Quantitative and qualitative evaluation of filter characteristics for wavelet packet compression of MR images.

We present an analysis of the characteristics of different filters for the compression of magnetic resonance images. Compression rates were 33:1 and 50:1. We compare the performance among different types of wavelets presented in the literature and provide quantitative (percentage of energy retained, peak signal to noise ratio) and qualitative (analysis by a group of seven experts) data to support our conclusions. Different types of coiflets, symlets and biorthogonal wavelets are analyzed, and we conclude that for the images under study (T1 weighed images in three planes), the best results are provided by the biorthogonal spline (Daubechies) wavelet 2,6. Several explanations for these results are mentioned.

Human electroencephalogram induces transient coherence in excitable spatiotemporal chaos.

A time series from a human electroencephalogram (EEG) is used as a local perturbation to a reaction-diffusion model with spatiotemporal chaos. For certain finite ranges of amplitude and frequency it is observed that the strongly irregular perturbations can induce transient coherence in the chaotic system. This could be interpreted as "on-line" detection of an inherently correlated pattern embedded in the EEG.

Self-exciting chaos as a dynamic model for irregular neural spiking

We introduce a nonlinear dynamical system with self-exciting chaotic dynamics. Its interspike interval return map shows a noisy Poisson-like distribution. Spike sequences from different initial conditions are unrelated but possess the same mean frequency. In the presence of noisy perturbations, sequences started from different initial conditions synchronize. The features of the model are compared with experimental results for irregular spike sequences in neurons. Self-exciting chaos offers a mechanism for temporal coding of complex input signals.