Presentation is loading. Please wait.

Presentation is loading. Please wait.

Zero-lag synchronization in neural populations: where are the strong evidences? The Human Brain and Behavior Laboratory Emmanuelle Tognoli 02/01/2008 Journal.

Similar presentations


Presentation on theme: "Zero-lag synchronization in neural populations: where are the strong evidences? The Human Brain and Behavior Laboratory Emmanuelle Tognoli 02/01/2008 Journal."— Presentation transcript:

1 Zero-lag synchronization in neural populations: where are the strong evidences? The Human Brain and Behavior Laboratory Emmanuelle Tognoli 02/01/2008 Journal Club http://www.ccs.fau.edu/hbbl.html

2 Synchronization at the microscopic level?

3 3

4 4 100ms 2mV

5 Translation of cortical phase models across levels

6 6 Syn-chronos 0  /2  /2  0  /2  /2  0  /2   /2  /3 50 msec 67 msec A B C 0 msec

7 Hypotheses about phase relationships in neural cell assemblies at macroscopic level

8 8 0  /2  /2  A 0 msec Electrical: Spatial summation Chemical: LTP/LTD Zero-Lag Synchronization

9 9 Electrical: Spatial summation Chemical: LTP/LTD

10 10 “…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 "However, there is an important discrepancy between the EEG phase patterns  (x) and the phase patterns of the model  j. The values of  (x) [real EEG] seldom exceed ±20°, or about 5 percent of the mean cycle duration of the ensemble average. The values for  ji [modeled EEG] range from +70° phase lead to –160° phase lag from the ensemble average” Freeman WJ., (1980). Use of Spatial Deconvolution to Compensate for Distortion of EEG by Volume Conduction. IEEE Transactions On Biomedical Engineering, Vol. Bme-27, No. 8.

11 11  =  - a sin  - 2b sin (2  ) +  Q  t Extended HKB model

12 Hypotheses about phase relationships in neural cell assemblies at macroscopic level Only zero lag Everything… but no antiphase (Near) inphase and (near) antiphase

13 Have we really seen the phase that everybody is talking about?

14 14

15 15

16 16

17 Theoretical hypothesis Mutual influence depends mechanistically on the phase (Markram: synchrony causes synaptic change)Mutual influence depends mechanistically on the phase (Markram: synchrony causes synaptic change) 17

18 Operational hypothesis 18 =f ( )

19 19

20 20 Zero-lag?

21 21 Phase preference? Phase locked?

22 22

23 23

24 24 Adapted from Molotchnikoff & Shumikhina, 2000

25 25

26 26 Tognoli & Kelso, (submitted)

27 27 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 Tognoli & Kelso, (submitted)

28 28 Tognoli & Kelso, (submitted) Two coupled oscillations

29 29 Tognoli & Kelso, (submitted) Two uncoupled oscillations

30 Conclusions: We found no solid evidence to support the preference for zero-lag synchronization in large-scale neural cell assemblies. Because inphase, antiphase, and other phases are differently affected by spurious synchrony, more studies are needed to characterize the real distribution of relative phase in coordinated brain states.


Download ppt "Zero-lag synchronization in neural populations: where are the strong evidences? The Human Brain and Behavior Laboratory Emmanuelle Tognoli 02/01/2008 Journal."

Similar presentations


Ads by Google