The human dynamic clamp as a paradigm for social interaction

Proceedings of the National Academy of Sciences of the United States of America

Volumn 111, Issue 35, 2014, Pages

  Dumas, Guillaume ^a   De Guzman, Gonzalo C ^a   Tognoli, Emmanuelle ^a   Kelso, J A Scott ^a,b  

^a FLORIDA ATLANTIC UNIVERSITY   (United States)

^b UNIVERSITY OF ULSTER   (United Kingdom)

Author keywords

Artificial agent; Computational social neuroscience; Dynamical systems; Human machine interface; Multiscale

Indexed keywords

ADAPTATION; ADAPTIVE BEHAVIOR; ADULT; ARTICLE; CONTROLLED STUDY; FEMALE; HAND MOVEMENT; HUMAN; HUMAN DYNAMIC CLAMP; HUMAN EXPERIMENT; INDEX FINGER; LEARNING; MALE; MATHEMATICAL MODEL; MATHEMATICAL PHENOMENA; NEUROPHYSIOLOGY; NORMAL HUMAN; PERCEPTION; PRIORITY JOURNAL; SKILL; SOCIAL BEHAVIOR; SOCIAL INTERACTION; THEORETICAL MODEL;

ARTIFICIAL AGENT; COMPUTATIONAL SOCIAL NEUROSCIENCE; DYNAMICAL SYSTEMS; HUMAN-MACHINE INTERFACE; MULTISCALE;

ADAPTATION, PSYCHOLOGICAL; ADOLESCENT; ADULT; ARTIFICIAL INTELLIGENCE; BEHAVIOR; BRAIN; FEMALE; FINGERS; HUMANS; INTERPERSONAL RELATIONS; MALE; MIDDLE AGED; MODELS, THEORETICAL; MOVEMENT; NEUROSCIENCES; PSYCHOMOTOR PERFORMANCE; SOFTWARE; USER-COMPUTER INTERFACE; YOUNG ADULT;

EID: 84907228223     PISSN: 00278424     EISSN: 10916490     Source Type: Journal    
DOI: 10.1073/pnas.1407486111     Document Type: Article

References (80)

1. Prinz AA, Abbott LF, Marder E (2004) The dynamic clamp comes of age. Trends Neurosci 27(4):218-224. (Pubitemid 38376409)
2. Sharp AA, Abbott LF, Marder E (1992) Artificial electrical synapses in oscillatory networks. J Neurophysiol 67(6):1691-1694.
3. Hodgkin AL, Huxley AF (1952) A quantitative description of membrane current and its application to conduction and excitation in nerve. J Physiol 117(4):500-544.
4. Hutcheon B, Miura RM, Puil E (1996) Models of subthreshold membrane resonance in neocortical neurons. J Neurophysiol 76(2):698-714. (Pubitemid 26284564)
5. Turrigiano GG, Marder E, Abbott LF (1996) Cellular short-term memory from a slow potassium conductance. J Neurophysiol 75(2):963-966. (Pubitemid 26073490)
6. Ma M, Koester J (1996) The role of K+ currents in frequency-dependent spike broadening in Aplysia R20 neurons: A dynamic-clamp analysis. J Neurosci 16(13):4089-4101. (Pubitemid 26192405)
7. Hughes SW, Cope DW, Tóth TI, Williams SR, Crunelli V (1999) All thalamocortical neurones possess a T-type Ca2+ 'window' current that enables the expression of bistabilitymediated activities. J Physiol 517(Pt 3):805-815. (Pubitemid 29306466)
8. Manor Y, Nadim F (2001) Frequency regulation demonstrated by coupling a model and a biological neuron. Neurocomputing 38-40:269-278. (Pubitemid 35276648)
9. Hari R, Kujala MV (2009) Brain basis of human social interaction: From concepts to brain imaging. Physiol Rev 89(2):453-479.
10. Kelso JAS (2009) Coordination dynamics. Encyclopedia of Complexity and System Science, ed Meyers RA (Springer, Berlin), pp 1537-1564.
11. Haken H, Kelso JAS, Bunz H (1985) A theoretical model of phase transitions in human hand movements. Biol Cybern 51(5):347-356. (Pubitemid 15135510)
12. Fuchs A (2013) Nonlinear Dynamics in Complex Systems: Theory and Applications for the Life, Neuro- and Natural Sciences (Springer, Heidelberg).
13. Huys R, Jirsa VK, eds (2010) Nonlinear Dynamics in Human Behavior (Springer, Berlin).
14. Huys R, Perdikis D, Jirsa VK (2014) Functional architectures and structured flows on manifolds: A dynamical framework for motor behavior. Psychol Rev, in press.
15. Jirsa VK, Kelso JAS (2005) The excitator as a minimal model for the coordination dynamics of discrete and rhythmic movement generation. J Mot Behav 37(1): 35 - 51.
16. Fink PW, Kelso JAS, Jirsa VK (2009) Perturbation-induced false starts as a test of the Jirsa-Kelso excitator model. J Mot Behav 41(2):147-157.
17. Saltzman EL, Munhall KG (1992) Skill acquisition and development: The roles of state-, parameter, and graph dynamics. J Mot Behav 24(1):49-57.
18. Righetti L, Buchli J, Ijspeert AJ (2009) Adaptive frequency oscillators and applications. The Open Cybernetics and Systemics Journal 3:64-69.
19. Schöner G, Kelso JAS (1988) A dynamic pattern theory of behavioral change. J Theor Biol 135(4):501-524.
20. Kelso JAS, Scholz JP, Schöner G (1988) Dynamics governs switching among patterns of coordination in biological movement. Phys Lett A 134(1):8-12.
21. Scholz JP, Kelso JAS (1990) Intentional switching between patterns of bimanual coordination depends on the intrinsic dynamics of the patterns. J Mot Behav 22(1):98-124. (Pubitemid 20167658)
22. De Luca C, Jantzen KJ, Comani S, Bertollo M, Kelso JAS (2010) Striatal activity during intentional switching depends on pattern stability. J Neurosci 30(9):3167-3174.
23. Rulkov NF, Sushchik MM, Tsimring LS, Abarbanel HDI (1995) Generalized synchronization of chaos in directionally coupled chaotic systems. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics 51(2):980- 994.
24. Kelso JAS, de Guzman GC, Reveley C, Tognoli E (2009) Virtual Partner Interaction (VPI): Exploring novel behaviors via coordination dynamics. PLoS ONE 4(6):e5749.
25. Kelso JAS, Dumas G, Tognoli E (2013) Outline of a general theory of behavior and brain coordination. Neural Netw 37:120-131.
26. Fuchs A, Kelso JAS (2009) Movement coordination. Encyclopedia of Complexity and System Sciences, ed Meyers RA (Springer, Berlin), pp 5718-5736.
27. Kay BA, Kelso JAS, Saltzman EL, Schöner G (1987) Space-time behavior of single and bimanual rhythmical movements: Data and limit cycle model. J Exp Psychol Hum Percept Perform 13(2):178-192.
28. Beek PJ, Schmidt RC, Morris AW, Sim MY, Turvey MT (1995) Linear and nonlinear stiffness and friction in biological rhythmic movements. Biol Cybern 73(6):499-507.
29. Peters J, Schaal S (2006) Reinforcement learning for parameterized motor primitives. Proceedings of the 2006 International Joint Conference on Neural Networks (Institute of Electrical and Electronics Engineers, New York), pp 73-80.
30. Friston K (2011) What is optimal about motor control? Neuron 72(3):488 -498.
31. Kohonen T (1982) Self-organized formation of topologically correct feature maps. Biol Cybern 43(1):59-69.
32. Harvey I, Di Paolo E, Wood R, Quinn M, Tuci E (2005) Evolutionary robotics: A new scientific tool for studying cognition. Artif Life 11(1-2):79-98. (Pubitemid 40394097)
33. Ermentrout B (1991) An adaptive model for synchrony in the firefly pteroptyx malaccae. J Math Biol 29(6):571-585.
34. Large EW, Jones MR (1999) The dynamics of attending: How people track time-varying events. Psychol Rev 106(1):119-159.
35. Righetti L, Buchli J, Ijspeert AJ (2006) Dynamic Hebbian learning in adaptive frequency oscillators. Physica D 216(2):269-281.
36. Kostrubiec V, Zanone PG, Fuchs A, Kelso JAS (2012) Beyond the blank slate: Routes to learning new coordination patterns depend on the intrinsic dynamics of the learnerexperimental evidence and theoretical model. Front Hum Neurosci 6(222):222.
37. Fink PW, Foo P, Jirsa VK, Kelso JA (2000) Local and global stabilization of coordination by sensory information. Exp Brain Res 134(1):9-20.
38. Jirsa VK, Fink P, Foo P, Kelso JAS (2000) Parametric stabilization of biological coordination: A theoretical model. J Biol Phys 26(2):85-112. (Pubitemid 30626450)
39. Kelso JAS (1995) Dynamic Patterns: The Self-Organization of Brain and Behavior (MIT Press, Cambridge, MA).
40. Kelso JAS, Del Colle JD, Schöner G (1990) Action-perception as a pattern formation process. Attention and Performance XIII, ed Jeannerod M (Erlbaum, Hillsdale, NJ), pp 139-169.
41. Fuchs A, Jirsa VK, Haken H, Kelso JAS (1996) Extending the HKB model of coordinated movement to oscillators with different eigenfrequencies. Biol Cybern 74(1):21-30.
42. Dumas G (2011) Towards a two-body neuroscience. Commun Integr Biol 4(3):349-352.
43. Drever J, de Guzman GC, Tognoli E, Kelso JAS (2011) Agency attribution in the virtual partner paradigm. Progress in Motor Control VIII: Recent Advances in Neural, Computational and Dynamical Approaches, ed Riley MA (University of Cincinnati, Cincinnati).
44. Aucouturier JJ, Ikegami T (2009) The illusion of agency: Two engineering approaches to compromise autonomy and reactivity in an artificial system. Adapt Behav 17(5): 402-420.
45. Barandiaran XE, Di Paolo E, Rohde M (2009) Defining agency: Individuality, normativity, asymmetry, and spatio-temporality in action. Adapt Behav 17(5):367-386.
46. Neuringer A, Voss C (1993) Approximating chaotic behavior. Psychol Sci 4(2):113-119.
47. Crutchfield JP, Farmer JD, Packard NH, Shaw RS (1986) Chaos. Sci Am 254(12):46-57.
48. Strogatz SH (2008) Nonlinear Dynamics and Chaos (Westview Press, Cambridge, MA).
49. Zanone PG, Kelso JAS (1992) Evolution of behavioral attractors with learning: Nonequilibrium phase transitions. J Exp Psychol Hum Percept Perform 18(2):403-421.
50. Howard IS, Ingram JN, Körding KP, Wolpert DM (2009) Statistics of natural movements are reflected in motor errors. J Neurophysiol 102(3):1902-1910.
51. Kelso JAS, Buchanan JJ, DeGuzman GC, Ding M (1993) Spontaneous recruitment and annihilation of degrees of freedom in biological coordination. Phys Lett A 179(4-5): 364-368.
52. Pfeiffer UJ, Timmermans B, Bente G, Vogeley K, Schilbach L (2011) A non-verbal Turing test: Differentiating mind from machine in gaze-based social interaction. PLoS ONE 6(11):e27591.
53. Auvray M, Lenay C, Stewart J (2008) Perceptual interactions in a minimalist virtual environment. New Ideas Psychol 27(1):32-47.
54. Froese T, Iizuka H, Ikegami T (2014) Embodied social interaction constitutes social cognition in pairs of humans: A minimalist virtual reality experiment. Sci Rep, 10.1038/ srep03672.
55. West RL, Lebiere C (2001) Simple games as dynamic, coupled systems: Randomness and other emergent properties. Cogn Syst Res 1(4):221-239. (Pubitemid 33718546)
56. Schilbach L, et al. (2013) Toward a second-person neuroscience. Behav Brain Sci 36(4): 393-414.
57. Perdikis D, Huys R, Jirsa VK (2011) Time scale hierarchies in the functional organization of complex behaviors. PLOS Comput Biol 7(9):e1002198.
58. Minati G (2012) Introduction to the meta-structures project: Prospective applications. World Futures 68(8):558-574.
59. Fuchs A, Jirsa VK, Kelso JAS (2000) Theory of the relation between human brain activity (MEG) and hand movements. Neuroimage 11(5 Pt 1):359-369. (Pubitemid 30346952)
60. Nagashino H, Kelso JAS (1992) Phase transitions in oscillatory neural networks. SPIE Science of Artificial Neural Networks 1710:279-287.
61. Beek PJ, Peper CE, Daffertshofer A (2002) Modeling rhythmic interlimb coordination: Beyond the Haken-Kelso-Bunz model. Brain Cogn 48(1):149-165. (Pubitemid 34095199)
62. Jirsa VK, Fuchs A, Kelso JAS (1998) Connecting cortical and behavioral dynamics: Bimanual coordination. Neural Comput 10(8):2019-2045. (Pubitemid 128464294)
63. Jirsa VK, Friedrich R, Haken H, Kelso JAS (1994) A theoretical model of phase transitions in the human brain. Biol Cybern 71(1):27-35.
64. Fitzhugh R (1961) Impulses and physiological states in theoretical models of nerve membrane. Biophys J 1(6):445-466.
65. Banerjee A, Jirsa VK (2007) How do neural connectivity and time delays influence bimanual coordination? Biol Cybern 96(2):265-278. (Pubitemid 46325767)
66. Demarse TB, Wagenaar DA, Blau AW, Potter SM (2001) The neurally controlled animat: Biological brains acting with simulated bodies. Auton Robots 11(3):305-310. (Pubitemid 33109979)
67. Kiss IZ, Rusin CG, Kori H, Hudson JL (2007) Engineering complex dynamical structures: Sequential patterns and desynchronization. Science 316(5833):1886-1889. (Pubitemid 47025785)
68. Yamashita Y, Tani J (2008) Emergence of functional hierarchy in a multiple timescale neural network model: A humanoid robot experiment. PLOS Comput Biol 4(11):e1000220.
69. Santos B, Barandiaran X, Husbands P, Aguilera M, Bedia M (2013) Sensorimotor coordination and metastability in a situated HKB model. Connect Sci 24(4):143-161.
70. Aguilera M, Bedia MG, Santos BA, Barandiaran XE (2013) The situated HKB model: How sensorimotor spatial coupling can alter oscillatory brain dynamics. Front Comput Neurosci 7:117.
71. Revel A, Andry P (2009) Emergence of structured interactions: From a theoretical model to pragmatic robotics. Neural Netw 22(2):116-125.
72. Sporns O, Tononi G, Kötter R (2005) The human connectome: A structural description of the human brain. PLOS Comput Biol 1(4):e42.
73. Larson-Prior LJ, et al.; WU-Minn HCP Consortium (2013) Adding dynamics to the Human Connectome Project with MEG. Neuroimage 80:190-201.
74. Izhikevich EM, Edelman GM (2008) Large-scale model of mammalian thalamocortical systems. Proc Natl Acad Sci USA 105(9):3593-3598. (Pubitemid 351723597)
75. Jirsa VK, Sporns O, Breakspear M, Deco G, McIntosh AR (2010) Towards the virtual brain: Network modeling of the intact and the damaged brain. Arch Ital Biol 148(3): 189-205.
76. Dumas G, Chavez M, Nadel J, Martinerie J (2012) Anatomical connectivity influences both intra- and inter-brain synchronizations. PLoS ONE 7(5):e36414.
77. Dumas G, Nadel J, Soussignan R, Martinerie J, Garnero L (2010) Inter-brain synchronization during social interaction. PLoS ONE 5(8):e12166.
78. Keysers C, Perrett DI (2004) Demystifying social cognition: A Hebbian perspective. Trends Cogn Sci 8(11):501- 507.
79. Billard A, Arbib M (2002) Mirror neurons and the neural basis for learning by imitation. Mirror Neurons and the Evolution of Brain and Language, Advances in Consciousness Research, eds Stamenov M, Gallese V (John Benjamins Publishing Co, Amsterdam), Vol 42, pp 343-352.
80. Turing AM (1950) Computing machinery and intelligence. Mind 59(236):433-460.