In vivo neuropil density from anatomical MRI and machine learning.

Brain energy budgets specify metabolic costs emerging from underlying mechanisms of cellular and synaptic activities. While current bottom-up energy budgets use prototypical values of cellular density and synaptic density, predicting metabolism from a person's individualized neuropil density would be ideal. We hypothesize that in vivo neuropil density can be derived from magnetic resonance imaging (MRI) data, consisting of longitudinal relaxation (T1) MRI for gray/white matter distinction and diffusion MRI for tissue cellularity (apparent diffusion coefficient, ADC) and axon directionality (fractional anisotropy, FA). We present a machine learning algorithm that predicts neuropil density from in vivo MRI scans, where ex vivo Merker staining and in vivo synaptic vesicle glycoprotein 2A Positron Emission Tomography (SV2A-PET) images were reference standards for cellular and synaptic density, respectively. We used Gaussian-smoothed T1/ADC/FA data from 10 healthy subjects to train an artificial neural network, subsequently used to predict cellular and synaptic density for 54 test subjects. While excellent histogram overlaps were observed both for synaptic density (0.93) and cellular density (0.85) maps across all subjects, the lower spatial correlations both for synaptic density (0.89) and cellular density (0.58) maps are suggestive of individualized predictions. This proof-of-concept artificial neural network may pave the way for individualized energy atlas prediction, enabling microscopic interpretations of functional neuroimaging data.

A 3D atlas of functional human brain energetic connectome based on neuropil distribution.

The human brain is energetically expensive, yet the key factors governing its heterogeneous energy distributions across cortical regions to support its diversity of functions remain unexplored. Here, we built up a 3D digital cortical energy atlas based on the energetic costs of all neuropil activities into a high-resolution stereological map of the human cortex with cellular and synaptic densities derived, respectively, from ex vivo histological staining and in vivo PET imaging. The atlas was validated with PET-measured glucose oxidation at the voxel level. A 3D cortical activity map was calculated to predict the heterogeneous activity rates across all cortical regions, which revealed that resting brain is indeed active with heterogeneous neuronal activity rates averaging around 1.2 Hz, comprising around 70% of the glucose oxidation of the cortex. Additionally, synaptic density dominates spatial patterns of energetics, suggesting that the cortical energetics rely heavily on the distribution of synaptic connections. Recent evidence from functional imaging studies suggests that some cortical areas act as hubs (i.e., interconnecting distinct and functionally active regions). An inverse allometric relationship was observed between hub metabolic rates versus hub volumes. Hubs with smaller volumes have higher synapse density, metabolic rate, and activity rates compared to nonhubs. The open-source BrainEnergyAtlas provides a granular framework for exploring revealing design principles in energy-constrained human cortical circuits across multiple spatial scales.

Simultaneous cortex-wide fluorescence Ca2+ imaging and whole-brain fMRI.

Achieving a comprehensive understanding of brain function requires multiple imaging modalities with complementary strengths. We present an approach for concurrent widefield optical and functional magnetic resonance imaging. By merging these modalities, we can simultaneously acquire whole-brain blood-oxygen-level-dependent (BOLD) and whole-cortex calcium-sensitive fluorescent measures of brain activity. In a transgenic murine model, we show that calcium predicts the BOLD signal, using a model that optimizes a gamma-variant transfer function. We find consistent predictions across the cortex, which are best at low frequency (0.009-0.08 Hz). Furthermore, we show that the relationship between modality connectivity strengths varies by region. Our approach links cell-type-specific optical measurements of activity to the most widely used method for assessing human brain function.

Filament-arrayed Bragg gratings for azimuthally resolved displacement sensing in single-mode fibers.

Filament arrays were inscribed off-axis in the core of standard single-mode telecommunication fiber, using femtosecond laser pulses. The flexible line-by-line writing formed uniform, parallel filaments, permitting Bragg grating sensing of the photoelastic response from inside of the narrow grating plane. Active monitoring of the Bragg resonance wavelength while driving a lateral fiber tip displacement directly informed on the fiber mechanics when coupled with opto-mechanical modelling. Overlaying of parallel and orthogonal gratings further provided a strongly contrasting azimuthal sensitivity, which paves the way for multi-dimensional displacement sensing with improved precision.

Manipulating geometric and optical properties of laser-inscribed nanogratings with a conical phase front.

The formation of volumetric nanogratings in fused silica by femtosecond laser pulses are shown to afford new opportunities for manipulating the physical shape and tailoring the optical properties of the modification zone by harnessing unconventional beam shapes. The nanograting assembly was observed to rigorously follow the beam elongation effects induced with conical-shaped phase fronts, permitting a scaling up of the writing volume. Detailed optical characterization of birefringence, dichroism, and scattering loss pointed to flexible new ways to tune the macroscopic optical properties, with advantages in decoupling the induced phase retardation from the modification thickness by controlling the conical phase front angle. Further insights into an unexpected asymmetric response from Gaussian beams modified with concave and convex phase fronts have been provided by nonlinear propagation simulations of the shaped-laser light.

Image Processing for Public Health Surveillance of Tobacco Point-of-Sale Advertising: Machine Learning-Based Methodology.

BACKGROUND: With a rapidly evolving tobacco retail environment, it is increasingly necessary to understand the point-of-sale (POS) advertising environment as part of tobacco surveillance and control. Advances in machine learning and image processing suggest the ability for more efficient and nuanced data capture than previously available. OBJECTIVE: The study aims to use machine learning algorithms to discover the presence of tobacco advertising in photographs of tobacco POS advertising and their location in the photograph. METHODS: We first collected images of the interiors of tobacco retailers in West Virginia and the District of Columbia during 2016 and 2018. The clearest photographs were selected and used to create a training and test data set. We then used a pretrained image classification network model, Inception V3, to discover the presence of tobacco logos and a unified object detection system, You Only Look Once V3, to identify logo locations. RESULTS: Our model was successful in identifying the presence of advertising within images, with a classification accuracy of over 75% for 8 of the 42 brands. Discovering the location of logos within a given photograph was more challenging because of the relatively small training data set, resulting in a mean average precision score of 0.72 and an intersection over union score of 0.62. CONCLUSIONS: Our research provides preliminary evidence for a novel methodological approach that tobacco researchers and other public health practitioners can apply in the collection and processing of data for tobacco or other POS surveillance efforts. The resulting surveillance information can inform policy adoption, implementation, and enforcement. Limitations notwithstanding, our analysis shows the promise of using machine learning as part of a suite of tools to understand the tobacco retail environment, make policy recommendations, and design public health interventions at the municipal or other jurisdictional scale.

Orthonasal versus retronasal glomerular activity in rat olfactory bulb by fMRI.

Odorants can reach olfactory receptor neurons (ORNs) by two routes: orthonasally, when volatiles enter the nasal cavity during inhalation/sniffing, and retronasally, when food volatiles released in the mouth pass into the nasal cavity during exhalation/eating. Previous work in humans has shown that both delivery routes of the same odorant can evoke distinct perceptions and patterns of neural responses in the brain. Each delivery route is known to influence specific responses across the dorsal region of the glomerular sheet in the olfactory bulb (OB), but spatial distributions across the entire glomerular sheet throughout the whole OB remain largely unexplored. We used functional MRI (fMRI) to measure and compare activations across the entire glomerular sheet in rat OB resulting from both orthonasal and retronasal stimulations of the same odors. We observed reproducible fMRI activation maps of the whole OB during both orthonasal and retronasal stimuli. However, retronasal stimuli required double the orthonasal odor concentration for similar response amplitudes. Regardless, both the magnitude and spatial extent of activity were larger during orthonasal versus retronasal stimuli for the same odor. Orthonasal and retronasal response patterns show overlap as well as some route-specific dominance. Orthonasal maps were dominant in dorsal-medial regions, whereas retronasal maps were dominant in caudal and lateral regions. These different whole OB encodings likely underlie differences in odor perception between these biologically important routes for odorants among mammals. These results establish the relationships between orthonasal and retronasal odor representations in the rat OB.

Compensating deep focusing distortion for femtosecond laser inscription of low-loss optical waveguides.

Various beam shaping approaches were examined to counter the negative influence of surface aberration arising when inscribing optical waveguides deeply inside of glass with a femtosecond laser. Aberration correction was found unable to completely recover the low-loss waveguide properties, prompting a comprehensive examination of waveguides formed with focused Gaussian-Bessel beams. Diverging conical phase fronts are presented as a hybrid means of partial aberration correction to improve insertion loss and a new, to the best of our knowledge, means of asymmetric beam shaping. In this way, low-loss waveguides are presented over shallow to deep writing depth (2.8 mm) where morphological and modal properties could be further tuned with conical phase front.

Wave effects on seedling establishment of three pioneer marsh species: survival, morphology and biomechanics.

BACKGROUND AND AIMS: It is important to have an in-depth mechanistic understanding of tidal marsh establishment and dynamics to ensure the long-term persistence of these valuable ecosystems. As wave forcing may be expected to impact seedling establishment, we studied the effect of water-imposed drag forces on seedling survival, morphology and biomechanical properties of three marsh pioneer species that are dominant along the salinity gradient in many areas around the world: Spartina anglica (salt to brackish), Scirpus maritimus (brackish) and Phragmites australis (brackish to fresh). METHODS: Using a newly developed plant-shaking mesocosm (PSM) that mimicked water-imposed wave drag forces, the effect of wave stress on seedling survival was examined, together with impacts on morphology and biomechanical properties. KEY RESULTS: After 7 weeks of exposure to wave stress, lowered seedling survival and growth for all species was revealed. Wave treatments increased the root/shoot biomass ratio to enhance anchorage and made seedlings more flexible (i.e. reduced flexural rigidity), which might be regarded as a mixed outcome between a stress avoidance and stress tolerance strategy. CONCLUSIONS: The different biomechanical responses between the three dominant marsh pioneer species, overall, make them less resistant to external stress. Therefore, our results indicate that the likelihood of marshes becoming established is reduced if wave energy increases. Despite the different biomechanical response of these three pioneer species to waves, the seedlings of all species were found to have low resistance to external stresses.

Behavioral self-organization underlies the resilience of a coastal ecosystem.

Self-organized spatial patterns occur in many terrestrial, aquatic, and marine ecosystems. Theoretical models and observational studies suggest self-organization, the formation of patterns due to ecological interactions, is critical for enhanced ecosystem resilience. However, experimental tests of this cross-ecosystem theory are lacking. In this study, we experimentally test the hypothesis that self-organized pattern formation improves the persistence of mussel beds (Mytilus edulis) on intertidal flats. In natural beds, mussels generate self-organized patterns at two different spatial scales: regularly spaced clusters of mussels at centimeter scale driven by behavioral aggregation and large-scale, regularly spaced bands at meter scale driven by ecological feedback mechanisms. To test for the relative importance of these two spatial scales of self-organization on mussel bed persistence, we conducted field manipulations in which we factorially constructed small-scale and/or large-scale patterns. Our results revealed that both forms of self-organization enhanced the persistence of the constructed mussel beds in comparison to nonorganized beds. Small-scale, behaviorally driven cluster patterns were found to be crucial for persistence, and thus resistance to wave disturbance, whereas large-scale, self-organized patterns facilitated reformation of small-scale patterns if mussels were dislodged. This study provides experimental evidence that self-organization can be paramount to enhancing ecosystem persistence. We conclude that ecosystems with self-organized spatial patterns are likely to benefit greatly from conservation and restoration actions that use the emergent effects of self-organization to increase ecosystem resistance to disturbance.

Ultrafast laser burst-train filamentation for non-contact scribing of optical glasses.

A systematic study of glass scribing is presented on the benefits of ultrafast laser burst trains in generating filamentation tracks to guide cleaving of glass substrates. The interplay of Kerr self-focusing, plasma defocusing, and burst-train accumulation effects in filament formation was characterized by time-resolved in-situ microscopic imaging. Various filament-track scribing geometries were compared with and without assistance from burst-train pulse delivery or surface V-groove ablation. The cleaving guidance and reproducibility were examined together with the breaking force, facet morphology and flexural strength of cleaved substrates to assess the overall scribing and cleaving quality. The reported results attest to the benefits and flexibility of burst-mode ultrafast laser interactions to assist cleaving of optically transparent materials along well formed filament arrays.

Ecosystem engineering creates a new path to resilience in plants with contrasting growth strategies.

Plant species can be characterized by different growth strategies related to their inherent growth and recovery rates, which shape their responses to stress and disturbance. Ecosystem engineering, however, offers an alternative way to cope with stress: modifying the environment may reduce stress levels. Using an experimental study on two seagrass species with contrasting traits, the slow-growing Zostera marina vs. the fast-growing Zostera japonica, we explored how growth strategies versus ecosystem engineering may affect their resistance to stress (i.e. addition of organic material) and recovery from disturbance (i.e. removal of above-ground biomass). Ecosystem engineering was assessed by measuring sulphide levels in the sediment porewater, as seagrass plants can keep sulphide levels low by aerating the rhizosphere. Consistent with predictions, we observed that the fast-growing species had a high capacity to recover from disturbance. It was also more resistant to stress and still able to maintain high standing stock with increasing stress levels because of its ecosystem engineering capacity. The slow-growing species was not able to maintain its standing stock under stress, which we ascribe to a weak capacity for ecosystem engineering regarding this particular stress. Overall, our study suggests that the combination of low-cost investment in tissues with ecosystem engineering to alleviate stress creates a new path in the growth trade-off between investment in strong tissues or fast growth. It does so by being both fast in recovery and more resistant. As such low-cost ecosystem engineering may occur in more species, we argue that it should be considered in assessing plant resilience.

Ecosystem-based coastal defence in the face of global change.

The risk of flood disasters is increasing for many coastal societies owing to global and regional changes in climate conditions, sea-level rise, land subsidence and sediment supply. At the same time, in many locations, conventional coastal engineering solutions such as sea walls are increasingly challenged by these changes and their maintenance may become unsustainable. We argue that flood protection by ecosystem creation and restoration can provide a more sustainable, cost-effective and ecologically sound alternative to conventional coastal engineering and that, in suitable locations, it should be implemented globally and on a large scale.

Spontaneous activity forms a foundation for odor-evoked activation maps in the rat olfactory bulb.

Fluctuations in spontaneous activity have been observed by many neuroimaging techniques, but because these resting-state changes are not evoked by stimuli, it is difficult to determine how they relate to task-evoked activations. We conducted multi-modal neuroimaging scans of the rat olfactory bulb, both with and without odor, to examine interaction between spontaneous and evoked activities. Independent component analysis of spontaneous fluctuations revealed resting-state networks, and odor-evoked changes revealed activation maps. We constructed simulated activation maps using resting-state networks that were highly correlated to evoked activation maps. Simulated activation maps derived by intrinsic optical signal (IOS), which covers the dorsal portion of the glomerular sheet, significantly differentiated one odor's evoked activation map from the other two. To test the hypothesis that spontaneous activity of the entire glomerular sheet is relevant for representing odor-evoked activations, we used functional magnetic resonance imaging (fMRI) to map the entire glomerular sheet. In contrast to the IOS results, the fMRI-derived simulated activation maps significantly differentiated all three odors' evoked activation maps. Importantly, no evoked activation maps could be significantly differentiated using simulated activation maps produced using phase-randomized resting-state networks. Given that some highly organized resting-state networks did not correlate with any odors' evoked activation maps, we posit that these resting-state networks may characterize evoked activation maps associated with odors not studied. These results emphasize that fluctuations in spontaneous activity form a foundation for active processing, signifying the relevance of resting-state mapping to functional neuroimaging.

Femtosecond laser filaments for rapid and flexible writing of fiber Bragg grating.

A new beam delivery method is introduced for controlling filament formation in optical fiber that enables point-by-point writing of 1st order fiber Bragg gratings (FBGs) with single femtosecond laser pulses. Uniform filament tracks with azimuthal symmetry were formed fully through the 9.3 µm core waveguide by a modified immersion focusing method to eliminate astigmatism by the cylindrical fiber shape. Filament arrays were precisely assembled inside of single-mode fiber, generating strong FBG resonances in the telecommunication band. Laser exposure control within this unique thin-grating geometry were key to manipulating the relative strength of the Bragg and cladding mode resonances while also independently tailoring their spectral resolution and features. This filament-by-filament writing rapidly forms gratings with highly flexible pattern control to tune wavelength, or introduce optical defects, demonstrated by a π-shifted FBG having a sharp 25 pm resonance embedded within a broader Bragg peak.

Impact of Global Mean Normalization on Regional Glucose Metabolism in the Human Brain.

Because the human brain consumes a disproportionate fraction of the resting body's energy, positron emission tomography (PET) measurements of absolute glucose metabolism (CMRglc) can serve as disease biomarkers. Global mean normalization (GMN) of PET data reveals disease-based differences from healthy individuals as fractional changes across regions relative to a global mean. To assess the impact of GMN applied to metabolic data, we compared CMRglc with and without GMN in healthy awake volunteers with eyes closed (i.e., control) against specific physiological/clinical states, including healthy/awake with eyes open, healthy/awake but congenitally blind, healthy/sedated with anesthetics, and patients with disorders of consciousness. Without GMN, global CMRglc alterations compared to control were detected in all conditions except in congenitally blind where regional CMRglc variations were detected in the visual cortex. However, GMN introduced regional and bidirectional CMRglc changes at smaller fractions of the quantitative delocalized changes. While global information was lost with GMN, the quantitative approach (i.e., a validated method for quantitative baseline metabolic activity without GMN) not only preserved global CMRglc alterations induced by opening eyes, sedation, and varying consciousness but also detected regional CMRglc variations in the congenitally blind. These results caution the use of GMN upon PET-measured CMRglc data in health and disease.

Integration of an O-band VCSEL on silicon photonics with polarization maintenance and waveguide coupling.

We demonstrate the hybrid integration of an O-band vertical-cavity surface-emitting laser (VCSEL) onto a silicon photonic chip using a grating coupler that is optimized to simultaneously provide feedback to maintain the single emission polarization and efficient in-plane coupling. The grating coupler was fabricated on silicon-on-insulator using a standard silicon photonics foundry process, and integrated with a commercially available VCSEL. A transparent VCSEL submount was fabricated with femtosecond laser templating and chemical etching to simplify the passive and active alignment steps. A record-high VCSEL-to-chip coupling efficiency of -5 dB was obtained at a bias current of 2.5 mA. The slope efficiency and output power are competitive with microcavity hybrid silicon lasers. The results show the feasibility of VCSELs as low threshold current on-chip sources for silicon photonics.

Second harmonic generation via femtosecond laser fabrication of poled, quasi-phase-matched waveguides in fused silica.

Second harmonic generation (SHG) is demonstrated in femtosecond laser written waveguides in fused silica through a combination of thermal poling and laser-based quasi-phase-matching (QPM) techniques. Quasi-phase-matching was controlled by the periodic erasure of induced nonlinearity through femtosecond laser erasure. A maximum SHG conversion efficiency of 6.6±0.5×10-5%/W is reported for the fundamental wavelength of 1552.8 nm with a phase-matching bandwidth of 4.4 nm for a 10.0 mm long waveguide. For a shorter sample, an effective second-order nonlinearity of χ(2)=0.012±0.001 pm/V was measured. Chirped QPM structures for wider SHG bandwidths also were demonstrated. Such periodically poled waveguides are promising for introducing nonlinear optical components within the 3D passive optical circuits that can be flexibly formed in fused silica by femtosecond laser writing.

Quantitative ß mapping for calibrated fMRI.

The metabolic and hemodynamic dependencies of the blood oxygenation level-dependent (BOLD) signal form the basis for calibrated fMRI, where the focus is on oxidative energy demanded by neural activity. An important part of calibrated fMRI is the power-law relationship between the BOLD signal and the deoxyhemoglobin concentration, which in turn is related to the ratio between oxidative demand (CMRO2) and blood flow (CBF). The power-law dependence between BOLD signal and deoxyhemoglobin concentration is signified by a scaling exponent ß. Until recently most studies assumed a ß value of 1.5, which is based on numerical simulations of the extravascular BOLD component. Since the basal value of CMRO2 and CBF can vary from subject-to-subject and/or region-to-region, a method to independently measure ß in vivo should improve the accuracy of calibrated fMRI results. We describe a new method for ß mapping through characterizing R2' - the most sensitive relaxation component of BOLD signal (i.e., the reversible magnetic susceptibility component that is predominantly of extravascular origin at high magnetic field) - as a function of intravascular magnetic susceptibility induced by an FDA-approved superparamagnetic contrast agent. In α-chloralose anesthetized rat brain, at 9.4 T, we measured ß values of ~0.8 uniformly across large neocortical swathes, with lower magnitude and more heterogeneity in subcortical areas. Comparison of ß maps in rats anesthetized with medetomidine and α-chloralose revealed that ß is independent of neural activity levels at these resting states. We anticipate that this method for ß mapping can help facilitate calibrated fMRI for clinical studies.