Chimera-like states in modular neural networks

Chimera states, namely the coexistence of coherent and incoherent behavior, were previously analyzed in complex networks. However, they have not been extensively studied in modular networks. Here, we consider a neural network inspired by the connectome of the C. elegans soil worm, organized into six interconnected communities, where neurons obey chaotic bursting dynamics. Neurons are assumed to be connected with electrical synapses within their communities and with chemical synapses across them. As our numerical simulations reveal, the coaction of these two types of coupling can shape the dynamics in such a way that chimera-like states can happen. They consist of a fraction of synchronized neurons which belong to the larger communities, and a fraction of desynchronized neurons which are part of smaller communities. In addition to the Kuramoto order parameter ?, we also employ other measures of coherence, such as the chimera-like ? and metastability ? indices, which quantify the degree of synchronization among communities and along time, respectively. We perform the same analysis for networks that share common features with the C. elegans neural network. Similar results suggest that under certain assumptions, chimera-like states are prominent phenomena in modular networks, and might provide insight for the behavior of more complex modular networks

Surface Phonons: Theoretical Methods and Results

peer reviewedThe theoretical methods currently in use for the calculation of surface phononsurface phonon dispersion curves and how they have evolved from the phenomenological force-constant models to the present day first principles theories are discussed. A selection of paradigmatic examples for the different classes of crystal surfaces is presented with comparisons to the experimental data obtained from helium atom scattering or electron energy-loss spectroscopy. © 2020, Springer Nature Switzerland AG