Bedside optical imaging of occipital resting-state functional connectivity in neonates

Overview of diffuse optical tomography and its clinical applications

Near-infrared diffuse optical tomography (DOT), one of the most sophisticated optical imaging techniques for observations through biological tissue, allows 3-D quantitative imaging of optical properties, which include functional and anatomical information. With DOT, it is expected to be possible to overcome the limitations of conventional near-infrared spectroscopy (NIRS) as well as offering the potential for diagnostic optical imaging. However, DOT has been under development for more than 30 years, and the difficulties in development are attributed to the fact that light is strongly scattered and that diffusive photons are used for the image reconstruction. The DOT algorithm is based on the techniques of inverse problems. The radiative transfer equation accurately describes photon propagation in biological tissue, while, because of its high computation load, the diffusion equation (DE) is often used as the forward model. However, the DE is invalid in low-scattering and/or highly absorbing regions and in the vicinity of light sources. The inverse problem is inherently ill-posed and highly undetermined. Here, we first summarize NIRS and then describe various approaches in the efforts to develop accurate and efficient DOT algorithms and present some examples of clinical applications. Finally, we discuss the future prospects of DOT.

Detection of resting state functional connectivity using partial correlation analysis: A study using multi-distance and whole-head probe near-infrared spectroscopy

Multichannel near-infrared spectroscopy (NIRS) is a functional neuroimaging modality that enables easy-to-use and noninvasive measurement of changes in blood oxygenation levels. We developed a clinically-applicable method for estimating resting state functional connectivity (RSFC) with NIRS using a partial correlation analysis to reduce the influence of extraneural components. Using a multi-distance probe arrangement NIRS, we measured resting state brain activity for 8min in 17 healthy participants. Independent component analysis was used to extract shallow and deep signals from the original NIRS data. Pearson's correlation calculated from original signals was significantly higher than that calculated from deep signals, while partial correlation calculated from original signals was comparable to that calculated from deep (cerebral-tissue) signals alone. To further test the validity of our method, we also measured 8min of resting state brain activity using a whole-head NIRS arrangement consisting of 17 cortical regions in 80 healthy participants. Significant RSFC between neighboring, interhemispheric homologous, and some distant ipsilateral brain region pairs was revealed. Additionally, females exhibited higher RSFC between interhemispheric occipital region-pairs, in addition to higher connectivity between some ipsilateral pairs in the left hemisphere, when compared to males. The combined results of the two component experiments indicate that partial correlation analysis is effective in reducing the influence of extracerebral signals, and that NIRS is able to detect well-described resting state networks and sex-related differences in RSFC.

Intraoperative optical mapping of epileptogenic cortices during non-ictal periods in pediatric patients

Complete removal of epileptogenic cortex while preserving eloquent areas is crucial in patients undergoing epilepsy surgery. In this manuscript, the feasibility was explored of developing a new methodology based on dynamic intrinsic optical signal imaging (DIOSI) to intraoperatively detect and differentiate epileptogenic from eloquent cortices in pediatric patients with focal epilepsy. From 11 pediatric patients undergoing epilepsy surgery, negatively-correlated hemodynamic low-frequency oscillations (LFOs, ~ 0.02-0.1 Hz) were observed from the exposed epileptogenic and eloquent cortical areas, as defined by electrocorticography (ECoG), using a DIOSI system. These LFOs were classified into multiple groups in accordance with their unique temporal profiles. Causal relationships within these groups were investigated using the Granger causality method, and 83% of the ECoG-defined epileptogenic cortical areas were found to have a directed influence on one or more cortical areas showing LFOs within the field of view of the imaging system. To understand the physiological origins of LFOs, blood vessel density was compared between epileptogenic and normal cortical areas and a statistically-significant difference (p < 0.05) was detected. The differences in blood-volume and blood-oxygenation dynamics between eloquent and epileptogenic cortices were also uncovered using a stochastic modeling approach. This, in turn, yielded a means by which to separate epileptogenic from eloquent cortex using hemodynamic LFOs. The proposed methodology detects epileptogenic cortices by exploiting the effective connectivity that exists within cortical regions displaying LFOs and the biophysical features contributed by the altered vessel networks within the epileptogenic cortex. It could be used in conjunction with existing technologies for epileptogenic/eloquent cortex localization and thereby facilitate clinical decision-making.

FC-NIRS: A Functional Connectivity Analysis Tool for Near-Infrared Spectroscopy Data

Functional near-infrared spectroscopy (fNIRS), a promising noninvasive imaging technique, has recently become an increasingly popular tool in resting-state brain functional connectivity (FC) studies. However, the corresponding software packages for FC analysis are still lacking. To facilitate fNIRS-based human functional connectome studies, we developed a MATLAB software package called “functional connectivity analysis tool for near-infrared spectroscopy data” (FC-NIRS). This package includes the main functions of fNIRS data preprocessing, quality control, FC calculation, and network analysis. Because this software has a friendly graphical user interface (GUI), FC-NIRS allows researchers to perform data analysis in an easy, flexible, and quick way. Furthermore, FC-NIRS can accomplish batch processing during data processing and analysis, thereby greatly reducing the time cost of addressing a large number of datasets. Extensive experimental results using real human brain imaging confirm the viability of the toolbox. This novel toolbox is expected to substantially facilitate fNIRS-data-based human functional connectome studies.

Multiregional functional near-infrared spectroscopy reveals globally symmetrical and frequency-specific patterns of superficial interference

Linear regression with short source-detector separation channels (S-channels) as references is an efficient way to overcome significant physiological interference from the superficial layer for functional near-infrared spectroscopy (fNIRS). However, the co-located configuration of S-channels and long source-detector separation channels (L-channels) is difficult to achieve in practice. In this study, we recorded superficial interference with S-channels in multiple scalp regions. We found that superficial interference has overall frequency-specific and globally symmetrical patterns. The performance of linear regression is also dependent on these patterns, indicating the possibility of simplifying the S-channel configurations for multiregional fNIRS imaging.

Dynamic functional connectivity revealed by resting-state functional near-infrared spectroscopy

The brain is a complex network with time-varying functional connectivity (FC) and network organization. However, it remains largely unknown whether resting-state fNIRS measurements can be used to characterize dynamic characteristics of intrinsic brain organization. In this study, for the first time, we used the whole-cortical fNIRS time series and a sliding-window correlation approach to demonstrate that fNIRS measurement can be ultimately used to quantify the dynamic characteristics of resting-state brain connectivity. Our results reveal that the fNIRS-derived FC is time-varying, and the variability strength (Q) is correlated negatively with the time-averaged, static FC. Furthermore, the Q values also show significant differences in connectivity between different spatial locations (e.g., intrahemispheric and homotopic connections). The findings are reproducible across both sliding-window lengths and different brain scanning sessions, suggesting that the dynamic characteristics in fNIRS-derived cerebral functional correlation results from true cerebral fluctuation.

Neurodevelopmental delay with critical congenital heart disease is mainly from prenatal injury not infant cardiac surgery: current evidence based on a meta-analysis of functional magnetic resonance imaging

OBJECTIVE

No consensus has been reached regarding whether brain injury related to congenital heart disease (CHD) is caused by infant cardiac surgery and/or prenatal injury resulting from the CHD. We performed this meta-analysis to identify the likely cause of neurodevelopmental delay in CHD patients.

METHODS

We carried out a literature search without language restriction in December 2013, retrieving records from PubMed, EMBASE, the Cochrane Library and the World Health Organization trials center, to identify studies applying functional magnetic resonance imaging (fMRI) evaluation of brain function before surgery and, in some cases, after surgery (both immediate term and short term postoperatively). The preoperative and postoperative fMRI results were extracted, and meta-analysis was performed using Revman 5.1.1 and STATA 11.0, according to the guidelines from the Cochrane review and MOOSE groups.

RESULTS

The electronic search yielded 937 citations. Full text was retrieved for 15 articles and eight articles (nine studies) were eligible for inclusion: six studies (n = 312 cases) with fMRI analysis before surgery and three (n = 36 cases) with complete perioperative fMRI analysis. The overall average diffusivity of CHD cases was significantly higher than that of controls, with a summarized standard (std) mean difference of 1.39 (95% CI, 0.70-2.08), and the fractional anisotropy was lower in CHD cases, with a summarized mean difference of -1.43 (95% CI, -1.95 to -0.91). N-acetylaspartate (NAA)/choline (Cho) for the whole brain was significantly lower in CHD cases compared with healthy ones, while lactate/Cho was significantly higher in CHD cases. Immediate term postoperatively, significant changes in NAA/creatine and NAA/Cho, relative to preoperative values, were found. However, the difference did not persist at the short-term follow-up.

CONCLUSION

This meta-analysis suggests that the delay in neurological development in newborns with CHD is due mainly to prenatal injury, and cardiac surgery might lead to mild brain injuries postoperatively, but fMRI shows recovery within a short period.

The potential of infant fMRI research and the study of early life stress as a promising exemplar

Functional magnetic resonance imaging (fMRI) research with infants and toddlers has increased rapidly over the past decade, and provided a unique window into early brain development. In the current report, we review the state of the literature, which has established the feasibility and utility of task-based fMRI and resting state functional connectivity MRI (rs-fcMRI) during early periods of brain maturation. These methodologies have been successfully applied beginning in the neonatal period to increase understanding of how the brain both responds to environmental stimuli, and becomes organized into large-scale functional systems that support complex behaviors. We discuss the methodological challenges posed by this promising area of research. We also highlight that despite these challenges, early work indicates a strong potential for these methods to influence multiple research domains. As an example, we focus on the study of early life stress and its influence on brain development and mental health outcomes. We illustrate the promise of these methodologies for building on, and making important contributions to, the existing literature in this field.

Use of resting-state functional MRI to study brain development and injury in neonates

Advances in methodology have led to expanded application of resting-state functional MRI (rs-fMRI) to the study of term and prematurely born infants during the first years of life, providing fresh insight into the earliest forms of functional cerebral development. In this review, we detail our evolving understanding of the use of rs-fMRI for studying neonates. We initially focus on the biological processes of cortical development related to resting-state network development. We then review technical issues principally affecting neonatal investigations, including the effects of subject motion during acquisition and image distortions related to magnetic susceptibility effects. We next summarize the literature in which rs-fMRI is used to study normal brain development during the early postnatal period, the effects of prematurity, and the effects of cerebral injury. Finally, we review potential future directions for the field, such as the use of complementary imaging modalities and advanced analysis techniques.

Functional Imaging of the Developing Brain at the Bedside Using Diffuse Optical Tomography

While histological studies and conventional magnetic resonance imaging (MRI) investigations have elucidated the trajectory of structural changes in the developing brain, less is known regarding early functional cerebral development. Recent investigations have demonstrated that resting-state functional connectivity MRI (fcMRI) can identify networks of functional cerebral connections in infants. However, technical and logistical challenges frequently limit the ability to perform MRI scans early or repeatedly in neonates, particularly in those at greatest risk for adverse neurodevelopmental outcomes. High-density diffuse optical tomography (HD-DOT), a portable imaging modality, potentially enables early continuous and quantitative monitoring of brain function in infants. We introduce an HD-DOT imaging system that combines advancements in cap design, ergonomics, and data analysis methods to allow bedside mapping of functional brain development in infants. In a cohort of healthy, full-term neonates scanned within the first days of life, HD-DOT results demonstrate strong congruence with those obtained using co-registered, subject-matched fcMRI and reflect patterns of typical brain development. These findings represent a transformative advance in functional neuroimaging in infants, and introduce HD-DOT as a powerful and practical method for quantitative mapping of early functional brain development in normal and high-risk neonates.

Data-driven approach to optimum wavelength selection for diffuse optical imaging

The production of accurate and independent images of the changes in concentration of oxyhemoglobin and deoxyhemoglobin by diffuse optical imaging is heavily dependent on which wavelengths of near-infrared light are chosen to interrogate the target tissue. Although wavelengths can be selected by theoretical methods, in practice the accuracy of reconstructed images will be affected by wavelength-specific and system-specific factors such as laser source power and detector sensitivity. We describe the application of a data-driven approach to optimum wavelength selection for the second generation of University College London's multichannel, time-domain optical tomography system (MONSTIR II). By performing a functional activation experiment using 12 different wavelengths between 690 and 870 nm, we were able to identify the combinations of 2, 3, and 4 wavelengths which most accurately reproduced the results obtained using all 12 wavelengths via an imaging approach. Our results show that the set of 2, 3, and 4 wavelengths which produce the most accurate images of functional activation are [770, 810], [770, 790, 850], and [730, 770, 810, 850] respectively, but also that the system is relatively robust to wavelength selection within certain limits. Although these results are specific to MONSTIR II, the approach we developed can be applied to other multispectral near-infrared spectroscopy and optical imaging systems.

Towards real-time detection of seizures in awake rats with GPU-accelerated diffuse optical tomography

BACKGROUND

Advancement in clinically relevant studies like seizure interruption using functional neuro imaging tools has shown that specific changes in hemodynamics precede and accompany seizure onset and propagation. However, preclinical seizure experiments need to be conducted in awake animals with images reconstructed and displayed in real-time.

METHODS

This article describes an approach that can be utilized to tackle these challenges. A subject specific head interface and restraining method was designed to allow for DOT to imaging of hemodynamic changes in unanesthetized rats during evoked acute seizures. Using CUDA programming model, the finite-element based nonlinear iterative algorithm for image reconstruction was parallelized.

RESULTS

Early hemodynamic changes were monitored in real time and observed tens of seconds prior to seizure onset. Utilizing the massive parallelization offered by graphic processing units (GPU), DOT was extended to online image reconstruction within 1s.

COMPARISON WITH EXISTING METHODS

Pre-seizure state related hemodynamic changes were detected in awake rats. 3D monitoring of hemodynamic changes was performed in real time with our parallelized image reconstruction procedure.

CONCLUSION

Diffuse optical tomography (DOT) is a promising neuroimaging tool for the investigation of seizures in awake animals.

Greater contribution of cerebral than extracerebral hemodynamics to near-infrared spectroscopy signals for functional activation and resting-state connectivity in infants

While near-infrared spectroscopy (NIRS) has been increasingly applied to neuroimaging and functional connectivity studies in infants, it has not been quantitatively examined as to what extent the deep tissue (such as cerebral tissue) as opposed to shallow tissue (such as scalp), contributes to NIRS signals measured in infants. A method for separating the effects of deep- and shallow-tissue layers was applied to data of nine sleeping three-month-old infants who had been exposed to 3-s speech sounds or silence (i.e., resting state) and whose hemodynamic changes over their bilateral temporal cortices had been measured by using an NIRS system with multiple source-detector (S-D) distances. The deep-layer contribution was found to be large during resting [67% at S-D 20 mm, 78% at S-D 30 mm for oxygenated hemoglobin (oxy-Hb)] as well as during the speech condition (72% at S-D 20 mm, 82% at S-D 30 mm for oxy-Hb). A left-right connectivity analysis showed that correlation coefficients between left and right channels did not differ between original- and deep-layer signals under no-stimulus conditions and that of original- and deep-layer signals were larger than those of the shallow layer. These results suggest that NIRS signals obtained in infants with appropriate S-D distances largely reflected cerebral hemodynamic changes.

A 4D neonatal head model for diffuse optical imaging of pre-term to term infants

Diffuse optical tomography is most accurate when an individual's MRI data can be used as a spatial prior for image reconstruction and for visualization of the resulting images of changes in oxy- and deoxy-hemoglobin concentration. As this necessitates an MRI scan to be performed for each study, which undermines many of the advantages of diffuse optical methods, the use of registered atlases to model the individual's anatomy is becoming commonplace. Infant studies require carefully age-matched atlases because of the rapid growth and maturation of the infant brain. In this paper, we present a 4D neonatal head model which, for each week from 29 to 44 weeks post-menstrual age, includes: 1) a multi-layered tissue mask which identifies extra-cerebral layers, cerebrospinal fluid, gray matter, white matter, cerebellum and brainstem, 2) a high-density tetrahedral head mesh, 3) surface meshes for the scalp, gray-matter and white matter layers and 4) cranial landmarks and 10-5 locations on the scalp surface. This package, freely available online at www.ucl.ac.uk/medphys/research/4dneonatalmodel can be applied by users of near-infrared spectroscopy and diffuse optical tomography to optimize probe locations, optimize image reconstruction, register data to cortical locations and ultimately improve the accuracy and interpretation of diffuse optical techniques in newborn populations.

Reduced interhemispheric functional connectivity of children with autism spectrum disorder: evidence from functional near infrared spectroscopy studies

Autism spectrum disorder (ASD) is a neuro-developmental disorder, which has been associated with atypical neural synchronization. In this study, functional near infrared spectroscopy (fNIRS) was used to study the differences in functional connectivity in bilateral inferior frontal cortices (IFC) and bilateral temporal cortices (TC) between ASD and typically developing (TD) children between 8 and 11 years of age. As the first report of fNIRS study on the resting state functional connectivity (RSFC) in children with ASD, ten children with ASD and ten TD children were recruited in this study for 8 minute resting state measurement. Compared to TD children, children with ASD showed reduced interhemispheric connectivity in TC. Children with ASD also showed significantly lower local connectivity in bilateral temporal cortices. In contrast to TD children, children with ASD did not show typical patterns of symmetry in functional connectivity in temporal cortex. These results support the feasibility of using the fNIRS method to assess atypical functional connectivity of cortical responses of ASD and its potential application in diagnosis.

Referential framework for transcranial anatomical correspondence for fNIRS based on manually traced sulci and gyri of an infant brain

Functional near infrared spectroscopy (fNIRS), which is compact, portable, and tolerant of body movement, is suitable for monitoring infant brain functions. Nevertheless, fNIRS also poses a technical problem in that it cannot provide structural information. Supplementation with structural magnetic resonance images (MRI) is not always feasible for infants who undergo fNIRS measurement. Probabilistic registration methods using an MRI database instead of subjects' own MRIs are optimized for adult studies and offer only limited resources for infant studies. To overcome this, we used high-quality infant MRI data for a 12-month-old infant and manually delineated segmented gyri from among the highly visible macroanatomies on the lateral cortical surface. These macroanatomical regions are primarily linked to the spherical coordinate system based on external cranial landmarks, and further to traditional 10-20-based head-surface positioning systems. While macroanatomical structures were generally comparable between adult and infant atlases, differences were found in the parietal lobe, which was positioned posteriorly at the vertex in the infant brain. The present study provides a referential framework for macroanatomical analyses in infant fNIRS studies. With this resource, multichannel fNIRS functional data could be analyzed in reference to macroanatomical structures through virtual and probabilistic registrations without acquiring subject-specific MRIs.

High-resolution photoacoustic tomography of resting-state functional connectivity in the mouse brain

The increasing use of mouse models for human brain disease studies presents an emerging need for a new functional imaging modality. Using optical excitation and acoustic detection, we developed a functional connectivity photoacoustic tomography system, which allows noninvasive imaging of resting-state functional connectivity in the mouse brain, with a large field of view and a high spatial resolution. Bilateral correlations were observed in eight functional regions, including the olfactory bulb, limbic, parietal, somatosensory, retrosplenial, visual, motor, and temporal regions, as well as in several subregions. The borders and locations of these regions agreed well with the Paxinos mouse brain atlas. By subjecting the mouse to alternating hyperoxic and hypoxic conditions, strong and weak functional connectivities were observed, respectively. In addition to connectivity images, vascular images were simultaneously acquired. These studies show that functional connectivity photoacoustic tomography is a promising, noninvasive technique for functional imaging of the mouse brain.

Resting-State Functional Brain Connectivity

Resting-state functional near-infrared spectroscopy (R-fNIRS) is an active area of interest and is currently attracting considerable attention as a new imaging tool for the study of resting-state brain function. Using variations in hemodynamic concentration signals, R-fNIRS measures the brain’s low-frequency spontaneous neural activity, combining the advantages of portability, low-cost, high temporal sampling rate and less physical burden to participants. The temporal synchronization of spontaneous neuronal activity in anatomically separated regions is referred to as resting-state functional connectivity (RSFC). In the past several years, an increasing body of R-fNIRS RSFC studies has led to many important findings about functional integration among local or whole-brain regions by measuring inter-regional temporal synchronization. Here, we summarize recent advances made in the R-fNIRS RSFC methodologies, from the detection of RSFC (e.g., seed-based correlation analysis, independent component analysis, whole-brain correlation analysis, and graph-theoretical topological analysis), to the assessment of RSFC performance (e.g., reliability, repeatability, and validity), to the application of RSFC in studying normal development and brain disorders. The literature reviewed here suggests that RSFC analyses based on R-fNIRS data are valid and reliable for the study of brain function in healthy and diseased populations, thus providing a promising imaging tool for cognitive science and clinics.

Test-retest reliability of graph metrics in functional brain networks: a resting-state fNIRS study

Recent research has demonstrated the feasibility of combining functional near-infrared spectroscopy (fNIRS) and graph theory approaches to explore the topological attributes of human brain networks. However, the test-retest (TRT) reliability of the application of graph metrics to these networks remains to be elucidated. Here, we used resting-state fNIRS and a graph-theoretical approach to systematically address TRT reliability as it applies to various features of human brain networks, including functional connectivity, global network metrics and regional nodal centrality metrics. Eighteen subjects participated in two resting-state fNIRS scan sessions held ∼20 min apart. Functional brain networks were constructed for each subject by computing temporal correlations on three types of hemoglobin concentration information (HbO, HbR, and HbT). This was followed by a graph-theoretical analysis, and then an intraclass correlation coefficient (ICC) was further applied to quantify the TRT reliability of each network metric. We observed that a large proportion of resting-state functional connections (∼90%) exhibited good reliability (0.6< ICC <0.74). For global and nodal measures, reliability was generally threshold-sensitive and varied among both network metrics and hemoglobin concentration signals. Specifically, the majority of global metrics exhibited fair to excellent reliability, with notably higher ICC values for the clustering coefficient (HbO: 0.76; HbR: 0.78; HbT: 0.53) and global efficiency (HbO: 0.76; HbR: 0.70; HbT: 0.78). Similarly, both nodal degree and efficiency measures also showed fair to excellent reliability across nodes (degree: 0.52∼0.84; efficiency: 0.50∼0.84); reliability was concordant across HbO, HbR and HbT and was significantly higher than that of nodal betweenness (0.28∼0.68). Together, our results suggest that most graph-theoretical network metrics derived from fNIRS are TRT reliable and can be used effectively for brain network research. This study also provides important guidance on the choice of network metrics of interest for future applied research in developmental and clinical neuroscience.

Functional connectivity in the first year of life in infants at-risk for autism: a preliminary near-infrared spectroscopy study

BACKGROUND

Autism spectrum disorder (ASD) has been called a "developmental disconnection syndrome," however the majority of the research examining connectivity in ASD has been conducted exclusively with older children and adults. Yet, prior ASD research suggests that perturbations in neurodevelopmental trajectories begin as early as the first year of life. Prospective longitudinal studies of infants at risk for ASD may provide a window into the emergence of these aberrant patterns of connectivity. The current study employed functional connectivity near-infrared spectroscopy (NIRS) in order to examine the development of intra- and inter-hemispheric functional connectivity in high- and low-risk infants across the first year of life.

METHODS

NIRS data were collected from 27 infants at high risk for autism (HRA) and 37 low-risk comparison (LRC) infants who contributed a total of 116 data sets at 3-, 6-, 9-, and 12-months. At each time point, HRA and LRC groups were matched on age, sex, head circumference, and Mullen Scales of Early Learning scores. Regions of interest (ROI) were selected from anterior and posterior locations of each hemisphere. The average time course for each ROI was calculated and correlations for each ROI pair were computed. Differences in functional connectivity were examined in a cross-sectional manner.

RESULTS

At 3-months, HRA infants showed increased overall functional connectivity compared to LRC infants. This was the result of increased connectivity for intra- and inter-hemispheric ROI pairs. No significant differences were found between HRA and LRC infants at 6- and 9-months. However, by 12-months, HRA infants showed decreased connectivity relative to LRC infants.

CONCLUSIONS

Our preliminary results suggest that atypical functional connectivity may exist within the first year of life in HRA infants, providing support to the growing body of evidence that aberrant patterns of connectivity may be a potential endophenotype for ASD.

Effects of preterm birth on intrinsic fluctuations in neonatal cerebral activity examined using optical imaging

Medical advancements in neonatology have significantly increased the number of high-risk preterm survivors. However, recent long-term follow-up studies have suggested that preterm infants are at risk for behavioral, educational, and emotional problems. Although clear relationships have been demonstrated between preterm infants and developmental problems during childhood and adolescence, less is known about the early indications of these problems. Recently, numerous studies on resting-state functional connectivity (RSFC) have demonstrated temporal correlations of activity between spatially remote cortical regions not only in healthy adults but also in neuropathological disorders and early childhood development. In order to compare RSFC of the cerebral cortex between preterm infants at term-equivalent ages and full-term neonates without any anatomical abnormality risk during natural sleep, we used an optical topography system, which is a recently developed extension of near-infrared spectroscopy. We clarified the presence of RSFC in both preterm infants and full-term neonates and showed differences between these groups. The principal differences were that on comparison of RSFC between the bilateral temporal regions, and bilateral parietal regions, RSFC was enhanced in preterm infants compared with full-term neonates; whereas on comparison of RSFC between the left temporal and left parietal regions, RSFC was enhanced in full-term neonates compared with preterm infants. We also demonstrated a difference between the groups in developmental changes of RSFC related to postmenstrual age. Most importantly, these findings suggested that preterm infants and full-term neonates follow different developmental trajectories during the perinatal period because of differences in perinatal experiences and physiological and structural development.

Functional connectivity of the cortex of term and preterm infants and infants with Down's syndrome

Near-infrared spectroscopy (NIRS) imaging studies have revealed the functional development of the human brain in early infancy. By measuring spontaneous fluctuations in cerebral blood oxygenation with NIRS, we can examine the developmental status of the functional connectivity of networks in the cortex. However, it has not been clarified whether premature delivery and/or chromosomal abnormalities affect the development of the functional connectivity of the cortex. In the current study, we investigated the spontaneous brain activity of sleeping infants who were admitted to a neonatal intensive care unit at term age. We classified them into the 3 following infant groups: (i) term-or-late-preterm, (ii) early-preterm, and (iii) Down's syndrome (DS). We used multichannel NIRS to measure the spontaneous changes in oxygenated hemoglobin (oxy-Hb) and deoxygenated hemoglobin (deoxy-Hb) at 10 measurement channels, which covered the frontal, temporal, and occipital regions. In order to reveal the functional connectivity of the cortical networks, we calculated the temporal correlations of the time-course signals among all of the pairs of measurement channels. The functional connectivity was classified into the 4 following types: (i) short-range, (ii) contralateral-transverse, (iii) ipsilateral-longitudinal, and (iv) control. In order to examine whether the local properties of hemodynamics reflected any pathological conditions, we calculated the phase differences between the oxy- and deoxy-Hb time-course signals in the 3 groups. The statistical analyses of the functional connectivity data showed main effects of group and the types of connectivity. For the group effect, the mean functional connectivity of the infants in the term-or-late-preterm group did not differ from that in the early-preterm group, and the mean functional connectivity of the infants in the DS group was lower than that in the other 2 groups. For the effect of types of connectivity, short-range connectivity was highest compared to any of the other types of connectivity, and the second highest connectivity was the contralateral-transverse one. The phase differences between the oxy- and deoxy-Hb changes showed that there were significant differences between the DS group and the other 2 groups. Our findings suggested that the development of the functional connectivity of cortical networks did not differ between term-or-late-preterm infants and early-preterm infants around term-equivalent ages, while DS infants had alterations in their functional connectivity development and local hemodynamics at term age. The highest short-range connectivity and the second highest contralateral-transverse connectivity suggested that the precursors for the basic cortical networks of functional connectivity were present at term age.

Translational optical imaging

OBJECTIVE

Optical imaging is experiencing significant technologic advances. Simultaneously, an array of specific optical imaging agents has brought new capabilities to biomedical research and is edging toward clinical use. We review progress in the translation of macroscopic optical imaging-including fluorescence-guided surgery and endoscopy, intravascular fluorescence imaging, diffuse fluorescence and optical tomography, and multispectral optoacoustics (photoacoustics)-for applications ranging from tumor resection and assessment of atherosclerotic plaques to dermatologic and breast examinations.

CONCLUSION

Optical imaging could play a major role in the move from imaging of structure and morphology to the visualization of the individual biologic processes underlying disease and could, therefore, contribute to more accurate diagnostics and improved treatment efficacy.

Revealing topological organization of human brain functional networks with resting-state functional near infrared spectroscopy

BACKGROUND

The human brain is a highly complex system that can be represented as a structurally interconnected and functionally synchronized network, which assures both the segregation and integration of information processing. Recent studies have demonstrated that a variety of neuroimaging and neurophysiological techniques such as functional magnetic resonance imaging (MRI), diffusion MRI and electroencephalography/magnetoencephalography can be employed to explore the topological organization of human brain networks. However, little is known about whether functional near infrared spectroscopy (fNIRS), a relatively new optical imaging technology, can be used to map functional connectome of the human brain and reveal meaningful and reproducible topological characteristics.

RESULTS

We utilized resting-state fNIRS (R-fNIRS) to investigate the topological organization of human brain functional networks in 15 healthy adults. Brain networks were constructed by thresholding the temporal correlation matrices of 46 channels and analyzed using graph-theory approaches. We found that the functional brain network derived from R-fNIRS data had efficient small-world properties, significant hierarchical modular structure and highly connected hubs. These results were highly reproducible both across participants and over time and were consistent with previous findings based on other functional imaging techniques.

CONCLUSIONS

Our results confirmed the feasibility and validity of using graph-theory approaches in conjunction with optical imaging techniques to explore the topological organization of human brain networks. These results may expand a methodological framework for utilizing fNIRS to study functional network changes that occur in association with development, aging and neurological and psychiatric disorders.

High-density diffuse optical tomography of term infant visual cortex in the nursery

Advancements in antenatal and neonatal medicine over the last few decades have led to significant improvement in the survival rates of sick newborn infants. However, this improvement in survival has not been matched by a reduction in neurodevelopmental morbidities with increasing recognition of the diverse cognitive and behavioral challenges that preterm infants face in childhood. Conventional neuroimaging modalities, such as cranial ultrasound and magnetic resonance imaging, provide an important definition of neuroanatomy with recognition of brain injury. However, they fail to define the functional integrity of the immature brain, particularly during this critical developmental period. Diffuse optical tomography methods have established success in imaging adult brain function; however, few studies exist to demonstrate their feasibility in the neonatal population. We demonstrate the feasibility of using recently developed high-density diffuse optical tomography (HD-DOT) to map functional activation of the visual cortex in healthy term-born infants. The functional images show high contrast-to-noise ratio obtained in seven neonates. These results illustrate the potential for HD-DOT and provide a foundation for investigations of brain function in more vulnerable newborns, such as preterm infants.

A NIRS-fMRI study of resting state network

Resting state functional connectivity, which is defined as temporal correlation of spontaneous activity between diverse brain regions, has been reported to form resting state networks (RSNs), consisting of a specific set of brain regions, based on functional magnetic resonance imaging (fMRI). Recently, studies using near-infrared spectroscopy (NIRS) reported that NIRS signals also show temporal correlation between different brain regions. The local relationship between NIRS and fMRI signals has been examined by simultaneously recording these signals when participants perform tasks or respond to stimuli. However, the NIRS-fMRI signal relationship during the resting state has been reported only between NIRS signals obtained within limited regions and whole brain fMRI signals. Therefore, it remains unclear whether NIRS signals obtained at diverse regions correlate with regional fMRI signals close to the NIRS measurement channels, especially in relation to the RSNs. In this study, we tested whether the signals measured by these different modalities during the resting state have the consistent characteristics of the RSNs. Specifically, NIRS signals during the resting state were acquired over the frontal, temporal, and occipital cortices while whole brain fMRI data was simultaneously recorded. First, by projecting the NIRS channel positions over the cerebral cortical surface, we identified the most likely anatomical locations of all NIRS channels used in the study. Next, to investigate the regional signal relationship between NIRS and fMRI, we calculated the cross-correlation between NIRS signals and fMRI signals in the brain regions adjacent to each NIRS channel. For each NIRS channel, we observed the local maxima of correlation coefficients between NIRS and fMRI signals within a radius of 2 voxels from the projection point. Furthermore, we also found that highly correlated voxels with the NIRS signal were mainly localized within brain tissues for all NIRS channels, with the exception of 2 frontal channels. Finally, by calculating the correlation between NIRS signals at a channel and whole brain fMRI signals, we observed that NIRS signals correlate with fMRI signals not only within brain regions adjacent to NIRS channels but also within distant brain regions constituting RSNs, such as the dorsal attention, fronto-parietal control, and default mode networks. These results support the idea that NIRS signals obtained at several cortical regions during the resting state mainly reflect regional spontaneous hemodynamic fluctuations that originate from spontaneous cortical activity, and include information that characterizes the RSNs. Because NIRS is relatively easy to use and a less physically demanding neuroimaging technique, our findings should facilitate a broad application of this technique to examine RSNs, especially for clinical populations and conditions unsuitable for fMRI.

Fast multispectral diffuse optical tomography system for in vivo three-dimensional imaging of seizure dynamics

We describe a multispectral continuous-wave diffuse optical tomography (DOT) system that can be used for in vivo three-dimensional (3-D) imaging of seizure dynamics. Fast 3-D data acquisition is realized through a time multiplexing approach based on a parallel lighting configuration--our system can achieve 0.12 ms per source per wavelength and up to a 14 Hz sampling rate for a full set of data for 3-D DOT image reconstruction. The system is validated using both static and dynamic tissue-like phantoms. An initial in vivo experiment using a rat model of seizure is also demonstrated.