion-extension, subjects view on a monitor either the movement of a finger (H) or an oscillating dot (D) for 15 seconds. To establish the self-paced rhythm, the viewing phase was preceded by an initial 15 second interval during which the subjects oscillate their index finger while viewing a central fixation cross. The stimulus movement frequency was fixed at either 10% below or 10% above the subject's self-paced rate as determined at the start of the experiment. A total of 32 trials ([hand,dot]x[sine,data]x[high frequency,low frequency]x4 trials) were collected. Bhattacharya, J., Pereda, E. & Petsche, H. (2003). Effective Detection of Coupling in Short and Noisy Bivariate Data. IEEE Transactions on systems, man, and cybernetics – Part B: Cybernetics, 33(1), 85-95. Kilner, J.M., Paulignan, Y. & Blakemore, S.J. (2003). An interference effect of observed biological movement on action. Current Biology, 13, 522-525. Oullier, O., de Guzman, G.C., Jantzen, K.J., Lagarde, J.F. & Kelso, J.A.S. (2004). Spontaneous interpersonal synchronization is modulated by the degree of visual coupling. Journal of Sport and Exercise Psychology, 26, S13. Sebanz, N., Knoblich, G. & Prinz, W. (2003). Representing others' actions: Just like one's own? Cognition, 88, B11-B21 Less More Supported by NIMH Grant MH42900