Suppression of cortical electrostimulation artifacts using pre-whitening and null projection.

Objective.Invasive brain-computer interfaces (BCIs) have shown promise in restoring motor function to those paralyzed by neurological injuries. These systems also have the ability to restore sensation via cortical electrostimulation. Cortical stimulation produces strong artifacts that can obscure neural signals or saturate recording amplifiers. While front-end hardware techniques can alleviate this problem, residual artifacts generally persist and must be suppressed by back-end methods.Approach.We have developed a technique based on pre-whitening and null projection (PWNP) and tested its ability to suppress stimulation artifacts in electroencephalogram (EEG), electrocorticogram (ECoG) and microelectrode array (MEA) signals from five human subjects.Main results.In EEG signals contaminated by narrow-band stimulation artifacts, the PWNP method achieved average artifact suppression between 32 and 34 dB, as measured by an increase in signal-to-interference ratio. In ECoG and MEA signals contaminated by broadband stimulation artifacts, our method suppressed artifacts by 78%-80% and 85%, respectively, as measured by a reduction in interference index. When compared to independent component analysis, which is considered the state-of-the-art technique for artifact suppression, our method achieved superior results, while being significantly easier to implement.Significance.PWNP can potentially act as an efficient method of artifact suppression to enable simultaneous stimulation and recording in bi-directional BCIs to biomimetically restore motor function.

Artifact propagation in subdural cortical electrostimulation: Characterization and modeling.

Cortical stimulation via electrocorticography (ECoG) may be an effective method for inducing artificial sensation in bi-directional brain-computer interfaces (BD-BCIs). However, strong electrical artifacts caused by electrostimulation may significantly degrade or obscure neural information. A detailed understanding of stimulation artifact propagation through relevant tissues may improve existing artifact suppression techniques or inspire the development of novel artifact mitigation strategies. Our work thus seeks to comprehensively characterize and model the propagation of artifacts in subdural ECoG stimulation. To this end, we collected and analyzed data from eloquent cortex mapping procedures of four subjects with epilepsy who were implanted with subdural ECoG electrodes. From this data, we observed that artifacts exhibited phase-locking and ratcheting characteristics in the time domain across all subjects. In the frequency domain, stimulation caused broadband power increases, as well as power bursts at the fundamental stimulation frequency and its super-harmonics. The spatial distribution of artifacts followed the potential distribution of an electric dipole with a median goodness-of-fit of R 2 = 0.80 across all subjects and stimulation channels. Artifacts as large as ±1,100 µV appeared anywhere from 4.43 to 38.34 mm from the stimulation channel. These temporal, spectral and spatial characteristics can be utilized to improve existing artifact suppression techniques, inspire new strategies for artifact mitigation, and aid in the development of novel cortical stimulation protocols. Taken together, these findings deepen our understanding of cortical electrostimulation and provide critical design specifications for future BD-BCI systems.

Benchtop and bedside validation of a low-cost programmable cortical stimulator in a testbed for bi-directional brain-computer-interface research.

Introduction: Bi-directional brain-computer interfaces (BD-BCI) to restore movement and sensation must achieve concurrent operation of recording and decoding of motor commands from the brain and stimulating the brain with somatosensory feedback. Methods: A custom programmable direct cortical stimulator (DCS) capable of eliciting artificial sensorimotor response was integrated into an embedded BCI system to form a safe, independent, wireless, and battery powered testbed to explore BD-BCI concepts at a low cost. The BD-BCI stimulator output was tested in phantom brain tissue by assessing its ability to deliver electrical stimulation equivalent to an FDA-approved commercial electrical cortical stimulator. Subsequently, the stimulator was tested in an epilepsy patient with subcortical electrocorticographic (ECoG) implants covering the sensorimotor cortex to assess its ability to elicit equivalent responses as the FDA-approved counterpart. Additional safety features (impedance monitoring, artifact mitigation, and passive and active charge balancing mechanisms) were also implemeneted and tested in phantom brain tissue. Finally, concurrent operation with interleaved stimulation and BCI decoding was tested in a phantom brain as a proof-of-concept operation of BD-BCI system. Results: The benchtop prototype BD-BCI stimulator's basic output features (current amplitude, pulse frequency, pulse width, train duration) were validated by demonstrating the output-equivalency to an FDA-approved commercial cortical electrical stimulator (R 2 > 0.99). Charge-neutral stimulation was demonstrated with pulse-width modulation-based correction algorithm preventing steady state voltage deviation. Artifact mitigation achieved a 64.5% peak voltage reduction. Highly accurate impedance monitoring was achieved with R 2 > 0.99 between measured and actual impedance, which in-turn enabled accurate charge density monitoring. An online BCI decoding accuracy of 93.2% between instructional cues and decoded states was achieved while delivering interleaved stimulation. The brain stimulation mapping via ECoG grids in an epilepsy patient showed that the two stimulators elicit equivalent responses. Significance: This study demonstrates clinical validation of a fully-programmable electrical stimulator, integrated into an embedded BCI system. This low-cost BD-BCI system is safe and readily applicable as a testbed for BD-BCI research. In particular, it provides an all-inclusive hardware platform that approximates the limitations in a near-future implantable BD-BCI. This successful benchtop/human validation of the programmable electrical stimulator in a BD-BCI system is a critical milestone toward fully-implantable BD-BCI systems.

Pre-whitening and Null Projection as an Artifact Suppression Method for Electrocorticography Stimulation in Bi-Directional Brain Computer Interfaces.

Electrocorticography (ECoG)-based bi-directional (BD) brain-computer interfaces (BCIs) are a forthcoming technology promising to help restore function to those with motor and sensory deficits. A major problem with this paradigm is that the cortical stimulation necessary to elicit artificial sensation creates strong electrical artifacts that can disrupt BCI operation by saturating recording amplifiers or obscuring useful neural signal. Even with state-of-the-art hardware artifact suppression methods, robust signal processing techniques are still required to suppress residual artifacts that are present at the digital back-end. Herein we demonstrate the effectiveness of a pre-whitening and null projection artifact suppression method using ECoG data recorded during a clinical neurostimulation procedure. Our method achieved a maximum artifact suppression of 21.49 dB and significantly increased the number of artifact-free frequencies in the frequency domain. This performance surpasses that of a more traditional independent component analysis methodology, while retaining a reduced complexity and increased computational efficiency.

Improving neuropsychological seizure lateralization in Spanish-speaking people with epilepsy in the US: The need to account for education and demographic differences.

OBJECTIVE: The objective of the study was to investigate the predictive seizure lateralization ability of the Neuropsychological Screening Battery for Hispanics (NeSBHIS) in an optimally, demographically matched cohort of primarily immigrant Spanish-speaking people with epilepsy (PWE) living in the US. Linguistically and culturally appropriate neuropsychological measures for Spanish-speaking people are increasingly needed in the US, especially as this diverse, international population grows. The NeSBHIS was developed to meet this need. Previous studies were inconclusive regarding its utility in epilepsy lateralization with PWE. Sample size and demographic variables, particularly educational levels, which anchor neuropsychological normative data and guide clinical use, limited the conclusions of earlier studies. METHODS: A retrospective study, the NeSBHIS battery's ability to predict seizure lateralization in a large cohort of Spanish-speaking PWE (n = 108) was conducted using normative data based on refined, smaller education ranges suggested by the author of the NeSBHIS, Pontón. RESULTS: Regression analysis revealed that four NeSBHIS subtests representing different cognitive domains produced the best model for predicting lateralization: 1) language, 2) attention/mental control, 3) visual memory recall, and 4) verbal memory recall. Prediction accuracy overall was 62% (67.3% for left hemisphere (LH) and 55.8% for right hemisphere (RH)). CONCLUSION: This study demonstrated the clinical utility of the NeSBHIS in seizure lateralization in a large cohort of Spanish-speaking PWE by analyzing standardized scores based on refined, education-based normative samples. These results also highlight that demographic variables, in particular, education, which varies greatly across Spanish-speaking nations in terms of compulsory educational opportunity and quality, must be accounted for more carefully in clinical and research practice.

A benchtop system to assess the feasibility of a fully independent and implantable brain-machine interface.

OBJECTIVE: State-of-the-art invasive brain-machine interfaces (BMIs) have shown significant promise, but rely on external electronics and wired connections between the brain and these external components. This configuration presents health risks and limits practical use. These limitations can be addressed by designing a fully implantable BMI similar to existing FDA-approved implantable devices. Here, a prototype BMI system whose size and power consumption are comparable to those of fully implantable medical devices was designed and implemented, and its performance was tested at the benchtop and bedside. APPROACH: A prototype of a fully implantable BMI system was designed and implemented as a miniaturized embedded system. This benchtop analogue was tested in its ability to acquire signals, train a decoder, perform online decoding, wirelessly control external devices, and operate independently on battery. Furthermore, performance metrics such as power consumption were benchmarked. MAIN RESULTS: An analogue of a fully implantable BMI was fabricated with a miniaturized form factor. A patient undergoing epilepsy surgery evaluation with an electrocorticogram (ECoG) grid implanted over the primary motor cortex was recruited to operate the system. Seven online runs were performed with an average binary state decoding accuracy of 87.0% (lag optimized, or 85.0% at fixed latency). The system was powered by a wirelessly rechargeable battery, consumed ∼150 mW, and operated for >60 h on a single battery cycle. SIGNIFICANCE: The BMI analogue achieved immediate and accurate decoding of ECoG signals underlying hand movements. A wirelessly rechargeable battery and other supporting functions allowed the system to function independently. In addition to the small footprint and acceptable power and heat dissipation, these results suggest that fully implantable BMI systems are feasible.

Characterization of Stimulation Artifact Behavior in Simultaneous Electrocorticography Grid Stimulation and Recording.

Bi-directional brain-computer interfaces (BCIs) require simultaneous stimulation and recording to achieve closed-loop operation. It is therefore important that the interface be able to distinguish between neural signals of interest and stimulation artifacts. Current bi-directional BCIs address this problem by temporally multiplexing stimulation and recording. This approach, however, is suboptimal in many BCI applications. Alternative artifact mitigation methods can be devised by investigating the mechanics of artifact propagation. To characterize stimulation artifact behaviors, we collected and analyzed electrocorticography (ECoG) data from eloquent cortex mapping. Ratcheting and phase-locking of stimulation artifacts were observed, as well as dipole-like properties. Artifacts as large as ±1,100 µV appeared as far as 15-37 mm away from the stimulating channel when stimulating at 10 mA. Analysis also showed that the majority of the artifact power was concentrated at the stimulation pulse train frequency (50 Hz) and its super-harmonics (100, 150, 200 Hz). Lower frequencies (0-32 Hz) experienced minimal artifact contamination. These findings could inform the design of future bi-directional ECoG-based BCIs.

Epilepsy surgery in the underserved Hispanic population improves depression, anxiety, and quality of life.

OBJECTIVE: The objective of this study was to investigate the effect of epilepsy surgery on depression, anxiety, and quality of life (QOL) in a Hispanic, primarily immigrant, Spanish-speaking population with intractable epilepsy (IE). METHODS: Patients with IE from a comprehensive epilepsy treatment center in an urban, public healthcare setting who underwent resective brain surgery between 2008 and 2014 (N=47) and completed presurgical and postsurgical neuropsychological evaluation were retrospectively identified. Presurgical and 1-year postsurgical Beck Depression Inventory-II (BDI-II), Beck Anxiety Inventory (BAI), and QOLIE-31 ratings were analyzed as postsurgical outcome measures. One-tailed paired sample t-tests were used to evaluate whether scores improved postoperatively. Established severity level classifications of depression and anxiety (i.e., minimal, mild, moderate, or severe) were used to analyze changes in occurrence of depression and anxiety. RESULTS: Medium to large improvements on the BDI-II and most QOLIE-31 subscales, with a smaller effect on the BAI and remaining QOLIE-31 subscales, were noted 1-year postsurgery. Levels of depression and anxiety were significantly reduced 1-year postsurgery. Depression, anxiety, and QOL improvements were robust and unaffected by gender, levels of education, or hemisphere of surgery. CONCLUSIONS: This study supports the positive benefits of epilepsy surgery on depression, anxiety, and QOL in Hispanic, primarily undocumented immigrant, Spanish-speaking people with epilepsy (PWE) in the US. These results are useful for educating this particular population about the possible benefits of surgery for IE and can enhance presurgical counseling.