English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

From Structure to Function, via Dynamics

MPS-Authors
/persons/resource/persons78753

Stetter,  Olav
Department of Nonlinear Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

/persons/resource/persons215420

Geisel,  Theo
Department of Nonlinear Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

/persons/resource/persons173457

Battaglia,  Demian
Department of Nonlinear Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

External Ressource
No external resources are shared
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Stetter, O., Soriano, J., Geisel, T., & Battaglia, D. (2013). From Structure to Function, via Dynamics. AIP Conference Proceedings, 64: 1510. doi:10.1063/1.4776502.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0029-103B-9
Abstract
Neurons in the brain are wired into a synaptic network that spans multiple scales, from local circuits within cortical columns to fiber tracts interconnecting distant areas. However, brain function require the dynamic control of inter-circuit interactions on time-scales faster than synaptic changes. In particular, strength and direction of causal influences between neural populations (described by the so-called directed functional connectivity) must be reconfigurable even when the underlying structural connectivity is fixed. Such directed functional influences can be quantified resorting to causal analysis of time-series based on tools like Granger Causality or Transfer Entropy. The ability to quickly reorganize inter-areal interactions is a chief requirement for performance in a changing natural environment. But how can manifold functional networks stem "on demand" from an essentially fixed structure? We explore the hypothesis that the self-organization of neuronal synchronous activity underlies the control of brain functional connectivity. Based on simulated and real recordings of critical neuronal cultures in vitro, as well as on mean-field and spiking network models of interacting brain areas, we have found that "function follows dynamics", rather than structure. Different dynamic states of a same structural network, characterized by different synchronization properties, are indeed associated to different functional digraphs (functional multiplicity). We also highlight the crucial role of dynamics in establishing a structure-to-function link, by showing that whenever different structural topologies lead to similar dynamical states, than the associated functional connectivities are also very similar (structural degeneracy).