Neurophotonics

SignificanceHyperspectral imaging sensors have rapidly advanced, aiding in tumor diagnostics for in-vivo brain tumors. Linescan cameras effectively distinguish between pathological and healthy tissue, while snapshot cameras offer a potential alternative to reduce acquisition time. AimOur research compares linescan and snapshot hyperspectral cameras for in-vivo brain tissues and chromophores identification. ApproachWe compared a lines-can pushbroom camera and a snapshot camera using images from 10 patients with various pathologies. Objective comparisons were made using unnormalized and normalized data for healthy and pathological tissues. We utilized Interquartile Range (IQR) for the Spectral Angle Mapping (SAM), the Goodness-of-Fit Coefficient (GFC), and the Root Mean Square Error (RMSE) within the 659.95 to 951.42 nm range. Additionally, we assessed the ability of both cameras to capture tissue chromophores by analyzing absorbance from reflectance information. ResultsThe SAM metric indicates reduced dispersion and high similarity between cameras for pathological samples, with a 9.68% IQR for normalized data compared to 2.38% for unnormalized data. This pattern is consistent across GFC and RMSE metrics, regardless of tissue type. Moreover, both cameras could identify absorption peaks of certain chromophores. For instance, using the absorbance measurements of the linescan camera we obtained SAM values below 0.235 for four peaks, regardless of the tissue and type of data under inspection. These peaks are: one for cytochrome b in its oxidised form at{lambda} = 422 nm, two for HbO2 at{lambda} = 542 nm and{lambda} = 576 nm, and one for water at{lambda} = 976 nm. ConclusionThe spectral signatures of the cameras show more similarity with unnormalized data, likely due to snapshot sensor noise, resulting in noisier signatures post-normalization. Comparisons in this study suggest that snapshot cameras might be viable alternatives to linescan cameras for real-time brain tissues identification.

Functional Near-Infrared Spectroscopy (fNIRS) holds transformative potential for research and clinical applications in neuroscience due to its non-invasive nature and adaptability to real-world settings. However, despite its promise, fNIRS signal quality is sensitive to individual differences in biophysical factors such as hair and skin characteristics, which can significantly impact the absorption and scattering of near-infrared light. If not properly addressed, these factors risk biasing fNIRS research by disproportionately affecting signal quality across diverse populations. Our results quantify the impact of various hair properties, skin pigmentation as well as head size, sex and age on signal quality, providing quantitative guidance for future hardware advances and methodological standards to help overcome these critical barriers to inclusivity in fNIRS studies. We provide actionable guidelines for fNIRS researchers, including a suggested metadata table and recommendations for cap and optode configurations, hair management techniques, and strategies to optimize data collection across varied participants. This research paves the way for the development of more inclusive fNIRS technologies, fostering broader applicability and improved interpretability of neuroimaging data in diverse populations.

SignificanceGenetically encoded voltage indicators (GEVIs) are a valuable tool for studying neural circuits in vivo, but the relative merits and limitations of one-photon (1P) vs. two-photon (2P) voltage imaging are not well characterized. AimWe consider the optical and biophysical constraints particular to 1P and 2P voltage imaging and compare the imaging properties of commonly used GEVIs under 1P and 2P excitation. ApproachWe measure brightness and voltage sensitivity of voltage indicators from commonly used classes under 1P and 2P illumination. We also measure the decrease in fluorescence as a function of depth in mouse brain. We develop a simple model of the number of measurable cells as a function of reporter properties, imaging parameters, and desired signal-to-noise ratio (SNR). We then discuss how the performance of voltage imaging would be affected by sensor improvements and by recently introduced advanced imaging modalities. ResultsCompared to 1P excitation, 2P excitation requires [~]104-fold more illumination power per cell to produce similar photon count rates. For voltage imaging with JEDI-2P in mouse cortex with a target SNR of 10 (spike height:baseline shot noise), a measurement bandwidth of 1 kHz, a thermally limited laser power of 200 mW, and an imaging depth of > 300 m, 2P voltage imaging using an 80 MHz source can record from no more 12 cells simultaneously. ConclusionsDue to the stringent photon-count requirements of voltage imaging and the modest voltage sensitivity of existing reporters, 2P voltage imaging in vivo faces a stringent tradeoff between shot noise and tissue photodamage. 2P imaging of hundreds of neurons with high SNR at depth > 300 m will require either major improvements in 2P GEVIs or qualitatively new approaches to imaging.

SignificanceCerebral autoregulation (CA) reflects the dynamic coupling among cerebral blood flow (CBF), intracranial pressure (ICP), and arterial blood pressure (ABP); its failure contributes to secondary brain injury. Existing bedside methods rely on indirect or spatially limited CBF surrogates and cannot resolve microvascular flow dynamics across space, depth, and time. AimTo develop, optimize, and apply a scalable, noncontact time-resolved laser speckle contrast imaging (TR-LSCI) platform for depth-sensitive, high-speed, wide-field CBF imaging during controlled ICP perturbations. ApproachTR-LSCI synchronizes a 20-MHz pulsed laser with a time-gated, single-photon avalanche diode (SPAD) camera (512 x 512 pixels) to detect diffuse photons at varying path lengths, enabling depth-resolved microvascular CBF imaging. Benchtop and mobile TR-LSCI systems were applied in adult rats and a neonatal piglet with synchronized invasive ICP and ABP measurements. ResultsTR-LSCI captured spatially heterogeneous, pulsatile CBF dynamics at up to 52 Hz over large cortical fields of view, with heart rate estimates statistically equivalent to those from ICP and ABP. Multivariable analysis identified reproducible, phase-dependent CA transitions encompassing preserved autoregulation, ABP-driven compensation, and ICP-constrained CBF suppression; notably, CBF alone exhibited distinct phase signatures. ConclusionsTR-LSCI enables dynamic, physiology-informed neurovascular monitoring and supports future bedside CA assessment.

SignificanceCerebral vascular reactivity is critical parameters of brain homeostasis in health and disease, but the investigational value of brain oxymetry is diminished by anesthesia and mechanical fixation of the mouse scull. AimWe needed to reduce the physical restrictivity of hemodynamic spectroscopy to enable Alzheimers disease (AD) studies in freely-moving mice. ApproachWe combined spectroscopy, spectral analysis software and a magnetic, implantable device to measure vascular reactivity in unanesthetized, freely-moving mice. We measured cerebral blood volume fraction (CBVF) and oxygen saturation (SO2). ResultsWe validated that our system could detect delayed cerebrovascular recovery from hypoxia in an orthotopic xenograft glioma model under anesthetized condition and we also found increased CBVF and impaired vascular reactivity during hypercapnia in a freely-moving mouse model of AD compared to wild-type littermates. ConclusionsOur optomechanical approach to reproducibly getting light into and out of the brain enabled us to successfully measure CBVF and SO2 during hypercapnia in unanesthetized freely-moving mice. We present hardware and software enabling oximetric analysis of metabolic activity, which provides a safe and reliable method for rapid assessment of vascular reactivity in murine disease models as well as CBVF and SO2.

SignificanceTwo-photon microscopy is used routinely for in vivo imaging of neural and vascular structure and function in rodents with a high resolution. Image quality, however, often degrades in deeper portions of the cerebral cortex. Strategies to improve deep imaging are therefore needed. We introduce such a strategy using gates of high repetition rate ultrafast pulse trains to increase signal level. AimWe investigate how signal generation, signal-to-noise ratio (SNR), and signal-to-background ratio (SBR) improve with pulse gating while imaging in vivo mouse cerebral vasculature. ApproachAn electro-optic modulator is used with a high-power (6 W) 80 MHz repetition rate ytterbium fiber amplifier to create gates of pulses at a 1 MHz repetition rate. We first measure signal generation from a Texas Red solution in a cuvette to characterize the system with no gating and at a 50%, 25%, and 12.5% duty cycle. We then compare signal generation, SNR, and SBR when imaging Texas Red-labeled vasculature using these conditions. ResultsWe find up to a 6.73-fold increase in fluorescent signal from a cuvette when using a 12.5% duty cycle pulse gating excitation pattern as opposed to a constant 80 MHz pulse train. We verify similar increases for in vivo imaging to that observed in cuvette testing. For deep imaging we find pulse gating to result in a 2.95-fold increase in SNR and a 1.37-fold increase in SBR on average when imaging mouse cortical vasculature at depths ranging from 950 m to 1050 m. ConclusionsWe demonstrate that a pulse gating strategy can either be used to limit heating when imaging superficial brain regions or used to increase signal generation in deep regions. These findings should encourage others to adopt similar pulse gating excitation schemes for imaging neural structure through two-photon microscopy.

SignificanceLaser speckle contrast imaging (LSCI) is widely used to measure blood flow, but speckle fluctuations may also encode biologically meaningful dynamics beyond perfusion. Foundational studies in dynamic light scattering (DLS) and micro-optical coherence tomography (OCT) have also demonstrated that slow coherent signal fluctuations can arise from energy-dependent intracellular motion in in vitro and ex vivo systems. Building upon these advances, recent work has shown that LSCI has the potential to detect slow speckle dynamics (SSD) correlated with cellular dynamics in vivo. However, the biophysical mechanisms underlying SSD in intact brain tissues remain insufficiently validated. Establishing a mechanistic bridge from controlled ex vivo and in vitro conditions to in vivo brain measurements is critical for translating speckle-based imaging beyond perfusion measurements to enable label-free assessment of cellular and metabolic activity in disease models. AimThe objective of this study is to investigate the biophysical origin of the SSD in vivo and evaluate its sensitivity to intracellular metabolic activity in brain tissue. ApproachWe utilize an epi-illumination LSCI system to measure speckle contrast as a function of camera exposure time and extract characteristic decorrelation time constants. SSD was investigated in acute mouse brain slices, where blood flow is absent, to eliminate vascular confounds. Cellular metabolism was systematically modulated using 2-deoxyglucose and glucose. Complementary in vivo measurements were performed to reveal SSDs response to hyperoxia and normoxia after ischemic stroke. ResultsSSD signals persisted in acute brain slices in the absence of blood flow. Inhibition of glycolysis significantly reduced SSD, while restoration of metabolic substrates partially recovered the signal. In in vivo measurements, SSD increased during hyperoxia compared to normoxia after ischemic stroke, suggesting increased oxygen-supported cellular metabolic activity. ConclusionsThese results indicate that SSD is sensitive to energy-dependent cellular processes closely tied to metabolic activity. SSD represents a previously uncharacterized, label-free in vivo optical contrast that enables assessment of cellular metabolic activity as well as vascular dynamics. This work establishes a mechanistic foundation for using SSD as a general optical marker of cellular viability in in vivo measurements.

Measurement of human neural activity with optically pumped magnetometers (OPMs) is rapidly proliferating, with sensitivity approaching that of cryogenic sensors. Most neuroscience research with OPMs to date has investigated neural responses below 70 Hz, but higher frequencies are also of interest. However, sensitivity to higher frequencies may be limited by both the inherent operating bandwidth of the current generation of zero-field OPMs as well as by their generally lower amplitude. To assess the upper bounds of OPM sensitivity we used the stereotypical retinal response to flashes of light. Retinal responses to light flashes characteristically exhibit a neural response above 70 Hz called the oscillatory potential (OP) when recorded with electroretinography (ERG). Here we adopt the term retinal high frequency oscillation (rHFO) to include measurement of similar activity with OPMs. Our comparison of magnetoretinography (MRG) and ERG shows that rHFO can be measured up to 140 Hz using rubidium-based zero-field OPMs.

SignificanceThe exponential growth of research utilizing functional near-infrared spectroscopy (fNIRS) systems has led to the emergence of modular fNIRS systems composed of repeating optical source/detector modules. Compared to conventional fNIRS systems, modular fNIRS systems are more compact and flexible, making wearable and long-time monitoring possible. However, the large number of design parameters makes designing a modular probe a daunting task. AimWe aim to create a systematic software platform to facilitate the design, characterization, and comparison of modular fNIRS probes. ApproachOur algorithm automatically tessellates any region-of-interest using user-specified module design parameters and outputs performance metrics such as spatial channel distributions, average brain sensitivity, and sampling rate estimates of the resulting probe. Automated algorithms for spatial coverage, orientation, and routing of repeated modules are also developed. ResultsWe developed a software platform to help explore a wide range of modular probe features and quantify their performances. We compare full-head probes using three different module shapes and highlight the trade-offs resulting from various module settings. Additionally, we show that one can apply this workflow to improve existing modular probes without needing to re-design or re-manufacture them. ConclusionOur flexible modular probe design platform shows promise in optimizing existing modular probes and investigating future modular designs.

Continuous-wave functional near-infrared spectroscopy (fNIRS) neuroimaging provides an estimate of relative changes in oxygenated and de-oxygenated hemoglobin content, from which regional neural activity is inferred. The relation between both signals is governed by neurovascular coupling mechanisms. However, the magnitude of concentration changes and the contribution of noise sources to each chromophore is unique. Subsequently, it is not apparent if either chromophore signal practically provides greater information about the underlying neural state and relation to an experimental condition. To assess this question objectively, we applied a machine-learning approach to four datasets and evaluated which hemoglobin signal best differentiated between experimental conditions. To further ensure the objective nature of the analysis, the algorithm utilized all samples from the epoched data rather than pre-selected features. Regardless of experimental task, brain region, or stimulus, the oxygenated hemoglobin signal was better able to differentiate between conditions than the de-oxygenated signal. Incorporating both signals into the analysis provided no additional improvement over oxygenated hemoglobin alone. These results indicate that oxyhemoglobin is the most informative fNIRS signal in relation to experimental condition.

Wide-field imaging from brain slices stained with a voltage sensitive dye (VSD) and simultaneously loaded with a Ca2+ indicator allows investigating neuronal excitability and synaptic transmission at multi-cellular scale. So far, achieving this type of combined imaging has been limited by experimental constraints. We assessed the ability of the red-IR emitting VSD ElectroFluor630 (EF-630) to be combined with blue-excitable green-emitting Ca2+ indicators to record signals elicited by electrical stimulation in hippocampal slices. Transversal mouse hippocampal slices were stained with EF-630. Ca2+ indicators, either Fluo-4, Fluo-8, Cal520 or Calbryte520, were loaded using their AM-ester forms. Fluorescence, during stimulation of the CA3 region was imaged at 5 kHz from hippocampal areas of [~]750X250 {micro}m2 at 1 {micro}m pixel resolution. After assessing all Ca2+ indicators, we selected Calbryte520 for achieving >30 minutes stable recordings in combination with EF-630. Action potentials and related Ca2+ transients were detected in the CA3 stimulated area whereas synaptic signals were observed in the CA1 region. On these signals, we tested the pharmacological blockade of either action potentials or glutamatergic synaptic potentials. We report novel optical measurements of both electrical and Ca2+ transients in brain slices, providing unique information on neuronal excitability and network activity.

SignificanceAccurate sensor placement is vital for non-invasive brain imaging, particularly for functional near infrared spectroscopy (fNIRS) and diffuse optical tomography (DOT), which lack standardized layouts like EEG. Custom, manually prepared probe layouts on textile caps are often imprecise and labor-intensive. AimWe introduce a method for creating personalized, 3D-printed headgear, enabling accurate translation of 3D brain coordinates to 2D printable panels for custom fNIRS and EEG sensor layouts, reducing costs and manual labor. ApproachOur approach uses atlas-based or subject-specific head models and a spring-relaxation algorithm for flattening 3D coordinates onto 2D panels, using 10-5 EEG coordinates for reference. This process ensures geometrical fidelity, crucial for accurate probe placement. Probe geometries and holder types are customizable and printed directly on the cap, making the approach agnostic to instrument manufacturers and probe types. ResultsOur ninjaCap method offers 2.2{+/-}1.5 mm probe placement accuracy. Over the last five years, we have developed and validated this approach with over 50 cap models and 500 participants. A cloud-based ninjaCap generation pipeline along with detailed instructions is now available at openfnirs.org. ConclusionsThe ninjaCap marks a significant advancement in creating individualized neuroimaging caps, reducing costs and labor while improving probe placement accuracy, thereby reducing variability in research.

Simultaneous fiber photometry and optogenetics is a powerful emerging technique for precisely studying the interactions of neuronal brain networks. However, spectral overlap between photometry and optogenetic components has severely limited the application of an all-optical approach. Due to spectral overlap, light from optogenetic stimulation saturates the photosensor and occludes photometry fluorescence, which is especially problematic in physically smaller model organism brains like mice. Here, we demonstrate the Multi-Frequency Interpolation X- talk removal algorithm (MuFIX, or {micro}FIX) for recovering crosstalk-contaminated photometry responses recorded with lock-in amplification. {micro}FIX exploits multi-frequency lock-in amplification by modeling the remaining uncontaminated data to interpolate across crosstalk- affected segments (R2 [~] 1.0); we found that this approach accurately recovers the original photometry response after demodulation (Pearsons r [~] 1.0). When applied to crosstalk- contaminated data, {micro}FIX recovered a photometry response closely resembling the dynamics of non-crosstalk photometry recorded simultaneously. Upon further verification using simulated and empirical data, we demonstrated that {micro}FIX reproduces any signal that underwent simulated crosstalk contamination (r [~] 1.0). We believe adopting {micro}FIX will enable experimental designs using simultaneous fiber photometry and optogenetics that were previously not feasible due to crosstalk.

Fluorescent imaging enables visualization of the specific molecules of interest with high contrast, and the use of multiple fluorophores in a single tissue sample allows visualization of complex relationships between biological molecules, cell types, and anatomy. The utility of fluorescent imaging in human tissue has been limited by endogenous pigments that can block the light path or emit an autofluorescence, thereby interfering with the specific imaging of target molecules. Although photobleachers have been developed to quench endogenous pigments, the lack of customizability limits their utility for a broad range of applications. Here, we present a high luminous-intensity photobleacher that is based on rigorous simulations of illumination patterns using the laws of radiation, along with the framework to maximize bleaching efficiency. This open-source project is designed to help researchers customize and scale according to the tissue types and the research goals. The photobleacher is applicable to both thin tissue slices and large-volume cleared tissue samples to enable serial three-dimensional imaging of postmortem human brain using multiplexed antibody or oligonucleotide probes. SIGNIFICANCE STATEMENTPhotobleaching is an effective technique for quenching endogenous pigments, enabling multiplexed fluorescent imaging of pigment-rich tissues, such as postmortem human samples. While many photobleaching strategies have been proposed, there is no standard guidance on how to design and use a photobleacher. This study introduces a general strategy for designing an effective, scalable, and customizable photobleacher, and proposes a workflow for properly treating tissues with the photobleacher. The technique enables high-contrast molecular visualization in tissues of various sizes, including large volumetric cleared tissues. Our framework will accelerate the quantitative understanding of human molecular anatomy and is applicable to diverse biological fields, including medical diagnostics.

Real-world neuroimaging requires true portability and sensitivity to detect signals from neuronal activity. Conventional methods such as MRI, EEG, or PET are constrained by their size and instrumentation complexity. Near Infra-Red (NIR) based optical methods have the potential for sensitive detection with a smaller footprint. Despite rapid advances in NIR detection there is no known device that is implementable using off-the-shelf integrated microprocessors and possesses the above desired characteristics along with proven sensitivity to detect task evoked responses. Here, we present a Bluetooth Low Energy (BLE)-enabled, high-sensitivity wearable functional near-infrared spectroscopy (fNIRS) device designed for untethered cortical hemodynamic monitoring during naturalistic cognitive tasks. Our fully integrated optical sensing device merges optical data acquisition and wireless transmission into a compact, cable-free platform with a very small footprint. This enables continuous multi-channel recording without placing any constraint on the subjects movement. We validate our device for reliable detection of task-evoked oxy- and deoxy-hemoglobin dynamics in the forearm, primary motor cortex, primary visual cortex, and prefrontal cortex. Subsequently, we capture real-time forebrain activity during a screen-based learning and memory task, revealing robust goal-specific hemodynamic responses. We formulate a method to identify the instances of peak neuronal activity and follow the "task Evoked Instances of Differential Oxygen influx(tEIDO)" as the subject is engaged in a task. These results highlight the potential of our proposed fNIRS device as a mobile neuroimaging solution for next-generation brain-computer interfaces and real-world cognitive monitoring. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/690628v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@1f55855org.highwire.dtl.DTLVardef@7a67b8org.highwire.dtl.DTLVardef@2f6146org.highwire.dtl.DTLVardef@9b6e0c_HPS_FORMAT_FIGEXP M_FIG C_FIG

Optogenetics allows manipulation of neural circuits in vivo with high spatial and temporal precision. However, combining this precision with control over a significant portion of the brain is technologically challenging (especially in larger animal models). Here, we have developed, optimised, and tested in vivo, the Utah Optrode Array (UOA), an electrically addressable array of optical needles and interstitial sites illuminated by 181 {micro}LEDs and used to optogenetically stimulate the brain. The device is specifically designed for non-human primate studies. Thinning the combined {micro}LED and needle backplane of the device from 300 {micro}m to 230 {micro}m improved the efficiency of light delivery to tissue by 80%, allowing lower {micro}LED drive currents, which improved power management and thermal performance. The spatial selectivity of each site was also improved by integrating an optical interposer to reduce stray light emission. These improvements were achieved using an innovative fabrication method to create an anodically bonded glass/silicon substrate with through-silicon vias etched, forming an optical interposer. Optical modelling was used to demonstrate that the tip structure of the device had a major influence on the illumination pattern. The thermal performance was evaluated through a combination of modelling and experiment, in order to ensure that cortical tissue temperatures did not rise by more than 1{degrees}C. The device was tested in vivo in the visual cortex of macaque expressing ChR2-tdTomato in cortical neurons. It was shown that the strongest optogenetic response occurred in the region surrounding the needle tips, and that the extent of the optogenetic response matched the predicted illumination profile based on optical modelling - demonstrating the improved spatial selectivity resulting from the optical interposer approach. Furthermore, different needle illumination sites generated different patterns of low-frequency potential (LFP) activity.

The primary objective of this study was to determine whether light stimulation can induce a persistent reduction in neuronal activity within the central nervous system. Using repeated pulses of blue light (5 seconds, {lambda} = 430 - 495nm at 19 mW, [~]2.4 mW/mm{superscript 2}) on cortical slices, we observed a robust and sustained decrease in evoked firing activity, approximately 60% relative to baseline, in cortical neurons from both male and female mice. This inhibitory effect persisted for more than twenty minutes following stimulation. In human cortical slices, the effect was more variable. While some neurons showed reduced activity, others, particularly those from female subjects, exhibited increased firing in response to light. The long-lasting modulation of neuronal excitability appears to result from changes in both the passive (membrane resistance and resting potential) and active (voltage-dependent Na and K channels) properties of neurons. These findings suggest that light stimulation within the visible spectrum may serve as a tool to treat brain pathologies produced by neuronal hyperexcitability. We propose a roadmap for further research, including in vivo validation, exploration of stimulation parameters, and evaluation in pathological models. Importantly, the infrastructure and protocols developed for optogenetic studies provide immediate opportunities to test the therapeutic potential of light alone, without requiring exogenous opsin expression.

IntroductionInvestigating cerebral oxygen saturation dynamics in awake animal models remains technically challenging due to motion artifacts and anesthesia-related biases. Here, we introduce a novel high-resolution ultrasound-photoacoustic (PA) imaging approach enabling real-time, non-invasive monitoring of deep cerebrovascular oxygenation dynamics in awake mice with intact skulls. Materials and MethodsSwiss male and female mice (n = 5-6) were head-fixed using a customized holder adapted to the Neurotar Mobile HomeCage floating platform. High-resolution ultrasound combined with PA imaging (VevoLAZR-X, VisualSonics) was used to discriminate oxyhemoglobin, deoxyhemoglobin, and total hemoglobin in multiple brain regions. Cerebrovascular responses were assessed under three paradigms: (i) baseline awake state vs. 2% isoflurane anesthesia, and (ii) right whisker stimulation to probe sensory-driven hemodynamics. ResultsPA imaging successfully resolved deep-brain oxygenation in awake, intact-skull mice. Under isoflurane anesthesia, we observed a rapid and transient increase in cerebrovascular sO{square} (p < 0.01). During whisker stimulation, we detected robust, region-specific increases in total hemoglobin, reflecting localized neurovascular coupling in awake mice. ConclusionsThis study establishes high-resolution PA imaging as a powerful, non-invasive tool to monitor cerebrovascular oxygenation dynamics in awake mice. By integrating baseline, anesthetic, and sensory paradigms, we demonstrate its potential to dissect neurovascular physiology without the confounding effects of anesthesia. These findings provide new opportunities for preclinical neuroscience research and translational applications investigating cerebral oxygen metabolism.

The recent development of optogenetic tools, to manipulate neuronal activity using light, provides opportunities for novel brain-machine interface (BMI) control systems for treating neurological conditions. An issue of critical importance, therefore, is how well light penetrates through brain tissue. We took two different approaches to estimate light penetration through rodent brain tissue. The first employed so-called "nucleated patches" from cells expressing the light-activated membrane channel, channelrhodopsin (ChR2). By recording light-activated currents, we used these nucleated patches as extremely sensitive, microscopic, biological light-meters, to measure light penetration through 300-700{micro}m thick slices of rodent neocortical tissue. The nucleated patch method indicates that the effective illumination drops off with increasing tissue thickness, corresponding to a space constant of 317{micro}m (95% confidence interval between 248-441{micro}m). We compared this with measurements taken from directly visualizing the illumination of brain tissue, orthogonal to the direction of the light. This yielded a contour map of reduced illumination with distance, which along the direction of light delivery, had a space constant,{tau} 453{micro}m. This yields a lower extinction coefficient, {micro}e (the reciprocal of{tau} , [~]3mm-1) than previous estimates, implying better light penetration from LED sources than these earlier studies suggest.

Functional near-infrared spectroscopy (fNIRS) is a portable, motion-tolerant neuroimaging method particularly well suited for developmental and naturalistic research. To evaluate the utility of fNIRS for studying individual differences and longitudinal changes, we measured activation and functional connectivity during a relational reasoning task in young adults (N = 73). We sought to (1) establish whether fNIRS captures frontoparietal activation patterns consistent with prior fMRI studies using similar paradigms, (2) assess the effect of the amount of data (number of task blocks) on signal strength and precision, (3) assess the paradigms measurement properties in the form of intra- and interindividual stability of activation and functional connectivity within and across testing sessions, and (4) examine whether grouping channels into anatomical regions of interest (ROIs) conferred benefits to the above. We observed robust task-evoked activation across lateral prefrontal and parietal cortices, with effect sizes on par with prior fMRI studies. Generally, we observed diminishing returns in effect size and measurement precision beyond [~]7 minutes. Internal consistency and test-retest reliability varied across metrics; while they were very low for a specific task contrast, they were extremely high for functional connectivity, confirming the robustness of channel- and ROI-level connectivity as a stable marker of functional architecture. Exploratory analyses supported prior observations of lower signal quality in participants with darker skin tones and hair, underscoring the need for inclusive methodological strategies. Together, these findings highlight key design considerations for optimizing longitudinal and individual-differences research on higher-level cognition, particularly in diverse and developmentally variable populations. HighlightsO_LIWe measured within- and between-session reliability of fNIRS metrics C_LIO_LICollecting more data yielded diminishing returns in effect size and precision C_LIO_LIThere were tradeoffs to aggregating channel data into regions of interest C_LIO_LIGeneral task activation was more reliable than a specific task contrast C_LIO_LIFunctional connectivity showed extremely high test-retest reliability C_LI