Electrode Cap for EEG-NIRS Co-Registration

Category: Brain science research

Time：2024-12-21

Introduction to fNIRS

In recent years, brain imaging technologies have made remarkable progress. Brain imaging techniques can be broadly categorized into two main types: 1) structural imaging, such as computed tomography (CT); and 2) functional imaging, such as electroencephalography (EEG). Aside from invasive methods (e.g., cortical electrography), non-invasive functional imaging approaches can primarily be divided into electrophysiological and metabolic methods. Electroencephalography is the most widely used electrophysiological technique, extensively applied in numerous research fields including neuroscience, neurorehabilitation, and brain-computer interfaces (BCIs). EEG measures neural activity with exceptional temporal resolution—on the order of milliseconds—but suffers from poor spatial resolution due to volume conduction effects, thereby limiting the accuracy of source localization. On the other hand, near-infrared spectroscopy (NIRS) is a promising tool for monitoring metabolic changes in the brain. Thanks to its inherent hemodynamic delay, NIRS offers good spatial resolution, albeit at the cost of lower temporal resolution. When confronted with electrical noise and motion-induced muscle artifacts, fNIRS proves more robust than EEG; thus, it can serve as a viable alternative to EEG in noisy environments.

Functional near-infrared spectroscopy (fNIRS) is a novel optical brain-imaging technique that uses near-infrared light to noninvasively, in real time, and continuously monitor changes in tissue oxygenation over extended periods. Near-infrared light—wavelengths ranging from 550 nm to 950 nm—can penetrate biological tissues of a certain thickness and is thus well-suited for assessing the oxygenation levels in the brain. In fNIRS, light emitters are placed on the scalp to shine light into the brain, while detectors measure the reflected light. By analyzing light at specific wavelengths, it is possible to quantify the absorption of hemoglobin and thereby assess blood flow in particular brain regions. As brain regions become more active, their oxygenation levels change accordingly. Researchers can use these changes in blood oxygenation and other related factors to identify brain activity in real time.

fNIRS has been widely applied to the study of normal brain functions in fields such as psychology, education, management, and sports science, as well as to research on brain mechanisms underlying various disease states, including schizophrenia, depression, epilepsy, and disorders of consciousness. Moreover, this technology holds unique advantages in the areas of cognitive development and disease diagnosis in children and infants.

Introduction to EEG-fNIRS

EEG boasts fine temporal resolution (millisecond-level accuracy) but suffers from limited spatial resolution; fNIRS, on the other hand, offers excellent spatial resolution (<1 cm) but has relatively limited temporal resolution (approximately 3 to 6 seconds). Multimodal fusion techniques based on EEG-fNIRS can integrate the advantages of both modalities in terms of temporal and spatial resolution. By combining EEG and fNIRS, it becomes possible to monitor the brain across multiple timescales, at various spatial resolutions, and through different underlying physiological processes. This multimodal integration enables simultaneous acquisition of both neuronal electrical activity and changes in cerebral hemodynamic oxygenation, providing a more comprehensive and accurate reflection of brain functional activity.

The simultaneous EEG and fNIRS system is receiving increasing attention. fNIRS is well-suited for artifact-free recording in conjunction with EEG, as near-infrared light does not interfere with electroencephalographic (EEG) measurements. Over the past decade, an increasing number of research approaches have focused on the concurrent acquisition of EEG and functional near-infrared spectroscopy (fNIRS). The combined EEG-fNIRS technique has demonstrated its advantages across multiple research fields. For instance, hybrid EEG-NIRS BCIs have shown superior classification accuracy compared to single-modality BCIs [1-2], and EEG-NIRS hybrid systems have also been employed to gain a deeper understanding of language functions in newborns and infants [3-4]. Correlation analyses involving EEG and fNIRS have further helped elucidate the complex relationship between electrophysiological and hemodynamic changes in neuroscience [5]. By jointly recording with EEG and fNIRS and performing fusion analysis, researchers have mapped activation response patterns of attention with high spatial and temporal resolution, shedding light on the intriguing neurohemodynamic coupling mechanisms underlying attention [6].

Both of these technologies feature safety, non-invasiveness, low cost, portability and mobility, easy signal acquisition, usability in natural environments, and the capability for long-term continuous monitoring. Compared to single-modal approaches, the EEG-fNIRS fusion technology enhances classification accuracy, increases the number of control commands, and enriches and strengthens system functionality by integrating features from different modalities (neuronal electrical activity signals and changes in hemoglobin concentration signals).

What difficulties does EEG-fNIRS multimodal fusion technology face?

On the one hand, the mismatch in temporal resolution and the inherent delay in hemodynamic responses can to some extent affect the synchrony of features. Morioka et al. proposed an EEG cortical current decoding method based on fNIRS information, using fNIRS features as prior knowledge to estimate cortical EEG signals from EEG data. They demonstrated that this approach outperforms decoding methods relying solely on EEG signals in spatial attention tasks. Sangtae et al. proposed a feature combination method based on feature normalization: by normalizing EEG and fNIRS features to fall within the 0–1 range and then summing these normalized features, they achieved better BCI performance than single-modality approaches in detecting drowsy driving tasks. Although further optimization and exploration are still needed, these two approaches hold promise as future solutions that could overcome the current limitations in fusing EEG and fNIRS features.

On the other hand, mismatches between the recording locations of EEG and fNIRS may affect the interpretation of the neurovascular coupling mechanism in the brain. To address this issue, during the experimental preparation phase, it is crucial to align the spatial positions of the EEG electrodes and the fNIRS optical probes as closely as possible. Since the hemodynamic response recorded by fNIRS is located midway between the light source and the detector, the EEG electrodes should be placed precisely at the midpoint between the light source and the detector, thereby ensuring spatial alignment between the two modalities. Additionally, the signal-to-noise ratio of fNIRS signals may be influenced by the subject’s hair; therefore, during the experimental preparation stage, it is essential to ensure that the optical probes make good contact with the scalp.

EEG-fNIRS combined electrode cap

To simultaneously measure EEG and fNIRS, it is necessary to seamlessly integrate EEG electrodes and fNIRS optical probes into a single electrode cap. Therefore, an important factor is the use of a combined EEG-fNIRS electrode cap. GreenTech can provide a solution for combined EEG-fNIRS electrode caps. Based on the specific research needs of users, we can perfectly integrate EEG electrodes and fNIRS electrodes into the same electrode cap.

Advantages of the Greentech EEG-fNIRS combined electrode cap:

1. A stable cap-mounted support structure that keeps the fNIRS light probes and EEG electrodes in fixed positions, ensuring artifact-free data.

2. The black cap body material ensures that ambient light does not cause distortion.

3. Both EEG electrodes and fNIRS optical probes are lightweight to minimize motion artifacts in the recordings.

4. A variety of freely configurable, wearable, multi-channel EEG-fNIRS combined electrode caps are available. The electrode positions can be flexibly adjusted according to the areas of interest in your study.

5. Different sizes are available, making it suitable for studies involving people of various age groups.

If you have any requirements for EEG-fNIRS combined electrode caps, please contact GreenTech’s technical staff in the research field. Contact: Dr. Li, phone number: 15926282558.

References

Fazli, S. et al. Enhanced performance by a hybrid NIRS-EEG brain-computer interface. Neuroimage 59, 519–529 (2012).
Fazli, S. & Lee, S.-W. Brain-computer interfacing: a multi-modal perspective. J. Comput. Sci. Eng. 7, 132–138 (2013).
Wallois, F., Mahmoudzadeh, M., Patil, A. & Grebe, R. The usefulness of simultaneous EEG-NIRS recording in language studies. Brain Lang. 121, 110–123 (2012).
Schneider, S. et al. Beyond the N400: Complementary access to early neural correlates of novel metaphor comprehension using combined electrophysiological and haemodynamic measurements. Cortex 53, 45–59 (2014).
Nasi, T. et al. Correlation of visual-evoked hemodynamic responses and potentials in human brain. Exp. Brain Res. 202, 561–570 (2010).
Zhao C, Guo J, Li D, Tao Y, Ding Y, Liu H, Song Y. 2019. Anticipatory alpha oscillation predicts attentional selection and hemodynamic response. Human Brain Mapping. 40:3606–3619.
Huang J, Wang F, Ding Y, Niu H, Tian F, Liu H, Song Y. 2015. Predicting N2pc from anticipatory HbO activity during sustained visuospatial attention: a concurrent fNIRS-ERP study. NeuroImage. 113:225–234.