NE_II_L: Neurosciences II. Lectures
Bálint Varga12, László Négyessy1 and Zoltán Somogyvári1
1 Computational Neuroscience and Complex Systems Research Group, Department of Computational Sciences, Wigner Research Centre for Physics, Budapest
2 János Szentágothai Doctoral School of Neurosciences, Semmelweis University, Budapest
Cognition emerges by counterstream feedforward and feedback interactions in the large-scale, hierarchical network of the cerebral cortex. Although cortical dynamics are rooted in the anatomical network, the relationship of structure and function is far from clear. The counterstream, as a topological feature of the network, is captured by the convergence and divergence of paths through directed links. So defined, the convergence degree (CD) reveals the reciprocal nature of forward and backward connections, and also hierarchically relevant integrative properties of areas.
To understand how topology shapes large-scale cortical functioning, and what is the relationship between anatomical (determined by the laminar distribution of connections), topological (defined by CD) and functional (determined by causal coupling) hierarchies.
We used CD to characterize the topology of signal flow properties and implemented an oscillating neural mass model of hierarchical network dynamics. Functional connectivity was computed by spectral Granger causality. Relationships of topology and dynamics were studied via correlations.
Similar to anatomical hierarchy, CD-based topological hierarchy showed high correlation with causal coupling in feedforward gamma and feedback alpha-beta band synchronizations in a subnetwork including low-level visual cortical areas. In contrast, causal coupling did not correlate with edge betweenness, another measure of the importance of network links. Considering the entire network, the CD-based hierarchy correlated well with both the anatomical and functional hierarchy for low-level areas that are hierarchically far apart. Conversely, in a large part of the anatomical network where hierarchical distances are small, correlations were not significant.
These findings indicate that at lower levels of cortical hierarchy interareal connectivity closely shapes large-scale oscillatory dynamics. However, at higher levels hierarchy is not strictly determined, allowing for a flexibility in hierarchical interactions needed to cope with varying demands.
This work was supported by the Hungarian Scientific Research Fund (OTKA); Grant Numbers: NN118902 and K135837, the Wigner RCP and the Eötvös Loránd Research Network (ELKH).
Semmelweis University, János Szentágothai Doctoral School of Neurosciences