SignificanceAlthough multidistance functional near-infrared spectroscopy (fNIRS) features higher spatial resolution and depth specificity compared with sparse fNIRS arrays, no open-access multidistance fNIRS dataset is available for motor and motion-artifact induction tasks.AimIn this data descriptor, we introduce an open-access, multidistance fNIRS dataset to facilitate algorithm development and validation.ApproachThe dataset was collected from 12 healthy young adults using a multidistance probe placed over the bilateral motor cortex. The experimental protocol included resting state task, ball-squeezing task, and motion-artifact induction task. Signal quality and motion artifact were quantitatively assessed using signal-to-noise ratio (SNR), motion artifact ratio (MAR), channel pruning statistics, and coefficient of variation (c.v.) across shorter (19 mm) and longer (32.9 mm) channels. The motion-artifact induction task was characterized using percent signal change, HbO/HbR concentration changes, and accelerometer data across six motion types.ResultsBoth resting and ball-squeezing tasks induced higher SNR and lower MAR than motion-artifact induction task. Shorter channels exhibited significantly higher SNR than longer channels during resting state. Unilateral ball-squeezing motion-induced oxy-hemoglobin increases in the contralateral motor cortex. Tilting up produced the largest and saying hello produced the smallest artifact across the six motion types. Head-tilting motions produced larger accelerometer changes than facial motions.ConclusionsWe expect that this open-access dataset will accelerate the development and validation of algorithms specifically designed for multidistance fNIRS.
SignificanceRepetition-based learning supports word recognition and reading fluency, yet its neural mechanisms remain poorly understood, particularly where deficits in consolidating repeated linguistic input may underlie reading and language difficulties. Establishing reliable neural markers of repetition-based learning is a critical first step toward characterizing the phenotypes of these difficulties in children.AimWe developed a whole-brain simultaneous functional near-infrared spectroscopy–electroencephalography (fNIRS–EEG) approach to capture fast temporal electrophysiological and spatially accurate hemodynamic signals during long-lag repetition learning.ApproachThirty participants performed a semantic judgment task with words repeated across four runs with intervening items, modeling repetition demands central to reading instruction. A multimodal decoding framework integrating electrophysiological, hemodynamic, and cross-modal fNIRS–EEG correlation features was used to classify repetition-based learning.ResultsRepeated words showed response time reductions. EEG captured a frontal N400-range repetition-related negativity and attenuation of alpha–beta suppression, reflecting changes in recognition-related and post-recognition processing. fNIRS revealed left inferior frontal and superior temporal efficiency increases alongside right supramarginal activation, suggesting integrative processing. Multimodal classifiers outperformed unimodal classifiers, indicating that each modality captured complementary aspects of learning.ConclusionsCombining fNIRS and EEG with multimodal machine learning provides a richer characterization of repetition-based learning than either modality alone, establishing a framework for phenotyping language learning capacity and identifying neural markers of reading difficulties in pediatric populations.
SignificanceAlzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory deficits, processes critically linked to mitochondrial dysfunction in the nervous system. Equally, adequate brain tissue oxygenation is essential for cerebral metabolism, and its impairment further compromises neuronal energy homeostasis. Together, mitochondrial dysfunction and disrupted cerebral oxygenation represent key interconnected pathological mechanisms underlying AD progression, highlighting the significance of targeting these pathways in understanding and managing the disease.AimCerebral energy metabolism in the cortex of wild-type (WT) and Alzheimer’s disease (AD) model mice was investigated using minimally invasive two-photon FLIM, with the protein-bound fraction of nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) a2% serving as a metric for mitochondrial metabolic activity. The probe “Ru(BPY)3” was calibrated to examine the dynamic nature of its phosphorescence lifetime to estimate the partial pressure of oxygen (pO2) in brain vasculature of live animals.ApproachSimultaneous two-photon fluorescence and phosphorescence lifetime imaging (2P-FLIM-PLIM) provides a minimally invasive approach to measure the metabolic state in combination with the pO2 in the vascularity of live animals. The metabolic state is obtained via FLIM of NAD(P)H, pO2 via the phosphorescence lifetime of Ru(BPY)3, an oxygen-sensitive exogenous probe.ResultsAD mouse cortices exhibit higher level of NAD(P)H a2% and lower level of pO2 compared with WT at anesthetized resting-state. 2P-PLIM investigation reveals that the lower level of pO2 in vascular network Alzheimer’s disease (AD) mice cortex indicates increased oxygen consumption in AD.ConclusionsThe concurrent application of simultaneous 2P-FLIM-PLIM in the mouse brain establishes this dual-modality protocol for the simultaneous assessment of cerebral metabolic alterations using biomarker NAD(P)H and ruthenium-based cerebrovascular oxygen tension measurements. These findings underscore the utility of this multiparametric optical imaging strategy in elucidating the interplay between mitochondrial metabolic dysfunction and impaired brain tissue oxygenation, providing a compelling platform for advancing mechanistic investigations into the neuropathological sequelae of Alzheimer’s disease.
Significance:Multiphoton microscopy with fluorescent indicators enables the monitoring of biomarker dynamics through changes in fluorescence intensity. However, quantitative interpretation remains challenging because fluorescence signals are highly sensitive to experimental conditions. Dual-color ratiometric approaches improve quantification, yet wavelength-dependent absorption and scattering of emitted photons can still introduce significant bias. Aim:This study aimed to develop a correction method for absorption and scattering effects to achieve unbiased dual-color ratiometric measurements in multiphoton microscopy. Approach:We developed an analytical model that incorporates the spectral optical properties of biological tissues and fluorophores. The model was applied to the rodent cerebral cortex parenchyma and to the lumen of individual blood vessels. Its predictions were evaluated using simulations and in vivo two-photon microscopy experiments. Results:In the cerebral cortex parenchyma, absorption and scattering bias dual-color ratiometric measurements by up to ∼ 100 % at depths of approximately ∼ 400 μ m . Our model accurately describes and corrects these effects. Within the vessel lumen, however, the situation is more complex: the model effectively corrects the biases in veins, but not in arterioles. Conclusions:Overall, the proposed model enhances the accuracy of biomarker quantification in multiphoton microscopy and provides practical tools for correcting optical biases in biological tissues.
Significance:Habituation is an early-developing cognitive process linked to learning, typically reflected in functional near-infrared spectroscopy (fNIRS) studies as a reduction in evoked hemodynamic response amplitude. Conventional fNIRS analyses rely on linear time-invariance assumptions, potentially limiting insight into how responses evolve across repeated stimulus presentations. Aim:To determine whether functional change point (FCPt) detection can characterize trial-specific changes in the infant hemodynamic response and reveal developmental differences in habituation timing. Approach:Functional data analysis (FDA) treats entire response curves as statistical objects. Within this framework, FCPt detection identifies statistically significant structural shifts in the mean response across trials. FCPt detection with wild binary segmentation was applied to group-level infant fNIRS data ( n = 204 ) collected from infants living in rural Gambia at 5, 8, and 12 months of age during a habituation and novelty detection paradigm. Results:Significant changes were identified within auditory cortical regions. A high proportion of detected change points corresponded to decreases in response magnitude at 8 and 12 months. Weighted ordinal regression revealed an age-related shift toward earlier occurrence of decreasing change points, with older infants' change points detected earlier within the trial sequence. Conclusion:FCPt detection provides temporal information on the infant hemodynamic response unavailable to conventional analysis. At the group level, this additional information has revealed an age-related difference in habituation timing during the first year of life, with older infants completing habituation sooner. This represents a previously overlooked developmental change in the habituation response. Future work on individual-level data may seek to investigate these findings with greater granularity.
