Universal properties of correlation transfer in integrate-and-fire neurons

One of the fundamental characteristics of a nonlinear system is how it transfers correlations in its inputs to correlations in its outputs. This is particularly important in the nervous system, where correlations between spiking neurons are prominent. Using linear response and asymptotic methods for pairs of unconnected integrate-and-fire (IF) neurons receiving white noise inputs, we show that this correlation transfer depends on the output spike firing rate in a strong, stereotyped manner, and is, surprisingly, almost independent of the interspike variance. For cells receiving heterogeneous inputs, we further show that correlation increases with the geometric mean spiking rate in the same stereotyped manner, greatly extending the generality of this relationship. We present an immediate consequence of this relationship for population coding via tuning curves

Does the 1/f frequency-scaling of brain signals reflect self-organized critical states?

Many complex systems display self-organized critical states characterized by 1/f frequency scaling of power spectra. Global variables such as the electroencephalogram, scale as 1/f, which could be the sign of self-organized critical states in neuronal activity. By analyzing simultaneous recordings of global and neuronal activities, we confirm the 1/f scaling of global variables for selected frequency bands, but show that neuronal activity is not consistent with critical states. We propose a model of 1/f scaling which does not rely on critical states, and which is testable experimentally.Comment: 3 figures, 6 page

An analytical approach for prediction of elastohydrodynamic friction with inlet shear heating and starvation

An analytical friction model is presented, predicting the coefficient of friction in elastohydrodynamic (EHD) contacts. Three fully formulated SAE 75W-90 axle lubricants are examined. The effect of inlet shear heating (ISH) and starvation is accounted for in the developed friction model. The film thickness and the predicted friction are compared with experimental measurements obtained through optical interferometry and use of a mini traction machine. The results indicate the significant contribution of ISH and starvation on both the film thickness and coefficient of friction. A strong interaction between those two phenomena is also demonstrated, along with their individual and combined contribution on the EHD friction

Timescales of spike-train correlation for neural oscillators with common drive

We examine the effect of the phase-resetting curve (PRC) on the transfer of correlated input signals into correlated output spikes in a class of neural models receiving noisy, super-threshold stimulation. We use linear response theory to approximate the spike correlation coefficient in terms of moments of the associated exit time problem, and contrast the results for Type I vs. Type II models and across the different timescales over which spike correlations can be assessed. We find that, on long timescales, Type I oscillators transfer correlations much more efficiently than Type II oscillators. On short timescales this trend reverses, with the relative efficiency switching at a timescale that depends on the mean and standard deviation of input currents. This switch occurs over timescales that could be exploited by downstream circuits

Motif Statistics and Spike Correlations in Neuronal Networks

Motifs are patterns of subgraphs of complex networks. We studied the impact of such patterns of connectivity on the level of correlated, or synchronized, spiking activity among pairs of cells in a recurrent network model of integrate and fire neurons. For a range of network architectures, we find that the pairwise correlation coefficients, averaged across the network, can be closely approximated using only three statistics of network connectivity. These are the overall network connection probability and the frequencies of two second-order motifs: diverging motifs, in which one cell provides input to two others, and chain motifs, in which two cells are connected via a third intermediary cell. Specifically, the prevalence of diverging and chain motifs tends to increase correlation. Our method is based on linear response theory, which enables us to express spiking statistics using linear algebra, and a resumming technique, which extrapolates from second order motifs to predict the overall effect of coupling on network correlation. Our motif-based results seek to isolate the effect of network architecture perturbatively from a known network state

Correlation transfer in stochastically driven oscillators over long and short time scales

In the absence of synaptic coupling, two or more neural oscillators may become synchronized by virtue of the statistical correlations in their noisy input streams. Recent work has shown that the degree of correlation transfer from input currents to output spikes depends not only on intrinsic oscillator dynamics, but also depends on the length of the observation window over which the correlation is calculated. In this paper we use stochastic phase reduction and regular perturbations to derive the correlation of the total phase elapsed over long time scales, a quantity which provides a convenient proxy for the spike count correlation. Over short time scales, we derive the spike count correlation directly using straightforward probabilistic reasoning applied to the density of the phase difference. Our approximations show that output correlation scales with the autocorrelation of the phase resetting curve over long time scales. We also find a concise expression for the influence of the shape of the phase resetting curve on the initial slope of the output correlation over short time scales. These analytic results together with numerical simulations provide new intuitions for the recent counterintuitive finding that type I oscillators transfer correlations more faithfully than do type II over long time scales, while the reverse holds true for the better understood case of short time scales.Comment: 9 pages, 7 figures, submitted to Physical Review

The effect of age on outcomes of coronary artery bypass surgery compared with balloon angioplasty or bare-metal stent implantation among patients with multivessel coronary disease. A collaborative analysis of individual patient data from 10 randomized trials.

OBJECTIVES: This study sought to assess whether patient age modifies the comparative effectiveness of coronary artery bypass graft (CABG) surgery and percutaneous coronary intervention (PCI). BACKGROUND: Increasingly, CABG and PCI are performed in older patients to treat multivessel disease, but their comparative effectiveness is uncertain. METHODS: Individual data from 7,812 patients randomized in 1 of 10 clinical trials of CABG or PCI were pooled. Age was analyzed as a continuous variable in the primary analysis and was divided into tertiles for descriptive purposes (≤56.2 years, 56.3 to 65.1 years, ≥65.2 years). The outcomes assessed were death, myocardial infarction and repeat revascularization over complete follow-up, and angina at 1 year. RESULTS: Older patients were more likely to have hypertension, diabetes, and 3-vessel disease compared with younger patients (p < 0.001 for trend). Over a median follow-up of 5.9 years, the effect of CABG versus PCI on mortality varied according to age (interaction p < 0.01), with adjusted CABG-to-PCI hazard ratios and 95% confidence intervals (CI) of 1.23 (95% CI: 0.95 to 1.59) in the youngest tertile; 0.89 (95% CI: 0.73 to 1.10) in the middle tertile; and 0.79 (95% CI: 0.67 to 0.94) in the oldest tertile. The CABG-to-PCI hazard ratio of less than 1 for patients 59 years of age and older. A similar interaction of age with treatment was present for the composite outcome of death or myocardial infarction. In contrast, patient age did not alter the comparative effectiveness of CABG and PCI on the outcomes of repeat revascularization or angina. CONCLUSIONS: Patient age modifies the comparative effectiveness of CABG and PCI on hard cardiac events, with CABG favored at older ages and PCI favored at younger ages

Estimating the effective elastic modulus and specific fracture energy of snowpack layers from field experiments

Measurements of the mechanical properties of snow are essential for improving our understanding and the prediction of snow failure and hence avalanche release. We performed fracture mechanical experiments in which a crack was initiated by a saw in a weak snow layer underlying cohesive snow slab layers. Using particle tracking velocimetry (PTV), the displacement field of the slab was determined and used to derive the mechanical energy of the system as a function of crack length. By fitting the estimates of mechanical energy to an analytical expression, we determined the slab effective elastic modulus and weak layer specific fracture energy for 80 different snowpack combinations, including persistent and nonpersistent weak snow layers. The effective elastic modulus of the slab ranged from 0.08 to 34 MPa and increased with mean slab density following a power-law relationship. The weak layer specific fracture energy ranged from 0.08 to 2.7 J m−2 and increased with overburden. While the values obtained for the effective elastic modulus of the slab agree with previously published low-frequency laboratory measurements over the entire density range, the values of the weak layer specific fracture energy are in some cases unrealistically high as they exceeded those of ice. We attribute this discrepancy to the fact that our linear elastic approach does not account for energy dissipation due to non-linear parts of the deformation in the slab and/or weak layer, which would undoubtedly decrease the amount of strain energy available for crack propagation