Burst Synchronization transition in neuronal network of networks Sun Xiaojuan Tsinghua University ICCN2010, Suzhou 2010-10-16.

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Presentation transcript:

Burst Synchronization transition in neuronal network of networks Sun Xiaojuan Tsinghua University ICCN2010, Suzhou

OUTLINE Background Background - Importance of synchronization in neuronal systems - Network of network structures of neuronal systems - Motivation of this work - Motivation of this work Burst synchronization (BS) transition in a neuronal network of networks Burst synchronization (BS) transition in a neuronal network of networks - Mathematical Models - Observed BS transition Conclusions Conclusions

Background

Importance of synchronization in neuronal systems Relationship between synchronization and cognitive behavior  Attention modulates synchronized neuronal firing in primate somatosensory cortex (Ref: Nature, 2000, 404: )  Attention modulates the firing rates of neurons in many parts of the visual system (Ref: Annu. Rev.Neurosci., 2000, 23, )  Expectation boosts synchrony in motor cortex: neurons in the primary motor cortex become transiently synchronized when a stimulus appears, or when it is expected to appear but it does not (Ref: Science, 1997, 278: )  Rivalry induces changes in synchrony in V1 (Ref: PNAS, 1997, 94: )

Importance of synchronization in neuronal systems Relationship between synchronization and brain disorders DisorderNeural synchronyCognitive dysfunctions EpilepsyIncrease in local synchrony; evidence for a reduction in long- range synchronization Perception, executive, processes, memory, attention, social cognitive Alzheimer’ s disease Reduced neural synchrony during resting state; evidence for reduced functional connectivity Working memory, perception, attention, executive process Parkinson’ s disease Increase in neural synchrony in the basal ganglia, but also between subcortical-cortical structures Especially motor functioning, but also perception, working memory,attention, executive process

 clustered structure (Ref. C.C. Hilgetag, Neuroinformatics, 2004, 2: ) Network of network structures of neuronal system Bars indicate borders between nodes in separate clusters.

 Not only clustered but also hierarchy (Ref. C.S. Zhou, et al. New J. Physics, 2007, 9: 178.) Network of network structures of neuronal system Neuronal system is complex and composed by network of networks

Motivation Cited from Ref: Shen Yu et al., PRE, 2008, 77:

BS transition in a neuronal network of networks

Mathematical Models Equations of the discussed neuronal network

Mathematical Models Neuronal Network structure:

BS transition in HR neuronal network Two cases:  M=2, consider the effects of inter- and intra- coupling strength, the random link probability on synchronization of the clustered neuronal network  M>2, except for the above mentioned three factors, we will further consider the effects of cluster numbers on synchronization.

BS transition in HR neuronal network M=2

BS transition in HR neuronal network

Cited from PRE_77_031920

BS transition in HR neuronal network We turn back to the first equation of Eq.(1) and rewrite it as

BS transition in HR neuronal network M>2

BS transition in HR neuronal network M>2

Conclusions

 Under some conditions, coupling strength inside or between subnetworks and the number of links can change the synchrony of a neuronal network, which has clustered structures.  The number of subnetworks inside a network also influence the synchrony.  Our results may give some implications for the importance of synaptic plasticity in neuronal systems.

Thanks for your attention! Thanks Prof. Qishao Lu and Prof. Guanrong Chen