PubMed · 6081278
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
C E Arregger. 1967. Some technical applications of reflected-light interference microscopy.. https://pubmed.ncbi.nlm.nih.gov/6081278/
Cite the original work for its findings. Save a collection to share your selection of sources.
KEEP EXPLORING
Far-from-equilibrium, spatially extended chaotic systems have generally eluded analytical solution, leading researchers to consider theories based on a statistical rather than a detailed knowledge of the microscopic length scales. Building on the recent discovery of a separation of length scales between macroscopic behavior and microscopic chaos, a simple far-from-equilibrium spatially extended chaotic system has been studied computationally at intermediate, coarse-grained scales. Equilibrium properties such as Gibbs distributions and detailed balance are recovered at these scales, which suggests that the macroscopic behavior of some far-from-equilibrium systems might be understood in terms of equilibrium statistical mechanics.
Two recent papers report the de novo design of a functioning biological circuit using well-characterized genetic elements.(1,2) Gardner et al. designed and constructed a genetic toggle switch while Elowitz and Leibler built an oscillating genetic circuit. Both circuits were designed with the aid of mathematical models. These papers demonstrate progress towards the unification of theory and experiment in the study of genetic circuits. Comparison of the predicted and observed behavior of the circuits, however, shows that the models explain only some of the circuits' properties. Further study of the observed behaviors not predicted by the model would lead to new insight into the properties of genetic networks. BioEssays 22:507-509, 2000.
The spike trains that transmit information between neurons are stochastic. We used the theory of random point processes and simulation methods to investigate the influence of temporal correlation of synaptic input current on firing statistics. The theory accounts for two sources for temporal correlation: synchrony between spikes in presynaptic input trains and the unitary synaptic current time course. Simulations show that slow temporal correlation of synaptic input leads to high variability in firing. In a leaky integrate-and-fire neuron model with spike afterhyperpolarization the theory accurately predicts the firing rate when the spike threshold is higher than two standard deviations of the membrane potential fluctuations. For lower thresholds the spike afterhyperpolarization reduces the firing rate below the theory's predicted level when the synaptic correlation decays rapidly. If the synaptic correlation decays slower than the spike afterhyperpolarization, spike bursts can occur during single broad peaks of input fluctuations, increasing the firing rate over the prediction. Spike bursts lead to a coefficient of variation for the interspike intervals that can exceed one, suggesting an explanation of high coefficient of variation for interspike intervals observed in vivo.