Neurophotonics

Pulsed infrared neural stimulation (INS, 1875nm the peak of energy absorption by water) is a non-viral method developed to activate single submillimeter sites in the brain. When used in ultrahigh-field fMRI, it reveals functionally specific brain-wide columnar networks comprising synaptically activated nodes. INS is non-damaging and effective for use in the human cortex and is useful for neural and behavioral neuromodulation in primates. To investigate how physiological state influences its cellular effects, we performed in vivo two-photon calcium imaging with GCaMP6s in mice and tracked identified cortical neurons in awake vs anesthetized states. Across the tested radiant exposures, INS-evoked responses differed markedly between states: under anesthesia, stimulation produced predominantly positive-going calcium responses, whereas during wakefulness the same identified neurons exhibited negative-going responses. Pharmacological manipulation of this baseline level by GABAergic signaling shifted response polarity in opposite directions: picrotoxin under anesthesia produced awake-like negative responses, whereas muscimol during wakefulness produced anesthetized-like positive responses. Trial-by-trial analyses further showed that the relationship between pre-stimulus baseline level and INS-evoked response depended on physiological state. Because INS relies on transient tissue heating, we also developed an in situ EGFP-based calibration approach to estimate temperature-related fluorescence changes. These fluoro-thermal contributions were modest at lower radiant exposures and became increasingly important at higher exposures, particularly near the fiber pathway. The low-intensity results are consistent with, but do not establish, a state-dependent feed-forward inhibitory framework. Together, these findings show that the neuronal response to focal INS is shaped by ongoing brain state and provide a practical framework for separating state-dependent calcium responses from temperature-related fluorescence effects, making INS a potentially versatile tool for neuroscience and clinical applications.

Significance: Wearable optical sensors could make continuous cerebral hemodynamic monitoring practical in daily life. Because any surface head sensor also samples extracerebral tissue, demonstrating cerebral relevance requires a reference that separates deep from superficial hemodynamics. Aim: We evaluated whether the Temple Brain Flow Index (Temple-BF), derived from a temple-worn photoplethysmographic wearable, covaried more strongly with the deeper (brain-assigned) than the superficial (scalp-assigned) hemodynamics recovered from time-domain near-infrared spectroscopy (TD-NIRS) during controlled postural challenges. Approach: Sixty sessions from 44 healthy young adult men were analyzed across three physiological challenges: 30{degrees} head-down tilt, stand-to-squat, and stand-to-supine transitions. Optical density and mean time of flight from a three-module TD-NIRS system were inverted with a Monte Carlo-derived two-layer model to obtain scalp- and brain-layer hemoglobin time series. Temple-BF was compared with these model-derived signals using lag-adjusted and zero-lag correlations, paired brain-versus-scalp comparisons, heart rate and short-separation-HbO adjusted partial correlations. Results: Median lag-adjusted correlations between Temple-BF and brain-layer {Delta}HbO traces were 0.912, 0.843, and 0.839 for head-down tilt, stand-to-squat, and stand-to-supine transitions, respectively; corresponding scalp-layer medians were 0.494, 0.700, and 0.767. Paired brain-minus-scalp differences were significant for head-down tilt (median 0.333, p < 0.001) and stand-to-squat (0.110, p < 0.001) but not for stand-to-supine (0.036, p = 0.082) transitions. Zero-lag brain-layer medians were 0.826, 0.701, and 0.796, and the association persisted after adjustment for heart rate (partial r = 0.832, 0.850, 0.654) and for short-separation superficial HbO (0.649, 0.570, 0.438). Transition-window correlations had medians of 0.878, 0.861, and 0.876, with directionally concordant transition responses in 59 of 60 sessions. Conclusions: Temple-BF tracked model-derived brain-layer TD-NIRS {Delta}HbO across all three postural challenges, with larger median correlations against the brain-layer than the scalp compartment in all three protocols, and transition responses in the same direction for almost all sessions. These results support Temple-BF as a relative marker of cerebral hemodynamic change during postural perturbations. Establishing cerebral specificity at the temple, and excluding residual systemic and superficial contributions, will require flow-sensitive references and fuller systemic monitoring.

Sleep disorders and wakefulness constitute a pronounced and pervasive health risk that contributes to numerous cerebral pathologies such as stroke, depression, and neurodegenerative disorders. The hippocampus (HC) plays vital roles in learning and memory and is especially susceptible to the pathological insults imposed by sleep deprivation (SD). While SD disrupts neuronal network signaling and triggers inflammatory processes, the impact of SD on metabolism within the HC presently remains poorly understood. In this study, we assessed the progressive and cumulative effects of partial SD in the live mouse HC CA1 region using two-photon microscopy. Using a custom-designed implantable cannula enabling direct HC visualization and administration of dyes and pharmacological agents directly to HC tissue, we longitudinally monitored spontaneous neuronal activity and partial pressure of oxygen (pO2) within HC CA1 tissue before and during a 7-day period of partial SD and after a 7- day period of recovery. Our results revealed a progressive decline in spontaneous neural activity, alongside sustained elevation in tissue pO2; during the 7-day partial SD period. Notably, after 7 days of recovery, neuronal activity did not return to baseline, and tissue oxygenation continued to increase. Our findings emphasize chronic SD's cumulative and enduring impairments to neuronal function and metabolism in the HC and reveal uncoupling between metabolic and functional recovery that outlasts the sleep restriction period.

Two-photon calcium imaging enables measurements of neural activity from individual neurons and their subcellular processes in awake animals. Axial brain motion can change measured fluorescence independently of neural activity and move small structures out of the imaging plane, confounding two-photon calcium measurements in behaving animals. We developed two complementary post-acquisition methods, selected according to whether the imaged structure remains detectable across the encountered depth range. When it does, z-stack correction estimates imaging depth from a separately acquired reference z-stack and uses an axial fluorescence profile specific to each neural structure to rescale fluorescence to a common reference depth. When a structure can leave a single imaging plane, volume-based z-registration reconstructs a common-depth movie from repeated acquisitions of closely spaced planes. In awake mice, both methods tracked experimentally imposed axial displacements within the sampled range, with depth-estimation root mean squared errors (RMSEs) below 1 m for z-stack correction and 0.69-1.03 m for volume-based z-registration. Correction changed fluorescence substantially for a subset of somata, with larger effects in axonal boutons. Both methods are implemented in suite2p-in-depth, a Python package that integrates with Suite2p and provides diagnostics for depth estimation, correction quality and data reliability. Together, these methods enable axial-motion artifacts to be assessed and corrected within established Suite2p workflows.

This study presents a systematic investigation of the brain's own microwave emissions in the 0.85-5.0 GHz range, aiming to validate microwave encephalography (MWEG) as a novel tool for cognitive state assessment. Early experiments (2016-2019) using comparisons with background noise, a control phantom, and different antenna types confirmed the endogenous origin of the recorded signals. In a 2021 experiment (118 measurements on one subject, right and left occipital areas), we observed a significant functional hemispheric asymmetry: the number of "substantial spikes" was significantly higher in darkness for the right hemisphere (p<0.001) and higher in light for the left hemisphere (p<0.001). A 2025 group study (three subjects) confirmed the asymmetry (p<0.05 for right, p<0.01 for left). We describe the signal processing pipeline, including spike detection and statistical analysis. Two complementary mathematical models are presented: an energy-based model linking optical input to microwave emission via neural activity modes, and an information-based model interpreting spectral changes in terms of structural pattern overlap with memory engrams. An estimation of the physical dimensions of possible brain resonators (2-22 mm) is provided. The results are discussed in the context of hemispheric specialization and the information commutation theory. This work opens new perspectives for developing low cost, contactless brain monitoring systems.

Background. Hematoporphyrin derivative (HpD, Hiporfin) is used for photodynamic therapy (PDT) of solid tumors but had never been evaluated for fluorescence guided resection (FGR) in glioma. We assessed Hiporfin fluorescence accuracy against histopathology in recurrent glioblastoma (rGBM) and the feasibility of adding cavity PDT to FGR. Methods. In this prospective single arm series, adults with rGBM received a single preoperative intravenous Hiporfin dose of 5 mg/kg before FGR under blue light excitation and 630 nm cavity PDT. Intraoperative fluorescence assessment was the index test and histopathology the reference standard. Specimen level diagnostic accuracy was pooled with bivariate random-effects modeling. Results. Of 63 specimens, 35 were true positive, 7 false positive, 8 false negative and 13 true negative. Pooled sensitivity was 0.751 (95% confidence interval 0.600 to 0.858) and specificity 0.606 (0.407 to 0.775); the crude positive predictive value was 0.833 (0.694 to 0.917) and the negative predictive value 0.619 (0.409 to 0.792). All seven false positive specimens were peritumoral tissue and the eight false negatives were non fluorescent tumor. FGR combined with cavity PDT was completed in all six patients without new neurological deficits. Conclusions. Hiporfin fluorescence identified rGBM with moderate accuracy: fluorescent regions were likely tumor, while non fluorescent tissue often still contained tumor. The main source of error was peritumoral tissue of the treated cavity, and not the drug or the optics. Hiporfin is a new fluorescence agent for glioma. One drug provides both fluorescence guidance during resection and immediate cavity PDT.

Objective. Temperature readings are routinely stratified by race and ethnicity, though significant group differences may reflect physiology, instrument noise, or categorization rather than biology. This study tests whether these categories partition facial infrared thermography measurements beyond individual variation and baseline device noise. Approach. A secondary analysis of thermography data (n = 951 adults) compares inner-canthus maximum (TCEmax) and full-face maximum (Tmax) temperatures across five administrative categories via one-way analysis of variance (ANOVA), mixed-effects modeling, Bland-Altman analysis against oral reference, and Monte Carlo sensitivity analysis. Main results. ANOVA returns significant group differences (p < 0.001; eta-squared = 0.04 for TCEmax, 0.03 for Tmax), but the total spread (0.2 to 0.3 degrees Celsius) is comparable to device accuracy and within-subject variability. Individual variation accounts for 95% of TCEmax variance, and adding simulated Gaussian noise to participant-level temperatures (sigma = 0.10 to 0.30 degrees Celsius) preserves the complete group-mean rank order in as few as 37.5% of iterations. Significance. Testing whether a group difference survives perturbation at the scale of instrument accuracy offers a check against treating significance alone as evidence of physiology. Here, observed group differences are small relative to measurement variability, and their physiological interpretation remains uncertain, with implications for clinical tools that treat administrative categories as biologically meaningful.

Background: Understanding fetal brain responses to hypoxia-ischemia is of growing interest, as it remains unclear to what extent these responses differ from those of newborns and whether developmental adaptations during gestation contribute to such differences. Materials and methods: Using a combination of broadband near-infrared spectroscopy (bNIRS) and diffuse correlation spectroscopy (DCS), we measured brain microvascular oxygen saturation (StO2), total hemoglobin concentration (THC), relative cerebral blood flow (rCBF), and the oxidation state of cytochrome c oxidase (oxCCO) during an acute ischemic challenge in the brains of five rabbit fetuses in utero. Simultaneous measurements were acquired from four control fetuses located in the contralateral uterine horn. Results: During the hypoxia-ischemia phase, we observed a rapid reduction of CBF (47% +/- 29%) and StO2, (from 64.7% +/- 1.5% at baseline to 40.6% +/- 2.0%) together with an increase of oxCCO (3.7 uM +/- 0.5 uM). Conclusion: The simultaneous increase in oxCCO and decrease in rCBF and StO2 during hypoxia-ischemia reveals a cerebral response pattern that differs from that commonly reported in the newborn brain. These findings support the hypothesis that unique developmental adaptations influence fetal cerebral metabolism during hypoxic-ischemic stress.

Objective: To develop and validate a dual-probe Diffuse Correlation Spectroscopy (DCS) system for non-invasive and simultaneous, monitoring of cerebral blood flow (CBF) in the bilateral Middle Cerebral Artery (MCA) territories, and expanding the utility of conventional DCS limited to cortical-volume-based CBF measurements to vessel-specific cerebral perfusion monitoring. Methods: A dual-probe DCS system was designed for non-invasive monitoring of MCA-specific perfusion. Probe placement and protocol optimization study has been performed using anatomical landmarks, motor and speech activation tasks in healthy volunteers. System stability and repeatability were further evaluated in a pilot cohort of 30 healthy (age, 25{+/-}7 years) participants using optimized probe position and protocol. A bilateral MCA ischemic Lacunar Infract stroke case report also validated the feasibility of the system in clinical settings. Results: Measurements demonstrated superior sensitivity towards MCA-territory perfusion at targeted probe locations compared to off-MCA positions. In pilot cohort, significant increase of 30.34 {+/-} 21.56% and 36.48 {+/-} 21.22% in rCBF corresponding to hand squeeze and speech task respectively showed reproducible physiological responsiveness of the system (p<0.001). Measurement done on a patient with bilateral MCA ischemic Lacunar Infract stroke showed a significant change of 30% during speech for both the MCAs but no significant change is observed for hand squeeze tasks. Conclusion: The custom built dual-probe DCS system enables non-invasive, operator-independent, targeted and continuous monitoring of rCBF within bilateral MCA territories. Significance: This approach enables the potential use of DCS system for bilateral and vessel-specific monitoring of cerebral perfusion in the MCA territories.

Extracellular L-lactate reports cellular metabolism, but resolving its dynamics alongside intracellular metabolism and neuronal activity remains challenging. Here we develop eLACCO3 and R-eLACCO3, green and red cell-surface lactate biosensors with Ca2+-independent responses and faster response and recovery kinetics in cultured cells. Selected variants provide larger fluorescence responses than their predecessors in brain cells, slices, and living mice and improve detection of glucose-evoked extracellular lactate oscillations. Combining R-eLACCO3 with GCaMP6f enabled imaging of extracellular L-lactate simultaneously with odor-evoked activity in anesthetized mice and cortical activity in awake mice. These biosensors enable multiplexed measurements of extracellular lactate dynamics in relation to intracellular metabolism and neuronal activity.

Volumetric imaging is increasingly important in fields such as neuroscience, where quantifying structure and mapping features are inherently three-dimensional problems. Block-face serial two-photon tomography (STPT) has emerged as a powerful approach for high-resolution, whole-organ volumetric imaging. STPT avoids complex sample preparation and balances image quality, speed, and scalability. However, STPT remains niche, in part because of the absence of flexible, general-purpose control software. Here we present BakingTray, an open-source software platform for STPT that extends ScanImage. BakingTrays modular framework accommodates diverse hardware configurations and allows users to build systems customised to their needs. Twelve such systems, which we call BrainSaws, have been constructed worldwide since 2016, with more under construction, and have so far contributed to 35 research papers. The three systems at the Sainsbury Wellcome Centre alone have acquired over 7,000 samples in a busy multi-user facility. We demonstrate the platform across its core neuroscience applications: electrode track localisation, brain-wide cell counting, and bulk projection mapping. Beyond these, we map the cell-type-specific synaptic output of inhibitory neurons in the ventral lateral geniculate nucleus and, with whole-mount staining, amyloid plaques brain-wide in a mouse model of Alzheimers disease. BakingTray is a mature platform for groups or facilities needing a customised volumetric imaging solution, whether built new or converted cheaply from an existing two-photon microscope.

Cardiac amyloidosis is caused by deposits of misfolded proteins in the heart and can lead to heart failure. Histological confirmation typically involves staining tissue sections with Congo red and examining them under polarized light for apple-green birefringence; however, achieving an interpretable, label-free, and observer-independent assessment remains challenging. Here we show that Pearson kurtosis of channel intensities within the amide I window provides an interpretable, fitting-free contrast for cardiac amyloid in unstained human cardiac tissue sections from ten participants imaged by ultrabroadband multiplex coherent anti-Stokes Raman scattering (CARS). In a discovery participant, high-kurtosis regions corresponded with Congo red-positive tissue in two CARS-histology pairs of adjacent sections (descriptive spatial AUCs, 0.79 and 0.73). Across 15 fields from nine additional participants, field-level kurtosis values did not overlap between severe-deposition and Congo red-negative tissue fields. Among the descriptors examined, kurtosis showed the largest standardized participant-level separation. Exploratory multivariate curve resolution yielded a deposit-associated component with aromatic-residue features shared with reagent transthyretin. In one field from the discovery participant, the second harmonic generation (SHG) signal, acquired simultaneously with CARS, showed a broadly inverse spatial pattern relative to the amide I kurtosis map, revealing distinct tissue-architectural contrast. Together, these findings support a potential label-free approach to detecting cardiac amyloid deposits that combines amide I kurtosis derived from broadband CARS with SHG-derived architectural contrast.

Significance: Fluorescence imaging remains largely qualitative and device-specific, limiting reproducibility and intersystem comparisons. SI-traceable radiometric characterization requires calibrated sources suitable for transferring known radiance to imaging systems. Aim: Establish and evaluate a compact, calibrated solid-state radiometric emitter target (RET) for SI-traceable radiance transfer, and assess methods for evaluating radiance invariance, imager responsivity, and extension of radiance transfer to digitally defined regions of interest (ROIs). Approach: The radiance invariance of an LED-based RET was evaluated by measuring its radiance across varying source-to-aperture distances and collection apertures. A previously described radiance-transfer formalism based on calibrated source radiance and collection geometry was implemented to determine imager responsivity (R{lambda}), which was evaluated across varying working distances and lens apertures. Grubbs and MAD outlier tests and one-way ANOVA were used to assess radiance and responsivity invariance. Finally, responsivity obtained using digitally defined ROIs was compared with matched physical apertures to assess ROI-based radiance transfer. Results: The measured RET radiance remained invariant across the tested source-to-aperture distances and collection apertures, with no significant differences observed across distance (p = 0.88) or aperture (p = 0.15). Imager responsivity remained stable across working distances for both tested lens configurations (p = 0.48 and p > 0.99). Responsivity was also invariant across lens apertures, except for deviations at f/11 that were consistent with practical aperture tolerances. Digitally defined ROIs reproduced responsivity values obtained using matched physical apertures, demonstrating that the radiance-transfer approach can be extended to image-defined regions. Conclusions: The presented methods provide an approach for evaluating compact LED-based sources for invariant-radiance emission and suitability for SI-traceable radiance transfer. The characterized RET supported stable imager responsivity across changes in imaging geometry and extension to digitally defined ROIs. These methods can be adapted to other LED-based sources, with further angular characterization and uncertainty analysis needed to establish broader applicability.

Electroencephalography (EEG) preprocessing determines signal quality and interpretation, particularly for transcranial magnetic stimulation combined with EEG (TMS-EEG), where recordings are affected by large and complex stimulation-related artifacts. Several preprocessing approaches have been developed, but substantial variability remains in how pipelines are implemented, documented, and evaluated across recordings, limiting reproducibility and comparability across studies. We developed NESTApp, a MATLAB-based graphical interface built on EEGLAB, to provide an accessible and reproducible framework for implementing and evaluating TMS-EEG preprocessing pipelines. Rather than prescribing a specific pipeline, NESTApp allows users to construct and consistently apply customisable workflows incorporating established EEGLAB and TMS-EEG processing tools, while automatically documenting processing decisions and parameters. Integrated quality-control procedures track data removal and flag recordings based on user-defined criteria, facilitating systematic evaluation across participants. The application also supports group-level visualisation and export of processed TMS-EEG measures for subsequent analyses. Applied to 29 recordings from 16 participants, NESTApp processed 27 and identified those requiring further inspection. By integrating pipeline implementation, documentation, quality control, and group-level evaluation within a single interface, NESTApp provides a transparent framework for TMS-EEG preprocessing that may improve reproducibility, facilitate consistent processing across cohorts, and lower technical barriers to the implementation of established preprocessing approaches.

Accurate hippocampal electric field (E-field) prediction is important for individualized electroconvulsive therapy (ECT) dosing and emerging deep-brain stimulation approaches such as temporal interference. Because hippocampal fields are far weaker than those beneath the stimulation electrodes, they are highly sensitive to tissue interfaces, conductivity contrasts, and numerical discretization, so numerical error can rival the physical uncertainties of anatomy and conductivity. We investigate this numerical component of hippocampal dosimetry using individualized head models from eleven ECT patients. Identical head40 segmentations, comprising 40 tissue compartments including the bilateral hippocampi, were simulated with three independent numerical methods: a charge-based boundary-element fast multipole method (BEM-FMM), a voxel-based hexahedral finite-element solver, and a conformal tetrahedral finite-element solver. For each, resolution was increased systematically and convergence assessed from the average hippocampal E-field magnitude. At the highest attainable resolutions, the three methods agreed closely, differing by 6%-7% in the left hippocampus and 9%-12% in the right. At default or coarse resolutions, however, they disagreed by 28.8% on average and up to 50.3% in the right hippocampus. Numerical convergence should therefore be established before differences are attributed to anatomical or conductivity uncertainty, and independent-solver agreement provides a practical basis for reliable hippocampal dosimetry.

Stereotaxic intracranial microinjection in mice is a critical step in neuroscience workflows, enabled by robust hardware design, precise operation, and neuroanatomical expertise. Manual injections are prone to error and stereotax-mountable commercial automated injectors are extremely expensive. Further, the knowledge needed for performing accurate intracranial injections and surgeries is heterogeneous and disparate. Here we demonstrate the design and characterization of the UD Neuroinjector software-hardware-knowledge architecture, which serves to both reduce the cost of performing precisely controlled stereotaxic microinjections and provide a web platform for planning accurate targeting of specific mouse brain regions. We designed the UD Neuroinjector using low-cost hardware and 3D-printed parts, with a total build-cost of $300 --- less than 0.1x the cost of a commercial injector. Arduino-based firmware enables programmable flow rates, automated injection and extraction, and manual joystick control. Capillary-fluid measurements show stable, highly linear displacement (R2 > 0.93) at commonly used injection rates. In a head-to-head comparison with a commercial injector, in vivo DAPI injections into the mouse thalamus showed comparable spread and DAPI+ cell counts. For effective experimental design of intracranial injections, the web-based components of our architecture provide AI-enabled assistance and atlas-guided navigation. We used a hybrid retrieval-augmented generation (RAG) approach to ground AI-assisted protocol guidance for mouse intracranial surgeries using a corpus of 3,738 papers. Using the Common Coordinate Framework version 3 (CCFv3), we designed an interactive tool for identifying target coordinates. Together, the UD Neuroinjector architecture integrates and enables efficient knowledge discovery, experimental design, planning, and implementation of mouse intracranial surgeries.

Mapping brain connections is paramount in neuroscience. Lacking has been a method that can systematically map mesoscale (<1mm) connections in the brain in vivo at brainwide scale. Mesoscale mapping is particularly important for NHPs in which information is represented in submillimeter clusters (e.g. cortical columns, striosomes, thalamic rods). Here, we present a method called INS-fMRI, which comprises optical stimulation of single sites in the brain using pulsed Infrared Neural Stimulation (INS), coupled with mapping of functionally connected sites in the brain using ultrahigh field fMRI. It is the only method available for mapping mesoscale connections rapidly (multiple networks mapped within single MRI sessions), systematically (allowing comparison of networks within single individuals), in vivo (no animal sacrifice needed), at whole brain scale, and without viral transfection. This method has broad applicability to a wide range of neuroscience questions. It can be used at any brain site, on different animal models, and on different MRI platforms. The ability to probe circuits repeatedly within single individuals also opens doors for studying changes in mesoscale circuits over time (e.g. for development, aging, disease studies). In addition, as this method circumvents the need for viral transfection, there is exciting potential for human clinical application.

Wearable light loggers are increasingly used to assess light exposure in everyday environments in studies of circadian physiology and sleep, yet their accuracy under diverse lighting conditions remains insufficiently understood. This study evaluated three commonly used wearable light loggers (ActLumus, Lido and OcuWEAR) by comparing measurements of photopic illuminance, melanopic equivalent daylight illuminance (m-EDI), and correlated colour temperature (CCT) against a reference spectroradiometer under controlled laboratory conditions and in the field. Measurements were conducted across fluorescent, incandescent, and multiple LED sources, as well as under dynamic daylight exposure. Device performance depended strongly on both light source characteristics and metric type. Illuminance exhibited lower variability, whereas m-EDI and CCT showed substantial device- and condition-specific biases, particularly under spectrally atypical illumination conditions. These differences were consistent with spectral mismatch effects arising from standard photometric calibration practices. Importantly, the impact of measurement bias varied by exposure context: under dim light conditions, small absolute deviations led to substantial misclassification relative to currently recommended thresholds, whereas brighter electric light and daylight conditions were more robust. These findings highlight that device- and context-dependent biases can influence the interpretation of light exposure in circadian and sleep research, underscoring the need for careful device selection and data interpretation.

Optical coherence tomography angiography (OCTA) has been extensively explored for the detection of pathological retinal changes arising in various ophthalmological diseases. Due to phase instability of conventional systems, most OCTA signal processing methods to date have relied on intensity-based averaging, despite the resulting lower contrast and dynamic range compared to coherent averaging approaches. In this work, we (1) present a novel computation pipeline that enables fully-coherent processing in any phase-stable or phase-unstable system, and (2) demonstrate the first angiography metric with integrated signal-to-noise ratio (SNR) correction and coherent spatiotemporal ensemble averaging effective in any OCT system. Our method does not rely on 2D en face projections or binarization to produce high-contrast en face views and it significantly enhances the contrast-to-noise ratio of computed OCTA volumes, particularly in regions with reduced SNR levels. Our OCTA volumes also have high cross-sectional quality, enabling the use of single-depth en face views and the localization of capillary paths in the axial dimension. We can now identify capillaries below the retinal pigment epithelium, near the lamina cribrosa in the optic cup, which was not previously possible due to low SNR. We also conducted an analysis of strategies for bias reduction in OCTA and developed the optimal method utilizing coherent spatiotemporal ensemble averaging. Because our method leverages coherent averaging across all dimensions, it provides flexibility in shaping the averaging kernel to target specific workflows. The value of this additional degree of freedom is illustrated in our vessel tracing investigations, in which the depth resolution was maximized by limiting coherent ensemble averaging to the two lateral dimensions even in presence of strong phase noise, enabling the identification of 3D features such as overlapping capillary paths.

Hypoxia impairs cognitive function, yet its effects on navigation and intrinsic brain activity remain poorly understood. This study investigated whether a continuous exposure to hypoxia (CH) or an intermittent exposure to hypoxia (IH) differentially influence navigation performance and resting-state electroencephalography (EEG) in healthy young adults. Seventy-two participants completed sham (FiO2 = .209) and hypoxia (FiO2 = .13) sessions during either a one hour of CH or IH intervention. Navigation was assessed using the Spatial Performance Assessment for Cognitive Evaluation (SPACE), while resting-state EEG was recorded before and after the intervention in a subset of participants (n = 40). EEG spectra were parameterised into periodic (alpha and beta power and central frequency) and aperiodic (exponent and offset) components. Aligned rank transform (ART) analyses of variance examined effects of hypoxia and intervention group, while linear regression determined whether reductions in peripheral oxygen saturation (SpO2) predicted changes in navigation or EEG. Hypoxia impaired multiple components of navigation, increasing path integration distance error and egocentric pointing angle error irrespective of intervention group, while mapping accuracy was preferentially impaired following IH and perspective taking performance following CH. Hypoxia also reduced alpha and beta power, beta central frequency, and aperiodic exponent, while aperiodic offset and alpha central frequency remained stable. The reduction in aperiodic exponent was primarily evident following IH, suggesting that the temporal pattern of oxygen delivery may influence specific neurophysiological responses. Contrary to our hypothesis, SpO2 reduction did not predict individual differences in navigation performance or EEG activity. These findings demonstrate that brief, moderate hypoxic exposure can disrupt allocentric and egocentric components of spatial navigation while selectively altering periodic and aperiodic features of intrinsic brain activity.