  A major challenge in neuroscience is posed by the need for relating the
emerging dynamical features of brain activity with the underlying modular
structure of neural connections, hierarchically organized throughout several
scales. The spontaneous emergence of coherence and synchronization across such
scales is crucial to neural function, while its anomalies often relate to
pathological conditions. Here we provide a numerical study of synchronization
dynamics in the human connectome network. Our purpose is to provide a detailed
characterization of the recently uncovered broad dynamic regime, interposed
between order and disorder, which stems from the hierarchical modular
organization of the human connectome. In this regime -similar in essence to a
Griffiths phase- synchronization dynamics are trapped within metastable
attractors of local coherence. Here we explore the role of noise, as an
effective description of external perturbations, and discuss how its presence
accounts for the ability of the system to escape intermittently from such
attractors and explore complex dynamic repertoires of locally coherent states,
in analogy with experimentally recorded patterns of cerebral activity.
