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Transition to Burst Synchronization on Complex Neuron Networks

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Title: Transition to Burst Synchronization on Complex Neuron Networks


1
Transition to Burst Synchronization onComplex
Neuron Networks
  • Zhonghuai Hou(???)
  • 2007.9 Nanjing
  • Department of Chemical Physics
  • Hefei National Lab of Physical Science at
    Microscale
  • University of Science and Technology of China

2
Our research interest
  • Statistical problems in mesoscopic chemical
    systems

Complexity Nonlinearity
  • Nonlinear Dynamics on complex networks

3
A Neuron
4
Diversity Morphology Physiology
  • Oscillation
  • Spiking
  • Bursting
  • Chaos

5
Neuron Network
  • Human Brain 1011 and 104

Complex Network
Small-World Scale-Free
  • Big Challenge Dynamics Functioning

6
An interesting phenomenon ...
  • Central Pattern Generator
  • Small microcircuits
  • Rhythmic motor commands
  • Striking feature
  • Individual irregular,chaotic bursts
  • Ensemble regular, rhythmic bursting

Mechanism ?
7
Related study
  • Chaos Regularization

N.F.Rulkov, PRL 86,183(2001)
8
Related study
  • Ordering Chaos by Random Shortcuts

F. Qi, Z.Hou, H. Xin, PRL 91, 064102 (2003)
9
Related Study
  • Ordering Bursting Chaos

Hindmarsh-Rose (HR) model system
M. Wang, Z.Hou, H.Xin. ChemPhysChem 7,579( 2006)
10
Synchronization of Bursting System
  • Beyond complete synchronization

Spike Syn...
Burst Syn...
11
The present work
  • Fixed Network increased coupling
  • Transition from chaos to BS
  • Different types of BS-states
  • Spike-adding
  • Bursting bifurcation
  • Dynamic cluster separation
  • Homoclinic orbits shrinking
  • Local mean field analysis

12
The model
  • Coupled HR system

SW Network N neurons M added links
Parameters
Chaotic
13
Transition to BS
14
Phase Trajectories
Bursting Bifur...
Spike Adding
15
Phase Transitions
16
Bursting Mechanism
Homoclinic Shrinking
Fast sub-system
Slow Parameter
Fold-Homoclinic(FHC)
Fold-Hopf(FH)
17
Local Mean Field
  • Fluctuate
  • Close to 0
  • Depend weakly on i

18
Perturbed HR system
19
Cluster separation
Valid Robust
20
Remarks
Easier
5 SPB
(Homogeneous)
Hard
6 SPB
Easy
FH
21
Conclusion
  • Transition to BS is investigated
  • Two distinct types of transition
  • Neuron degree is important
  • Local mean field approximation
  • Large, Homogeneous HR network with many random
    links in between can show transition from
    spatiotemporal chaos to
  • BS-states with FHC- and FH-bursting

22
  • Thank you !
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