Passive acoustic mapping utilizing optimal beamforming in ultrasound therapy monitoring.

Passive acoustic mapping (PAM) is a promising imaging method that enables real-time three-dimensional monitoring of ultrasound therapy through the reconstruction of acoustic emissions passively received on an array of ultrasonic sensors. A passive beamforming method is presented that provides greatly improved spatial accuracy over the conventionally used time exposure acoustics (TEA) PAM reconstruction algorithm. Both the Capon beamformer and the robust Capon beamformer (RCB) for PAM are suggested as methods to reduce interference artifacts and improve resolution, which has been one of the experimental issues previously observed with TEA.

Fast transient networks in spontaneous human brain activity.

To provide an effective substrate for cognitive processes, functional brain networks should be able to reorganize and coordinate on a sub-second temporal scale. We used magnetoencephalography recordings of spontaneous activity to characterize whole-brain functional connectivity dynamics at high temporal resolution. Using a novel approach that identifies the points in time at which unique patterns of activity recur, we reveal transient (100-200 ms) brain states with spatial topographies similar to those of well-known resting state networks.

Non-Gaussian probabilistic MEG source localisation based on kernel density estimation.

There is strong evidence to suggest that data recorded from magnetoencephalography (MEG) follows a non-Gaussian distribution. However, existing standard methods for source localisation model the data using only second order statistics, and therefore use the inherent assumption of a Gaussian distribution. In this paper, we present a new general method for non-Gaussian source estimation of stationary signals for localising brain activity from MEG data.

Tremor suppression by rhythmic transcranial current stimulation.

Tremor can dominate Parkinson's disease and yet responds less well to dopaminergic medications than do other cardinal symptoms of this condition. Deep brain stimulation can provide striking tremor relief, but the introduction of stimulating electrodes deep in the substance of the brain carries significant risks, including those of hemorrhage. Here, we pioneer an alternative approach in which we noninvasively apply transcranial alternating current stimulation (TACS) over the motor cortex to induce phase cancellation of the rest tremor rhythm.

Thin-film sparse boundary array design for passive acoustic mapping during ultrasound therapy.

A new 2-D hydrophone array for ultrasound therapy monitoring is presented, along with a novel algorithm for passive acoustic mapping using a sparse weighted aperture. The array is constructed using existing polyvinylidene fluoride (PVDF) ultrasound sensor technology, and is utilized for its broadband characteristics and its high receive sensitivity. For most 2-D arrays, high-resolution imagery is desired, which requires a large aperture at the cost of a large number of elements.

Fusion of magnetometer and gradiometer sensors of MEG in the presence of multiplicative error.

Novel neuroimaging techniques have provided unprecedented information on the structure and function of the living human brain. Multimodal fusion of data from different sensors promises to radically improve this understanding, yet optimal methods have not been developed. Here, we demonstrate a novel method for combining multichannel signals.

A bio-impedance probe to assess liver steatosis during transplant surgery.

This work addresses the design of a bioimpedance probe to assess steatosis on the exposed liver in the donor during liver transplant surgery. Whereas typically bioimpedance uses needle probes to avoid surface effects, for clinical reasons a non-penetrative probe is required. In addition the need to ensure that the measurement is representative of the bulk tissue suggests a larger probe than is normally used to ensure a sufficiently large measurement volume.

An adaptive spectral estimation technique to detect cavitation in HIFU with high spatial resolution.

In ultrasound-guided high-intensity focused ultrasound (HIFU) therapy, the changes observed on tissue are subtle during treatment; some ultrasound-guided HIFU protocols rely on the observation of significant brightness changes as the indicator of tissue lesions. The occurrence of a distinct hyperechogenic region ("bright-up") around the focus is often associated with acoustic cavitation resulting in microbubble formation, but it may indicate different physical events such as larger bubbles from boiling (known to alter acoustic impedance) or sometimes lesion formation. A reliable method to distinguish and spatially localize these causes within the tissue would assist the control of HIFU delivery, which is the subject of this paper.

Application of a null-beamformer to source localisation in MEG data of deep brain stimulation.

In this paper, we present an analysis of magnetoencephalography (MEG) signals from a patient with whole-body chronic pain in order to investigate changes in neural activity induced by DBS. The patient is one of the few cases treated using DBS of the anterior cingulate cortex (ACC). Using MEG to reconstruct the neural activity of interest is challenging because of interference to the signal from the DBS device.

Demand driven deep brain stimulation: regimes and autoregressive hidden Markov implementation.

Deep brain stimulation is an increasingly prevalent surgical option in the treatment of a multitude of neurological conditions, most notably Parkinson's disease. The development of a neurofeedback device is driven primarily by stimulator habituation, surgical risk factors, the cost of battery replacement, and reported neuropsychiatric side-effects under prolonged chronic administration. Here we present two distinct regimes for stimulation delivery in chronic and acute symptomatic conditions, presented in the context of Parkinsonian bradykinesias and tremor.

Model-based ultrasound temperature visualization during and following HIFU exposure.

This paper describes the application of signal processing techniques to improve the robustness of ultrasound feedback for displaying changes in temperature distribution in treatment using high-intensity focused ultrasound (HIFU), especially at the low signal-to-noise ratios that might be expected in in vivo abdominal treatment. Temperature estimation is based on the local displacements in ultrasound images taken during HIFU treatment, and a method to improve robustness to outliers is introduced. The main contribution of the paper is in the application of a Kalman filter, a statistical signal processing technique, which uses a simple analytical temperature model of heat dispersion to improve the temperature estimation from the ultrasound measurements during and after HIFU exposure.