Near-infrared spectroscopy (NIRS) offers the potential to characterize resting-state functional connectivity (RSFC) in populations that are not easily assessed otherwise, such as young infants. In addition to the advantages of NIRS, one should also consider that the RS-NIRS signal requires specific data preprocessing and analysis. In particular, the RS-NIRS signal shows a colored frequency spectrum, which can be observed as temporal autocorrelation, thereby introducing spurious correlations. To address this issue, prewhitening of the RS-NIRS signal has been recently proposed as a necessary step to remove the signal temporal autocorrelation and therefore reduce false-discovery rates. However, the impact of this step on the analysis of experimental RS-NIRS data has not been thoroughly assessed prior to the present study. Here, the results of a standard preprocessing pipeline in a RS-NIRS dataset acquired in infants are compared with the results after incorporating two different prewhitening algorithms. Our results with a standard preprocessing replicated previous studies. Prewhitening altered RSFC patterns and disrupted the antiphase relationship between oxyhemoglobin and deoxyhemoglobin. We conclude that a better understanding of the effect of prewhitening on RS-NIRS data is still needed before directly considering its incorporation to the standard preprocessing pipeline.

Neurophotonics is an exploding field that spans the intersection of light and neurons for fundamental discovery and clinical translation. Optical technologies have significantly impacted brain research by probing into the mysteries of the brain, modulating brain activity, and improving patient care. Based on a discussion held at the International Conference on Biophotonics 2017, a group of leading researchers brainstormed to identify areas of unmet need in neuroscience and medicine, where biophotonics research could have the highest affect. We present two areas of future growth that spans basic research and clinical needs: management of chronic pain and interventional neuroimmunology. There are many directions within these areas that could be pursued for the ultimate goal of improved understanding of the brain and enhanced care of patients with neurological disorders.

We summarize the available in vivo validation of cerebral near-infrared spectroscopy (NIRS) oximetry to inform future in vivo validation strategies. In particular, to establish a way forward in the assessment of NIRS instrumentation for future randomized trials, a systematic literature search is performed. The records are screened and abstracts are assessed to select studies fulfilling our inclusion criteria. Twenty-two pediatric and 28 adult studies are analyzed after exclusion of three articles in each group. All studies compare regional cerebral tissue oxygenation measured by cerebral NIRS to invasive measurement of central or jugular venous oxygen saturation. In studies without Bland–Altman plots, we extracted data from scatter plots enabling estimation of mean difference (MD), standard deviation (SD), and limits of agreement (LOA). To assess the agreement between rStO₂ (regional cerebral tissue oxygenation) estimated by NIRS and by blood samples, weighted averages of the MDs and SDs from each study are calculated. We found a fair agreement between the overall mean of cerebral tissue oxygenation and the mean of a reference value measured by co-oximetry whatever NIRS instrument or site of blood sampling used. Cerebral oxygenation overestimates the reference at low values, some instruments apparently more than others. Thus, a high degree of scatter and a lack of a good reference method complicate in vivo validation of NIRS. It is difficult to draw any firm conclusions despite the large number of studies, and the result of this review leaves us questioning if more of such validation studies of cerebral NIRS oximetry are really needed. Furthermore, the combination of lack of validation and poor repeatability is an important issue when designing a randomized clinical trial of implementing cerebral NIRS oximetry into clinical care.

Functional near-infrared spectroscopy (fNIRS) signals are prone to problems caused by motion artifacts and physiological noises. These noises unfortunately reduce the fNIRS sensitivity in detecting the evoked brain activation while increasing the risk of statistical error. In fNIRS measurements, the repetitive resting-stimulus cycle (so-called block-design analysis) is commonly adapted to increase the sample number. However, these blocks are often affected by noises. Therefore, we developed an adaptive algorithm to identify, reject, and select the noise-free and/or least noisy blocks in accordance with the preset acceptance rate. The main features of this algorithm are personalized evaluation for individual data and controlled rejection to maintain the sample number. Three typical noise criteria (sudden amplitude change, shifted baseline, and minimum intertrial correlation) were adopted. Depending on the quality of the dataset used, the algorithm may require some or all noise criteria with distinct parameters. Aiming for real applications in a pediatric study, we applied this algorithm to fNIRS datasets obtained from attention deficit/hyperactivity disorder (ADHD) children as had been studied previously. These datasets were divided for training and validation purposes. A validation process was done to examine the feasibility of the algorithm regardless of the types of datasets, including those obtained under sample population (ADHD or typical developing children), intervention (nonmedication and drug/placebo administration), and measurement (task paradigm) conditions. The algorithm was optimized so as to enhance reproducibility of previous inferences. The optimum algorithm design involved all criteria ordered sequentially (0.047 mM mm of amplitude change, 0.029  mM  mm  /  s of baseline slope, and 0.6  ×  interquartile range of outlier threshold for each criterion, respectively) and presented complete reproducibility in both training and validation datasets. Compared to the visual-based rejection as done in the previous studies, the algorithm achieved 71.8% rejection accuracy. This suggests that the algorithm has robustness and potential to substitute for visual artifact-detection.

An emerging method in the field of neural stimulation is the use of photons to activate neurons. The possible advantage of optical stimulation over electrical is attributable to its spatially selective activation of small neuron populations, which is promising in generating superior spatial resolution in neural interfaces. Two principal methods are explored for cochlear prostheses: direct stimulation of nerves with infrared light and optogenetics. This paper discusses basic requirements for developing a light delivery system (LDS) for the cochlea and provides examples for building such devices. The proposed device relies on small optical sources, which are assembled in an array to be inserted into the cochlea. The mechanical properties, the biocompatibility, and the efficacy of optrodes have been tested in animal models. The force required to insert optrodes into a model of the human scala tympani was comparable to insertion forces obtained for contemporary cochlear implant electrodes. Side-emitting diodes are powerful enough to evoke auditory responses in guinea pigs. Chronic implantation of the LDS did not elevate auditory brainstem responses over 26 weeks.

Obstructive apnea causes periodic changes in cerebral and systemic hemodynamics, which may contribute to the increased risk of cerebrovascular disease of patients with obstructive sleep apnea (OSA) syndrome. The improved understanding of the consequences of an apneic event on the brain perfusion may improve our knowledge of these consequences and then allow for the development of preventive strategies. Our aim was to characterize the typical microvascular, cortical cerebral blood flow (CBF) changes in an OSA population during an apneic event. Sixteen patients (age 58  ±  8  years, 75% male) with a high risk of severe OSA were measured with a polysomnography device and with diffuse correlation spectroscopy (DCS) during one night of sleep with 1365 obstructive apneic events detected. All patients were later confirmed to suffer from severe OSA syndrome with a mean of 83  ±  15 apneas and hypopneas per hour. DCS has been shown to be able to characterize the microvascular CBF response to each event with a sufficient contrast-to-noise ratio to reveal its dynamics. It has also revealed that an apnea causes a peak increase of microvascular CBF (30  ±  17  %  ) at the end of the event followed by a drop (−20  ±  12  %  ) similar to what was observed in macrovascular CBF velocity of the middle cerebral artery. This study paves the way for the utilization of DCS for further studies on these populations.

An automated dual-resolution serial optical coherence tomography (2R-SOCT) scanner is developed. The serial histology system combines a low-resolution (25  μm  /  voxel) 3  ×   OCT with a high-resolution (1.5  μm  /  voxel) 40  ×   OCT to acquire whole mouse brains at low resolution and to target specific regions of interest (ROIs) at high resolution. The 40  ×   ROIs positions are selected either manually by the microscope operator or using an automated ROI positioning selection algorithm. Additionally, a multimodal and multiresolution registration pipeline is developed in order to align the 2R-SOCT data onto diffusion MRI (dMRI) data acquired in the same ex vivo mouse brains prior to automated histology. Using this imaging system, 3 whole mouse brains are imaged, and 250 high-resolution 40  ×   three-dimensional ROIs are acquired. The capability of this system to perform multimodal imaging studies is demonstrated by labeling the ROIs using a mouse brain atlas and by categorizing the ROIs based on their associated dMRI measures. This reveals a good correspondence of the tissue microstructure imaged by the high-resolution OCT with various dMRI measures such as fractional anisotropy, number of fiber orientations, apparent fiber density, orientation dispersion, and intracellular volume fraction.

Monitoring of cerebral blood flow (CBF) and autoregulation are essential components of neurocritical care, but continuous noninvasive methods for CBF monitoring are lacking. Diffuse correlation spectroscopy (DCS) is a noninvasive diffuse optical modality that measures a CBF index (CBF_i) in the cortex microvasculature by monitoring the rapid fluctuations of near-infrared light diffusing through moving red blood cells. We tested the feasibility of monitoring CBF_i with DCS in at-risk patients in the Neurosciences Intensive Care Unit. DCS data were acquired continuously for up to 20 h in six patients with aneurysmal subarachnoid hemorrhage, as permitted by clinical care. Mean arterial blood pressure was recorded synchronously, allowing us to derive autoregulation curves and to compute an autoregulation index. The autoregulation curves suggest disrupted cerebral autoregulation in most patients, with the severity of disruption and the limits of preserved autoregulation varying between subjects. Our findings suggest the potential of the DCS modality for noninvasive, long-term monitoring of cerebral perfusion, and autoregulation.

We investigate a scheme for noninvasive continuous monitoring of absolute cerebral blood flow (CBF) in adult human patients based on a combination of time-resolved dynamic contrast-enhanced near-infrared spectroscopy (DCE-NIRS) and diffuse correlation spectroscopy (DCS) with semi-infinite head model of photon propogation. Continuous CBF is obtained via calibration of the DCS blood flow index (BFI) with absolute CBF obtained by intermittent intravenous injections of the optical contrast agent indocyanine green. A calibration coefficient (γ) for the CBF is thus determined, permitting conversion of DCS BFI to absolute blood flow units at all other times. A study of patients with acute brain injury (N  =  7) is carried out to ascertain the stability of γ. The patient-averaged DCS calibration coefficient across multiple monitoring days and multiple patients was determined, and good agreement between the two calibration coefficients measured at different times during single monitoring days was found. The patient-averaged calibration coefficient of 1.24  ×  10⁹    (  mL  /  100  g  /  min  )    /    (  cm²  /  s  )   was applied to previously measured DCS BFI from similar brain-injured patients; in this case, absolute CBF was underestimated compared with XeCT, an effect we show is primarily due to use of semi-infinite homogeneous models of the head.

The use of functional near-infrared spectroscopy (fNIRS) in block designs provides measures of cortical activity in ecologically valid environments. However, in some cases, the use of block designs may be problematic when data are not corrected for performance in a time-restricted block. We sought to investigate the effects of task complexity and processing speed on hemodynamic responses in an fNIRS block design. To differentiate the effects of task complexity and processing speed, 20 subjects completed the trail making test (TMT) in two versions (TMT-A versus TMT-B) and three different speed levels (slow versus moderate versus fast). During TMT-A, subjects are asked to connect encircled numbers in numerically ascending order (1-2-3…). In the more complex TMT-B, subjects are instructed to connect encircled numbers and letters in alternating ascending order (1-A-2-B…). To illustrate the obscuring effects of processing speed on task complexity, we perform two different analyses. First, we analyze the classical measures of oxygenated blood, and second, we analyze the measures corrected for the number of processed items. Our results show large effects for processing speed within the bilateral inferior frontal gyrus, left dorsolateral prefrontal cortex, and superior parietal lobule (SPL). The TMT contrast did not show significant effects with classical measures, although trends are observed for higher activation during TMT-B. When corrected for processed items, higher activity for TMT-B in comparison to TMT-A is found within the SPL. The results are discussed in light of recent research designs, and simple to use correction methods are suggested.

Disruptions and alterations to cerebral energy metabolism play a vital role in the onset and progression of many neurodegenerative disorders and cerebral pathologies. In order to precisely understand the complex alterations underlying Alzheimer’s disease (AD) progression, in vivo imaging at the microscopic level is required in preclinical animal models. Utilizing two-photon fluorescence lifetime imaging microscopy and the phasor analysis method, we have observed AD-related variations of endogenous fluorescence of reduced nicotinamide adenine dinucleotide (NADH) in vivo. We collected NADH FLIM images from the cerebral cortices of both APPswe:PS1dE9 mice to model amyloid β plaque accumulation and corresponding age-matched wildtype controls. Distinct variations in NADH fluorescence lifetime between wildtype and AD mice, as well as variations related to proximity from amyloid plaques, are obvervable via the phasor method. The combination of NADH FLIM and phasor analysis allows for a minimally invasive, high-resolution technique to characterize the adverse effects of amyloid β accumulation on mitochondrial energy metabolism and could guide our understanding of preclinical AD pathology.

Previously introduced bundles of hundreds or thousands of microfibers have the potential to extend optical access to deep brain regions, sampling fluorescence activity throughout a three-dimensional volume. Each fiber has a small diameter (8  μm) and follows a path of least resistance, splaying during insertion. By superimposing the fiber sensitivity profile for each fiber, we model the interface properties for a simulated neural population. Our modeling results suggest that for small (<200) bundles of fibers, each fiber will collect fluorescence from a small number of nonoverlapping neurons near the fiber apertures. As the number of fibers increases, the bundle delivers more uniform excitation power to the region, moving to a regime where fibers collect fluorescence from more neurons and there is greater overlap between neighboring fibers. Under these conditions, it becomes feasible to apply source separation to extract individual neural contributions. In addition, we demonstrate a source separation technique particularly suited to the interface. Our modeling helps establish performance expectations for this interface and provides a framework for estimating neural contributions under a range of conditions.

This erratum corrects an error in “Adaptive algorithm utilizing acceptance rate for eliminating noisy epochs in block-design functional near-infrared spectroscopy data: application to study in attention deficit/hyperactivity disorder children.”