Significance: Stem cell therapies are of interest for treating a variety of neurodegenerative diseases and injuries of the spinal cord. However, the lack of techniques for longitudinal monitoring of stem cell therapy progression is inhibiting clinical translation.

Aim: The goal of this study is to demonstrate an intraoperative imaging approach to guide stem cell injection to the spinal cord in vivo. Results may ultimately support the development of an imaging tool that spans intra- or postoperative environments to guide therapy throughout treatment.

Approach: Stem cells were labeled with Prussian blue nanocubes (PBNCs) to facilitate combined ultrasound and photoacoustic (US/PA) imaging to visualize stem cell injection and delivery to the spinal cord in vivo. US/PA results were confirmed by magnetic resonance imaging (MRI) and histology.

Results: Real-time intraoperative US/PA image-guided injection of PBNC-labeled stem cells and three-dimensional volumetric images of injection provided feedback necessary for successful delivery of therapeutics into the spinal cord. Postoperative MRI confirmed delivery of PBNC-labeled stem cells.

Conclusions: The nanoparticle-augmented US/PA approach successfully detected injection and delivery of stem cells into the spinal cord, confirmed by MRI. Our work demonstrated in vivo feasibility, which is a critical step toward the development of a US/PA/MRI platform to monitor regenerative spinal cord therapies.

Significance: Having a clear understanding of functional hyperemia is crucial for functional brain imaging and neurological disease research. Vasodilation induced by sensory stimulus propagates from the arterioles to the upstream pial arteries in a retrograde fashion. As retrograde vasodilation occurs briefly in the early stage of functional hyperemia, an imaging technique with a high temporal resolution is required for its measurement.

Aim: We aimed to present an imaging method to measure stimulus-induced retrograde vasodilation in awake animals.

Approach: An imaging method based on optical coherence tomography angiography, which enables a high-speed and label-free vessel diameter measurement, was developed and applied for the investigation.

Results: The propagation speed of retrograde vasodilation of pial artery was measured in awake mice. Other characteristics of functional hyperemia such as temporal profile and amplitude of the vascular response were also investigated.

Conclusions: Our results provide detailed information of stimulus-induced hemodynamic response in the brain of awake mice and suggest the potential utility of our imaging method for the study of functional hyperemia in normal and diseased brain.

Significance: We propose a video-based, motion-resilient, and fast method for estimating the position of optodes on the scalp.

Aim: Measuring the exact placement of probes (e.g., electrodes and optodes) on a participant’s head is a notoriously difficult step in acquiring neuroimaging data from methods that rely on scalp recordings (e.g., electroencephalography and functional near-infrared spectroscopy) and is particularly difficult for any clinical or developmental population. Existing methods of head measurements require the participant to remain still for a lengthy period of time, are laborious, and require extensive training. Therefore, a fast and motion-resilient method is required for estimating the scalp location of probes.

Approach: We propose an innovative video-based method for estimating the probes’ positions relative to the participant’s head, which is fast, motion-resilient, and automatic. Our method builds on capitalizing the advantages and understanding the limitations of cutting-edge computer vision and machine learning tools. We validate our method on 10 adult subjects and provide proof of feasibility with infant subjects.

Results: We show that our method is both reliable and valid compared to existing state-of-the-art methods by estimating probe positions in a single measurement and by tracking their translation and consistency across sessions. Finally, we show that our automatic method is able to estimate the position of probes on an infant head without lengthy offline procedures, a task that has been considered challenging until now.

Conclusions: Our proposed method allows, for the first time, the use of automated spatial co-registration methods on developmental and clinical populations, where lengthy, motion-sensitive measurement methods routinely fail.

Significance: Wide-field measurement of cellular membrane dynamics with high spatiotemporal resolution can facilitate analysis of the computing properties of neuronal circuits. Quantum microscopy using a nitrogen-vacancy (NV) center is a promising technique to achieve this goal.

Aim: We propose a proof-of-principle approach to NV-based neuron functional imaging.

Approach: This goal is achieved by engineering NV quantum sensors in diamond nanopillar arrays and switching their sensing mode to detect the changes in the electric fields instead of the magnetic fields, which has the potential to greatly improve signal detection. Apart from containing the NV quantum sensors, nanopillars also function as waveguides, delivering the excitation/emission light to improve sensitivity. The nanopillars also improve the amplitude of the neuron electric field sensed by the NV by removing screening charges. When the nanopillar array is used as a cell niche, it acts as a cell scaffolds which makes the pillars function as biomechanical cues that facilitate the growth and formation of neuronal circuits. Based on these growth patterns, numerical modeling of the nanoelectromagnetics between the nanopillar and the neuron was also performed.

Results: The growth study showed that nanopillars with a 2-μm pitch and a 200-nm diameter show ideal growth patterns for nanopillar sensing. The modeling showed an electric field amplitude as high as ≈1.02  ×  10¹⁰  mV  /  m at an NV 100 nm from the membrane, a value almost 10 times the minimum field that the NV can detect.

Conclusion: This proof-of-concept study demonstrated unprecedented NV sensing potential for the functional imaging of mammalian neuron signals.

Significance: A major obstacle to studying resident microglia has been their similarity to infiltrating immune cell types and the lack of unique protein markers for identifying the functional state. Given the role of microglia in all neural diseases and insults, accurate tools for detecting their function beyond morphologic alterations are necessary.

Aims: We hypothesized that microglia would have unique metabolic fluxes in reduced nicotinamide adenine dinucleotide (NADH) that would be detectable by relative changes in fluorescence lifetime imaging microscopy (FLIM) parameters, allowing for identification of their activation status. Fluorescence lifetime of NADH has been previously demonstrated to show differences in metabolic fluxes.

Approach: Here, we investigate the use of the label-free method of FLIM-based detection of the endogenous metabolic cofactor NADH to identify microglia and characterize their activation status. To test whether microglial activation would also confer a unique NADH lifetime signature, murine primary microglial cultures and adult mice were treated with lipopolysaccharide (LPS).

Results: We found that LPS-induced microglia activation correlates with detected changes in NADH lifetime and its free-bound ratio. This indicates that NADH lifetime can be used to monitor microglia activation in a label-free fashion. Moreover, we found that there is an LPS dose-dependent change associated with reactive microglia lifetime fluxes, which is also replicated over time after LPS treatment.

Conclusion: We have demonstrated a label-free way of monitoring microglia activation via quantifying lifetime of endogenous metabolic coenzyme NADH. Upon LPS-induced activation, there is a significant change in the fluorescence lifetime following activation. Together, these results indicate that NADH FLIM approaches can be used as a method to characterize microglia activation state, both in vitro and ex vivo.

Significance: Amyloid-beta (A-β) plaques are pathological protein deposits formed in the brain of Alzheimer’s disease (AD) patients upon disease progression. Further research is needed to elucidate the complex underlying mechanisms involved in their formation using label-free, tissue preserving, and volumetric techniques.

Aim: The aim is to achieve a one-to-one correlation of optical coherence tomography (OCT) data to histological micrographs of brain tissue using 1060-nm swept source OCT.

Approach: A-β plaques were investigated in ex-vivo AD brain tissue using OCT with the capability of switching between two magnifications. For the exact correlation to histology, a 3D-printed tool was designed to generate samples with parallel flat surfaces. Large field-of-view (FoV) and sequentially high-resolution volumes at different locations were acquired. The large FoV served to align the OCT to histology images; the high-resolution images were used to visualize fine details.

Results: The instrument and the presented method enabled an accurate correlation of histological micrographs with OCT data. A-β plaques were identified as hyperscattering features in both FoV OCT modalities. The plaques identified in volumetric OCT data were in good agreement with immunohistochemically derived micrographs.

Conclusion: OCT combined with the 3D-printed tool is a promising approach for label-free, nondestructive, volumetric, and fast tissue analysis.

Significance: The cerebral metabolic rate of oxygen (CMRO₂) is an important indicator of brain function and pathology. Knowledge about its magnitude is also required for proper interpretation of the blood oxygenation level-dependent (BOLD) signal measured with functional MRI. Despite the need for estimating CMRO₂, no gold standard exists. Traditionally, the estimation of CMRO₂ has been pursued with somewhat indirect approaches combining several different types of measurements with mathematical modeling of the underlying physiological processes. The recent ability to measure the level of oxygen (pO₂) in cortex with two-photon resolution in in vivo conditions has provided a more direct way for estimating CMRO₂, but has so far only been used to estimate the average CMRO₂ close to cortical penetrating arterioles in rats.

Aim: The aim of this study was to propose a method to provide spatial maps of CMRO₂ based on two-photon pO₂ measurements.

Approach: The method has two key steps. First, the pO₂ maps are spatially smoothed to reduce the effects of noise in the measurements. Next, the Laplace operator (a double spatial derivative) in two spatial dimensions is applied on the smoothed pO₂ maps to obtain spatially resolved CMRO₂ estimates.

Result: The smoothing introduces a bias, and a balance must be found where the effects of the noise are sufficiently reduced without introducing too much bias. In this model-based study, we explored this balance using synthetic model-based data, that is, data where the spatial maps of CMRO₂ were preset and thus known. The corresponding pO₂ maps were found by solving the Poisson equation, which relates CMRO₂ and pO₂. MATLAB code for using the method is provided.

Conclusion: Through this model-based study, we propose a method for estimating CMRO₂ with high spatial resolution based on measurements of pO₂ in cerebral cortex.

Significance: Light-field microscopy (LFM) enables high signal-to-noise ratio (SNR) and light efficient volume imaging at fast frame rates. Voltage imaging with genetically encoded voltage indicators (GEVIs) stands to particularly benefit from LFM’s volumetric imaging capability due to high required sampling rates and limited probe brightness and functional sensitivity.

Aim: We demonstrate subcellular resolution GEVI light-field imaging in acute mouse brain slices resolving dendritic voltage signals in three spatial dimensions.

Approach: We imaged action potential-induced fluorescence transients in mouse brain slices sparsely expressing the GEVI VSFP-Butterfly 1.2 in wide-field microscopy (WFM) and LFM modes. We compared functional signal SNR and localization between different LFM reconstruction approaches and between LFM and WFM.

Results: LFM enabled three-dimensional (3-D) localization of action potential-induced fluorescence transients in neuronal somata and dendrites. Nonregularized deconvolution decreased SNR with increased iteration number compared to synthetic refocusing but increased axial and lateral signal localization. SNR was unaffected for LFM compared to WFM.

Conclusions: LFM enables 3-D localization of fluorescence transients, therefore eliminating the need for structures to lie in a single focal plane. These results demonstrate LFM’s potential for studying dendritic integration and action potential propagation in three spatial dimensions.

Significance: Deficits in sensorimotor function in persons with type II diabetes mellitus (PwDM) have traditionally been considered a result of peripheral nerve damage. Emerging evidence has suggested that factors outside of nerve damage due to type II diabetes mellitus, such as impaired hemodynamic function, contribute significantly to both sensory and motor deficits in PwDM.

Aim: The focus of the current study was to evaluate functional cortical hemodynamic activity during sensory and motor tasks in PwDM.

Approach: Functional near-infrared spectroscopy was used to monitor oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) across the cortex during sensory and motor tasks involving the hands.

Results: Decline in HbO across sensory and motor regions of interest was found in PwDM with simultaneous deficits in manual motor tasks, providing the first evidence of functional cortical hemodynamic activity deficits relating to motor dysfunction in PwDM. Similar deficits were neither specifically noted in HbR nor during evaluation of sensory function. Health state indices, such as A_1c, blood pressure, body mass index, and cholesterol, were found to clarify group effects.

Conclusions: Further work is needed to clarify potential sex-based differences in PwDM during motor tasks as well as the root of reduced cortical HbO indices but unchanged HbR indices in PwDM.

Significance: Functional near-infrared spectroscopy (fNIRS) uses surface-placed light sources and detectors to record underlying changes in the brain due to fluctuations in hemoglobin levels and oxygenation. Since these measurements are recorded from the surface of the scalp, the mapping from underlying regions-of-interest (ROIs) in the brain space to the fNIRS channel space measurements depends on the registration of the sensors, the anatomy of the head/brain, and the sensitivity of these diffuse measurements through the tissue. However, small displacements in the probe position can change the distribution of recorded brain activity across the fNIRS measurements.

Aim: We propose an approach using either individual or atlas-based brain-space anatomical information to define ROI-based statistical hypotheses to test the null involvement of specific regions, which allows us to test the analogous ROI across subjects while adjusting for fNIRS probe placement and sensitivity differences due to head size variations without a localizer task.

Approach: We use the optical forward model to project the underlying brain-space ROI into a tapered contrast vector, which defines the relative weighting of the fNIRS channels contributing to the ROI and allows us to test the null hypothesis of no brain activity in this region during a functional task. We demonstrate this method through simulation and compare the sensitivity-specificity of this approach to other conventional methods.

Results: We examine the performance of this method in the scenario where head size and probe registration are both an accurately known parameters and where this is subject to unknown experimental errors. This method is compared with the performance of the conventional method using 364 different simulation parameter combinations.

Conclusion: The proposed method is always recommended in ROI-based analysis, since it significantly improves the analysis performance without a localizer task, wherever the fNIRS probe registration is known or unknown.

Significance: Isolating task-evoked brain signals from background physiological noise (e.g., cardiac, respiratory, and blood pressure fluctuations) poses a major challenge for the analysis of functional near-infrared spectroscopy (fNIRS) data.

Aim: The performance of several analytic methods to separate background physiological noise from brain activity including spatial and temporal filtering, regression, component analysis, and the use of short-separation (SS) measurements were quantitatively compared.

Approach: Using experimentally recorded background signals (breath-hold task), receiver operating characteristics simulations were performed by adding various levels of additive synthetic “brain” responses in order to examine the sensitivity and specificity of several previously proposed analytic approaches.

Results: We found that the use of SS fNIRS channels as regressors of no-interest within a linear regression model was the best performing approach examined. Furthermore, we found that the addition of all available SS data, including all recorded channels and both hemoglobin species, improved the method performance despite the additional degrees-of-freedom of the models. When SS data were not available, we found that principal component filtering using a separate baseline scan was the best alternative.

Conclusions: The use of multiple SS measurements as regressors of no interest implemented in a robust, iteratively prewhitened, general linear model has the best performance of the tested existing methods.

Significance: Cerebral blood flow is an important biomarker of brain health and function as it regulates the delivery of oxygen and substrates to tissue and the removal of metabolic waste products. Moreover, blood flow changes in specific areas of the brain are correlated with neuronal activity in those areas. Diffuse correlation spectroscopy (DCS) is a promising noninvasive optical technique for monitoring cerebral blood flow and for measuring cortex functional activation tasks. However, the current state-of-the-art DCS adoption is hindered by a trade-off between sensitivity to the cortex and signal-to-noise ratio (SNR).

Aim: We aim to develop a scalable method that increases the sensitivity of DCS instruments.

Approach: We report on a multispeckle DCS (mDCS) approach that is based on a 1024-pixel single-photon avalanche diode (SPAD) camera. Our approach is scalable to >100,000 independent speckle measurements since large-pixel-count SPAD cameras are becoming available, owing to the investments in LiDAR technology for automotive and augmented reality applications.

Results: We demonstrated a 32-fold increase in SNR with respect to traditional single-speckle DCS.

Conclusion: A mDCS system that is based on a SPAD camera serves as a scalable method toward high-sensitivity DCS measurements, thus enabling both high sensitivity to the cortex and high SNR.

Significance: The reliability of functional near-infrared spectroscopy (fNIRS) measurements is reduced by systemic physiology. Short-channel regression algorithms aim at removing systemic “noise” by subtracting the signal measured at a short source–detector separation (mainly scalp hemodynamics) from the one of a long separation (brain and scalp hemodynamics). In literature, incongruent approaches on the selection of the optimal regressor signal are reported based on different assumptions on scalp hemodynamics properties.

Aim: We investigated the spatial and temporal distribution of scalp hemodynamics over the sensorimotor cortex and evaluated its influence on the effectiveness of short-channel regressions.

Approach: We performed hand-grasping and resting-state experiments with five subjects, measuring with 16 optodes over sensorimotor areas, including eight 8-mm channels. We performed detailed correlation analyses of scalp hemodynamics and evaluated 180 hand-grasping and 270 simulated (overlaid on resting-state measurements) trials. Five short-channel regressor combinations were implemented with general linear models. Three were chosen according to literature, and two were proposed based on additional physiological assumptions [considering multiple short channels and their Mayer wave (MW) oscillations].

Results: We found heterogeneous hemodynamics in the scalp, coming on top of a global close-to-homogeneous behavior (correlation 0.69 to 0.92). The results further demonstrate that short-channel regression always improves brain activity estimates but that better results are obtained when heterogeneity is assumed. In particular, we highlight that short-channel regression is more effective when combining multiple scalp regressors and when MWs are additionally included.

Conclusion: We shed light on the selection of optimal regressor signals for improving the removal of systemic physiological artifacts in fNIRS. We conclude that short-channel regression is most effective when assuming heterogeneous hemodynamics, in particular when combining spatial- and frequency-specific information. A better understanding of scalp hemodynamics and more effective short-channel regression will promote more accurate assessments of functional brain activity in clinical and research settings.