Collapse of multi-headed chimera states in biologically based neuronal networks.

Chimera states are spatiotemporal patterns with coherent and incoherent dynamics coexisting. These patterns are believed to be involved in important neurophysiological phenomena, such as unihemispheric sleep, multitasking, and epileptic seizures. We explore the emergence and collapse of chimeras in a network of locally coupled excitatory neurons. We consider a biologically realistic conductance-based neuron model that incorporates slow potassium and calcium ion channels, enabling the reproduction of pyramidal neuron dynamics. By varying the coupling strength and the local connectivity radius, we identify transitions from regular spiking to chimera states with one or more incoherent domains. We demonstrate that the number of heads depends on the neuronal connectivity. The multi-headed chimeras exhibit shorter average collapse times than single-headed ones. Our findings contribute to a deeper understanding of transient spatiotemporal structures in biologically inspired excitable models.