title: Frequency modulation dynamics in neural networks.
abstract: The VCON model described here shares certain qualitative features of stimulus-response characteristics with the data in FIGURE 1 and TABLE 1. At the same time, it provides an uncomplicated methodology for modelling neural networks that emphasizes their frequency aspects. In particular, models based on VCONs are amenable to the rotation vector method, which can be used to uncover stable synchronization of firing within a network. This is described in the appendix, where it is shown that the stable firing patterns within the network correspond to minima of an associated (local) energy function. We have seen here how a model of a simple CPG for breathing can be constructed and analyzed. Similar models for rhythm splitting of small mammal activity cycles, sound location networks, and motility in the gastrointestinal tract have been constructed, and large networks of VCONs have been shown to have stable spatial patterns of synchronization.
mesh_terms: D000200:Action Potentials; D003964:Diaphragm / Q000294:innervation / Q000502:physiology; D008433:Mathematics; D008465:Mechanoreceptors / Q000502:physiology; D008959:Models, Neurological; D009431:Neural Conduction; D009474:Neurons / Q000502:physiology*; D018377:Neurotransmitter Agents / Q000378:metabolism; D012119:Respiration; D013569:Synapses / Q000502:physiology; D009435:Synaptic Transmission
chemical_list: D018377:Neurotransmitter Agents