title: Functional dissociation of brain rhythms in social coordination.
abstract: OBJECTIVE
  The goal of this research was to investigate sub-band modulations in the mu domain in dyads performing different social coordination tasks.
  
  
  METHODS
  Dyads of subjects performed rhythmic finger movement under three different task conditions: intrinsic - maintain self-produced movement while ignoring their partner's movement; in-phase - synchronize with partner; and anti-phase - maintain syncopation with partner. Movement profiles of the dyads were used to estimate a synchronization index (SI) to verify differences in coordination according to each task. EEG was recorded during task performance and at baseline (partner's actions hidden from view). Log power ratios of mu band activity (active against baseline) were used to assess the relative levels of synchronization/de-synchronization in both the upper and lower mu bands.
  
  
  RESULTS
  Results confirm a functional dissociation of lower (8-10 Hz) and upper (10-12 Hz) mu bands in social coordination tasks. Lower mu band activity was independent of specific modulations across tasks and hemispheric preferences. Upper mu band activity was sensitive to coordination tasks and exhibited marked differences between the hemispheres. Accentuated de-synchronization of right relative to left hemisphere in the anti-phase task appeared related to the greater demand of perceptual-motor discrimination. Left hemisphere de-synchronization in both in-phase and anti-phase coordination was interpreted in terms of successful production of imitation. Right hemisphere synchronization in the intrinsic task was interpreted as inhibition of an imitative response tendency.
  
  
  CONCLUSIONS
  Functional dissociation of lower and upper mu band and hemispheric preferences exists in real-time social coordination.
  
  
  CONCLUSIONS
  This research attests to the merit of analyzing sub-band activity in the alpha-mu domain in order to identify neural correlates of social coordination. Such 'neuromarkers' may be relevant for brain disorders such as apraxia and autism.
authors.affiliation: Intelligent Systems Research Centre, School of Computing and Intelligent Systems, University of Ulster, Magee Campus, Londonderry BT487JL, Northern Ireland, UK. m.naeem@ulster.ac.uk
authors.forename: Muhammad
authors.initials: M
authors.lastname: Naeem
authors.forename: Girijesh
authors.initials: G
authors.lastname: Prasad
authors.forename: David R
authors.initials: DR
authors.lastname: Watson
authors.forename: J A Scott
authors.initials: JA
authors.lastname: Kelso
mesh_terms: D000328:Adult; D000704:Analysis of Variance; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D004569:Electroencephalography; D005260:Female; D005385:Fingers / Q000294:innervation; D007839:Functional Laterality; D006801:Humans; D008297:Male; D009068:Movement / Q000502:physiology*; D010507:Periodicity; D011597:Psychomotor Performance / Q000502:physiology*; D012919:Social Behavior; D013057:Spectrum Analysis; D055815:Young Adult