Adaptations are important in computational neuroscience for their roles in mediating phase response curves and further in affecting spike frequency adaptation, however, their effects on coherent synchronization under different nature of functional circuits are not understood. In this research, the investigators adopt a simple neuron model with adaptation currents which mediate phase response curves in qualitatively different ways, in studying neuronal synchronization emerged from various functional circuits. These investigations include study in stochastic synchrony induced from noise driven of non-interacting neurons, in frequency locking responses resulted from periodically forced entertainment, in coherent synchrony emerged from mutual interactions with increasing intensity, and in coherent synchrony derived from randomly connected networks.
These studies will bring important insights on how adaptations influence the functional neuronal synchronizations in considered circuits, and further lead to a better understanding in distinct biological functional features. Another significant impact of this research is that it facilitates a realistically tuned (via adaptations) yet computationally undemanding model to build networks, in understanding the following coherent neural information coding, such as cortical information processing in neocortex (induced various cognitive functions), or synchronous responses in olfactory bulbs (lead to odor perceptions), visual entrainment in thalamocortical relays (as an anesthetic used during surgery for a relaxation aid), or heat-beat entrainment in respiratory system (used as the foundation to the understanding and treatment of human respiratory problems), selective attention and memory in the cortex, or coherent synchronization in Parkinson and epilepsy diseases, and high connectivity in adjacent areas, and decreased connectivity in increased distant areas among segregated areas of the cortex, or low connectivity in local cortical circuits.
