Multiple thresholds in a model system of noisy ion channels.

Voltage-activated ion channels vary randomly between open and closed states, influenced by the membrane potential and other factors. Signal transduction is enhanced by noise in a simple ion channel model. The enhancement occurs in a finite range of signals; the range can be extended using populations of channels.

[Ca2+] oscillations in a model of energy-dependent Ca2+ uptake by the endoplasmic reticulum.

Active Ca2+ transport in living cells necessitates controlled supply of metabolic energy. Direct coupling between sarco/endoplasmic reticulum (ER) Ca2+ ATPases (SERCA) and intracellular energy-generation sites has been well established experimentally. On the basis of these experimental findings we propose a pump-driven model to investigate complex dynamic properties of a cell system.

Higher-order probabilistic perceptrons as Bayesian inference engines.

An explicit structural connection is established between the Bayes optimal classifier operating on K binary input variables and a corresponding two-layer perceptron having normalized output activities and couplings from input to output units of all orders up to K. With suitable modification of connection weights and biases, such a higher-order probabilistic perceptron should in principle be able to learn the statistics of the classification problem and match the a posteriori probabilities given by Bayes optimal inference. Specific training algorithms are developed that allow this goal to be approximated in a controlled variational sense.