Felix Scholkmann

A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology

This year marks the 20th anniversary of functional near-infrared spectroscopy and imaging (fNIRS/fNIRI). As the vast majority of commercial instruments developed until now are based on continuous wave technology, the aim of this publication is to review the current state of instrumentation and methodology of continuous wave fNIRI. For this purpose we provide an overview of the commercially available instruments and address instrumental aspects such as light sources, detectors and sensor arrangements. Methodological aspects, algorithms to calculate the concentrations of oxy- and deoxyhemoglobin and approaches for data analysis are also reviewed. From the single-location measurements of the early years, instrumentation has progressed to imaging initially in two dimensions (topography) and then three (tomography). The methods of analysis have also changed tremendously, from the simple modified Beer-Lambert law to sophisticated image reconstruction and data analysis methods used today. Due to these advances, fNIRI has become a modality that is widely used in neuroscience research and several manufacturers provide commercial instrumentation. It seems likely that fNIRI will become a clinical tool in the foreseeable future, which will enable diagnosis in single subjects.

How to detect and reduce movement artifacts in near-infrared imaging using moving standard deviation and spline interpolation.

Near-infrared imaging (NIRI) is a neuroimaging technique which enables us to non-invasively measure hemodynamic changes in the human brain. Since the technique is very sensitive, the movement of a subject can cause movement artifacts (MAs), which affect the signal quality and results to a high degree. No general method is yet available to reduce these MAs effectively. The aim was to develop a new MA reduction method. A method based on moving standard deviation and spline interpolation was developed. It enables the semi-automatic detection and reduction of MAs in the data. It was validated using simulated and real NIRI signals. The results show that a significant reduction of MAs and an increase in signal quality are achieved. The effectiveness and usability of the method is demonstrated by the improved detection of evoked hemodynamic responses. The present method can not only be used in the postprocessing of NIRI signals but also for other kinds of data containing artifacts, for example ECG or EEG signals.

Between-brain connectivity during imitation measured by fNIRS.

The present study aimed to step into two-person neuroscience by investigating the hemodynamic correlates of between-brain connectivity involved in imitation and its dependency on pacing stimuli. To test this approach, we used wireless functional near-infrared spectroscopy (fNIRS) to record simultaneously during imitation performance of a paced finger-tapping task (PFT) in two subjects over premotor cortices (PMC). During the imitation (IM) condition, a model and an imitator were recorded while tapping in synchrony with auditory stimuli separated by a constant interval (stimulus-paced mode, St-P), followed by tapping without the pacing stimulus (self-paced mode, Se-P). During the control (CO) condition, each subject (single 1 and 2) performed the PFT task with the same pacing mode pattern, but alone without reference to each other. Using wavelet transform coherence (WTC) analysis evaluating functional connectivity between brains, we found (1) that IM revealed a larger coherence increase between the model and the imitator as compared to the CO condition. (2) Within the IM condition, a larger coherence increase was found during Se-P as compared to St-P mode. Using Granger-causality (G-causality) analysis evaluating effective connectivity between brains, we found (3) that IM revealed larger G-causality as compared to the CO condition and (4) that within the IM condition, the signal of the model G-caused that of the imitator to a greater extent as compared to vice versa. Our findings designate fNIRS as suitable tool for monitoring between-brain connectivity during dynamic interactions between two subjects and that those measurements might thereby provide insight into activation patterns not detectable using typical single-person experiments. Overall, the results of the present study demonstrate the potential of simultaneously assessing brain hemodynamics in interacting subjects in several research areas where social interactions are involved.

False positives and false negatives in functional near-infrared spectroscopy: issues, challenges, and the way forward

Abstract. We highlight a significant problem that needs to be considered and addressed when performing functional near-infrared spectroscopy (fNIRS) studies, namely the possibility of inadvertently measuring fNIRS hemodynamic responses that are not due to neurovascular coupling. These can be misinterpreted as brain activity, i.e., “false positives” (errors caused by wrongly assigning a detected hemodynamic response to functional brain activity), or mask brain activity, i.e., “false negatives” (errors caused by wrongly assigning a not observed hemodynamic response in the presence of functional brain activity). Here, we summarize the possible physiological origins of these issues and suggest ways to avoid and remove them.

End-tidal CO2: an important parameter for a correct interpretation in functional brain studies using speech tasks.

The aim was to investigate the effect of different speech tasks, i.e. recitation of prose (PR), alliteration (AR) and hexameter (HR) verses and a control task (mental arithmetic (MA) with voicing of the result on end-tidal CO2 (PETCO2), cerebral hemodynamics and oxygenation. CO2 levels in the blood are known to strongly affect cerebral blood flow. Speech changes breathing pattern and may affect CO2 levels. Measurements were performed on 24 healthy adult volunteers during the performance of the 4 tasks. Tissue oxygen saturation (StO2) and absolute concentrations of oxyhemoglobin ([O2Hb]), deoxyhemoglobin ([HHb]) and total hemoglobin ([tHb]) were measured by functional near-infrared spectroscopy (fNIRS) and PETCO2 by a gas analyzer. Statistical analysis was applied to the difference between baseline before the task, 2 recitation and 5 baseline periods after the task. The 2 brain hemispheres and 4 tasks were tested separately. A significant decrease in PETCO2 was found during all 4 tasks with the smallest decrease during the MA task. During the recitation tasks (PR, AR and HR) a statistically significant (p<0.05) decrease occurred for StO2 during PR and AR in the right prefrontal cortex (PFC) and during AR and HR in the left PFC. [O2Hb] decreased significantly during PR, AR and HR in both hemispheres. [HHb] increased significantly during the AR task in the right PFC. [tHb] decreased significantly during HR in the right PFC and during PR, AR and HR in the left PFC. During the MA task, StO2 increased and [HHb] decreased significantly during the MA task. We conclude that changes in breathing (hyperventilation) during the tasks led to lower CO2 pressure in the blood (hypocapnia), predominantly responsible for the measured changes in cerebral hemodynamics and oxygenation. In conclusion, our findings demonstrate that PETCO2 should be monitored during functional brain studies investigating speech using neuroimaging modalities, such as fNIRS, fMRI to ensure a correct interpretation of changes in hemodynamics and oxygenation.

General equation for the differential pathlength factor of the frontal human head depending on wavelength and age

Abstract. Continuous-wave near-infrared spectroscopy and near-infrared imaging enable the measurement of relative concentration changes in oxy- and deoxyhemoglobin and thus hemodynamics and oxygenation. The accuracy of determined changes depends mainly on the modeling of the light transport through the probed tissue. Due to the highly scattering nature of tissue, the light path is longer than the source–detector separation (d). This is incorporated in modeling by multiplying d by a differential pathlength factor (DPF) which depends on several factors such as wavelength, age of the subject, and type of tissue. In the present work, we derive a general DPF equation for the frontal human head, incorporating dependency on wavelength and age, based on published data. We validated the equation using different data sets of experimentally determined DPFs from six independent studies.

Human Intracranial High Frequency Oscillations (HFOs) Detected by Automatic Time-Frequency Analysis

Objectives High frequency oscillations (HFOs) have been proposed as a new biomarker for epileptogenic tissue. The exact characteristics of clinically relevant HFOs and their detection are still to be defined. Methods We propose a new method for HFO detection, which we have applied to six patient iEEGs. In a first stage, events of interest (EoIs) in the iEEG were defined by thresholds of energy and duration. To recognize HFOs among the EoIs, in a second stage the iEEG was Stockwell-transformed into the time-frequency domain, and the instantaneous power spectrum was parameterized. The parameters were optimized for HFO detection in patient 1 and tested in patients 2–5. Channels were ranked by HFO rate and those with rate above half maximum constituted the HFO area. The seizure onset zone (SOZ) served as gold standard. Results The detector distinguished HFOs from artifacts and other EEG activity such as interictal epileptiform spikes. Computation took few minutes. We found HFOs with relevant power at frequencies also below the 80–500 Hz band, which is conventionally associated with HFOs. The HFO area overlapped with the SOZ with good specificity > 90% for five patients and one patient was re-operated. The performance of the detector was compared to two well-known detectors. Conclusions Compared to methods detecting energy changes in filtered signals, our second stage - analysis in the time-frequency domain - discards spurious detections caused by artifacts or sharp epileptic activity and improves the detection of HFOs. The fast computation and reasonable accuracy hold promise for the diagnostic value of the detector.

A new methodical approach in neuroscience: assessing inter-personal brain coupling using functional near-infrared imaging (fNIRI) hyperscanning.

Since the first demonstration of how to simultaneously measure brain activity using functional magnetic resonance imaging (fMRI) on two subjects about 10 years ago, a new paradigm in neuroscience is emerging: measuring brain activity from two or more people simultaneously, termed “hyperscanning”. The hyperscanning approach has the potential to reveal inter-personal brain mechanisms underlying interaction-mediated brain-to-brain coupling. These mechanisms are engaged during real social interactions, and cannot be captured using single-subject recordings. In particular, functional near-infrared imaging (fNIRI) hyperscanning is a promising new method, offering a cost-effective, easy to apply and reliable technology to measure inter-personal interactions in a natural context. In this short review we report on fNIRI hyperscanning studies published so far and summarize opportunities and challenges for future studies.

Trial-to-trial variability differentiates motor imagery during observation between low versus high responders: a functional near-infrared spectroscopy study.

Trial-to-trial variability is a well-known issue in brain signals measured using functional near-infrared spectroscopy (fNIRS). We aimed to investigate whether trial-to-trial variability does provide information about individual performance. Seventeen subjects observed a virtual reality grasping task in first-person view while either imagining (motor imagery during observation, MIO) or imitating (motor execution, ME) the movements. Each condition was performed with the display in one of two positions, a conventional vertical position and a mirrored horizontal position which placed the virtual arm in the correct position relative to the viewpoint. Averaged oxy-hemoglobin concentration Δ[O(2)Hb] showed that the responses could be differentiated into two distinct groups: low responders (LR) and high responders (HR). Within groups, two main sources of trial-to-trial variability were identified: (a) the Δ[O(2)Hb] amplitude, with largest amplitudes in ME conditions (group HR) and smallest amplitudes in MIO conditions (group LR), and (b) the sign of Δ[O(2)Hb], with positive responses occurring most frequently during ME (group HR) and negative responses most frequently during MIO (group LR). Furthermore, the trial-to-trial dynamics differed between groups and could be described in group LR as inverted polynomial U-shaped curve in the mirror conditions (ME-mirror, MIO-mirror). Last, trial-to-trial variability was significantly dependent on task modality, i.e. ME (group HR) versus MIO (group LR), and/or the mirrored display positions (group LR). Our results show a relationship of trial-to-trial variability to individual MI performance, which may be of significance for neurorehabilitation applications. Although the sources of trial-to-trial variability remain unknown, we suggest that they may contribute to future neurofeedback applications.

Measuring tissue hemodynamics and oxygenation by continuous-wave functional near-infrared spectroscopy—how robust are the different calculation methods against movement artifacts?

Continuous-wave near-infrared spectroscopy and imaging enable tissue hemodynamics and oxygenation to be determined non-invasively. Movements of the investigated subject can cause movement artifacts (MAs) in the recorded signals. The strength and type of MAs induced depend on the measurement principle. The aim of the present study was to investigate the quantitative relationship between different single-distance (SD) and multi-distance (MD) measurement methods and their susceptibility to MAs. We found that each method induces MAs to a different degree, and that MD methods are more robust against MAs than SD methods.