T-type calcium channels promote predictive homeostasis of input-output relations in thalamocortical neurons of lateral geniculate nucleus - Hong, Su Z.; Kim, Haram R.; Fiorillo, Christopher D. (Frontiers in Computational Neuroscience, 2014)
A general theory views the function of all neurons as prediction, and one component of this theory is that of “predictive homeostasis” or “prediction error.” It is well established that sensory systems adapt so that neuronal output maintains sensitivity to sensory input, in accord with information theory. Predictive homeostasis applies the same principle at the cellular level, where the challenge is to maintain membrane excitability at the optimal homeostatic level so that spike generation is maximally sensitive to small gradations in synaptic drive. Negative feedback is a hallmark of homeostatic mechanisms, as exemplified by depolarization-activated potassium channels. However, T-type calcium channels exhibit positive feedback that appears at odds with the theory. In thalamocortical neurons of lateral geniculate nucleus (LGN), T-type channels are capable of causing bursts of spikes with an all-or-none character in response to excitation from a hyperpolarized potential. This “burst mode” would partially uncouple visual input from spike output and reduce the information spikes convey about gradations in visual input. However, past observations of T-type-driven bursts may have resulted from unnaturally high membrane excitability. By mimicking natural patterns of synaptic conductance that occur during vision, we found that T-type channels in rat brain slices did not cause bursts, but rather enabled retinogeniculate excitation to cause spikes despite sustained hyperpolarization, thereby restoring the homeostatic input-output relation observed at depolarized potentials. Our results suggest that T-type channels help to maintain a single optimal mode of transmission rather than creating a second mode. In addition, our results provide evidence for the general theory, which seeks to predict the properties of a neuron’s ion channels and synapses given knowledge of natural patterns of synaptic input.