  We show that chimera patterns can be induced by noise in nonlocally coupled
neural networks in the excitable regime. In contrast to classical chimeras,
occurring in noise-free oscillatory networks, they have features of two
phenomena: coherence resonance and chimera states. Therefore, we call them
coherence-resonance chimeras. These patterns demonstrate the constructive role
of noise and appear for intermediate values of noise intensity, which is a
characteristic feature of coherence resonance. In the coherence-resonance
chimera state a neural network of identical elements splits into two coexisting
domains with different behavior: spatially coherent and spatially incoherent, a
typical property of chimera states. Moreover, these noise-induced chimera
states are characterized by alternating behavior: coherent and incoherent
domains switch periodically their location. We show that this alternating
switching can be explained by analyzing the coupling functions.
