Simultaneous fNIRS and thermal infrared imaging during cognitive task reveal autonomic correlates of prefrontal cortex activity

Functional Near Infrared-Spectroscopy (fNIRS) represents a powerful tool to non-invasively study task-evoked brain activity. fNIRS assessment of cortical activity may suffer for contamination by physiological noises of different origin (e.g. heart beat, respiration, blood pressure, skin blood flow), both task-evoked and spontaneous. Spontaneous changes occur at different time scales and, even if they are not directly elicited by tasks, their amplitude may result task-modulated. In this study, concentration changes of hemoglobin were recorded over the prefrontal cortex while simultaneously recording the facial temperature variations of the participants through functional infrared thermal (fIR) imaging. fIR imaging provides touch-less estimation of the thermal expression of peripheral autonomic. Wavelet analysis revealed task-modulation of the very low frequency (VLF) components of both fNIRS and fIR signals and strong coherence between them. Our results indicate that subjective cognitive and autonomic activities are intimately linked and that the VLF component of the fNIRS signal is affected by the autonomic activity elicited by the cognitive task. Moreover, we showed that task-modulated changes in vascular tone occur both at a superficial and at larger depth in the brain. Combined use of fNIRS and fIR imaging can effectively quantify the impact of VLF autonomic activity on the fNIRS signals

The Temporal Confounding Effects of Extra-cerebral Contamination Factors on the Hemodynamic Signal Measured by Functional Near-Infrared Spectroscopy

Introduction: Functional near-infrared spectroscopy (fNIRS) has been broadly applied for optical brain imaging. This method is hemodynamic-based functional brain imaging relying on the measurement of the neurovascular coupling to detect changes in cerebral neuronal activities. The extra-cerebral hemodynamic changes are important contaminating factors in fNIRS measurements. This error signal can be misinterpreted as cerebral activities during fNIRS studies. Recently, it was assumed that temporal changes in deoxygenated hemoglobin concentration [HHb] was hardly affected by superficial blood flow, and it was proposed that the activation maps could be determined from [HHb] at large source-detector separation.Methods: In the current study, we measured the temporal changes in [HHb] using a continues-wave fNIRS device at large source-detector separation, while superficial blood flow was stimulated by infrared lasers. A mesh-based Monte Carlo code was applied to estimate fNIRS sensitivity to superficial hemodynamic changes in a realistic 3D MRI-based brain phantom.Results: First, we simulated photon migration in a four-layered human-head slab model to calculate PPLs and fNIRS sensitivity. Then, the localization of the infrared laser inside a realistic brain model was studied using the Monte Carlo method. Finally, the changes in [HHb] over the prefrontal cortex of six adult males were measured by fNIRS at a source-detector separation of 3 cm. The results demonstrated that the relation between fNIRS sensitivity and an increase in S-D separation was nonlinear and a correlation between shallow and deep signals was observed.Conclusion: The presented results demonstrated that the temporal changes in the superficial blood flow could strongly affect HHb measurement at large source-detector separation. Hence, the cerebral activity map extracted from the [HHb] signal was mainly contaminated by superficial blood flow

Computational models for functional near-infrared spectroscopy and imaging

Functional near-infrared spectroscopy (fNIRS) is a neuro-monitoring tool that is non-invasive, non-ionising, cost efficient, and portable. Its application for the traumatic brain injury patients is a well suggested approach due to its role in being able to continuously monitor key biomarkers such as the tissue oxygenation and blood haemoglobin level to understand the flow of blood supply to the tissue in the brain to assess injury in patients. In light of the great potential that fNIRS has to offer in neuro-monitoring in critical care, it is hindered by the inconsistency seldom seen in multiple research works that can be attributed to the assumptions made on tissue scattering properties to decouple their dependency along with absorption properties that can provide information about the key biomarkers useful in neuro-monitoring. These inconsistencies can also be attributed to the application of an inaccurate model to represent photon migration in underlying the biological tissue, or it can also be attributed to the unavoidable contamination of the measured fNIRS data by the superficial (skin and scalp) tissue, which is intended to probe the brain tissue, due to the typical placing of measurement probes on the head. The possibility to overcome these challenges in fNIRS methodology is examined in this thesis, and the proposed methods to overcome these are derived theoretically and validated on numerical simulation and experimental data to demonstrate better performance as compared to existing methods. A spectrally constrained approach is designed to efficiently circumvent the coupling of absorption and scattering properties to directly yield more accurate estimates of oxygenation levels for the cerebral tissue showing an average improvement of 6.6% as compared to a conventional and widely used approach of spatially resolved spectroscopy, in estimating the tissue oxygenation level. The uncertainty factor in the knowledge of scattering coefficient of the tissue, which is a key limitation in the conventional approach, is shown to be removed in the proposed spectrally constrained approach, therefore maintaining the methodology of subject and tissue-type independence. With the demonstration of better performance on spectral constrained approach, the role of more spectral information i.e., broadband intensity data, to allow recovery of more information is also explored and is demonstrated that when the data is measured on a complex tissue such as the human head, an often used simple semi-infinite model based layered recovery can lead to uncertain results, whereas, by using an appropriate model accounting for the tissue-boundary structure and geometry, the tissue oxygenation levels are recovered with an error of 4.2%, and brain depth with an error of 11.8%. The algorithm is finally used together with human subject data, to demonstrate the robustness in application and repeatability in the recovered parameters that adhere well to expected published parameters. Finally, the signal regression of fNIRS data to reduce superficial signal contamination which is well defined for a continuous wave (CW) fNIRS system is expanded to another data-types, namely phase data as used in frequency-domain (FD) fNIRS systems, by proposing a new approach for FD fNIRS that utilizes a short-separation intensity signal directly to regress both intensity and phase measurements. This is shown to provide a better regression of superficial signal contamination from both intensity and phase data-types. Intensity-based phase regression is shown to achieve a better suppression of superficial signal contamination by 68% whereas for phase-based phase regression the suppression is only by 13%. Phase-based phase regression is also shown to generate false-positives in the image reconstruction of haemodynamic activations from the cortex, which is not desirable and therefore this work provides a better methodology for minimizing the superficial signal contamination for FD fNIRS. All the parameter recovery models and signal processing methods presented in this work, in addition to their better performance that is shown, carry an additional and most prominent advantage of being able to be applied to all existing NIRS systems without any additional instrumentation or measurement for the purpose of providing a more accurate and robust neuro-monitoring tool

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

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

Biophysical modeling of hemodynamic-based neuroimaging techniques

Thesis (Ph. D. in Medical Engineering and Medical Physics)--Harvard-MIT Program in Health Sciences and Technology, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (pages 163-182).Two different hemodynamic-based neuroimaging techniques were studied in this work. Near-Infrared Spectroscopy (NIRS) is a promising technique to measure cerebral hemodynamics in a clinical setting due to its potential for continuous monitoring. However, the presence of strong systemic interference in the signal significantly limits our ability to recover the hemodynamic response without averaging tens of trials. Developing a new methodology to clean the NIRS signal from systemic interference and isolate the cortical signal would therefore significantly increase our ability to recover the hemodynamic response opening the door for clinical NIRS studies such as epilepsy. Toward this goal, a new method based on multi-distance measurements and state-space modeling was developed and further optimized to remove systemic physiological oscillations contaminating the NIRS signal. Furthermore, the cortical and pial contributions to the NIRS signal were quantified using a new multimodal regression analysis. Functional Magnetic Resonance Imaging (fMRI) based on the Blood Oxygenation Level Dependent (BOLD) response has become the method of choice for exploring brain function, and yet the physiological basis of this technique is still poorly understood. Despite the effort, a detailed and validated model relating the signal measured to the physiological changes occurring in the cortical tissue is still lacking. Modeling the BOLD signal is challenging because of the difficulty to take into account the complex morphology of the cortical microvasculature, the distribution of oxygen in those microvessels and its dynamics during neuronal activation. Here, we overcome this difficulty by performing Monte Carlo simulations over real microvascular networks and oxygen distributions measured in vivo on rodents, at rest and during forepaw stimulation, using two-photon microscopy. Our model reveals for the first time the specific contribution of individual vascular compartment to the BOLD signal, for different field strengths and different cortical orientations. Our model makes a new prediction: the amplitude of the BOLD signal produced by a given physiological change during neuronal activation depends on the spatial orientation of the cortical region in the MRI scanner. This occurs because veins are preferentially oriented either perpendicular or parallel to the cortical surface in the gray matter.by Louis Gagnon.Ph.D.in Medical Engineering and Medical Physic

Optical Cerebral Blood Flow Monitoring of Mice to Men

This thesis describes cerebral hemodynamic monitoring with the optical techniques of diffuse optical spectroscopy (DOS) and diffuse correlation spectroscopy (DCS). DOS and DCS both employ near-infrared light to investigate tissue physiology millimeters to centimeters below the tissue surface. DOS is a static technique that analyzes multispectral tissue-scattered light intensity signals with a photon diffusion approach (Chapter 2) or a Modified Beer-Lambert law approach (Chapter 3) to derive tissue oxy- and deoxy-hemoglobin concentrations, which are in turn used to compute tissue oxygen saturation and blood volume (Section 2.13). DCS is a qualitatively different dynamic technique that analyzes rapid temporal fluctuations in tissue-scattered light with a correlation diffusion approach to derive tissue blood flow (Chapter 4). Further, in combination these measurements of blood flow and blood oxygenation provide access to tissue oxygen metabolism (Section 7.6). The new contributions of my thesis to the diffuse optics field are a novel analysis technique for the DCS signal (Chapter 5), and a novel approach for separating cerebral hemodynamic signals from extra-cerebral artifacts (Chapter 6). The DCS analysis technique extends the Modified Beer-Lambert approach for DOS to the DCS measurement. This new technique has some useful advantages compared to the correlation diffusion approach. It facilitates real-time flow monitoring in complex tissue geometries, provides a novel route for increasing DCS measurement speed, and can be used to probe tissues wherein light transport is non-diffusive (Chapter 5). It also can be used to filter signals from superficial tissues. For separation of cerebral hemodynamic signals from extra-cerebral artifacts, the Modified Beer-Lambert approach is employed in a pressure modulation scheme, which determines subject-specific contributions of extra-cerebral and cerebral tissues to the DCS/DOS signals by utilizing probe pressure modulation to induce variations in extra-cerebral hemodynamics while cerebral hemodynamics remain constant (Chapter 6). In another novel contribution, I used optical techniques to characterize neurovascular coupling at several levels of cerebral ischemia in a rat model (Chapter 7). Neurovascular coupling refers to the relationship between increased blood flow and oxygen metabolism and increased neuronal activity in the brain. In the rat, localized neuronal activity was increased from functional forepaw stimulation. Under normal flow levels, I (and others) observed that the increase in cerebral blood flow (surrogate for oxygen delivery) from forepaw stimulation exceeded the increase in cerebral oxygen metabolism by about a factor of 2. My measurements indicate that this mismatch between oxygen delivery and consumption are more balanced during ischemia (Chapter 7). In Chapters 2 and 3, I review the underlying theory for the photon diffusion model and the Modified Beer-Lambert law for DOS analysis. I also review the correlation diffusion approach for analyzing DCS signals in Chapter 4. My hope is that readers new to the field will find these background chapters helpful

Pressure modulation algorithm to separate cerebral hemodynamic signals from extracerebral artifacts

We introduce and validate a pressure measurement paradigm that reduces extracerebral contamination from superficial tissues in optical monitoring of cerebral blood flow with diffuse correlation spectroscopy (DCS). The scheme determines subject-specific contributions of extracerebral and cerebral tissues to the DCS signal by utilizing probe pressure modulation to induce variations in extracerebral blood flow. For analysis, the head is modeled as a two-layer medium and is probed with long and short source-detector separations. Then a combination of pressure modulation and a modified Beer-Lambert law for flow enables experimenters to linearly relate differential DCS signals to cerebral and extracerebral blood flow variation without a priori anatomical information. We demonstrate the algorithm’s ability to isolate cerebral blood flow during a finger-tapping task and during graded scalp ischemia in healthy adults. Finally, we adapt the pressure modulation algorithm to ameliorate extracerebral contamination in monitoring of cerebral blood oxygenation and blood volume by near-infrared spectroscopy.Peer ReviewedPostprint (published version

Time domain, near-infrared diffuse optical methods for path length resolved, non-invasive measurement of deep-tissue blood flow

The non-invasive and, often, continuous measurement of the hemodynamics of the body, and for the main purposes of this thesis, the brain, is desired because both the instantaneous values and their changes over time constantly adapt to the conditions affecting the body and its environment. They are altered in pathological situations and in response to increased function. It is desirable for these measurements to be continuous, reliable, minimally invasive, and relatively inexpensive. In recent years, optical techniques that, by using diffusing and deep-reaching (up to few centimeters) light at skin-safe levels of intensity, combine the aforementioned characteristics, have increasingly become used in clinical and research settings. However, to date there is, on one side the need to expand the number and scope of translational studies, and, on the other, to address shortcomings like the contamination of signals from unwanted tissue volumes (partial volume effects). A further important goal is to increase the depth of penetration of light without affecting the non-invasive nature of diffuse optics. My PhD was aimed at several aspects of this problem; (i) the development of new, more advanced methods, i.e. the time/pathlength resolved, to improve the differentiation between superficial and deeper tissues layers, (ii) the exploration of new application areas, i.e. to characterize the microvascular status of bones, to study the functional response of the baby brain, and (iii) to improve the quality control of the systems , i.e. by introducing a long shelf-life dynamic phantom. In conceptual order, first I introduce long shelf-life reference standards for diffuse correlation spectroscopy. Secondly, I describe the use of an existing hybrid time domain and diffuse correlation spectroscopy system to monitor the changes that some pathological conditions, in this case osteoporosis and human immunodeficiency virus infection, may have on many aspects of the human bone tissue that are currently not easy to measure (i.e. invasively assessed) by conventional techniques. Thirdly, I describe the development of a novel time domain optical technique that intimately combines, introducing many previously unmet advancements, the two previously cited optical spectroscopy techniques. For the first time I was able to produce a time domain device and protocol that can monitor the blood flow in vivo in the head and muscles of healthy humans. Lastly, I describe a device and method that I have used to monitor changes in blood flow in healthy human infants of three to five months of age, for the first time in this age bracket, as a marker of activation following visual stimulation. Overall, this work pushes the limit of the technology that makes use of diffuse light to minimally invasively, continuously, and reliably monitor endogenous markers of pathological and physiological processes in the human body.La medición no invasiva y, a menudo, continua de la hemodinámica del cuerpo, y para los propósitos principales de esta tesis, del cerebro, es conveniente porque tanto los valores instantáneos como sus variaciones en el tiempo se adaptan constantemente a las condiciones que afectan el cuerpo humano y su entorno. Estas suelen alterarse en situaciones patológicas o como respuesta a una mayor función. Es deseable que estas mediciones sean continuas, confiables, mínimamente invasivas y relativamente asequibles. En los últimos años, las técnicas ópticas que, mediante el uso de luz difusa para medir los tejidos en profundidad (hasta unos pocos centímetros) mediante niveles de intensidad que son seguros para la piel, combinan las características arriba mencionadas, se han utilizado cada vez más tanto en entornos clínicos como de investigación. Sin embargo, al día de hoy hay, por un lado, la necesidad de ampliar el número y el ámbito de los estudios translacionales y, por el otro, de suplir a las deficiencias como por ejemplo la contaminación de volúmenes de tejido no deseados (efectos de volumen parcial). Otro objetivo importante es aumentar la profundidad de penetración de la luz sin afectar la naturaleza no invasiva de la óptica difusa. Mi doctorado está destinado a mejorar varios aspectos de este problema; (i) el desarrollo de nuevos métodos más avanzados, es decir, el método resuelto en el tiempo/trayectoria de los fotones, para mejorar la diferenciación entre los tejidos superficiales y profundos, (ii) la exploración de nuevas áreas de aplicación, es decir, para caracterizar el estado microvascular de los huesos, para estudiar la respuesta funcional del cerebro en los niños, y (iii) para mejorar el control de calidad de los sistemas, es decir, mediante la introducción de un phantom dinámico de larga vida útil. En orden conceptual, primero voy a introducir estándares de referencia de larga vida útil para la espectroscopia de correlación difusa (DCS). En segundo lugar, voy a describir el uso de un sistema híbrido espectroscopia tiempo-resuelta (TRS) con DCS ya existente para monitorizar los cambios que algunas condiciones patológicas, en este caso la osteoporosis y la infección por el virus de la inmunodeficiencia humana, pueden comportar para muchos aspectos del tejido óseo humano que actualmente no se pueden medir con facilidad (es decir, se van evaluado de forma invasiva) mediante técnicas convencionales. En tercer lugar, voy a describir el desarrollo de una novedosa técnica óptica en el dominio temporal que combina íntimamente, introduciendo muchos avances previamente no cumplidos, TRS y DCS. Por primera vez pude producir un dispositivo y un protocolo tiempo-resueltos para medir el flujo de la sangre en la cabeza y en los músculos de seres humanos sanos. Por último, en esta tesis voy a describir un dispositivo y un método que he usado para monitorear los cambios en el flujo sanguíneo como marcadores de activación del cerebro debida a estímulos visivos en bebés entre tres y cinco meses de edad. En general, este trabajo amplia los limites de la tecnología que hace uso de la luz difusa para monitorizar, de forma mínimamente invasiva, continua y confiable los marcadores endógenos de procesos patológicos y fisiológicos en el cuerpo humano.Postprint (published version

Frequency-domain analysis of fNIRS fluctuations induced by rhythmic mental arithmetic

Functional near-infrared spectroscopy (fNIRS) is an increasingly used technology for imaging neural correlates of cognitive processes. However, fNIRS signals are commonly impaired by task-evoked and spontaneous hemodynamic oscillations of non-cerebral origin, a major challenge in fNIRS research. In an attempt to isolate the task-evoked cortical response, we investigated the coupling between hemodynamic changes arising from superficial and deep layers during mental effort. For this aim, we applied a rhythmic mental arithmetic task to induce cyclic hemodynamic fluctuations suitable for effective frequency-resolved measurements. Twenty university students aged 18–25 years (eight males) underwent the task while hemodynamic changes were monitored in the forehead using a newly developed NIRS device, capable of multi-channel and multi-distance recordings. We found significant task-related fluctuations for oxy-and deoxy-hemoglobin, highly coherent across shallow and deep tissue layers, corroborating the strong influence of surface hemodynamics on deep fNIRS signals. Importantly, after removing such surface contamination by linear regression, we show that the frontopolar cortex response to a mental math task follows an unusual inverse oxygenation pattern. We confirm this finding by applying for the first time an alternative method to estimate the neural signal, based on transfer function analysis and phasor algebra. Altogether, our results demonstrate the feasibility of using a rhythmic mental task to impose an oscillatory state useful to separate true brain functional responses from those of non-cerebral origin. This separation appears to be essential for a better understanding of fNIRS data and to assess more precisely the dynamics of the neuro-visceral link