Neuronal basis of Hammel's model for set-point thermoregulation

Abstract

In 1965, H. T. Hammel proposed a neuronal model to explain set-point thermoregulation. His model was based on a synaptic network encompassing four different types of hypothalamic neurons: i.e., warm-sensitive and temperature-insensitive neurons and heat loss and heat production effector neurons. Although some modifications to this model are suggested, recent electrophysiological and morphological studies support many of the model's major tenets. Hypothalamic warm-sensitive neurons integrate core and peripheral thermal information. These neurons sense changes in hypothalamic temperature, and they orient their dendrites medially and laterally to receive ascending afferent input from cutaneous thermoreceptors. Temperature-insensitive neurons have a different dendritic orientation and may provide constant reference signals, which are important in determining thermoregulatory set points. In Hammel's model, temperature-sensitive and -insensitive neurons send mutually antagonistic synaptic inputs to effector neurons controlling various thermoregulatory responses. The model predicts that warm-sensitive neurons synaptically excite heat loss effector neurons and inhibit heat production effector neurons. In recent studies, one counterpart of these effector neurons may be "excitatory postsynaptic potential-driven neurons," the activity of which is dependent on synaptic excitation from nearby cells. Excitatory postsynaptic potential-driven neurons have sparse dendrites that appear to be specifically oriented, either medially or laterally, presumably to receive selective synaptic input from a discrete source. Another counterpart of effector neurons may be "silent neurons," which have extensive dendritic branches that may receive synaptic excitation from remote sources. Because some silent neurons receive synaptic inhibition from nearby warm-sensitive neurons, Hammel's model would predict that they have a role in heat production or heat retention responses.