1. EEG COORDINATION DYNAMICS: self-organization in the brain The Human Brain and Behavior Laboratory Emmanuelle Tognoli 12/17/2007 Merck – West-Point http://www.ccs.fau.edu/hbbl.html

2. Introduction The paradigm of EEG in “cognitive neuroscience” The Human Brain and Behavior Laboratory http://www.ccs.fau.edu/hbbl.html

4. local areas inter-areal connectivity, circuits

5. Neuromarkers of social behavior A dual EEG study The Human Brain and Behavior Laboratory http://www.ccs.fau.edu/hbbl.html

7. SUBJECTS: Sixteen subjects (10 males, 6 females, aged between 22 and 41 years, (mean 29 years). Constituted 8 pairs: 4 gender-mixed; 3 male-male; 1 female- female. All right-handed on the basis of self-report. Had normal or corrected-to-normal vision and reported no history of neurological disease. t=20-40st=40-60st=0-20s TRIALS: 36 trials lasting 1 minute. Vision of the other controlled through fast- switching (1.2ms) LCD screen, turning transparent at t=20s and back to opaque at t=40s DUAL-EEG RECORDING: Dual-EEG recorded using two 60-channel EEG caps with Ag-AgCl electrodes (Falk Minow Services, Germany) arranged according to the 10 percent system (midline and rows 1 to 8), with 2 distinct referential montages. Signals directed to a single amplifier (Synamp2, Neuroscan, Texas) analog filtered (Butterworth, bandpass from 0.05 Hz ( -12 dB/octave) to 200 Hz (- 24 dB/octave), amplified (gain= 2010) and digitized at 1000 Hz with a 24 bits ADC in the range ±950 microV (vertical resolution of 0.11nV). Recording performed with the respective grounds located at FPz sites and the references at the corresponding linked mastoids. Impedances maintained below 10 kOhms. TASK: perform regular continuous finger movements at a comfortable pace during one minute trials. Subjects are instructed to adopt the most comfortable pace, at any time during the trial

9. Spatio-spectral patterns 16.384 sec Fs: 1000 Hz Samples: 16384 Spectral Resolution: 0.06Hz Space (scalp surface): 2D Frequency: 1D Amplitude: 1D

14. + =  ERS  ERD  ERD trouble

15. Assessment: method is sensitive (small change -obscured by other processes- can be detected) cracks-down sources of inter-individual variability has a good construct validity (the measure of mu is a measure of mu, not a measure of mixed processes) differentiates difficultly distinguishable neural activities essentially yields information about local areas (see after) The Human Brain and Behavior Laboratory http://www.ccs.fau.edu/hbbl.html

17. Assessment: method is sensitive (small change -obscured by other processes- can be detected) cracks-down sources of inter-individual variability has a good construct validity (the measure of mu is a measure of mu, not a measure of mixed processes) differentiates difficultly distinguishable neural activities essentially yields information about local areas (see after) The Human Brain and Behavior Laboratory http://www.ccs.fau.edu/hbbl.html

18.      variant  

19. Assessment: method is sensitive (small change -obscured by other processes- can be detected) cracks-down sources of inter-individual variability has a good construct validity (the measure of mu is a measure of mu, not a measure of mixed processes) differentiates difficultly distinguishable neural activities essentially yields information about local areas (see after) The Human Brain and Behavior Laboratory http://www.ccs.fau.edu/hbbl.html

20. Theory of Coordination Dynamics: Self-organization of oscillatory ensembles The Human Brain and Behavior Laboratory http://www.ccs.fau.edu/hbbl.html

22. 0  /2  /2  0  /2  /2  0  /2   /2  /3 50 msec 67 msec A B C 0 msec

23.  =  - a sin  - 2b sin (2  ) +  Q  t

24. “…my evidence in the past 18 years for sustained synchrony (never antiphasic), for spatial phase gradients in intracranial EEGs from high-density arrays, and for phase cones with phase velocities corresponding to intracortical axonal propagation velocities as evidence for state transitions.” Walter Freeman

25. 0  /2  /2  A 0 msec Electrical: Spatial summation Chemical: LTP/LTD Zero-Lag Synchronization

26. Transiently Synchronized Neural Cell Assemblies: Phase Locking in the brain? The Human Brain and Behavior Laboratory http://www.ccs.fau.edu/hbbl.html

27. Inphase in scalp EEG?

28. 28 Antiphase in scalp EEG? Indeed by the plenty (too many):

29. Rodriguez et al., 1999 Nature

30. broken symmetry  =  - a sin  - 2b sin (2  ) +  Q  t    Brief Rare Smaller amplitude

31. Forward models Where is the true antiphase? The same volume conduction effect that emphasizes spurious antiphase synchrony also attenuates real antiphase synchrony.

32. Forward models of source pairs: states and transitions The Human Brain and Behavior Laboratory http://www.ccs.fau.edu/hbbl.html

33. E1: A E1 : amplitude at location 1 f E1 :frequency at location 1  E1 : phase at location 1 E2: A E2 : amplitude at location 1 f E2 : frequency at location 1  E2 : phase at location 1 S1: A S1 : amplitude at location 1 f S1 :frequency at location 1  S1 : phase at location 1 S2: A S2 : amplitude at location 1 f S2 : frequency at location 1  S2 : phase at location 1 E1=0.95*S1+p*S2 E2=0.95*S2+p*S1

36. Transitions, intermittency, uncoupled areas

38. AMPLITUDE MODULATION

39. Assessment: While the average picture (part I): -discarded critical information (inter-areal coupling) -created intra- and inter-individual variability -occasionally created fictive properties -prevented introduction many variables/steps in protocols (parameter spaces) The continuous method: -yields first deterministic findings of inter-areal synchronization -has temporal resolution at the limit of recording instruments (pharmaco-dynamics) -has maximal consistency -and above all…

40. Epistemological viewpoint anterior posterior Left right

41. Epistemological viewpoint Interest in real time behavior, especially transients: how to deal with them? If the temporal definition of their onset is insufficient or if their recurrence is too low (remember: average hundreds), we cannot analyze them. Even if we can analyze evoked activity, we may not want to seed the pseudo-real time EEG in the real- real time behavior: Models of EEG

42. In general, EEG amplitude IS NOT speaking about cortical source strength

43. CP4

44. Mu: wicket- shaped (en arceau) Topology: lateral parietal Topology: central/rolan dique Topology: posterior/occi pital Phi: triangular Alpha: sinusoidal