Improving the time efficiency of the Fourier synthesis method for slice selection in magnetic resonance imaging.

The design of slice selective pulses for magnetic resonance imaging can be cast as an optimal control problem. The Fourier synthesis method is an existing approach to solve these optimal control problems. In this method the gradient field as well as the excitation field are switched rapidly and their amplitudes are calculated based on a Fourier series expansion. Here, we provide a novel insight into the Fourier synthesis method via representing the Bloch equation in spherical coordinates. Based on the spherical Bloch equation, we propose an alternative sequence of pulses that can be used for slice selection which is more time efficient compared to the original method. Simulation results demonstrate that while the performance of both methods is approximately the same, the required time for the proposed sequence of pulses is half of the original sequence of pulses. Furthermore, the slice selectivity of both sequences of pulses changes with radio frequency field inhomogeneities in a similar way. We also introduce a measure, referred to as gradient complexity, to compare the performance of both sequences of pulses. This measure indicates that for a desired level of uniformity in the excited slice, the gradient complexity for the proposed sequence of pulses is less than the original sequence.

Probability Steiner trees and maximum parsimony in phylogenetic analysis.

The phylogenetic tree (PT) problem has been studied by a number of researchers as an application of the Steiner tree problem, a well-known network optimisation problem. Of all the methods developed for phylogenies the maximum parsimony (MP) method is a simple and commonly used method because it relies on directly observable changes in the input nucleotide or amino acid sequences. In this paper we show that the non-uniqueness of the evolutionary pathways in the MP method leads us to consider a new model of PTs. In this so-called probability representation model, for each site a node in a PT is modelled by a probability distribution of nucleotide or amino acid states, and hence the PT at a given site is a probability Steiner tree, i.e. a Steiner tree in a high-dimensional vector space. In spite of the generality of the probability representation model, in this paper we restrict our study to constructing probability phylogenetic trees (PPT) using the parsimony criterion, as well as discussing and comparing our approach with the classical MP method. We show that for a given input set although the optimal topology as well as the total tree length of the PPT is the same as the PT constructed by the classical MP method, the inferred ancestral states and branch lengths are different and the results given by our method provide a plausible alternative to the classical ones.

Maximum parsimony, substitution model, and probability phylogenetic trees.

The problem of inferring phylogenies (phylogenetic trees) is one of the main problems in computational biology. There are three main methods for inferring phylogenies-Maximum Parsimony (MP), Distance Matrix (DM) and Maximum Likelihood (ML), of which the MP method is the most well-studied and popular method. In the MP method the optimization criterion is the number of substitutions of the nucleotides computed by the differences in the investigated nucleotide sequences. However, the MP method is often criticized as it only counts the substitutions observable at the current time and all the unobservable substitutions that really occur in the evolutionary history are omitted. In order to take into account the unobservable substitutions, some substitution models have been established and they are now widely used in the DM and ML methods but these substitution models cannot be used within the classical MP method. Recently the authors proposed a probability representation model for phylogenetic trees and the reconstructed trees in this model are called probability phylogenetic trees. One of the advantages of the probability representation model is that it can include a substitution model to infer phylogenetic trees based on the MP principle. In this paper we explain how to use a substitution model in the reconstruction of probability phylogenetic trees and show the advantage of this approach with examples.

A prototype 64-electrode stimulator in 65 nm CMOS process towards a high density epi-retinal prosthesis.

This paper presents a highly flexible 64-electrode stimulator using 65 nm CMOS process fabricated as a stage towards a 1024-electrode epi-retinal prosthesis, which aims to restore partial vision in patients suffering from eye diseases such as retinitis pigmentosa (RP) and age-related macular degradation (AMD). The stimulator drives 64 electrodes with many flexible features, which are necessary before making a complete 1024-electrode implant chip. Each electrode driver can provide a bi-phasic stimulus current with fully programmable parameters such as amplitude, pulse duration, inter-phase gap, and stimulation rate. The electrode driver operates in an alternately pull-push manner with only one current source working at a time, which helps reduce headroom voltage while controlling charge balance at the active electrode. The stimulator varies both stimulus current amplitude and stimulation rate to represent phosphene brightness. The stimulus current amplitude starts from the tissue depolarization threshold with 64 different levels. The selection of active and return electrodes is arbitrary, any electrodes and any number of them can be selected at any time. The power consumption of the stimulator is 400 µW excluding the stimulus power. Measurement results verify correct operation. The stimulator is easily scaled up to drive 1024 electrodes.

A fully flexible stimulator using 65 nm CMOS process for 1024-electrode epi-retinal prosthesis.

This paper presents a fully flexible stimulator using 65 nm CMOS process for a 1024-electrode epi-retinal prosthesis. The stimulator can select any number of electrodes at any time and also supports both mono-polar and multi-polar stimulation. Furthermore, the stimulator supports a wide range of stimulus parameters. A novel feature is that the electrode driver operates in an alternately pull-push manner, which helps reduce headroom voltage while guaranteeing charge balance at the active electrode. The use of positive supplies instead of both positive and negative supplies simplifies CMOS circuit design. The current distribution between two nearby simultaneously active electrode groups was investigated and measurement result showed a maximum current crosstalk of 8%.

Oesophageal techniques for deriving the lung dynamics of quietly breathing sheep.

An airway monitoring system was developed to record the lung dynamics of sheep using oesophageal pressure techniques. These techniques are minimally invasive and do not impede the animal from breathing spontaneously. This study investigates three methods for deriving lung resistance (R) and compliance (C) by evaluating their ability to select regular breaths amongst artefact effected signals. The Multi Linear Regression method, the Modified Mead-Whittenberger (MMW) method and Isovolumetric method were tested against signals with movement and/or swallowing artifacts. Their coefficient of variation (% CV) revealed that the MMW had the least variation with R at 35% CV and C at 25 % CV. The lung dynamics for 14 quietly breathing sheep were R = 1.5 +/- 0.5 cmH2O/l/s, C = 0.20 +/- 0.08 l/cmH2O, tidal volume = 0.25 +/- 0.05 litres and respiratory rate = 26 +/- 6 bpm.

Stability and motor adaptation in human arm movements.

In control, stability captures the reproducibility of motions and the robustness to environmental and internal perturbations. This paper examines how stability can be evaluated in human movements, and possible mechanisms by which humans ensure stability. First, a measure of stability is introduced, which is simple to apply to human movements and corresponds to Lyapunov exponents. Its application to real data shows that it is able to distinguish effectively between stable and unstable dynamics. A computational model is then used to investigate stability in human arm movements, which takes into account motor output variability and computes the force to perform a task according to an inverse dynamics model. Simulation results suggest that even a large time delay does not affect movement stability as long as the reflex feedback is small relative to muscle elasticity. Simulations are also used to demonstrate that existing learning schemes, using a monotonic antisymmetric update law, cannot compensate for unstable dynamics. An impedance compensation algorithm is introduced to learn unstable dynamics, which produces similar adaptation responses to those found in experiments.