Two interacting brains: a dual-EEG study of social coordination. E. Tognoli - J. Lagarde - G.C. De Guzman - J.A.S. Kelso Center For Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, FL, USA Society for Neurosciences, Washington, 2005 Two interacting brains: a dual-EEG study of social coordination. E. Tognoli - J. Lagarde - G.C. De Guzman - J.A.S. Kelso Center For Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, FL, USA Society for Neurosciences, Washington, 2005 Human Brain and Behavior Laboratory Center for Complex Systems and Brain Sciences – – – – visit us at

Introduction Our theoretical framework: coordination dynamics (Kelso, 1995) ->principle of self- organization in mutually coupled systems. Our questions: - Behavioral change elicited by viewing the other subject's behavior - Corresponding changes in brain dynamics - Creation of social networks: “assemblies of neurons between-brain coalesced into mutually- constrained oscillatory activity” We study the spontaneous motor coordination of two subjects exposed to the view of each other while performing rhythmical finger movement. Mirror-neurons in monkeys (Di Pellegrino et al., 1992) and homologous structures in humans (Grèzes et al., 2003) are active both during execution of a movement and observation of a conspecific performing the same movement. Observation of others’ movements produces embodiment (Rizzolatti et al., 2002) which appears to be related to understanding other’s intentions by simulation (Blakemore & Decety, 2001). Hence, perception/action coupling is a privileged entry-point for scientifically tackling the problem of neurobiological correlates of social interactions.

method The vision of each other is controlled by a fast-switching (1.2ms) LCD screen, turning transparent at t=20s and back to opaque at t=40s Pairs of subjects (n=16, p=8) perform regular continuous finger movements at a comfortable pace during one minute trials. Their simultaneous EEG (1000 Hz, 1 ½ inch inter-electrode distance, 61channels) is acquired with a DUAL-EEG system Their finger movement is collected with two light-axis goniometers t=20-40st=40-60st=0-20s They are instructed to adopt the most comfortable pace, at any time during the trial.

Behavioral profile Episodic transitions to a coupled behavior Only inphase stable Antiphase and inphase stable Effect of the initial phase

Behavioral profile converging changes in frequency of movement: 71% of the trials transient phase-locking: 33% complete state of phase-locking: 25% “Social neglect”Transient phase-locking Fully synchronized inphase Fully synchronized antiphase Fully synchronized with continuation Changes in frequency and phase

Behavioral profile Definition of roles I: changes in frequency One subject changes more; here “red” is the leader (driver), “blue” the follower Both subject change equally None of the subjects changes. Roles are not defined.

81% of the subjects show some decrease in the 8-20Hz frequency bands during visual contact. 19% of the subjects don’t. Changes in the EEG during visual contact ? Brain dynamics

The change in the average spectrum does not reflect a stationary process, but a rarefaction of bursts

Brain dynamics anterior posterior Left right Maximal difference (during-before) over parietal electrodes. Some sinusoidal waves, some triangular (see fig.). Topography central, parietal or occipital. Topology and morphology of these oscillations ?

Brain dynamics Are the left and right hemispheres differentially affected ? Hypothesis: performance of finger movement recruits the contralateral hemisphere. Observation of the other’s movement counterbalances to the ipsilateral hemisphere? -> Reduced asymmetry in two subjects (13%), and increase in two subjects (13%).

Brain dynamics Is coherence between-brain increased during vision ? Idiosyncrasic patterns, for example, this frontal (driver) to parietal (follower) network

During visual contact, the amplitude was decreased in the band [8-20Hz]. Owing to their morphology and topography, several oscillatory mechanisms can be considered including alpha (sustained attention to the partner), mu (increased movement preparation; recruitment of the mirror-neuron system, MNS), and beta (increased demand on motor processing). We explored the hypothesis of a reduced hemispheric asymmetry during perception of the other’s movement (recruitment of the trans-hemispheric MNS system). Such a pattern of result was met in only 13% of the present sample. We conclude that changes in hemipsheric asymmetry is not a generalized feature of mirror-neuron recruitment during concurrent self-execution and other- observation, but may underlie some roles during social coordination. We also identified some idiosyncrasic patterns of between-brain coupling. These patterns await a more in-depth understanding of the roles of each individual within the pair. Discussion

We demonstrated that in a social context, the motor behavior of subjects changes, expressing a coupling between them. Those behavioral changes carry the hallmarks of coordination dynamics: Alteration of intrinsic frequency Phase-locking with preferential coordination modes inphase and antiphase. The brain dynamics exhibited some changes during visual contact as well. One pervasive change was a suppression of alpha and mu/low-beta oscillations. These results suggest the importance of attentional (Mulholland, 1969) and mirror-neuron factors (Fadiga et al, 2005) in social coordination. The variability in oscillatory changes (frequency, topography, asymmetry) probably reflect several strategies and roles rather than a generalized activation of the MNS by observation. conclusion

Acknowledgments: we thank Kevin Powell ( for gracious loan of the LCD screen. Support Contributed By: National Institute of Mental Health (MH42900). references Di Pelligrino et al., (1992). Experimental Brain Research, 91, Grèzes et al., (2003). NeuroImage, 18, Rizzolatti et al., (2002). In Meltzoff & Prinz. The imitative mind: Development, evolution, and brain bases. New York: Cambridge University Press. Blakemore & Decety, (2001). Nature Review Neuroscience, 2, Kelso (1995). Dynamic Patterns: The Self-Organization of Brain and Behavior. MIT press. Mulholland, (1969) In Evans & Mullholand. Attention in Neurophysiology, Butterworths, London. Fadiga et al., (2005). Current Opinion In Neurobiology, 15 (2):