A. Perry, N. F. Troje, and S. Bentin, Exploring motor system contributions to the perception of social information: Evidence from EEG activity in the mu/alpha frequency range, Social Neuroscience, vol.25, issue.3, pp.272-284, 2010.
DOI : 10.1016/S0896-6273(03)00679-2

G. Dumas, J. Nadel, R. Soussignan, J. Martinerie, and L. Garnero, Inter-Brain Synchronization during Social Interaction, PLoS ONE, vol.10, issue.177, p.12166, 2010.
DOI : 10.1371/journal.pone.0012166.t002

URL : https://hal.archives-ouvertes.fr/hal-00679917

K. Yun, K. Watanabe, and S. Shimojo, Interpersonal body and neural synchronization as a marker of implicit social interaction, Scientific reports, p.959, 2012.
DOI : 10.1002/(SICI)1097-0193(1999)8:4<194::AID-HBM4>3.0.CO;2-C

M. L. Walters, K. Dautenhahn, R. T. Boekhorst, K. L. Koay, C. Kaouri et al., The influence of subjects' personality traits on personal spatial zones in a human-robot interaction experiment, ROMAN 2005. IEEE International Workshop on Robot and Human Interactive Communication, 2005., pp.347-352, 2005.
DOI : 10.1109/ROMAN.2005.1513803

S. Boucenna, S. Anzalone, E. Tilmont, D. Cohen, and M. Chetouani, Learning of Social Signatures Through Imitation Game Between a Robot and a Human Partner, IEEE Transactions on Autonomous Mental Development, vol.6, issue.3, pp.213-225, 2014.
DOI : 10.1109/TAMD.2014.2319861

S. Boucenna, D. Cohen, A. N. Meltzoff, P. Gaussier, and M. Chetouani, Robots Learn to Recognize Individuals from Imitative Encounters with People and Avatars, Scientific Reports, vol.4, issue.1, 2016.
DOI : 10.3389/fnbot.2013.00016

URL : https://hal.archives-ouvertes.fr/hal-01279447

A. N. Meltzoff, P. K. Kuhl, J. Movellan, and T. J. Sejnowski, Foundations for a New Science of Learning, Science, vol.13, issue.5, pp.284-288, 2009.
DOI : 10.3102/0013189X08322683

S. Boucenna, P. Gaussier, and L. Hafemeister, Development of First Social Referencing Skills: Emotional Interaction as a Way to Regulate Robot Behavior, IEEE Transactions on Autonomous Mental Development, vol.6, issue.1, pp.42-55, 2014.
DOI : 10.1109/TAMD.2013.2284065

URL : https://hal.archives-ouvertes.fr/hal-00871109

A. N. Meltzoff and J. Decety, What imitation tells us about social cognition: a rapprochement between developmental psychology and cognitive neuroscience, Philosophical Transactions of the Royal Society of London B: Biological Sciences, pp.491-500, 2003.
DOI : 10.1098/rstb.2002.1261

A. N. Meltzoff and M. K. Moore, Early imitation within a functional framework: The importance of person identity, movement, and development, Infant Behavior and Development, vol.15, issue.4, pp.479-505, 1992.
DOI : 10.1016/0163-6383(92)80015-M

P. Gaussier and S. Zrehen, PerAc: A neural architecture to control artificial animals, Robotics and Autonomous Systems, vol.16, issue.2-4, pp.291-320, 1995.
DOI : 10.1016/0921-8890(95)00052-6

S. Boucenna, P. Gaussier, P. Andry, and L. Hafemeister, A Robot Learns the Facial Expressions Recognition and Face/Non-face Discrimination Through an Imitation Game, International Journal of Social Robotics, vol.31, issue.1, pp.633-652, 2014.
DOI : 10.1109/TPAMI.2008.52

S. Murata, K. Hirano, H. Arie, S. Sugano, and T. Ogata, Analysis of imitative interactions between humans and a robot with a neurodynamical system, System Integration (SII), 2016 IEEE/SICE International Symposium on. IEEE, pp.343-348, 2016.

T. Kanungo, D. M. Mount, N. S. Netanyahu, C. D. Piatko, R. Silverman et al., An efficient k-means clustering algorithm: analysis and implementation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, issue.7, pp.881-892, 2002.
DOI : 10.1109/TPAMI.2002.1017616

B. Widrow and M. E. Hoff, Adaptive switching circuits, IRE WESCON convention record, pp.96-104, 1960.
DOI : 10.21236/AD0241531