Neurophotonics最新文献

Significance: Cerebral blood flow (CBF) and cerebral blood volume (CBV) are key metrics for regional cerebrovascular monitoring. Simultaneous, non-invasive measurement of CBF and CBV at different brain locations would advance cerebrovascular monitoring and pave the way for brain injury detection as current brain injury diagnostic methods are often constrained by high costs, limited sensitivity, and reliance on subjective symptom reporting.

Aim: We aim to develop a multi-channel non-invasive optical system for measuring CBF and CBV at different regions of the brain simultaneously with a cost-effective, reliable, and scalable system capable of detecting potential differences in CBF and CBV across different regions of the brain.

Approach: The system is based on speckle contrast optical spectroscopy and consists of laser diodes and board cameras, which have been both tested and investigated for safe use on the human head. Apart from the universal serial bus connection for the camera, the entire system, including its battery power source, is integrated into a wearable headband and is powered by 9-V batteries.

Results: The temporal dynamics of both CBF and CBV in a cohort of five healthy subjects were synchronized and exhibited similar cardiac period waveforms across all six channels. The potential use of our six-channel system for detecting the physiological sequelae of brain injury was explored in two subjects, one with moderate and one with significant structural brain damage, where the six-point CBF and CBV measurements were referenced to structural magnetic resonance imaging (MRI) scans.

Conclusions: We pave the way for a viable multi-point optical instrument for measuring CBF and CBV. Its cost-effectiveness allows for baseline metrics to be established prior to injury in populations at risk for brain injury.

Internal states involve brain-wide changes that subserve coordinated behavioral and physiological responses for adaptation to changing environments and body states. Investigations of single neurons or small populations have yielded exciting discoveries for the field of neuroscience, but it has been increasingly clear that the encoding of internal states involves the simultaneous representation of multiple different variables in distributed neural ensembles. Thus, an understanding of the representation and regulation of internal states requires capturing large population activity and benefits from approaches that allow for parsing intermingled, genetically defined cell populations. We will explain imaging technologies that permit recording from large populations of single neurons in rodents and the unique capabilities of these technologies in comparison to electrophysiological methods. We will focus on findings for appetitive and aversive states given their high relevance to a wide range of psychiatric disorders and briefly explain how these approaches have been applied to models of psychiatric disease in rodents. We discuss challenges for studying internal states which must be addressed with future studies as well as the therapeutic implications of findings from rodents for improving treatments for psychiatric diseases.

Significance: Neuronal dendritic spines are central elements for memory and learning. Their morphology correlates with synaptic strength and is a proxy for function. Classic light microscopy cannot resolve spine morphology well, and techniques with higher resolution (electron microscopy and super-resolution light microscopy) typically do not provide spine data in large fields of view, e.g., along entire dendrites. Therefore, it remains unclear if spine types are organized on mesoscopic scales, despite their undisputed importance for understanding the brain.

Aim: Recently, it was shown that the distribution of spine type is dendrite-specific in the turtle cortex, suggesting a mesoscopic organization, but leaving the question open if such a dendrite specificity also exists in mammals. Here, we determine if such a difference in spine-type distribution among dendrites also exists in the mouse brain.

Approach: We used super-resolution stimulated emission depletion microscopy of complete dendrites and advanced morphological analysis in three dimensions to decipher morphological differences of spines on different dendrites.

Results: We found that spines of different shapes decorate different dendrites of the same neuron to a varying extent. Significant differences among the dendrites are apparent, based on spine classes as well as based on quantitative descriptors, such as spine length or head size.

Conclusions: Our findings may indicate that it is an evolutionarily conserved principle that individual dendrites have distinct distributions of spine types hinting at individual roles.

Significance: Despite the availability of various anti-seizure medications, nearly 1/3 of epilepsy patients experience drug-resistant seizures. These patients are left with invasive surgical options that do not guarantee seizure remission. The development of novel treatment options depends on elucidating the complex biology of seizures and brain networks.

Aim: We aimed to develop an experimental paradigm that uses anatomical network information, functional connectivity, and in vivo seizure models to determine how brain networks, and their manipulation, affect seizure propagation.

Approach: Guided by a known anatomical network, we applied widefield calcium imaging to determine how neural activity and seizures spread through the network regions, focusing on the primary somatosensory cortex and secondary motor cortex. We used in vivo microstimulation to induce suprathreshold excitatory activation and compared this reproducible stimulus with acute pharmacologically induced spontaneous seizure propagation. In a proof-of-concept experiment, we ablated a single node within this bilateral network and measured the effect on propagation and recruitment. Similar preliminary experiments were repeated in a chronic seizure model.

Results: The microstimulation of the somatosensory cortex propagated in a distinct pattern throughout the bilateral network with sequential reproducible node recruitment. Seizures recapitulated this same pattern, indicating a hijacking of existing pathways. Ablation of a key node in the network in the secondary motor cortex changed contralateral spread. Early chronic cobalt seizure data are presented.

Conclusion: Here, we demonstrate a paradigm for combining widefield calcium imaging with microstimulation, cortical ablation, and seizure mapping to determine how anatomical networks inform the propagation patterns of cortical seizures. These experiments can be extended to long-term tracking of epilepsy to study epileptogenesis in other cortical networks. Our proof-of-concept findings suggest that this paradigm may be useful in the development of novel therapies for drug-resistant epilepsy patients and can be extended to the study of other disorders involving brain networks.

Significance: Alzheimer's disease (AD) is a brain disorder characterized by its multifactorial nature and complex pathogenesis, highlighting the necessity for multimodal and individualized interventions. Among emerging therapies, near-infrared (NIR) light treatment shows promise as a therapeutic modality for AD. However, existing clinical studies lack sufficient data on light dosimetry, parameter optimization, and dose-response.

Aim: A versatile framework was developed to enable patient-individualized Monte Carlo simulation. A standardized dataset was established, including digital phantoms derived from 20 AD patients who received NIR light treatment.

Approach: The phantoms were synthesized and mapped with multispectral optical parameters, integrating cortical parcellation, subcortical segmentation, and sparse annotation. Structure-related light fluence pathways and dose-response relationships were elucidated using simulation results and cognitive/functional assessments.

Results: The capability for enhancing simulation fidelity and exploring dose-response relationships was verified using standard templates and clinical data. Linear independence was identified between changes in activities of daily living scale scores and energy deposition in gray matter.

Conclusions: The framework offers a solution toward dose-response analysis, parameter optimization, and safety control in the clinical translation for multiple treatment paradigms, demonstrating promise for individualized, standardized, and precise intervention planning.

Significance: Decoding naturalistic content from brain activity has important neuroscience and clinical implications. Information about visual scenes and intelligible speech has been decoded from cortical activity using functional magnetic resonance imaging (fMRI) and electrocorticography, but widespread applications are limited by the logistics of these technologies.

Aim: High-density diffuse optical tomography (HD-DOT) offers image quality approaching that of fMRI but with the silent, open scanning environment afforded by optical methods, thus opening the door to more naturalistic research and applications. Although early visual decoding studies with HD-DOT have been promising, decoding of naturalistic auditory and multisensory stimulus information from HD-DOT data has not been established.

Approach: Audiovisual decoding was investigated using HD-DOT data collected from participants who viewed a library of movie clips. A template-matching strategy was used to decode which movie clip a participant viewed based on their HD-DOT data. Factors affecting decoding performance-including trial duration and number of decoding choices-were systematically evaluated.

Results: Decoding accuracy was 94.2% for four-way decoding utilizing 4 min of data per trial as a starting point. As parameters were made more stringent, decoding performance remained significantly above chance with strong effect sizes down to 15-s trials and up to 32 choices. Comparable decoding accuracies were obtained when cortical sampling was confined to visual and auditory regions and when participants were presented with purely auditory or visual clips.

Conclusions: HD-DOT data sample cortical hemodynamics with sufficient resolution and fidelity to support decoding complex, naturalistic, multisensory stimuli via template matching. These results provide a foundation for future studies on more intricate decoding algorithms to reconstruct diverse features of novel naturalistic stimuli from HD-DOT data.

Expansion microscopy is a super-resolution technique in which physically enlarging the samples in an isotropic manner increases inter-molecular distances such that nano-scale structures can be resolved using light microscopy. This is particularly useful in neuroscience as many important structures are smaller than the diffraction limit. Since its invention in 2015, a variety of expansion microscopy protocols have been generated and applied to advance knowledge in many prominent organisms in neuroscience, including zebrafish, mice, Drosophila, and Caenorhabditis elegans. We review the last decade of expansion microscopy-enabled advances with a focus on neuroscience.

Significance: The deep cortical microvasculature is closely linked to the pathogenesis of Alzheimer's disease (AD). However, tail artifacts from superficial cortical vessels often interfere with detecting deep vessels in optical coherence tomography angiography (OCTA) imaging. A more accurate method to assess deep cortical vasculature is crucial for understanding its relationship with AD onset.

Aim: We aim to reduce superficial vessel artifacts in OCTA imaging and improve the visualization and analysis of deep cortical microvasculature in an AD mouse model.

Approach: We introduced the optical attenuation coefficient decorrelation (OACD) method for OCTA, effectively reducing tail artifacts from superficial cortex vessels. This method was used to visualize and quantitatively analyze deep cortical microvasculature in vivo in a mouse model of AD.

Results: The OACD method significantly reduced superficial vessel artifacts, leading to clearer imaging of the deep cortical vasculature. Quantitative analysis revealed that changes in the deep cortical microvasculature were more pronounced than in the superficial vasculature, suggesting a more direct involvement of the deep vessels in AD progression.

Conclusions: The proposed OACD method enhances OCTA imaging by reducing tail artifacts from superficial vessels, facilitating improved assessment of deep cortical microvasculature. These findings suggest that deep cortical vascular changes may play a key role in the pathogenesis of AD, offering potential insights for early detection and monitoring of AD progression.

Significance: The diffusion approximation (DA) is used in functional near-infrared spectroscopy (fNIRS) studies despite its known limitations due to the presence of cerebrospinal fluid (CSF). Many of these studies rely on a set of empirical CSF optical properties, recommended by a previous simulation study, that were not selected for the purpose of minimizing DA modeling errors.

Aim: We aim to directly quantify the accuracy of DA solutions in brain models by comparing those with the gold-standard solutions produced by the mesh-based Monte Carlo (MMC), based on which we derive updated recommendations.

Approach: For both a five-layer head and Colin27 atlas models, we obtain DA solutions by independently sweeping the CSF absorption ( ${\mu }_a$ ) and reduced scattering ( ${\mu }_{s^{\text{'}}}$ ) coefficients. Using an MMC solution with literature CSF optical properties as a reference, we compute the errors for surface fluence, total brain sensitivity, and brain energy deposition, and identify the optimized settings where such error is minimized.

Results: Our results suggest that previously recommended CSF properties can cause significant errors (8.7% to 52%) in multiple tested metrics. By simultaneously sweeping ${\mu }_a$ and ${\mu }_s^{\text{'}}$ , we can identify infinite numbers of solutions that can exactly match DA with MMC solutions for any single tested metric. Furthermore, it is also possible to simultaneously minimize multiple metrics at multiple source/detector separations, leading to our updated recommendation of setting ${\mu }_s^{\text{'}}=0.15{\mathrm{mm}}^{-1}$ while maintaining physiological ${\mu }_a$ for CSF in DA simulations.

Conclusions: Our updated recommendation of CSF equivalent optical properties can greatly reduce the model mismatches between DA and MMC solutions at multiple metrics without sacrificing computational speed. We also show that it is possible to eliminate such a mismatch for a single or a pair of metrics of interest.

Significance: Stroke is the leading cause of chronic disability in the United States. How stroke size affects post-stroke repair and recovery is poorly understood.

Aim: We aim to investigate the effects of stroke size on early repair patterns and determine how early changes in neuronal circuits and networks predict functional outcomes after stroke.

Approach: We used wide-field optical imaging, photothrombosis, and the cylinder-rearing assay to examine changes in neuronal circuit and network activity in the context of functional recovery after stroke.

Results: Larger strokes ablating $S{1}_{\mathrm{FP}}$ caused diffuse and widespread forepaw stimulus-evoked cortical activation, including contralesional regions evolving within 4 weeks post-stroke; smaller strokes resulted in more focused ipsilesional activation. Larger strokes decreased neuronal fidelity and bilateral coherence during stimulation of either the affected or unaffected forepaw within this 4-week period. Mice in the larger lesion group demonstrated hyperconnectivity within the contralesional hemisphere at the resting state. Greater degrees of remapping diffusivity, neuronal fidelity degradation, and hyperconnectivity predicted worse 8-week recovery after statistically controlling for the effect of infarct size.

Conclusions: These results suggest that diffuse patterns of remapping, and desynchronization and hyperconnectivity of cortical networks, evolving early after stroke may reflect maladaptive plasticity, predicting poor long-term functional recovery.