Study of neurovascular coupling in humans via simultaneous magnetoencephalography and diffuse optical imaging acquisition

Lights on music cognition: A systematic and critical review of fNIRS applications and future perspectives

Research investigating the neural processes related to music perception and production constitutes a well-established field within the cognitive neurosciences. While most neuroimaging tools have limitations in studying the complexity of musical experiences, functional Near-Infrared Spectroscopy (fNIRS) represents a promising, relatively new tool for studying music processes in both laboratory and ecological settings, which is also suitable for both typical and pathological populations across development. Here we systematically review fNIRS studies on music cognition, highlighting prospects and potentialities. We also include an overview of fNIRS basic theory, together with a brief comparison to characteristics of other neuroimaging tools. Fifty-nine studies meeting inclusion criteria (i.e., using fNIRS with music as the primary stimulus) are presented across five thematic sections. Critical discussion of methodology leads us to propose guidelines of good practices aiming for robust signal analyses and reproducibility. A continuously updated world map is proposed, including basic information from studies meeting the inclusion criteria. It provides an organized, accessible, and updatable reference database, which could serve as a catalyst for future collaborations within the community. In conclusion, fNIRS shows potential for investigating cognitive processes in music, particularly in ecological contexts and with special populations, aligning with current research priorities in music cognition.

Multimodal neuroimaging with optically pumped magnetometers: A simultaneous MEG-EEG-fNIRS acquisition system

Multimodal neuroimaging plays an important role in neuroscience research. Integrated noninvasive neuroimaging modalities, such as magnetoencephalography (MEG), electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), allow neural activity and related physiological processes in the brain to be precisely and comprehensively depicted, providing an effective and advanced platform to study brain function. Noncryogenic optically pumped magnetometer (OPM) MEG has high signal power due to its on-scalp sensor layout and enables more flexible configurations than traditional commercial superconducting MEG. Here, we integrate OPM-MEG with EEG and fNIRS to develop a multimodal neuroimaging system that can simultaneously measure brain electrophysiology and hemodynamics. We conducted a series of experiments to demonstrate the feasibility and robustness of our MEG-EEG-fNIRS acquisition system. The complementary neural and physiological signals simultaneously collected by our multimodal imaging system provide opportunities for a wide range of potential applications in neurovascular coupling, wearable neuroimaging, hyperscanning and brain-computer interfaces.

Exploring the extent of source imaging: Recent advances in noninvasive electromagnetic brain imaging

Electrophysiological source imaging (ESI) has been successfully employed in many brain imaging applications during the last 20 years. ESI estimates of underlying brain networks provide millisecond resolution of dynamic brain processes; yet, it remains to be a challenge to further improve the spatial resolution of ESI modality, in particular on its capability of imaging the extent of underlying brain sources. In this review, we discuss the recent developments in signal processing and machine learning that have made it possible to image the extent, i.e. size, of underlying brain sources noninvasively, using scalp electromagnetic measurements from electroencephalogram (EEG) and magnetoencephalogram (MEG) recordings.

Best practices for fNIRS publications

The application of functional near-infrared spectroscopy (fNIRS) in the neurosciences has been expanding over the last 40 years. Today, it is addressing a wide range of applications within different populations and utilizes a great variety of experimental paradigms. With the rapid growth and the diversification of research methods, some inconsistencies are appearing in the way in which methods are presented, which can make the interpretation and replication of studies unnecessarily challenging. The Society for Functional Near-Infrared Spectroscopy has thus been motivated to organize a representative (but not exhaustive) group of leaders in the field to build a consensus on the best practices for describing the methods utilized in fNIRS studies. Our paper has been designed to provide guidelines to help enhance the reliability, repeatability, and traceability of reported fNIRS studies and encourage best practices throughout the community. A checklist is provided to guide authors in the preparation of their manuscripts and to assist reviewers when evaluating fNIRS papers.

A Narrative Review on Clinical Applications of fNIRS

Functional near-infrared spectroscopy (fNIRS) is a relatively new imaging modality in the functional neuroimaging research arena. The fNIRS modality non-invasively investigates the change of blood oxygenation level in the human brain utilizing the transillumination technique. In the last two decades, the interest in this modality is gradually evolving for its real-time monitoring, relatively low-cost, radiation-less environment, portability, patient-friendliness, etc. Including brain-computer interface and functional neuroimaging research, this technique has some important application of clinical perspectives such as Alzheimer's disease, schizophrenia, dyslexia, Parkinson's disease, childhood disorders, post-neurosurgery dysfunction, attention, functional connectivity, and many more can be diagnosed as well as in some form of assistive modality in clinical approaches. Regarding the issue, this review article presents the current scopes of fNIRS in medical assistance, clinical decision making, and future perspectives. This article also covers a short history of fNIRS, fundamental theories, and significant outcomes reported by a number of scholarly articles. Since this review article is hopefully the first one that comprehensively explores the potential scopes of the fNIRS in a clinical perspective, we hope it will be helpful for the researchers, physicians, practitioners, current students of the functional neuroimaging field, and the related personnel for their further studies and applications.

Integration of Spatial Information Increases Reproducibility in Functional Near-Infrared Spectroscopy

As functional near-infrared spectroscopy (fNIRS) is developed as a neuroimaging technique and becomes an option to study a variety of populations and tasks, the reproducibility of the fNIRS signal is still subject of debate. By performing test-retest protocols over different functional tasks, several studies agree that the fNIRS signal is reproducible over group analysis, but the inter-subject and within-subject reproducibility is poor. The high variability at the first statistical level is often attributed to global systemic physiology. In the present work, we revisited the reproducibility of the fNIRS signal during a finger-tapping task across multiple sessions on the same and different days. We expanded on previous studies by hypothesizing that the lack of spatial information of the optodes contributes to the low reproducibility in fNIRS, and we incorporated a real-time neuronavigation protocol to provide accurate cortical localization of the optodes. Our proposed approach was validated in 10 healthy volunteers, and our results suggest that the addition of neuronavigation can increase the within-subject reproducibility of the fNIRS data, particularly in the region of interest. Unlike traditional approaches to positioning the optodes, in which low intra-subject reproducibility has been found, we were able to obtain consistent and robust activation of the contralateral primary motor cortex at the intra-subject level using a neuronavigation protocol. Overall, our findings support the hypothesis that at least part of the variability in fNIRS cannot be only attributed to global systemic physiology. The use of neuronavigation to guide probe positioning, as proposed in this work, has impacts to longitudinal protocols performed with fNIRS.

Cooperation Makes a Group be More Creative

This study investigated how cooperative and competitive interaction modes affect the group creative performance. The participants were recruited as dyads to solve 2 problems either demanding divergent thinking (alternative uses task, AUT) or not (object characteristic task, OCT). The dyads solved 1 of the 2 problems in the cooperative mode and the other in the competitive mode. Functional near-infrared spectroscopy (fNIRS)-based hyperscanning was used to record their neural activities in the prefrontal and right temporal-parietal junction (r-TPJ) regions. Results revealed the dyads showed higher AUT fluency, AUT originality, OCT fluency, and cooperation level in the cooperative mode than in the competitive mode. The fNIRS data revealed increased (task-baseline) interpersonal brain synchronization (IBS) in the right dorsolateral prefrontal cortex (r-DLPFC) and r-TPJ, only for dyads in the AUT/cooperation condition. In both r-DLPFC and r-TPJ, the IBS of dyads in the AUT/cooperation condition was stronger than in the AUT/competition and OCT/cooperation. Moreover, a stronger IBS was evoked between the regions in prefrontal and posterior temporal regions in the AUT/cooperation condition, as compared with the competition mode. These findings suggest that enhanced IBS may underlie the positive effects of cooperation as compared with the competition in terms of group creativity.

Within-group synchronization in the prefrontal cortex associates with intergroup conflict

Individuals immersed in groups sometimes lose their individuality, take risks they would normally avoid and approach outsiders with unprovoked hostility. In this study, we identified within-group neural synchronization in the right dorsolateral prefrontal cortex (rDLPFC) and the right temporoparietal junction (rTPJ) as a candidate mechanism underlying intergroup hostility. We organized 546 individuals into 91 three-versus-three-person intergroup competitions, induced in-group bonding or no-bonding control manipulation and measured neural activity and within-group synchronization using functional near-infrared spectroscopy. After in-group bonding (versus control), individuals gave more money to in-group members than to out-group members and contributed more money to outcompete their rivals. In-group bonding decreased rDLPFC activity and increased functional connectivity between the rDLPFC and the rTPJ. Especially during the out-group attack, in-group bonding also increased within-group synchronization in both the rDLPFC and the rTPJ, and within-group rDLPFC synchronization positively correlated with intergroup hostility. Within-group synchronized reduction in prefrontal activity might explain how in-group bonding leads to impulsive and collective hostility toward outsiders.

Comparison of group-level, source localized activity for simultaneous functional near-infrared spectroscopy-magnetoencephalography and simultaneous fNIRS-fMRI during parametric median nerve stimulation

Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique, which uses light to measure changes in cerebral blood oxygenation through sensors placed on the surface of the scalp. We recorded concurrent fNIRS with magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) in order to investigate the group-level correspondence of these measures with source-localized fNIRS estimates. Healthy participants took part in both a concurrent fNIRS-MEG and fNIRS-fMRI neuroimaging session during two somatosensory stimulation tasks, a blocked design median nerve localizer and parametric pulsed-pair median nerve stimulation using interpulse intervals from 100 to 500 ms. We found the spatial correlation for estimated activation patterns from the somatosensory task was [Formula: see text], 0.57, and [Formula: see text] and the amplitude correlation was [Formula: see text], 0.52, and [Formula: see text] for fMRI-MEG, fMRI-fNIRS oxy-hemoglobin, and fMRI-fNIRS deoxy-hemoglobin signals, respectively. Taken together, these results show good correspondence among the fMRI, fNIRS, and MEG with the great majority of the difference across modalities being driven by lower sensitivity for deeper brain sources in MEG and fNIRS. These results provide an important validation of source-localized fNIRS in the context of concurrent multimodal imaging for future studies of the relationship between physiological effects in the human brain.

Cooperation in lovers: An fNIRS-based hyperscanning study

This study investigated interactive exchange in lovers and the associated interpersonal brain synchronization (IBS) using functional near-infrared spectroscopy (fNIRS)-based hyperscanning. Three types of female-male dyads, lovers, friends, and strangers, performed a cooperation task during which brain activity was recorded in right frontoparietal regions. We measured better cooperative behavior in lover dyads compared with friend and stranger dyads. Lover dyads demonstrated increased IBS in right superior frontal cortex, which also covaried with their task performance. Granger causality analyses in lover dyads revealed stronger directional synchronization from females to males than from males to females, suggesting different roles for females and males during cooperation. Our study refines the theoretical explanation of romantic interaction between lovers. Hum Brain Mapp 38:831-841, 2017. © 2016 Wiley Periodicals, Inc.

Imaging brain activity during seizures in freely behaving rats using a miniature multi-modal imaging system

We report on a miniature label-free imaging system for monitoring brain blood flow and blood oxygenation changes in awake, freely behaving rats. The device, weighing 15 grams, enables imaging in a ∼ 2 × 2 mm field of view with 4.4 μm lateral resolution and 1 - 8 Hz temporal sampling rate. The imaging is performed through a chronically-implanted cranial window that remains optically clear between 2 to > 6 weeks after the craniotomy. This imaging method is well suited for longitudinal studies of chronic models of brain diseases and disorders. In this work, it is applied to monitoring neurovascular coupling during drug-induced absence-like seizures 6 weeks following the craniotomy.

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.

Transcranial laser stimulation improves human cerebral oxygenation

Background and Objective

Transcranial laser stimulation of the brain with near‐infrared light is a novel form of non‐invasive photobiomodulation or low‐level laser therapy (LLLT) that has shown therapeutic potential in a variety of neurological and psychological conditions. Understanding of its neurophysiological effects is essential for mechanistic study and treatment evaluation. This study investigated how transcranial laser stimulation influences cerebral hemodynamics and oxygenation in the human brain in vivo using functional near‐infrared spectroscopy (fNIRS).

Materials and Methods

Two separate experiments were conducted in which 1,064‐nm laser stimulation was administered at (1) the center and (2) the right side of the forehead, respectively. The laser emitted at a power of 3.4 W and in an area of 13.6 cm², corresponding to 0.25 W/cm² irradiance. Stimulation duration was 10 minutes. Nine healthy male and female human participants of any ethnic background, in an age range of 18–40 years old were included in each experiment.

Results

In both experiments, transcranial laser stimulation induced an increase of oxygenated hemoglobin concentration (Δ[HbO₂]) and a decrease of deoxygenated hemoglobin concentration (Δ[Hb]) in both cerebral hemispheres. Improvements in cerebral oxygenation were indicated by a significant increase of differential hemoglobin concentration (Δ[HbD] = Δ[HbO₂] − Δ[Hb]). These effects increased in a dose‐dependent manner over time during laser stimulation (10 minutes) and persisted after laser stimulation (6 minutes). The total hemoglobin concentration (Δ[HbT] = Δ[HbO2] + Δ[Hb]) remained nearly unchanged in most cases.

Conclusion

Near‐infrared laser stimulation applied to the forehead can transcranially improve cerebral oxygenation in healthy humans. Lasers Surg. Med. 48:343–349, 2016. © 2016 The Authors. Lasers in Surgery and Medicine Published by Wiley Periodicals, Inc.

Using an achiasmic human visual system to quantify the relationship between the fMRI BOLD signal and neural response

Achiasma in humans causes gross mis-wiring of the retinal-fugal projection, resulting in overlapped cortical representations of left and right visual hemifields. We show that in areas V1-V3 this overlap is due to two co-located but non-interacting populations of neurons, each with a receptive field serving only one hemifield. Importantly, the two populations share the same local vascular control, resulting in a unique organization useful for quantifying the relationship between neural and fMRI BOLD responses without direct measurement of neural activity. Specifically, we can non-invasively double local neural responses by stimulating both neuronal populations with identical stimuli presented symmetrically across the vertical meridian to both visual hemifields, versus one population by stimulating in one hemifield. Measurements from a series of such doubling experiments show that the amplitude of BOLD response is proportional to approximately 0.5 power of the underlying neural response. Reanalyzing published data shows that this inferred relationship is general.

Contributions and complexities from the use of in vivo animal models to improve understanding of human neuroimaging signals

Many of the major advances in our understanding of how functional brain imaging signals relate to neuronal activity over the previous two decades have arisen from physiological research studies involving experimental animal models. This approach has been successful partly because it provides opportunities to measure both the hemodynamic changes that underpin many human functional brain imaging techniques and the neuronal activity about which we wish to make inferences. Although research into the coupling of neuronal and hemodynamic responses using animal models has provided a general validation of the correspondence of neuroimaging signals to specific types of neuronal activity, it is also highlighting the key complexities and uncertainties in estimating neural signals from hemodynamic markers. This review will detail how research in animal models is contributing to our rapidly evolving understanding of what human neuroimaging techniques tell us about neuronal activity. It will highlight emerging issues in the interpretation of neuroimaging data that arise from in vivo research studies, for example spatial and temporal constraints to neuroimaging signal interpretation, or the effects of disease and modulatory neurotransmitters upon neurovascular coupling. We will also give critical consideration to the limitations and possible complexities of translating data acquired in the typical animals models used in this area to the arena of human fMRI. These include the commonplace use of anesthesia in animal research studies and the fact that many neuropsychological questions that are being actively explored in humans have limited homologs within current animal models for neuroimaging research. Finally we will highlighting approaches, both in experimental animals models (e.g. imaging in conscious, behaving animals) and human studies (e.g. combined fMRI-EEG), that mitigate against these challenges.

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.

Neurovascular coupling in normal aging: a combined optical, ERP and fMRI study

Brain aging is characterized by changes in both hemodynamic and neuronal responses, which may be influenced by the cardiorespiratory fitness of the individual. To investigate the relationship between neuronal and hemodynamic changes, we studied the brain activity elicited by visual stimulation (checkerboard reversals at different frequencies) in younger adults and in older adults varying in physical fitness. Four functional brain measures were used to compare neuronal and hemodynamic responses obtained from BA17: two reflecting neuronal activity (the event-related optical signal, EROS, and the C1 response of the ERP), and two reflecting functional hemodynamic changes (functional magnetic resonance imaging, fMRI, and near-infrared spectroscopy, NIRS). The results indicated that both younger and older adults exhibited a quadratic relationship between neuronal and hemodynamic effects, with reduced increases of the hemodynamic response at high levels of neuronal activity. Although older adults showed reduced activation, similar neurovascular coupling functions were observed in the two age groups when fMRI and deoxy-hemoglobin measures were used. However, the coupling between oxy- and deoxy-hemoglobin changes decreased with age and increased with increasing fitness. These data indicate that departures from linearity in neurovascular coupling may be present when using hemodynamic measures to study neuronal function.

Effects of spatial pattern scale of brain activity on the sensitivity of DOT, fMRI, EEG and MEG

The objective of this work is to quantify how patterns of cortical activity at different spatial scales are measured by noninvasive functional neuroimaging sensors. We simulated cortical activation patterns at nine different spatial scales in a realistic head model and propagated this activity to magnetoencephalography (MEG), electroencephalography (EEG), diffuse optical tomography (DOT), and functional magnetic resonance imaging (fMRI) sensors in arrangements that are typically used in functional neuroimaging studies. We estimated contrast transfer functions (CTF), correlation distances in sensor space, and the minimum resolvable spatial scale of cortical activity for each modality. We found that CTF decreases as the spatial extent of cortical activity decreases, and that correlations between nearby sensors depend on the spatial extent of cortical activity. For cortical activity on the intermediate spatial scale of 6.7 cm(2), the correlation distances (r>0.5) were 1.0 cm for fMRI, 2.0 cm for DOT, 12.8 for EEG, 9.5 cm for MEG magnetometers and 9.7 cm for MEG gradiometers. The resolvable spatial pattern scale was found to be 1.43 cm(2) for MEG magnetometers, 0.88 cm(2) for MEG gradiometers, 376 cm(2) for EEG, 0.75 cm(2) for DOT, and 0.072 cm(2) for fMRI. These findings show that sensitivity to cortical activity varies substantially as a function of spatial scale within and between the different imaging modalities. This information should be taken into account when interpreting neuroimaging data and when choosing the number of nodes for network analyses in sensor space.

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

A noninvasive head probe that combines near-infrared spectroscopy (NIRS) and electroencephalography (EEG) for simultaneous measurement of neural dynamics and hemodynamics in the brain is presented. It is composed of a compliant expandable mechanism that accommodates a wide range of head size variation and an elastomeric web that maintains uniform sensor contact pressure on the scalp as the mechanism expands and contracts. The design is intended to help maximize optical and electrical coupling and to maintain stability during head movement. Positioning electrodes at the inion, nasion, central, and preauricular fiducial locations mechanically shapes the probe to place 64 NIRS optodes and 65 EEG electrodes following the 10-5 scalp coordinates. The placement accuracy, precision, and scalp pressure uniformity of the sensors are evaluated. A root-mean-squared (RMS) positional precision of 0.89 ± 0.23 mm, percent arc subdivision RMS accuracy of 0.19 ± 0.15%, and mean normal force on the scalp of 2.28 ± 0.88 N at 5 mm displacement were found. Geometric measurements indicate that the probe will accommodate the full range of adult head sizes. The placement accuracy, precision, and uniformity of sensor contact pressure of the proposed head probe are important determinants of data quality in noninvasive brain monitoring with simultaneous NIRS-EEG.

Calibrating the BOLD signal during a motor task using an extended fusion model incorporating DOT, BOLD and ASL data

Multimodal imaging improves the accuracy of the localization and the quantification of brain activation when measuring different manifestations of the hemodynamic response associated with cerebral activity. In this study, we incorporated cerebral blood flow (CBF) changes measured with arterial spin labeling (ASL), Diffuse Optical Tomography (DOT) and blood oxygen level-dependent (BOLD) recordings to reconstruct changes in oxy- (ΔHbO(2)) and deoxyhemoglobin (ΔHbR). Using the Grubb relation between relative changes in CBF and cerebral blood volume (CBV), we incorporated the ASL measurement as a prior to the total hemoglobin concentration change (ΔHbT). We applied this ASL fusion model to both synthetic data and experimental multimodal recordings during a 2-s finger-tapping task. Our results show that the new approach is very powerful in estimating ΔHbO(2) and ΔHbR with high spatial and quantitative accuracy. Moreover, our approach allows the computation of baseline total hemoglobin concentration (HbT(0)) as well as of the BOLD calibration factor M on a single subject basis. We obtained an average HbT(0) of 71 μM, an average M value of 0.18 and an average increase of 13% in cerebral metabolic rate of oxygen (CMRO(2)), all of which are in agreement with values previously reported in the literature. Our method yields an independent measurement of M, which provides an alternative measurement to validate the hypercapnic calibration of the BOLD signal.

Frontiers in optical imaging of cerebral blood flow and metabolism

In vivo optical imaging of cerebral blood flow (CBF) and metabolism did not exist 50 years ago. While point optical fluorescence and absorption measurements of cellular metabolism and hemoglobin concentrations had already been introduced by then, point blood flow measurements appeared only 40 years ago. The advent of digital cameras has significantly advanced two-dimensional optical imaging of neuronal, metabolic, vascular, and hemodynamic signals. More recently, advanced laser sources have enabled a variety of novel three-dimensional high-spatial-resolution imaging approaches. Combined, as we discuss here, these methods are permitting a multifaceted investigation of the local regulation of CBF and metabolism with unprecedented spatial and temporal resolution. Through multimodal combination of these optical techniques with genetic methods of encoding optical reporter and actuator proteins, the future is bright for solving the mysteries of neurometabolic and neurovascular coupling and translating them to clinical utility.

Anesthesia and the quantitative evaluation of neurovascular coupling

Anesthesia has broad actions that include changing neuronal excitability, vascular reactivity, and other baseline physiologies and eventually modifies the neurovascular coupling relationship. Here, we review the effects of anesthesia on the spatial propagation, temporal dynamics, and quantitative relationship between the neural and vascular responses to cortical stimulation. Previous studies have shown that the onset latency of evoked cerebral blood flow (CBF) changes is relatively consistent across anesthesia conditions compared with variations in the time-to-peak. This finding indicates that the mechanism of vasodilation onset is less dependent on anesthesia interference, while vasodilation dynamics are subject to this interference. The quantitative coupling relationship is largely influenced by the type and dosage of anesthesia, including the actions on neural processing, vasoactive signal transmission, and vascular reactivity. The effects of anesthesia on the spatial gap between the neural and vascular response regions are not fully understood and require further attention to elucidate the mechanism of vascular control of CBF supply to the underlying focal and surrounding neural activity. The in-depth understanding of the anesthesia actions on neurovascular elements allows for better decision-making regarding the anesthetics used in specific models for neurovascular experiments and may also help elucidate the signal source issues in hemodynamic-based neuroimaging techniques.

Quantitative assessment of diffuse optical tomography sensitivity to the cerebral cortex using a whole-head probe

We quantify the variability in diffuse optical tomography (DOT) sensitivity over the cortical surface in eight young adult subjects. We use the 10/5 electroencephalography system as a basis for our whole-head optical high-density probe design. The contrast-to-noise ratio (CNR) is calculated along with the percentage of the cortex that is above a CNR = 0 dB threshold. We also quantify the effect of including vasculature on the forward model and list our assumptions that allow us to estimate light penetration depth in the head. We show that using the 10/5 system for the optical probe design allows for the measurement of 37% of the cortical surface on average, with a mean CNR in the visible region of 5.5 dB. Certain anatomical regions, such as the lateral occipital cortex, had a very high percentage above the CNR threshold, while other regions such as the cingulate cortex were not measurable. Vasculature blocked optical sensitivity over 1% of the cortex. Cortical coverage was positively correlated with intracranial volume and relative cerebrospinal fluid volume, and negatively correlated with relative scalp volume and skull volume. These contributions allow experimenters to understand how anatomical variation in a subject population may impact DOT or functional near-infrared spectroscopy measurements.

A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application

This review is aimed at celebrating the upcoming 20th anniversary of the birth of human functional near-infrared spectroscopy (fNIRS). After the discovery in 1992 that the functional activation of the human cerebral cortex (due to oxygenation and hemodynamic changes) can be explored by NIRS, human functional brain mapping research has gained a new dimension. fNIRS or optical topography, or near-infrared imaging or diffuse optical imaging is used mainly to detect simultaneous changes in optical properties of the human cortex from multiple measurement sites and displays the results in the form of a map or image over a specific area. In order to place current fNIRS research in its proper context, this paper presents a brief historical overview of the events that have shaped the present status of fNIRS. In particular, technological progresses of fNIRS are highlighted (i.e., from single-site to multi-site functional cortical measurements (images)), introduction of the commercial multi-channel systems, recent commercial wireless instrumentation and more advanced prototypes.

Adaptive changes in the neuromagnetic response of the primary and association somatosensory areas following repetitive tactile hand stimulation in humans

Cortical adaptation in the primary somatosensory cortex (SI) has been probed using different stimulation modalities and recording techniques, in both human and animal studies. In contrast, considerably less knowledge has been gained about the adaptation profiles in other areas of the cortical somatosensory network. Using magnetoencephalography (MEG), we examined the patterns of short-term adaptation for evoked responses in SI and somatosensory association areas during tactile stimulation applied to the glabrous skin of the hand. Cutaneous stimuli were delivered as trains of serial pulses with a constant frequency of 2 Hz and 4 Hz in separate runs, and a constant inter-train interval of 5 s. The unilateral stimuli elicited transient responses to the serial pulses in the train, with several response components that were separated by independent component analysis. Subsequent source reconstruction techniques identified regional generators in the contralateral SI and somatosensory association areas in the posterior parietal cortex (PPC). Activity in the bilateral secondary somatosensory cortex (i.e., SII/PV) was also identified, although less consistently across subjects. The dynamics of the evoked activity in each area and the frequency-dependent adaptation effects were assessed from the changes in the relative amplitude of serial responses in each train. We show that the adaptation profiles in SI and PPC areas can be quantitatively characterized from neuromagnetic recordings using tactile stimulation, with the sensitivity to repetitive stimulation increasing from SI to PPC. A similar approach for SII/PV has proven less straightforward, potentially due to the tendency of these areas to respond selectively to certain stimuli.

A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping

Functional neuroimaging commands a dominant role in current neuroscience research. However its use in bedside clinical and certain neuro-scientific studies has been limited because the current tools lack the combination of being non-invasive, non-ionizing and portable while maintaining moderate resolution and localization accuracy. Optical neuroimaging satisfies many of these requirements, but, until recent advances in high-density diffuse optical tomography (HD-DOT), has been hampered by limited resolution. While early results of HD-DOT have been promising, a quantitative voxel-wise comparison and validation of HD-DOT against the gold standard of functional magnetic resonance imaging (fMRI) has been lacking. Herein, we provide such an analysis within the visual cortex using matched visual stimulation protocols in a single group of subjects (n=5) during separate HD-DOT and fMRI scanning sessions. To attain the needed voxel-to-voxel co-registration between HD-DOT and fMRI image spaces, we implemented subject-specific head modeling that incorporated MRI anatomy, detailed segmentation, and alignment of source and detector positions. Comparisons of the visual responses found an average localization error between HD-DOT and fMRI of 4.4+/-1mm, significantly less than the average distance between cortical gyri. This specificity demonstrates that HD-DOT has sufficient image quality to be useful as a surrogate for fMRI.

Towards a model-based integration of co-registered electroencephalography/functional magnetic resonance imaging data with realistic neural population meshes

Brain activity can be measured with several non-invasive neuroimaging modalities, but each modality has inherent limitations with respect to resolution, contrast and interpretability. It is hoped that multimodal integration will address these limitations by using the complementary features of already available data. However, purely statistical integration can prove problematic owing to the disparate signal sources. As an alternative, we propose here an advanced neural population model implemented on an anatomically sound cortical mesh with freely adjustable connectivity, which features proper signal expression through a realistic head model for the electroencephalogram (EEG), as well as a haemodynamic model for functional magnetic resonance imaging based on blood oxygen level dependent contrast (fMRI BOLD). It hence allows simultaneous and realistic predictions of EEG and fMRI BOLD from the same underlying model of neural activity. As proof of principle, we investigate here the influence on simulated brain activity of strengthening visual connectivity. In the future we plan to fit multimodal data with this neural population model. This promises novel, model-based insights into the brain's activity in sleep, rest and task conditions.

Neurovascular coupling is brain region-dependent

Despite recent advances in alternative brain imaging technologies, functional magnetic resonance imaging (fMRI) remains the workhorse for both medical diagnosis and primary research. Indeed, the number of research articles that utilise fMRI have continued to rise unabated since its conception in 1991, despite the limitation that recorded signals originate from the cerebral vasculature rather than neural tissue. Consequently, understanding the relationship between brain activity and the resultant changes in metabolism and blood flow (neurovascular coupling) remains a vital area of research. In the past, technical constraints have restricted investigations of neurovascular coupling to cortical sites and have led to the assumption that coupling in non-cortical structures is the same as in the cortex, despite the lack of any evidence. The current study investigated neurovascular coupling in the rat using whole-brain blood oxygenation level-dependent (BOLD) fMRI and multi-channel electrophysiological recordings and measured the response to a sensory stimulus as it proceeded through brainstem, thalamic and cortical processing sites - the so-called whisker-to-barrel pathway. We found marked regional differences in the amplitude of BOLD activation in the pathway and non-linear neurovascular coupling relationships in non-cortical sites. The findings have important implications for studies that use functional brain imaging to investigate sub-cortical function and caution against the use of simple, linear mapping of imaging signals onto neural activity.

The effect of different anesthetics on neurovascular coupling

To date, the majority of neurovascular coupling studies focused on the thalamic afferents' activity in layer IV and the corresponding large spiking activity as responsible for functional hyperemia. This paper highlights the role of the secondary and late cortico-cortical transmission in neurovascular coupling. Simultaneous scalp electroencephalography (EEG) and diffuse optical imaging (DOI) measurements were obtained during multiple conditions of event-related electrical forepaw stimulation in 33 male Sprague-Dawley rats divided into 6 groups depending on the maintaining anesthetic - alpha-chloralose, pentobarbital, ketamine-xylazine, fentanyl-droperidol, isoflurane, or propofol. The somatosensory evoked potentials (SEP) were decomposed into four components and the question of which best predicts the hemodynamic responses was investigated. Results of the linear regression analysis show that the hemodynamic response is best correlated with the secondary and late cortico-cortical transmissions and not with the initial thalamic input activity in layer IV. Baseline cerebral blood flow (CBF) interacts with neural activity and influences the evoked hemodynamic responses. Finally, neurovascular coupling appears to be the same across all anesthetics used.

Multimodal functional imaging using fMRI-informed regional EEG/MEG source estimation

We propose a novel method, fMRI-Informed Regional Estimation (FIRE), which utilizes information from fMRI in E/MEG source reconstruction. FIRE takes advantage of the spatial alignment between the neural and the vascular activities, while allowing for substantial differences in their dynamics. Furthermore, with a region-based approach, FIRE estimates the model parameters for each region independently. Hence, it can be efficiently applied on a dense grid of source locations. The optimization procedure at the core of FIRE is related to the re-weighted minimum-norm algorithms. The weights in the proposed approach are computed from both the current source estimates and fMRI data, leading to robust estimates in the presence of silent sources in either fMRI or E/MEG measurements. We employ a Monte Carlo evaluation procedure to compare the proposed method to several other joint E/MEG-fMRI algorithms. Our results show that FIRE provides the best trade-off in estimation accuracy between the spatial and the temporal accuracy. Analysis using human E/MEG-fMRI data reveals that FIRE significantly reduces the ambiguities in source localization present in the minimum-norm estimates, and that it accurately captures activation timing in adjacent functional regions.

Cross-correlation of motor activity signals from dc-magnetoencephalography, near-infrared spectroscopy, and electromyography

Neuronal and vascular responses due to finger movements were synchronously measured using dc-magnetoencephalography (dcMEG) and time-resolved near-infrared spectroscopy (trNIRS). The finger movements were monitored with electromyography (EMG). Cortical responses related to the finger movement sequence were extracted by independent component analysis from both the dcMEG and the trNIRS data. The temporal relations between EMG rate, dcMEG, and trNIRS responses were assessed pairwise using the cross-correlation function (CCF), which does not require epoch averaging. A positive lag on a scale of seconds was found for the maximum of the CCF between dcMEG and trNIRS. A zero lag is observed for the CCF between dcMEG and EMG. Additionally this CCF exhibits oscillations at the frequency of individual finger movements. These findings show that the dcMEG with a bandwidth up to 8 Hz records both slow and faster neuronal responses, whereas the vascular response is confirmed to change on a scale of seconds.

Linear and nonlinear relationships between visual stimuli, EEG and BOLD fMRI signals

In the present study, the cascaded interactions between stimuli and neural and hemodynamic responses were modeled using linear systems. These models provided the theoretical hypotheses that were tested against the electroencephalography (EEG) and blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) data recorded from human subjects during prolonged periods of repeated visual stimuli with a variable setting of the inter-stimulus interval (ISI) and visual contrast. Our results suggest that (1) neural response is nonlinear only when ISI<0.2 s, (2) BOLD response is nonlinear with an exclusively vascular origin when 0.25<ISI<4.2 s, (3) vascular response nonlinearity reflects a refractory effect, rather than a ceiling effect, and (4) there is a strong linear relationship between the BOLD effect size and the integrated power of event-related synaptic current activity, after modeling and taking into account the vascular refractory effect. These conclusions offer important insights into the origins of BOLD nonlinearity and the nature of neurovascular coupling, and suggest an effective means to quantitatively interpret the BOLD signal in terms of neural activity. The validated cross-modal relationship between fMRI and EEG may provide a theoretical basis for the integration of these two modalities.

Multimodal functional imaging using fMRI-informed regional EEG/MEG source estimation

We propose a novel method, fMRI-Informed Regional Estimation (FIRE), which utilizes information from fMRI in E/MEG source reconstruction. FIRE takes advantage of the spatial alignment between the neural and the vascular activities, while allowing for substantial differences in their dynamics. Furthermore, with the regional approach, FIRE can be efficiently applied to a dense grid of sources. Inspection of our optimization procedure reveals that FIRE is related to the re-weighted minimum-norm algorithms, the difference being that the weights in the proposed approach are computed from both the current estimates and fMRI data. Analysis of both simulated and human fMRI-MEG data shows that FIRE reduces the ambiguities in source localization present in the minimum-norm estimates. Comparisons with several joint fMRI-E/MEG algorithms demonstrate robustness of FIRE in the presence of sources silent to either fMRI or E/MEG measurements.