Improving functional magnetic resonance imaging motor studies through simultaneous electromyography recordings

Denoising of the gradient artifact present in simultaneous studies of muscle blood oxygen level dependent (BOLD) signal and electromyography (EMG)

The MR-induced gradient artifact affects EMG recordings during simultaneous muscle BOLD/EMG acquisitions. However, no dedicated hardware can remove the gradient artifact easily, and alternative methods are expensive and time-consuming. This study aimed to develop three denoising methods requiring different processing levels and MR-compatible hardware. At two time points, surface EMG was recorded from the lower leg of 6 participants (50:50 sex ratio, age = 26.24.6 yrs., height = 173.59.2 cm, weight = 71.511.4 kg) using a plantar flexion-based block design consisting of 30s of rest followed by 30s of flexion for 5 min, under three conditions: inside the MRI bore, with and without a BOLD sequence (3 T, BOLD sequence, GRE EPI, 10 slices, 64×64 matrix, 2 mm thickness, and TE/TR/flip = 35/3000 ms/70), and outside the MRI environment. Simultaneous BOLD/EMG recordings were denoised using average artifact subtraction with three methods of artifact template creation, each having varying timing and hardware requirements. Method M1 builds the artifact template by recording the scanner triggers coming from the MRI; M2 creates the artifact template with a constant artifact period computed as TR/[number of slices]; M3 estimates the artifact template by looking at the periodicity of the gradient artifact located in the EMG recordings. Following postprocessing, SNR analysis was performed, comparing rest-to-flexion periods, to assess the efficacy of denoising methods and to compare differences between conditions. Linear mixed-effects models showed no significant differences in the mean SNR between denoising methods (p = 0.656). Furthermore, EMG SNR measurements were significantly affected by the magnetic environment (p < 0.05) but not by muscle fatigue over time (p = 0.975). EMG recordings contaminated with gradient artifacts during simultaneous BOLD/EMG can be efficiently denoised using all proposed methods, with two methods requiring no extra hardware. With minimal post-processing, EMG can easily be performed during muscle BOLD MRI studies.

MRI Compatible Lumbopelvic Movement Measurement System to Validate and Capture Task Performance During Neuroimaging

Research suggests that structural and functional changes within the brain are associated with chronic low back pain, and these cortical alterations might contribute to impaired sensorimotor control of the trunk and hips in this population. However, linking sensorimotor brain changes with altered movement of the trunk and hips during task-based neuroimaging presents significant challenges. An MRI-safe pressure measurement system was developed to ensure proper task completion during neuroimaging by capturing movement patterns of the trunk (sensors under the lower back) and hips (sensors embedded in the foam roll under the knees). Pressure changes were measured outside of the scanner by digital differential pressure sensors to capture time-series data and analog pressure gauges for real-time determination of task performance occurring within an MRI bore during brain imaging. This study examined the concurrent validity of air pressure changes between the digital and analog sensors. The digital and analog data were compared in 23 participants during the performance of modified bilateral and unilateral right and left hip bridges. Spearman's correlations were calculated for each sensor during the three bridging tasks and showed high positive correlations, indicating that over 87% of pressure change from the analog gauge can be explained by the pressure from the digital sensor. Bland-Altman plots showed no bias and mean differences were under three mmHg. This pressure system improves the rigor of future studies by validating the digital data from the system and increasing the capabilities of capturing lumbopelvic task performance occurring inside the scanner bore.

Mapping of Spatiotemporal Auricular Electrophysiological Signals Reveals Human Biometric Clusters

Underneath the ear skin there are rich vascular network and sensory nerve branches. Hence, the 3D mapping of auricular electrophysiological signals can provide new biomedical perspectives. However, it is still extremely challenging for current sensing techniques to cover the entire ultra-curved auricle. Here, a 3D graphene-based ear-conformable sensing device with embedded and distributed 3D electrodes for full-auricle physiological monitoring is reported. As a proof-of-concept, spatiotemporal auricular electrical skin resistance (AESR) mapping is demonstrated for the first time, and human subject-specific AESR distributions are observed. From the data of more than 30 ears (both right and left ears), the auricular region-specific AESR changes after cycling exercise are observed in 98% of the tests and are clustered into four groups via machine learning-based data analyses. Correlations of AESR with heart rate and blood pressure are also studied. This 3D electronic platform and AESR-based biometrical findings show promising biomedical applications.

Large-area MRI-compatible epidermal electronic interfaces for prosthetic control and cognitive monitoring

Skin-interfaced medical devices are critically important for diagnosing disease, monitoring physiological health and establishing control interfaces with prosthetics, computer systems and wearable robotic devices. Skin-like epidermal electronic technologies can support these use cases in soft and ultrathin materials that conformally interface with the skin in a manner that is mechanically and thermally imperceptible. Nevertheless, schemes so far have limited the overall sizes of these devices to less than a few square centimetres. Here, we present materials, device structures, handling and mounting methods, and manufacturing approaches that enable epidermal electronic interfaces that are orders of magnitude larger than previously realized. As a proof-of-concept, we demonstrate devices for electrophysiological recordings that enable coverage of the full scalp and the full circumference of the forearm. Filamentary conductive architectures in open-network designs minimize radio frequency-induced eddy currents, forming the basis for structural and functional compatibility with magnetic resonance imaging. We demonstrate the use of the large-area interfaces for the multifunctional control of a transhumeral prosthesis by patients who have undergone targeted muscle-reinnervation surgery, in long-term electroencephalography, and in simultaneous electroencephalography and structural and functional magnetic resonance imaging.

Impact of a single bout of aerobic exercise on regional brain perfusion and activation responses in healthy young adults

Purpose

Despite the generally accepted view that aerobic exercise can have positive effects on brain health, few studies have measured brain responses to exercise over a short time span. The purpose of this study was to examine the impact within one hour of a single bout of exercise on brain perfusion and neuronal activation.

Methods

Healthy adults (n = 16; age range: 20–35 yrs) were scanned using Magnetic Resonance Imaging (MRI) before and after 20 minutes of exercise at 70% of their age-predicted maximal heart rate. Pseudo-continuous arterial spin labeling (pcASL) was used to measure absolute cerebral blood flow (CBF) prior to exercise (pre) and at 10 min (post-10) and 40 min (post-40) post-exercise. Blood oxygenation level dependent (BOLD) functional MRI (fMRI) was performed pre and post-exercise to characterize activation differences related to a go/no-go reaction time task.

Results

Compared to pre-exercise levels, grey matter CBF was 11% (±9%) lower at post-10 (P<0.0004) and not different at post-40 (P = 0.12), while global WM CBF was increased at both time points post-exercise (P<0.0006). Regionally, the hippocampus and insula showed a decrease in perfusion in ROI-analysis at post-10 (P<0.005, FDR corrected), whereas voxel-wise analysis identified elevated perfusion in the left medial postcentral gyrus at post-40 compared to pre (p_corrected = 0.05). BOLD activations were consistent between sessions, however, the left parietal operculum showed reduced BOLD activation after exercise.

Conclusion

This study provides preliminary evidence of regionalized brain effects associated with a single bout of aerobic exercise. The observed acute cerebrovascular responses may provide some insight into the brain’s ability to change in relation to chronic interventions.

Magnetic resonance imaging to visualize stroke and characterize stroke recovery: a review

The global burden of stroke continues to grow. Although stroke prevention strategies (e.g., medications, diet, and exercise) can contribute to risk reduction, options for acute interventions (e.g., thrombolytic therapy for ischemic stroke) are limited to the minority of patients. The remaining patients are often left with profound neurological disabilities that substantially impact quality of life, economic productivity, and increase caregiver burden. In the last decade, however, the future outlook for such patients has been tempered by movement toward the view that the brain is capable of reorganizing after injury. Many now view brain recovery after stroke as an area of scientific research with large potential for therapeutic advances, far into the future (Broderick and William, 2004). As a probe of brain anatomy, function and physiology, magnetic resonance imaging (MRI) is a non-invasive and highly versatile modality that promises to play a particularly important role in such research. Here we provide a basic review of MRI physical principles and applications for assessing stroke, looking toward the future role MRI may play in improving stroke rehabilitation methods and stroke recovery.

Accounting for movement increases sensitivity in detecting brain activity in Parkinson's disease

Parkinson's disease (PD) is manifested by motor impairment, which may impede the ability to accurately perform motor tasks during functional magnetic resonance imaging (fMRI). Both temporal and amplitude deviations of movement performance affect the blood oxygenation level-dependent (BOLD) response. We present a general approach for assessing PD patients' movement control employing simultaneously recorded fMRI time series and behavioral data of the patients' kinematics using MR-compatible gloves. Twelve male patients with advanced PD were examined with fMRI at 1.5T during epoch-based visually paced finger tapping. MR-compatible gloves were utilized online to quantify motor outcome in two conditions with or without dopaminergic medication. Modeling of individual-level brain activity included (i) a predictor consisting of a condition-specific, constant-amplitude boxcar function convolved with the canonical hemodynamic response function (HRF) as commonly used in fMRI statistics (standard model), or (ii) a custom-made predictor computed from glove time series convolved with the HRF (kinematic model). Factorial statistics yielded a parametric map for each modeling technique, showing the medication effect on the group level. Patients showed bilateral response to levodopa in putamen and globus pallidus during the motor experiment. Interestingly, kinematic modeling produced significantly higher activation in terms of both the extent and amplitude of activity. Our results appear to account for movement performance in fMRI motor experiments with PD and increase sensitivity in detecting brain response to levodopa. We strongly advocate quantitatively controlling for motor performance to reach more reliable and robust analyses in fMRI with PD patients.

fMRI brain mapping during motion capture and FES induced motor tasks: signal to noise ratio assessment

Functional Electrical Stimulation (FES) is a well known clinical rehabilitation procedure, however the neural mechanisms that underlie this treatment at Central Nervous System (CNS) level are still not completely understood. Functional magnetic resonance imaging (fMRI) is a suitable tool to investigate effects of rehabilitative treatments on brain plasticity. Moreover, monitoring the effective executed movement is needed to correctly interpret activation maps, most of all in neurological patients where required motor tasks could be only partially accomplished. The proposed experimental set-up includes a 1.5 T fMRI scanner, a motion capture system to acquire kinematic data, and an electro-stimulation device. The introduction of metallic devices and of stimulation current in the MRI room could affect fMRI acquisitions so as to prevent a reliable activation maps analysis. What we are interested in is that the Blood Oxygenation Level Dependent (BOLD) signal, marker of neural activity, could be detected within a given experimental condition and set-up. In this paper we assess temporal Signal to Noise Ratio (SNR) as image quality index. BOLD signal change is about 1-2% as revealed by a 1.5 T scanner. This work demonstrates that, with this innovative set-up, in the main cortical sensorimotor regions 1% BOLD signal change can be detected at least in the 93% of the sub-volumes, and almost 100% of the sub-volumes are suitable for 2% signal change detection. The integrated experimental set-up will therefore allows to detect FES induced movements fMRI maps simultaneously with kinematic acquisitions so as to investigate FES-based rehabilitation treatments contribution at CNS level.

Simultaneous measurements of kinematics and fMRI: compatibility assessment and case report on recovery evaluation of one stroke patient

BACKGROUND

Correlating the features of the actual executed movement with the associated cortical activations can enhance the reliability of the functional Magnetic Resonance Imaging (fMRI) data interpretation. This is crucial for longitudinal evaluation of motor recovery in neurological patients and for investigating detailed mutual interactions between activation maps and movement parameters.Therefore, we have explored a new set-up combining fMRI with an optoelectronic motion capture system, which provides a multi-parameter quantification of the performed motor task.

METHODS

The cameras of the motion system were mounted inside the MR room and passive markers were placed on the subject skin, without any risk or encumbrance. The versatile set-up allows 3-dimensional multi-segment acquisitions including recording of possible mirror movements, and it guarantees a high inter-sessions repeatability.We demonstrated the integrated set-up reliability through compatibility tests. Then, an fMRI block-design protocol combined with kinematic recordings was tested on a healthy volunteer performing finger tapping and ankle dorsal- plantar-flexion. A preliminary assessment of clinical applicability and perspectives was carried out by pre- and post rehabilitation acquisitions on a hemiparetic patient performing ankle dorsal- plantar-flexion. For all sessions, the proposed method integrating kinematic data into the model design was compared with the standard analysis.

RESULTS

Phantom acquisitions demonstrated the not-compromised image quality. Healthy subject sessions showed the protocols feasibility and the model reliability with the kinematic regressor. The patient results showed that brain activation maps were more consistent when the images analysis included in the regression model, besides the stimuli, the kinematic regressor quantifying the actual executed movement (movement timing and amplitude), proving a significant model improvement. Moreover, concerning motor recovery evaluation, after one rehabilitation month, a greater cortical area was activated during exercise, in contrast to the usual focalization associated with functional recovery. Indeed, the availability of kinematics data allows to correlate this wider area with a higher frequency and a larger amplitude of movement.

CONCLUSIONS

The kinematic acquisitions resulted to be reliable and versatile to enrich the fMRI images information and therefore the evaluation of motor recovery in neurological patients where large differences between required and performed motion can be expected.

fMRI-Compatible Registration of Jaw Movements Using a Fiber-Optic Bend Sensor

A functional magnetic resonance imaging (fMRI)-compatible fiber-optic bend sensor was investigated to assess whether the device could be used effectively to monitor opening and closing of the jaw during an fMRI experiment at 3 T. In contrast to surface electromyography, a bend sensor fixed to the chin of the participant is fast and easy to use and is not affected by strong electromagnetic fields. Bend sensor recordings are characterized by high validity (compared with concurrent video recordings of mouth opening) and high reliability (comparing two independent measurements). The results of this study indicate that a bend sensor is able to record the opening and closing of the jaw associated with different overt speech conditions (producing the utterances /a/, /pa/, /pataka/) and the opening of the mouth without speech production. Data post-processing such as filtering was not necessary. There are several potential applications for bend sensor recordings of speech-related jaw movements. First, bend sensor recordings are a valuable tool to assess behavioral performance, such as response latencies, accuracies, and completion times, which is particularly important in children, seniors, or patients with various neurological or psychiatric conditions. Second, the timing information provided by bend sensor data may improve the predicted hemodynamic response that is used for fMRI analysis based on the general linear model (GLM). Third, bend sensor recordings may be included in GLM analyses not for statistical contrast purposes, but as a covariate of no interest, accounting for part of the data variance to model fMRI artifacts due to motion outside the field of view.

Brain activity during a motor learning task: an fMRI and skin conductance study

Measuring electrodermal activity (EDA) during fMRI is an effective means of studying the influence of task-related arousal, inferred from autonomic nervous system activity, on brain activation patterns. The goals of this study were: (1) to measure reliable EDA from healthy individuals during fMRI involving an effortful unilateral motor task, (2) to explore how EDA recordings can be used to augment fMRI data analysis. In addition to conventional hemodynamic modeling, skin conductance time series data were used as model waveforms to generate activation images from fMRI data. Activations from the EDA model produced significantly different brain regions from those obtained with a standard hemodynamic model, primarily in the insula and cingulate cortices. Onsets of the EDA changes were synchronous with the hemodynamic model, but EDA data showed additional transient features, such as a decrease in amplitude with time, and helped to provide behavioral evidence suggesting task difficulty decreased with movement repetition. Univariate statistics also confirmed that several brain regions showed early versus late session effects. Partial least squares (PLS) multivariate analysis of EDA and fMRI data provided complimentary, additional insight on how the motor network varied over the course of a single fMRI session. Brain regions identified in this manner included the insula, cingulate gyrus, pre- and postcentral gyri, putamen and parietal cortices. These results suggest that recording EDA during motor fMRI experiments provides complementary information that can be used to improve the fMRI analysis, particularly when behavioral or task effects are difficult to model a priori.