Autoregressive models for biomedical signal processing.

Autoregressive models are ubiquitous tools for the analysis of time series in many domains such as computational neuroscience and biomedical engineering. In these domains, data is, for example, collected from measurements of brain activity. Crucially, this data is subject to measurement errors as well as uncertainties in the underlying system model.

Solving the Bloch equation with periodic excitation using harmonic balancing: application to Rabi modulated excitation.

In waveform design for magnetic resonance applications, periodic continuous-wave excitation offers potential advantages that remain largely unexplored because of a lack of understanding of the Bloch equation with periodic continuous-wave excitations. Using harmonic balancing techniques the steady state solutions of the Bloch equation with periodic excitation can be effectively solved. Moreover, the convergence speed of the proposed series approximation is such that a few terms in the series expansion suffice to obtain a very accurate description of the steady state solution.

Modelling extracellular electrical stimulation: part 4. Effect of the cellular composition of neural tissue on its spatio-temporal filtering properties.

Objective: The objective of this paper is to present a concrete application of the cellular composite model for calculating the membrane potential, described in an accompanying paper.

Approach: A composite model that is used to determine the membrane potential for both longitudinal and transverse modes of stimulation is demonstrated.

Main Results: Two extreme limits of the model, near-field and far-field for an electrode close to or distant from a neuron, respectively, are derived in this paper.

Modelling extracellular electrical stimulation: part 3. Derivation and interpretation of neural tissue equations.

Objective: A common approach in modelling extracellular electrical stimulation is to represent neural tissue by a volume conductor when calculating the activating function as the driving term in a cable equation for the membrane potential. This approach ignores the cellular composition of tissue, including the neurites and their combined effect on the extracellular potential. This has a number of undesirable consequences.

Rabi resonance in spin systems: theory and experiment.

The response of a magnetic resonance spin system is predicted and experimentally verified for the particular case of a continuous wave amplitude modulated radiofrequency excitation. The experimental results demonstrate phenomena not previously observed in magnetic resonance systems, including a secondary resonance condition when the amplitude of the excitation equals the modulation frequency. This secondary resonance produces a relatively large steady state magnetisation with Fourier components at harmonics of the modulation frequency.

Bayesian model evidence for order selection and correlation testing.

Model selection is a critical component of data analysis procedures, and is particularly difficult for small numbers of observations such as is typical of functional MRI datasets. In this paper we derive two Bayesian evidence-based model selection procedures that exploit the existence of an analytic form for the linear Gaussian model class. Firstly, an evidence information criterion is proposed as a model order selection procedure for auto-regressive models, outperforming the commonly employed Akaike and Bayesian information criteria in simulated data.

Patient-specific bivariate-synchrony-based seizure prediction for short prediction horizons.

This paper evaluates the patient-specific seizure prediction performance of pre-ictal changes in bivariate-synchrony between pairs of intracranial electroencephalographic (iEEG) signals within 15min of a seizure in patients with pharmacoresistant focal epilepsy. Prediction horizons under 15min reduce the durations of warning times and should provide adequate time for a seizure control device to intervene. Long-term continuous iEEG was obtained from 6 patients.

Seizure detection using seizure probability estimation: comparison of features used to detect seizures.

This paper analyses seizure detection features and their combinations using a probability-based scalp EEG seizure detection framework developed by Marc Saab and Jean Gotman. Our method was evaluated on 525 h of data, including 88 seizures in 21 patients. The individual performances of the three features used by Saab and Gotman were compared to six alternative features, and combinations of these nine features were analyzed in order to find a superior detector.

Magnetic resonance described in the excitation dependent rotating frame of reference.

An excitation dependent rotating frame of reference to observe the magnetic resonance phenomenon is introduced in this paper that, to the best of our knowledge, has not been used previously in the nuclear magnetic resonance context. The mathematical framework for this new rotating frame of reference is presented based on time scaling the Bloch equation after transformation to the classical rotating frame of reference whose transverse plane is rotating at the Larmor frequency. To this end, the Bloch equation is rewritten in terms of a magnetisation vector observed from the excitation dependent rotating frame of reference.

Voxelwise regularisation of high angular resolution diffusion imaging data.

The problem of noise suppression in high angular resolution diffusion MRI data is approached through direct regularisation of the apparent diffusion coefficient profiles. The proposed algorithm is derived in a Bayesian framework in the style of the traditional techniques for image restoration using Markov random field models. In a novel departure from the classical approach, a Markov random field model is applied within each voxel across gradient directions, thus smoothing the image data without inducing additional spatial dependencies that would render region-of-interest statistical testing of diffusion characteristics invalid.

Chronic airway disease: deteriorating pulmonary function in sheep associated with repeated challenges of house dust mite.

The aim of this work was to characterize lung function and cellular responses in a large animal model for chronic asthma. All sheep were sensitized to house dust mite (HDM) by subcutaneous injection of HDM before lung challenges. Groups of sheep were given weekly lung challenges with either HDM (n = 12) or saline (control, n = 5) for 3 months.