  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 the neural network
of the \textit{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 $\rho$, we also employ other measures of
coherence, such as the chimera-like $\chi$ and metastability $\lambda$ 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 \textit{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.
