Toward Completely Sampled Extracellular Neural Recording During fMRI.

This work aims to estimate severe fMRI scanning artifacts in extracellular neural recordings made at ultrahigh magnetic field strengths in order to remove the artifact interferences and uncover the complete neural electrophysiology signal. We build on previous work that used PCA to denoise EEG recorded during fMRI, adapting it to cover the much larger frequency range (1-6000 Hz) of the extracellular field potentials (EFPs) observed by extracellular neural recordings. We examine the singular value decomposition (SVD)-PCA singular value shrinkage (SVS) and compare two shrinkage rules and a sliding template subtraction approach. Additionally, we present a new technique for estimating the singular value upper bounds in spontaneous neural activity recorded in the isoflurane anesthetized rat that uses the temporal first difference of the neural signal. The approaches are tested on artificial datasets to examine their efficacy in detecting extracellular action potentials (EAPs: 300-6000 Hz) recorded during fMRI gradient interferences. Our results indicate that it is possible to uncover the EAPs recorded during gradient interferences. The methods are then tested on natural (non-artificial) datasets recorded from the cortex of isoflurane anesthetized rats, where both local field potential (LFP: 1-300 Hz) and EAP signals are analyzed. The SVS methods are shown to be advantageous compared to sliding template subtraction, especially in the high frequency range corresponding to EAPs. Our novel approach moves us towards simultaneous fMRI and completely sampled neural recording (1-6000Hz with no temporal gaps), providing the opportunity for further study of spontaneous brain function and neurovascular coupling at ultrahigh field in the isoflurane anesthetized rat.

Reference-Free Adaptive Filtering of Extracellular Neural Signals Recording in Ultra-High Field Magnetic Resonance Imaging Scanners: Removal of Periodic Interferences.

This paper focuses on the removal of periodic artifacts from neural signals recorded in rats in ultra-high field (UHF) MRI scanners, using a reference free adaptive feedforward method. Recording extracellular neural signals in the UHF environment is motivated by the desire to combine neural recording and UHF functional magnetic resonance imaging (fMRI) to better understand brain function. However, the neural signals are found to have extremely high noise artifacts of a periodic nature due to electromagnetic interference and due to small oscillatory motions. In particular, noise at 60 Hz and several harmonics of 60 Hz, sinusoidal noise from a pump, and low frequency breathing motion artifacts are observed. Due to significant overlap between the noise frequencies and the neural frequency region of interest, band pass filters cannot be effectively utilized in this application. Hence, this paper develops adaptive least squares feedforward cancellation filters to remove the periodic artifacts. The interference fundamental frequency is identified precisely using an implementation of k-means in an iterative approach. The paper includes significant animal data from rats recorded in an IACUC-approved procedure in 9.4T and 16.4T MRI machines. For breathing artifacts filtered from 4 rats, the mean signal cancellation values at the harmonic interference frequencies are 5.18, 12.97, and 20.87 dB/Hz for a sliding template subtraction, a single-stage impulse reference method, and the cascaded adaptive filtering approach respectively. For pump artifacts filtered from 2 chronically implanted rats, mean signal cancellation values are 2.85, 9.52 and 12.06 dB/Hz respectively. The experimental results show that periodic noise is very effectively removed by the developed cascaded adaptive least squares feedforward algorithm.

Novel Composite Gold-Aluminum Electrode with Application to Neural Recording and Stimulation in Ultrahigh Field Magnetic Resonance Imaging Scanners.

Traditional electrodes used for neural recording and stimulation generate large regions of signal void (no functional MRI signal) when used in ultrahigh field (UHF) MRI scanners. This is a significant disadvantage when simultaneous neural recording/stimulation and fMRI signal acquisition is desired, for example in understanding the functional mechanisms of deep brain stimulation (DBS). In this work, a novel gold-aluminum microwire neural electrode is presented which overcomes this disadvantage. The gold-aluminum design greatly reduces the magnetic susceptibility difference between the electrode and brain tissue leading to significantly reduced regions of signal void. Gold-aluminum microwire samples are imaged at ultrahigh field 16.4 Tesla and compared with gold-only and aluminum-only microwire samples. First, B0 field mapping was used to quantify field distortions at 16.4T and compared with analytical computations in an agarose phantom. The gold-aluminum microwire samples generated substantially less field distortion and signal loss in comparison with gold-only and aluminum-only samples at 16.4T using gradient echo imaging and echo planar imaging sequences. Next, the proposed gold-aluminum electrode was used to successfully record local field potential signals from a rat cortex. The newly proposed gold-aluminum microwire electrode exhibits reduced field distortions and signal loss at 16.4T, a finding which translates to MRI scanners of lower magnetic field strengths as well. The design can be easily reproduced for widespread study of DBS using MRI in animal models. Additionally, the use of non-reactive gold and aluminum materials presents an avenue for translation to human implant applications in the future.

Adaptive virtual referencing for the extraction of extracellularly recorded action potentials in noisy environments.

OBJECTIVE: Removal of common mode noise and artifacts from extracellularly measured action potentials, herein referred to as spikes, recorded with multi-electrode arrays (MEAs) which included severe noise and artifacts generated by an ultrahigh field (UHF) 16.4 Tesla magnetic resonance imaging (MRI) scanner. APPROACH: An adaptive virtual referencing (AVR) algorithm is used to remove artifacts and thus enable extraction of neural spike signals from extracellular recordings in anesthetized rat brains. A 16-channel MEA with 150-micron inter-site spacing is used, and a virtual reference is created by spatially averaging the 16 signal channels which results in a reference signal without extracellular spiking activity while preserving common mode noise and artifacts. This virtual reference signal is then used as the input to an adaptive FIR filter which optimally scales and time-shifts the reference to each specific electrode site to remove the artifacts and noise. MAIN RESULTS: By removing artifacts and reducing noise, the neural spikes at each electrode site can be well extracted, even from data originally recorded with a high noise floor due to electromagnetic interference and artifacts generated by a 16.4T MRI scanner. The AVR method enables many more spikes to be detected than would otherwise be possible. Further, the filtered spike waveforms can be well separated from each other using PCA feature extraction and semi-supervised k-means clustering. While data in a 16.4T MRI scanner contains significantly more noise and artifacts, the developed AVR method enables similar data quality to be extracted as recorded on benchtop experiments outside the MRI scanner. SIGNIFICANCE: AVR of extracellular spike signals recorded with MEAs has not been previously reported and fills a technical need by enabling low-noise extracellular spike extraction in noisy and challenging environments such as UHF MRI that will enable further study of neuro-vascular coupling at UHF.

Computation of Magnetic Field Distortions and Impact on T2*-weighted MRI with Application to Magnetic Susceptibility Parameter Estimation.

A two-step numerical computation of T2* signal weighting maps in gradient echo magnetic resonance imaging in the presence of an object with varied susceptibility property is presented. In the first step, the magnetic scalar potential is computed for an arbitrary 2D magnetic susceptibility distribution using an algebraic solver. The corresponding magnetic field disturbance is computed from the magnetic scalar potential. In the second step, nonlinear operations are used to compute T2* from the magnetic field disturbance and then to generate a map of T2* signal weighting. The linearity of the first step of the solution process is used to implement a superposition of basis solutions approach that increases computational efficiency. Superposition of basis solutions, computed from a system composed of a single node of differing magnetic susceptibility from the surround, herein referred to as the base system, is found to provide an accurate estimation of the scalar potential for arbitrary susceptibility distributions. Afterwards, nonlinear computation of the T2* signal weighting maps can be performed. The properties of the algebraic magnetic scalar potential solver are discussed in this work. Finally, the linearity of the magnetic scalar potential solver is used to estimate the magnetic susceptibility of various objects from in vitro MR-imaging data acquired at 9.4T.

Carbon Nano-Structured Neural Probes Show Promise for Magnetic Resonance Imaging Applications.

OBJECTIVE: Previous animal studies have demonstrated that carbon nanotube (CNT) electrodes provide several advantages of preferential cell growth and better signal-to-noise ratio when interfacing with brain neural tissue. This work explores another advantage of CNT electrodes, namely their MRI compatibility. MRI-compatible neural electrodes that do not produce image artifacts will allow simultaneous co-located functional MRI and neural signal recordings, which will help improve our understanding of the brain. APPROACH: Prototype CNT electrodes on polyimide substrates are fabricated and tested in vitro and in vivo in rat brain at 9.4T. To understand the results of the in vitro and in vivo studies, a simulation model based on numerical computation of the magnetic field around a two-dimensional object in a tissue substrate is developed. MAIN RESULTS: The prototype electrodes are found to introduce negligible image artifacts in structural and functional imaging sequences in vitro and in vivo. Simulation results confirm that CNT prototype electrodes produce less magnetic field distortion than traditional metallic electrodes due to a combination of both superior material properties and geometry. By using CNT films, image artifacts can be nearly eliminated at magnetic fields of strength up to 9.4T. At the same time, the high surface area of a CNT film provides high charge transfer and enables neural local field potential (LFP) recordings with an equal or better signal-to-noise ratio (SNR) than traditional electrodes. SIGNIFICANCE: CNT film electrodes can be used for simultaneous MRI and electrophysiology in animal models to investigate fundamental neuroscience questions and clinically relevant topics such as epilepsy.