Neurophotonics最新文献

Significance: Neural activation in functional near-infrared spectroscopy (fNIRS) signals is inherently convolved with, and temporally blurred by, a hemodynamic response function (HRF). Accurately modeling HRF variability during deconvolution improves neural activity recovery.

Aim: We present the Python-based HRfunc tool for estimating local HRF distributions and neural activity from fNIRS through deconvolution. HRFs are stored within a tree and a hash table hybrid data structure for efficient spatial and contextual identification of relevant HRFs.

Approach: To test the HRfunc tool, we conducted two analyses with hemoglobin and estimated neural activity, a general linear model (GLM) analysis on a single subject, child executive function task ( $n=79$ ), and a neural synchrony analysis assessing wavelet coherence between child-parent dyads (92 dyads).

Results: Estimated HRFs contained a generally canonical shape. Within estimated neural activity, kurtosis increased, skew remained stable, and signal-to-noise ratio decreased. Neural synchrony lateralization effects emerged, and consistent GLM outcomes were observed.

Conclusions: These results support the use of the HRfunc tool for estimating event-based HRFs and neural activity in fNIRS studies. Through collective sharing of HRFs, an HRF database will be established to provide access to estimated HRFs across brain regions, subject ages, and experimental contexts.

Significance: Although the transmission of auditory information in the brain has been extensively studied, the mechanism underlying fine auditory discrimination remains incompletely understood. The basal region of the ventromedial nucleus of the thalamus (bVM) has recently been found to convey frequency-specific auditory information to the primary auditory cortex (A1). Inhibition of the bVM significantly impairs fine auditory discrimination in mice. These findings indicate that the bVM plays an important role in frequency information processing. However, direct functional evidence for tonotopic organization within the bVM is still lacking.

Aim: We aimed to investigate whether bVM neurons exhibit a spatially ordered frequency preference, using a simple yet efficient in vivo functional mapping strategy.

Approach: To characterize the response properties of bVM neurons projecting to A1, we combined Cre-dependent retrograde viral labeling with fiber photometry in awake mice. Using a "one recording site per animal" strategy, we systematically recorded from 26 distinct locations and successfully reconstructed the tonotopic map of the bVM.

Results: We identified a mediolateral tonotopic gradient within the bVM, with best frequencies progressing from low in medial regions to high in lateral regions.

Conclusions: Our findings provide direct functional evidence of tonotopic organization within the bVM, supporting its role as an auditory relay and its contribution to fine auditory discrimination.

Significance: Functional near-infrared spectroscopy (fNIRS) is a unique neuroimaging methodology with high portability and tolerance of motion, making it well-suited to research in dynamic real-world environments. However, it is crucial to carefully design fNIRS paradigms to suit the unique requirements of real-world research settings. We outline key design principles and considerations for fNIRS studies.

Aim: In this paper, we address the lack of guidance on experimental design for fNIRS, which in our growing field can help to educate new fNIRS researchers and improve the quality and applicability of fNIRS research across various settings.

Approach: Here, we provide a primer for how to design fNIRS studies and overcome challenges in fNIRS experimental design, with a focus on naturalistic real-world research, which has gathered increased research interest in recent years.

Conclusions: We conclude by outlining seven key design principles researchers can use to guide experimental design for fNIRS research.

Neurophotonics Associate Editors Edgar Guevara and Rickson C. Mesquita, along with Felipe Orihuela-Espina, share their perceptions of the evolution of functional near-infrared spectroscopy in Latin America based on a retrospective literature review and the narratives of three other scientists from the region.

Traditional methods for assessing photothrombotic stroke rely on in vivo imaging techniques or ex vivo histological analyses. Unlike in vivo modalities such as magnetic resonance imaging (MRI), light sheet fluorescence microscopy (LSFM) provides cellular-level high-resolution imaging without motion artifacts and can capture fine-scale morphological features of infarcts. In addition, compared with conventional histology, LSFM preserves organ integrity as the entire brain is imaged without the need for serial sectioning, thereby enabling accurate volumetric reconstruction of ischemic lesions. Here, we introduce an in-depth semi-automated method for reliable quantification of stroke volume using LSFM in optically cleared whole mouse brains following photothrombotic stroke. We demonstrate that the infarct can be delineated via endogenous autofluorescence, providing a reproducible and robust method for ischemic volume assessment. Our data show that LSFM-based stroke volume measurements are strongly correlated with in vivo laser speckle contrast imaging, in vivo MRI, and cresyl violet histology measures of stroke volume. Moreover, we show that the ischemic core remains autofluorescent regardless of the tissue preparation method, supporting the applicability of LSFM for both freshly processed and long-term stored samples. Overall, our findings validate LSFM as a reliable, versatile, and powerful alternative method for stroke volume quantification, offering significant advantages for experimental stroke research.

Significance: Acknowledgement of a lack of inclusivity in human subjects-focused wearable neuroimaging research has emerged in recent years due to a number of common practices. Women of color are most negatively impacted by this systemic exclusion in wearable neuroimaging research, specifically with respect to functional near-infrared spectroscopy (fNIRS) research.

Aim: We aim to demonstrate the effectiveness of holistic and inclusive practices in the recruitment and retention of women of color in an fNIRS research study.

Approach: The development of inclusive approaches involves consideration of study design elements, study participant recruitment and retention, pre-fNIRS session assessment considerations, and adjustments to data collection practices during fNIRS assessment. Approaches taken in each of these study stages are described.

Results: All participants remained enrolled and participated in the study through the online survey (S0), first in-person session (S1), and second in-person (fNIRS) session (S2), leading to a study retention rate of 100%.

Conclusions: The inclusion of four key recommendations in addition to prior recommendations can help reduce exclusionary practices in human subjects-focused fNIRS research, particularly in recruiting and retaining women of color. Improvement of this approach is expected through iterative modifications and the inclusion of additional holistic practices.

Significance: Cochlear implants (CIs) are a proven intervention for severe hearing loss; however, outcomes vary widely among CI recipients. Emerging evidence suggests that cortical adaptation to the electric hearing provided by CIs play a crucial role.

Aim: We investigate cortical brain activation differences in CI users, comparing individuals with good speech understanding (good performers, GP) to those with poor outcomes (poor performers, PP) alongside a control group with normal hearing (NH).

Approach: We recruited 46 CI users and 26 NH participants to perform a clinically adapted audiovisual speech comprehension task while we measured their brain activity using functional near-infrared spectroscopy (fNIRS). We corroborated our findings with objective and behavioral data.

Results: Our findings showed distinct brain activation patterns associated with speech understanding. GP showed comparable brain activation patterns to NH in audio-only conditions, indicative of successful hearing rehabilitation. Further, both GP and PP participants showed an adaptive mechanism during visual speech processing. However, compared with GP, PP relied heavily on visual cues and showed altered neural resource allocation during audio-only conditions, potentially limiting their overall rehabilitation success.

Conclusions: fNIRS revealed significant differences in brain activation between GP and PP, highlighting the role of cortical factors in CI rehabilitation. Understanding these neural mechanisms has the potential to lead to better patient counseling, optimized postoperative management, and personalized therapeutic strategies to improve outcomes for CI users.

Significance: The combination of two-photon calcium imaging and targeted two-photon optogenetic stimulation, termed all-optical interrogation, provides spatial and temporal precision when recording and manipulating neural circuit activity in vivo. All-optical experiments often use red-shifted opsins in combination with green fluorescent reporters of neuronal activity. However, their excitation spectra still partially overlap, meaning that the imaging laser can excite the opsin. Although some care has been taken in the past to understand the effects of this spectral overlap; further work is required to understand its impact on the findings of all-optical studies.

Aim: We aimed to investigate whether two-photon imaging of the green fluorescent calcium reporter GCaMP6s at 920 nm increase the rate of response desensitization in neurons targeted for two-photon stimulation at 1035 nm expressing the red-shifted opsin C1V1.

Approach: We systematically varied either the inter-stimulus interval or the duration of two-photon calcium imaging during targeted two-photon optogenetic stimulation of mouse layer 2/3 barrel cortex or visual cortex neurons.

Results: We found that two-photon imaging at 920 nm decreases trial-by-trial photostimulation responses in targeted C1V1-expressing neurons-an effect that is exacerbated at shorter inter-stimulus intervals. This is consistent with the imaging laser increasing the rate of opsin desensitization. Reduced photostimulation responses are not limited to targeted cells and are found across the field of view. Such network effects are less pronounced at shorter imaging doses.

Conclusions: Our results provide methodological optimizations that enable trial-by-trial decreases in photostimulation response to be mitigated in all-optical experiments. This will reduce an external source of trial-by-trial variability in future all-optical experiments.

Significance: In functional near-infrared spectroscopy (fNIRS) research, ensuring signal quality is a critical preprocessing step. However, traditional index-based metrics such as the coefficient of variation (CV) and scalp coupling index (SCI) rely on arbitrary thresholds and often misclassify channels.

Aim: We present DL-QC-fNIRS, a deep learning framework for the automated, channel-wise assessment of signal quality.

Approach: Our method involves generating continuous wavelet transform scalograms of oxyhemoglobin signals and employing subject-specific cardiac frequency extraction to improve physiological specificity. These inputs are then classified using convolutional neural networks (CNNs). We benchmarked four CNN architectures (GoogLeNet, ResNet-50, SqueezeNet, and EfficientNet-B0) on two independent datasets and one combined heterogeneous dataset.

Results: GoogLeNet achieved the highest accuracy ( $>93\%$ ) on the combined dataset, demonstrating strong sensitivity and specificity across test sets. Compared with CV and SCI, DL-QC-fNIRS yielded markedly higher F1-scores and a more favorable balance between sensitivity and specificity.

Conclusions: DL-QC-fNIRS is provided as an open-source MATLAB-based graphical interface, enabling accessible and standardized integration into fNIRS workflows. These findings highlight DL-QC-fNIRS as a scalable, expert-level tool for improving the reliability and reproducibility of optical neuroimaging data.

Traumatic brain injury (TBI) can lead to long-lasting impairments in cerebral perfusion, making early detection of microvascular changes critical for guiding clinical interventions. We employed time-domain diffuse correlation spectroscopy (TD-DCS) at 1064 nm to noninvasively quantify depth-resolved cerebral blood flow (CBF) and low-frequency oscillations (LFOs) in a mouse model of closed-head injury. By analyzing earlier photon arrivals (with greater superficial weighting) and later photon arrivals (with enhanced sensitivity to deeper tissue), we identified a significant drop in CBF shortly after injury, with partial recovery observed at 2 h post-trauma. Power spectral analysis of the blood flow index (BFI, a diffusion coefficient proportional to CBF) revealed significant alterations in LFO bands, particularly in slow-5 (0.01 to 0.027 Hz) and slow-3 (0.073 to 0.198 Hz) ranges. These differences, assessed using a paired Wilcoxon rank-sum test ( $p<0.05$ ), were more pronounced than BFI alterations alone, indicating that LFOs may serve as sensitive biomarkers of neurovascular disruption. Our findings demonstrate the feasibility of TD-DCS for relative depth-sensitive monitoring of cerebral hemodynamics and oscillatory dynamics after TBI and highlight its potential utility in translational neurotrauma research.