Compliant head probe for positioning electroencephalography electrodes and near-infrared spectroscopy optodes

ninjaCap: A fully customizable and 3D printable headgear for fNIRS and EEG brain imaging

Significance

Accurate sensor placement is vital for non-invasive brain imaging, particularly for functional near infrared spectroscopy (fNIRS) and diffuse optical tomography (DOT), which lack standardized layouts like EEG. Custom, manually prepared probe layouts on textile caps are often imprecise and labor-intensive.

Aim

We introduce a method for creating personalized, 3D-printed headgear, enabling accurate translation of 3D brain coordinates to 2D printable panels for custom fNIRS and EEG sensor layouts, reducing costs and manual labor.

Approach

Our approach uses atlas-based or subject-specific head models and a spring-relaxation algorithm for flattening 3D coordinates onto 2D panels, using 10-5 EEG coordinates for reference. This process ensures geometrical fidelity, crucial for accurate probe placement. Probe geometries and holder types are customizable and printed directly on the cap, making the approach agnostic to instrument manufacturers and probe types.

Results

Our ninjaCap method offers 2.2±1.5 mm probe placement accuracy. Over the last five years, we have developed and validated this approach with over 50 cap models and 500 participants. A cloud-based ninjaCap generation pipeline along with detailed instructions is now available at openfnirs.org.

Conclusions

The ninjaCap marks a significant advancement in creating individualized neuroimaging caps, reducing costs and labor while improving probe placement accuracy, thereby reducing variability in research.

Comparison of brain activation and functional outcomes between physical and virtual reality box and block test: a case study

PURPOSE

Immersive Virtual Reality (VR) systems allow for highly repetitive tasks to be performed within a virtual environment that increases practice in home environments. VR can increase access to rehabilitation by reducing access barriers. However, rehabilitation outcomes between immersive VR systems and conventional physical rehabilitation are not well understood. The purpose of this case study was to assess the use of a custom clinically based VR simulation for testing gross hand dexterity with an individual with chronic stroke.

MATERIALS AND METHODS

The participant performed the box and blocks test (BBT) in an immersive VR environment and a physical environment. Three trials of the BBT were performed with their less-affected and affected hands each in both environments while measuring cortical activity using fNIRS. Rests were given between trials and environment conditions.

RESULTS

Our results show that there was no statistical difference in the number of blocks moved between the physical and VR BBT for both the affected and less-affected hands. Furthermore, our results also indicate no statistically significant difference between the physical BBT and VR BBT conditions on contralateral motor cortex activation, suggesting that cortical involvement is comparable between physical and VR conditions.

CONCLUSIONS

These results suggest that an immersive VR system may be able to elicit functional and motor cortex activations that are comparable to the conventional physical BBT. Importantly, these findings highlights the potential benefits of VR therapy as a remote therapy intervention and/or to increase the effectiveness and practicality of current in-person rehabilitation programs.Implications for rehabilitationThese findings highlight the potential benefits of immersive virtual reality as a remote therapy intervention.Immersive virtual reality use has potential benefits to increase the effectiveness and practicality of current in-person rehabilitation programs.

A Newcomer's Guide to Functional Near Infrared Spectroscopy Experiments

This review presents a practical primer for functional near-infrared spectroscopy (fNIRS) with respect to technology, experimentation, and analysis software. Its purpose is to jump-start interested practitioners considering utilizing a non-invasive, versatile, nevertheless challenging window into the brain using optical methods. We briefly recapitulate relevant anatomical and optical foundations and give a short historical overview. We describe competing types of illumination (trans-illumination, reflectance, and differential reflectance) and data collection methods (continuous wave, time domain and frequency domain). Basic components (light sources, detection, and recording components) of fNIRS systems are presented. Advantages and limitations of fNIRS techniques are offered, followed by a list of very practical recommendations for its use. A variety of experimental and clinical studies with fNIRS are sampled, shedding light on many brain-related ailments. Finally, we describe and discuss a number of freely available analysis and presentation packages suited for data analysis. In conclusion, we recommend fNIRS due to its ever-growing body of clinical applications, state-of-the-art neuroimaging technique and manageable hardware requirements. It can be safely concluded that fNIRS adds a new arrow to the quiver of neuro-medical examinations due to both its great versatility and limited costs.

Reshaping cortical activity with subthalamic stimulation in Parkinson's disease during finger tapping and gait mapped by near infrared spectroscopy

Exploration of motor cortex activity is essential to understanding the pathophysiology in Parkinson's Disease (PD), but only simple motor tasks can be investigated using a fMRI or PET. We aim to investigate the cortical activity of PD patients during a complex motor task (gait) to verify the impact of deep brain stimulation in the subthalamic nucleus (DBS-STN) by using Near-Infrared-Spectroscopy (NIRS). NIRS is a neuroimaging method of brain cortical activity using low-energy optical radiation to detect local changes in (de)oxyhemoglobin concentration. We used a multichannel portable NIRS during finger tapping (FT) and gait. To determine the signal activity, our methodology consisted of a pre-processing phase for the raw signal, followed by statistical analysis based on a general linear model. Processed recordings from 9 patients were statistically compared between the on and off states of DBS-STN. DBS-STN led to an increased activity in the contralateral motor cortex areas during FT. During gait, we observed a concentration of activity towards the cortex central area in the "stimulation-on" state. Our study shows how NIRS can be used to detect functional changes in the cortex of patients with PD with DBS-STN and indicates its future use for applications unsuited for PET and a fMRI.

Simultaneous EEG, eye-tracking, behavioral, and screen-capture data during online German language learning

This article presents concurrent multimodal data, including EEG, eye-tracking, and behavioral data (cursor movements and clicks), acquired from individuals (N = 22) while engaging in several German language lessons using the web-based Duolingo interface. Lessons were restricted to visual learning only (excluding audio and speech components), including reading and writing vocabulary words and sentences, and matching vocabulary to images. EEG data was collected using the open-source OpenBCI device utilizing dry Ag-AgCl electrodes, while eye-tracking data was recorded using the Gazepoint GP3 system. Timestamped screen captures associated with mouse click and keypress events and user behavior (cursor movements) were acquired using AutoHotKey macro scripts. These data provide neural (EEG), gaze (eye-tracking), and behavioral (mouse movements, clicks, and keypresses) data, with respect to presented language-learning media (Duolingo screen captures) for a wide range of possible scientific analyses and methods development.

Augmented reality-based electrode guidance system for reliable electroencephalography

Background

In longitudinal electroencephalography (EEG) studies, repeatable electrode positioning is essential for reliable EEG assessment. Conventional methods use anatomical landmarks as fiducial locations for the electrode placement. Since the landmarks are manually identified, the EEG assessment is inevitably unreliable because of individual variations among the subjects and the examiners. To overcome this unreliability, an augmented reality (AR) visualization-based electrode guidance system was proposed.

Methods

The proposed electrode guidance system is based on AR visualization to replace the manual electrode positioning. After scanning and registration of the facial surface of a subject by an RGB-D camera, the AR of the initial electrode positions as reference positions is overlapped with the current electrode positions in real time. Thus, it can guide the position of the subsequently placed electrodes with high repeatability.

Results

The experimental results with the phantom show that the repeatability of the electrode positioning was improved compared to that of the conventional 10–20 positioning system.

Conclusion

The proposed AR guidance system improves the electrode positioning performance with a cost-effective system, which uses only RGB-D camera. This system can be used as an alternative to the international 10–20 system.

Shining a Light on Awareness: A Review of Functional Near-Infrared Spectroscopy for Prolonged Disorders of Consciousness

Qualitative clinical assessments of the recovery of awareness after severe brain injury require an assessor to differentiate purposeful behavior from spontaneous behavior. As many such behaviors are minimal and inconsistent, behavioral assessments are susceptible to diagnostic errors. Advanced neuroimaging tools can bypass behavioral responsiveness and reveal evidence of covert awareness and cognition within the brains of some patients, thus providing a means for more accurate diagnoses, more accurate prognoses, and, in some instances, facilitated communication. The majority of reports to date have employed the neuroimaging methods of functional magnetic resonance imaging, positron emission tomography, and electroencephalography (EEG). However, each neuroimaging method has its own advantages and disadvantages (e.g., signal resolution, accessibility, etc.). Here, we describe a burgeoning technique of non-invasive optical neuroimaging—functional near-infrared spectroscopy (fNIRS)—and review its potential to address the clinical challenges of prolonged disorders of consciousness. We also outline the potential for simultaneous EEG to complement the fNIRS signal and suggest the future directions of research that are required in order to realize its clinical potential.

Motion artifact detection and correction in functional near-infrared spectroscopy: a new hybrid method based on spline interpolation method and Savitzky-Golay filtering

Motion artifact contamination in near-infrared spectroscopy (NIRS) data has become an important challenge in realizing the full potential of NIRS for real-life applications. Various motion correction algorithms have been used to alleviate the effect of motion artifacts on the estimation of the hemodynamic response function. While smoothing methods, such as wavelet filtering, are excellent in removing motion-induced sharp spikes, the baseline shifts in the signal remain after this type of filtering. Methods, such as spline interpolation, on the other hand, can properly correct baseline shifts; however, they leave residual high-frequency spikes. We propose a hybrid method that takes advantage of different correction algorithms. This method first identifies the baseline shifts and corrects them using a spline interpolation method or targeted principal component analysis. The remaining spikes, on the other hand, are corrected by smoothing methods: Savitzky-Golay (SG) filtering or robust locally weighted regression and smoothing. We have compared our new approach with the existing correction algorithms in terms of hemodynamic response function estimation using the following metrics: mean-squared error, peak-to-peak error ([Formula: see text]), Pearson's correlation ([Formula: see text]), and the area under the receiver operator characteristic curve. We found that spline-SG hybrid method provides reasonable improvements in all these metrics with a relatively short computational time. The dataset and the code used in this study are made available online for the use of all interested researchers.

A Preliminary Study on Precision Image Guidance for Electrode Placement in an EEG Study

Conventional methods for positioning electroencephalography electrodes according to the international 10/20 system are based on the manual identification of the principal 10/20 landmarks via visual inspection and palpation, inducing intersession variations in their determined locations due to structural ambiguity or poor visibility. To address the variation issue, we propose an image guidance system for precision electrode placement. Following the electrode placement according to the 10/20 system, affixed electrodes are laser-scanned together with the facial surface. For subsequent procedures, the laser scan is conducted likewise after positioning the electrodes in an arbitrary manner, and following the measurement of fiducial electrode locations, frame matching is performed to determine a transformation from the coordinate frame of the position tracker to that of the laser-scanned image. Finally, by registering the intra-procedural scan of the facial surface to the reference scan, the current tracking data of the electrodes can be visualized relative to the reference goal positions without manually measuring the four principal landmarks for each trial. The experimental results confirmed that use of the electrode navigation system significantly improved the electrode placement precision compared to the conventional 10/20 system (p < 0.005). The proposed system showed the possibility of precise image-guided electrode placement as an alternative to the conventional manual 10/20 system.

Use of near-infrared spectroscopy in the investigation of brain activation during cognitive aging: A systematic review of an emerging area of research

The cognitive neuroscience of aging is a growing and stimulating research area. The development of neuroimaging techniques in the past two decades has considerably increased our understanding of the brain mechanisms that might underlie cognitive performance and resulting changes due to normal aging. Beside traditional metabolic neuroimaging techniques, such as Positron Emission Tomography and functional Magnetic Resonance Imaging, near infrared spectroscopy (NIRS), an optical imaging technique allowing to monitor real-time cerebral blood oxygenation, has gained recent interest in this field. The aim of the present review paper, after briefly presenting the NIRS technique, is to review and to summarize the recent results of neuroimaging studies using this technique in the field of cognitive aging. The reviewed literature shows that, despite low spatial resolution and cerebral depth penetration, this technique provides consistent findings on the reduced hemodynamic activity as a function of chronological age, mainly in the prefrontal cortex. Important moderators of brain hemodynamics, such as cognitive load, subjects' characteristics and experimental conditions, for which the NIRS technique is sensitive, are discussed. Strengths and weaknesses of functional NIRS in the field of cognitive aging are presented and finally, novel perspectives of research are proposed.

Hemodynamic correlates of spontaneous neural activity measured by human whole-head resting state EEG+fNIRS

The brains of awake, resting human subjects display spontaneously occurring neural activity patterns whose magnitude is typically many times greater than those triggered by cognitive or perceptual performance. Evoked and resting state activations affect local cerebral hemodynamic properties through processes collectively referred to as neurovascular coupling. Its investigation calls for an ability to track both the neural and vascular aspects of brain function. We used scalp electroencephalography (EEG), which provided a measure of the electrical potentials generated by cortical postsynaptic currents. Simultaneously we utilized functional near-infrared spectroscopy (NIRS) to continuously monitor hemoglobin concentration changes in superficial cortical layers. The multi-modal signal from 18 healthy adult subjects allowed us to investigate the association of neural activity in a range of frequencies over the whole-head to local changes in hemoglobin concentrations. Our results verified the delayed alpha (8-16Hz) modulation of hemodynamics in posterior areas known from the literature. They also indicated strong beta (16-32Hz) modulation of hemodynamics. Analysis revealed, however, that beta modulation was likely generated by the alpha-beta coupling in EEG. Signals from the inferior electrode sites were dominated by scalp muscle related activity. Our study aimed to characterize the phenomena related to neurovascular coupling observable by practical, cost-effective, and non-invasive multi-modal techniques.

Modeling Neurovascular Coupling from Clustered Parameter Sets for Multimodal EEG-NIRS

Despite significant improvements in neuroimaging technologies and analysis methods, the fundamental relationship between local changes in cerebral hemodynamics and the underlying neural activity remains largely unknown. In this study, a data driven approach is proposed for modeling this neurovascular coupling relationship from simultaneously acquired electroencephalographic (EEG) and near-infrared spectroscopic (NIRS) data. The approach uses gamma transfer functions to map EEG spectral envelopes that reflect time-varying power variations in neural rhythms to hemodynamics measured with NIRS during median nerve stimulation. The approach is evaluated first with simulated EEG-NIRS data and then by applying the method to experimental EEG-NIRS data measured from 3 human subjects. Results from the experimental data indicate that the neurovascular coupling relationship can be modeled using multiple sets of gamma transfer functions. By applying cluster analysis, statistically significant parameter sets were found to predict NIRS hemodynamics from EEG spectral envelopes. All subjects were found to have significant clustered parameters (P < 0.05) for EEG-NIRS data fitted using gamma transfer functions. These results suggest that the use of gamma transfer functions followed by cluster analysis of the resulting parameter sets may provide insights into neurovascular coupling in human neuroimaging data.

Correspondence of electroencephalography and near-infrared spectroscopy sensitivities to the cerebral cortex using a high-density layout

This study investigates the correspondence of the cortical sensitivity of electroencephalography (EEG) and near-infrared spectroscopy (NIRS). EEG forward model sensitivity to the cerebral cortex was calculated for 329 EEG electrodes following the 10-5 EEG positioning system using a segmented structural magnetic resonance imaging scan of a human subject. NIRS forward model sensitivity was calculated for the same subject using 156 NIRS source-detector pairs selected from 32 source and 32 detector optodes positioned on the scalp using a subset of the 10-5 EEG positioning system. Sensitivity correlations between colocalized NIRS source-detector pair groups and EEG channels yielded R = 0.46 ± 0.08. Groups of NIRS source-detector pairs with maximum correlations to EEG electrode sensitivities are tabulated. The mean correlation between the point spread functions for EEG and NIRS regions of interest (ROI) was R = 0.43 ± 0.07. Spherical ROIs with radii of 26 mm yielded the maximum correlation between EEG and NIRS averaged across all cortical mesh nodes. These sensitivity correlations between EEG and NIRS should be taken into account when designing multimodal studies of neurovascular coupling and when using NIRS as a statistical prior for EEG source localization.

Algorithm to find high density EEG scalp coordinates and analysis of their correspondence to structural and functional regions of the brain

BACKGROUND

Interpretation and analysis of electroencephalography (EEG) measurements relies on the correspondence of electrode scalp coordinates to structural and functional regions of the brain.

NEW METHOD

An algorithm is introduced for automatic calculation of the International 10-20, 10-10, and 10-5 scalp coordinates of EEG electrodes on a boundary element mesh of a human head. The EEG electrode positions are then used to generate parcellation regions of the cerebral cortex based on proximity to the EEG electrodes.

RESULTS

The scalp electrode calculation method presented in this study effectively and efficiently identifies EEG locations without prior digitization of coordinates. The average of electrode proximity parcellations of the cortex were tabulated with respect to structural and functional regions of the brain in a population of 20 adult subjects.

COMPARISON WITH EXISTING METHODS

Parcellations based on electrode proximity and EEG sensitivity were compared. The parcellation regions based on sensitivity and proximity were found to have 44.0 ± 11.3% agreement when demarcated by the International 10-20, 32.4 ± 12.6% by the 10-10, and 24.7 ± 16.3% by the 10-5 electrode positioning system.

CONCLUSIONS

The EEG positioning algorithm is a fast and easy method of locating EEG scalp coordinates without the need for digitized electrode positions. The parcellation method presented summarizes the EEG scalp locations with respect to brain regions without computation of a full EEG forward model solution. The reference table of electrode proximity versus cortical regions may be used by experimenters to select electrodes that correspond to anatomical and functional regions of interest.

Optimal optode montage on electroencephalography/functional near-infrared spectroscopy caps dedicated to study epileptic discharges

Functional near-infrared spectroscopy (fNIRS), acquired simultaneously with electroencephalography (EEG), allows the investigation of hemodynamic brain responses to epileptic activity. Because the presumed epileptogenic focus is patient-specific, an appropriate source/detector (SD) montage has to be reconfigured for each patient. The combination of EEG and fNIRS, however, entails several constraints on montages, and finding an optimal arrangement of optodes on the cap is an important issue. We present a method for computing an optimal SD montage on an EEG/fNIRS cap that focuses on one or several specific brain regions; the montage maximizes the spatial sensitivity. We formulate this optimization problem as a linear integer programming problem. The method was evaluated on two EEG/fNIRS caps. We simulated absorbers at different locations on a head model and generated realistic optical density maps on the scalp. We found that the maps of optimal SD montages had spatial resolution properties comparable to those of regular SD arrangements for the whole head with significantly fewer sensors than regular SD arrangements. In addition, we observed that optimal montages yielded improved spatial density of fNIRS measurements over the targeted regions together with an increase in signal-to-noise ratio.

Reducing motion artifacts for long-term clinical NIRS monitoring using collodion-fixed prism-based optical fibers

As the applications of near-infrared spectroscopy (NIRS) continue to broaden and long-term clinical monitoring becomes more common, minimizing signal artifacts due to patient movement becomes more pressing. This is particularly true in applications where clinically and physiologically interesting events are intrinsically linked to patient movement, as is the case in the study of epileptic seizures. In this study, we apply an approach common in the application of EEG electrodes to the application of specialized NIRS optical fibers. The method provides improved optode-scalp coupling through the use of miniaturized optical fiber tips fixed to the scalp using collodion, a clinical adhesive. We investigate and quantify the performance of this new method in minimizing motion artifacts in healthy subjects, and apply the technique to allow continuous NIRS monitoring throughout epileptic seizures in two epileptic in-patients. Using collodion-fixed fibers reduces the percent signal change of motion artifacts by 90% and increases the SNR by 6 and 3 fold at 690 and 830 nm wavelengths respectively when compared to a standard Velcro-based array of optical fibers. The SNR has also increased by 2 fold during rest conditions without motion with the new probe design because of better light coupling between the fiber and scalp. The change in both HbO and HbR during motion artifacts is found to be statistically lower for the collodion-fixed fiber probe. The collodion-fixed optical fiber approach has also allowed us to obtain good quality NIRS recording of three epileptic seizures in two patients despite excessive motion in each case.