A chronic generalized bi-directional brain-machine interface.

A bi-directional neural interface (NI) system was designed and prototyped by incorporating a novel neural recording and processing subsystem into a commercial neural stimulator architecture. The NI system prototype leverages the system infrastructure from an existing neurostimulator to ensure reliable operation in a chronic implantation environment. In addition to providing predicate therapy capabilities, the device adds key elements to facilitate chronic research, such as four channels of electrocortigram/local field potential amplification and spectral analysis, a three-axis accelerometer, algorithm processing, event-based data logging, and wireless telemetry for data uploads and algorithm/configuration updates. The custom-integrated micropower sensor and interface circuits facilitate extended operation in a power-limited device. The prototype underwent significant verification testing to ensure reliability, and meets the requirements for a class CF instrument per IEC-60601 protocols. The ability of the device system to process and aid in classifying brain states was preclinically validated using an in vivo non-human primate model for brain control of a computer cursor (i.e. brain-machine interface or BMI). The primate BMI model was chosen for its ability to quantitatively measure signal decoding performance from brain activity that is similar in both amplitude and spectral content to other biomarkers used to detect disease states (e.g. Parkinson's disease). A key goal of this research prototype is to help broaden the clinical scope and acceptance of NI techniques, particularly real-time brain state detection. These techniques have the potential to be generalized beyond motor prosthesis, and are being explored for unmet needs in other neurological conditions such as movement disorders, stroke and epilepsy.

Simulation of B1 field distribution and intrinsic signal-to-noise in cardiac MRI as a function of static magnetic field.

Two issues that pertain to the optimal static magnetic field for cardiac MRI were addressed: intrinsic signal-to-noise ratio (ISNR) and radiofrequency power deposition. From 1.5 to 9.5 T, proton Larmor frequencies of 63 to 400 MHz, numerical simulations were performed of the RF fields from a surface coil and a body coil loaded by a heterogeneous, three-dimensional, symmetric model of the human chest. The RF field distribution, the power required to produce the RF field, and the ISNR at the center of the heart were computed. The model was validated by comparison with experimental data up to 4 T. The RF field distortion was quantified and found to increase linearly up to 6 T due mostly to dielectric resonance modes. Body coil simulations beyond 6 T showed the onset of higher-order modes at the center of the heart. A range of expected RF power requirements was constructed as a function of field up to 9.5 T for surface coils and up to 6.8 T for body coils. Over this range of static field, ISNR for a constant coil geometry was bracketed by an upper limit that was slightly greater than linear with field and a lower limit that was slightly less than linear with field. The RF power and ISNR showed a strong dependence on chest thickness at 1.5 and 4.0 T. Additionally, independent of chest thickness, the model predicts a lower limit of a factor of 5 increase in RF power as the static field is increased from 1.5 to 4 T. Implications for imaging with other nuclei are discussed. Methods for checking the self-consistency of electrodynamic simulations are presented.

The intrinsic signal-to-noise ratio in human cardiac imaging at 1.5, 3, and 4 T.

Cardiac imaging is inherently demanding on the signal-to-noise performance of the MR scanner and may benefit from high field strengths. However, the complex behavior of the radiofrequency field in the human body at high frequencies makes model-based analyses difficult. This study aims to obtain reliable comparisons of the signal-to-noise profile in the human chest in vivo at 1.5, 3, and 4 T. By using an RF-field-mapping method, it is shown that the intrinsic signal-to-noise increases with the field strength up to 4 T with a less than linear relation. The RF field profile is markedly distorted at 4 T, and the onset of this distortion is dependent on the body size. The high power deposition and the consequences of the RF field distortion are discussed.

The evaluation of dielectric resonators containing H2O or D2O as RF coils for high-field MR imaging and spectroscopy.

Electromagnetic resonators consisting of low-loss dielectric material and/or metallic boundaries are widely used in microwave technologies. These dielectric resonators usually have high Q factors and well-defined field distributions. Magnetic resonance imaging was shown as a way of visualizing the magnetic field distribution of the resonant modes of these resonators, if the dielectric body contains NMR sensitive nuclei. Dielectric resonators have also been proposed as RF coils for magnetic resonance experiments. The feasibility of this idea in high-field MR is discussed here. Specifically, the dielectric resonances of cylindrical water columns were characterized at 170.7 MHz (4 T 1H Larmor frequency), and evaluated as NMR transmit and receive coils. The dielectric resonance of a cylindrical volume of D2O was used to image a hand at 170.7 MHz. This study demonstrated that MRI is an effective way of visualizing the magnetic field in dielectric structures such as a water cylinder, and can potentially be generalized to solid-state dielectric devices. The possible applications of dielectric resonators other than simple cylindrical volumes in MRI and MR solution spectroscopy at high field strengths are also discussed.

Multi-electrode array for measuring evoked potentials from surface of ferret primary auditory cortex.

Using silicon-integrated circuit technology, we have fabricated a flexible multi-electrode array and used it for measuring evoked potentials at the surface of the ferret primary auditory cortex (AI). Traditionally, maps of cortical activity are recorded from numerous sequential penetrations with a single electrode. A common problem with this approach is that the state of the cortex (defined in part by level of anesthesia and number of active cells) changes during the time required to generate these maps. The multi-electrode array reduces this problem by allowing the recording of 24 locations simultaneously. The specific array described in this report is designed to record cortical activity over a 1 mm2 area. It is comprised of 24 gold electrodes (40 x 40 microns2) each spaced 210 microns apart. These electrodes are connected to contact pads via gold leads (5 cm in length). The electrodes, leads, and contact pads are sandwiched between two layers of polyimide. The polyimide passivates the device and makes the device flexible enough to conform to the shape of the cortex. The fabrication procedures described here allow various other layouts and areas to be readily implemented. Measurements of the electrical properties of the electrodes, together with details of the multichannel amplification, acquisition, and display of the data are also discussed. Finally, results of AI mapping experiments with these arrays are illustrated.