Brain charts for the human lifespan.

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

Brain age predicts mortality.

Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, 'brain-predicted age', derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N=2001), then tested in the Lothian Birth Cohort 1936 (N=669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death.

Optical vector network analysis of ultranarrow transitions in 166Er3+ : 7LiYF4 crystal.

We present optical vector network analysis (OVNA) of an isotopically purified Er1663+:LiYF47 crystal. The OVNA method is based on generation and detection of a modulated optical sideband by using a radio-frequency vector network analyzer. This technique is widely used in the field of microwave photonics for the characterization of optical responses of optical devices such as filters and high-Q resonators. However, dense solid-state atomic ensembles induce a large phase shift on one of the optical sidebands that results in the appearance of extra features on the measured transmission response. We present a simple theoretical model that accurately describes the observed spectra and helps to reconstruct the absorption profile of a solid-state atomic ensemble as well as corresponding change of the refractive index in the vicinity of atomic resonances.

Common and distinct patterns of grey-matter volume alteration in major depression and bipolar disorder: evidence from voxel-based meta-analysis.

Finding robust brain substrates of mood disorders is an important target for research. The degree to which major depression (MDD) and bipolar disorder (BD) are associated with common and/or distinct patterns of volumetric changes is nevertheless unclear. Furthermore, the extant literature is heterogeneous with respect to the nature of these changes. We report a meta-analysis of voxel-based morphometry (VBM) studies in MDD and BD. We identified studies published up to January 2015 that compared grey matter in MDD (50 data sets including 4101 individuals) and BD (36 data sets including 2407 individuals) using whole-brain VBM. We used statistical maps from the studies included where available and reported peak coordinates otherwise. Group comparisons and conjunction analyses identified regions in which the disorders showed common and distinct patterns of volumetric alteration. Both disorders were associated with lower grey-matter volume relative to healthy individuals in a number of areas. Conjunction analysis showed smaller volumes in both disorders in clusters in the dorsomedial and ventromedial prefrontal cortex, including the anterior cingulate cortex and bilateral insula. Group comparisons indicated that findings of smaller grey-matter volumes relative to controls in the right dorsolateral prefrontal cortex and left hippocampus, along with cerebellar, temporal and parietal regions were more substantial in major depression. These results suggest that MDD and BD are characterised by both common and distinct patterns of grey-matter volume changes. This combination of differences and similarities has the potential to inform the development of diagnostic biomarkers for these conditions.

The neuroanatomy of subthreshold depressive symptoms in Huntington's disease: a combined diffusion tensor imaging (DTI) and voxel-based morphometry (VBM) study.

BACKGROUND: Depressive symptoms are prominent psychopathological features of Huntington's disease (HD), making a negative impact on social functioning and well-being. METHOD: We compared the frequencies of a history of depression, previous suicide attempts and current subthreshold depression between 61 early-stage HD participants and 40 matched controls. The HD group was then split based on the overall HD group's median Hospital Anxiety and Depression Scale-depression score into a group of 30 non-depressed participants (mean 0.8, s.d. = 0.7) and a group of 31 participants with subthreshold depressive symptoms (mean 7.3, s.d. = 3.5) to explore the neuroanatomy underlying subthreshold depressive symptoms in HD using voxel-based morphometry (VBM) and diffusion tensor imaging (DTI). RESULTS: Frequencies of history of depression, previous suicide attempts or current subthreshold depressive symptoms were higher in HD than in controls. The severity of current depressive symptoms was also higher in HD, but not associated with the severity of HD motor signs or disease burden. Compared with the non-depressed HD group DTI revealed lower fractional anisotropy (FA) values in the frontal cortex, anterior cingulate cortex, insula and cerebellum of the HD group with subthreshold depressive symptoms. In contrast, VBM measures were similar in both HD groups. A history of depression, the severity of HD motor signs or disease burden did not correlate with FA values of these regions. CONCLUSIONS: Current subthreshold depressive symptoms in early HD are associated with microstructural changes - without concomitant brain volume loss - in brain regions known to be involved in major depressive disorder, but not those typically associated with HD pathology.

A neuroimaging measure to capture heterogeneous patterns of atrophy in Parkinson's disease and dementia with Lewy bodies.

INTRODUCTION: Parkinson's disease (PD) and Dementia with Lewy bodies (DLB) show heterogeneous brain atrophy patterns which group-average analyses fail to capture. Neuroanatomical normative modelling overcomes this by comparing individuals to a large reference cohort. Patient-specific atrophy patterns are measured objectively and summarised to index overall neurodegeneration (the 'total outlier count'). We aimed to quantify patterns of neurodegenerative dissimilarity in participants with PD and DLB and evaluate the potential clinical relevance of total outlier count by testing its association with key clinical measures in PD and DLB. MATERIALS AND METHODS: We included 108 participants with PD and 61 with DLB. PD participants were subclassified into high and low visual performers as this has previously been shown to stratify those at increased dementia risk. We generated z-scores from T1w-MRI scans for each participant relative to normative regional cortical thickness and subcortical volumes, modelled in a reference cohort (n = 58,836). Outliers (z < -1.96) were aggregated across 169 brain regions per participant. To measure dissimilarity, individuals' Hamming distance scores were calculated. We also examined total outlier counts between high versus low visual performance in PD; and PD versus DLB; and tested associations between these and cognition. RESULTS: There was significantly greater inter-individual dissimilarity in brain-outlier patterns in PD poor compared to high visual performers (W = 522.5; p < 0.01) and in DLB compared to PD (W = 5649; p < 0.01). PD poor visual performers had significantly greater total outlier counts compared to high (ß = -4.73 (SE = 1.30); t = -3.64; p < 0.01) whereas a conventional group-level GLM failed to identify differences. Higher total outlier counts were associated with poorer MoCA (ß = -0.55 (SE = 0.27), t = -2.04, p = 0.05) and composite cognitive scores (ß = -2.01 (SE = 0.79); t = -2.54; p = 0.02) in DLB, and visuoperception (ß = -0.67 (SE = 0.19); t = -3.59; p < 0.01), in PD. CONCLUSIONS: Neuroanatomical normative modelling shows promise as a clinically informative technique in PD and DLB, where patterns of atrophy are variable.

Medical operations in the 21st century: application of TAK among wartime medical assets.

Advances in technology have improved the ability for real-time communication and enhanced awareness of medically related information on the battlefield. A government off-the-shelf platform, Team Awareness Kit (TAK), may enhance the ability for battlefield healthcare delivery, evacuation, telecommunication, and medical command and control. Integration of TAK into existing medical infrastructure provides a global view of resources, patient movement and direct communication, significantly reducing the 'fog of war' as it relates to battlefield injury and evacuation. Rapid integration and adoption are technically feasible with minimal resource investment. This technology can be rapidly scaled for the increasingly interconnected world of healthcare delivery.

Thalamic white matter macrostructure and subnuclei volumes in Parkinson's disease depression.

Depression is a common non-motor feature of Parkinson's disease (PD) which confers significant morbidity and is challenging to treat. The thalamus is a key component in the basal ganglia-thalamocortical network critical to the pathogenesis of PD and depression but the precise thalamic subnuclei involved in PD depression have not been identified. We performed structural and diffusion-weighted imaging (DWI) on 76 participants with PD to evaluate the relationship between PD depression and grey and white matter thalamic subnuclear changes. We used a thalamic segmentation method to divide the thalamus into its 50 constituent subnuclei (25 each hemisphere). Fixel-based analysis was used to calculate mean fibre cross-section (FC) for white matter tracts connected to each subnucleus. We assessed volume and FC at baseline and 14-20 months follow-up. A generalised linear mixed model was used to evaluate the relationship between depression, subnuclei volume and mean FC for each thalamic subnucleus. We found that depression scores in PD were associated with lower right pulvinar anterior (PuA) subnucleus volume. Antidepressant use was associated with higher right PuA volume suggesting a possible protective effect of treatment. After follow-up, depression scores were associated with reduced white matter tract macrostructure across almost all tracts connected to thalamic subnuclei. In conclusion, our work implicates the right PuA as a relevant neural structure in PD depression and future work should evaluate its potential as a therapeutic target for PD depression.

Measuring the temperature dependence of individual two-level systems by direct coherent control.

We demonstrate a new method to directly manipulate the state of individual two-level systems (TLSs) in phase qubits. It allows one to characterize the coherence properties of TLSs using standard microwave pulse sequences, while the qubit is used only for state readout. We apply this method to measure the temperature dependence of TLS coherence for the first time. The energy relaxation time T1 is found to decrease quadratically with temperature for the two TLSs studied in this work, while their dephasing time measured in Ramsey and spin-echo experiments is found to be T1 limited at all temperatures.

Sensing of fluctuating nanoscale magnetic fields using nitrogen-vacancy centers in diamond.

New magnetometry techniques based on nitrogen-vacancy (NV) defects in diamond allow for the detection of static (dc) and oscillatory (ac) nanoscopic magnetic fields, yet are limited in their ability to detect fields arising from randomly fluctuating (FC) environments. We show here that FC fields restrict dc and ac sensitivities and that probing the NV dephasing rate in a FC environment should permit the characterization of FC fields inaccessible to dc and ac techniques. FC sensitivities are shown to be comparable to those of ac magnetometry and require no additional experimental overhead or sample control.

Ab initio calculation of energy levels for phosphorus donors in silicon.

The s manifold energy levels for phosphorus donors in silicon are important input parameters for the design and modeling of electronic devices on the nanoscale. In this paper we calculate these energy levels from first principles using density functional theory. The wavefunction of the donor electron's ground state is found to have a form that is similar to an atomic s orbital, with an effective Bohr radius of 1.8 nm. The corresponding binding energy of this state is found to be 41 meV, which is in good agreement with the currently accepted value of 45.59 meV. We also calculate the energies of the excited 1s(T 2) and 1s(E) states, finding them to be 32 and 31 meV respectively.

Bone density in young women is associated with body weight and muscle strength but not dietary intakes.

Potential determinants of bone mineral density (BMD) were studied cross-sectionally in 115 healthy, sexually mature Caucasian women aged 18 years. Bone mineral density (Hologic QDR1000W) of the lumbar spine, proximal femur (five sites), and distal tibia and fibula; fasting blood and urine calcium biochemistry; serum sex hormone levels (follicular phase); nutrient intakes; aerobic fitness; trunk muscle strength; and habitual activity levels were measured. The effects of heredity were considered by measuring the BMD of 107 of the subjects' mothers. Simple and stepwise regression analysis were used to identify significant determinants of BMD at each of the regions studied. The analysis indicated that significant bivariate correlations exist between BMD at all sites and body weight (r = 0.23-0.47, p < or = 0.01), lean body weight (r = 0.34-0.46), trunk strength (r = 0.27-0.47), physical activity score (r = 0.20-0.25), and aerobic fitness (r = 0.29-0.45). Dietary calcium intake correlated significantly with BMD at the trochanter site only (r = 0.19), and none of the biochemical or hormonal indices measured correlated consistently with BMD at any site. Significant correlations between the BMD of mothers and daughters ranged from r = 0.43 at lumbar spine to r = 0.34 at the intertrochanteric site. Paired t-tests showed the daughters had significantly (p < 0.03) lower BMD than their mothers at the lumbar spine (98 +/- 12% [mean +/- SD]) and significantly higher (p < 0.002) BMD at the femoral neck, trochanter, and total hip sites (110 +/- 16%, 108 +/- 17%, 103 +/- 14%, respectively). When stepwise regression analysis included weight-corrected strength of the trunk flexor muscles (Corr Flex), weight-corrected aerobic fitness (Corr VO2max), physical activity score, and body weight, body weight was the only significant determinant of BMD at all sites. Corr Flex made significant contributions at all sites except the femoral neck, while Corr VO2max made additional contribution at the femoral neck, trochanter, total hip, and shaft of femur sites. These variables accounted for 13-27% of the variance in BMD. The addition of mother's BMD to these independent variables, in stepwise regression analysis, improved the prediction to 18-31% of the variance.

The student selection process in three countries.

Of ninety institutions in three countries surveyed by a mail questionnaire, responses were received from 68 baccalaureate programmes in physiotherapy, a return rate of 76%. Selection criteria for all programmes were shown to be multiple, with the student's previous academic achievement used in every instance. A proportion of programmes indicated the use of objective measures of ability, interest and personality but rarely were these used in any combination. The majority of programmes use the interview, references, student's objectives and experience in physical therapy in combination. No respondents indicated specific weighting for any of these factors and the questionnaire did not seek this information specifically.

Movement dysfunction in patients with Parkinson's disease: A literature review.

Experimental evidence has shown that people with Parkinson's disease have deficits in the initiation and execution of movements. The delay in response initiation may be due to impairment in the organisation or translation of motor programs into muscle actions. The slowness in the execution of simple movements may result from inappropriate scaling of muscle activity, defective predictive function or defective memory for the computed forces. Extra slowness in the execution of complicated concurrent movements appears to be a result of deficits in switching from one program to another within a motor plan in sequential movements, or in superimposition of motor programs to form a motor plan in simultaneous movements.

Body mass index, but not FTO genotype or major depressive disorder, influences brain structure.

Obesity and major depressive disorder (MDD) are highly prevalent and often comorbid health conditions. Both are associated with differences in brain structure and are genetically influenced. Yet, little is known about how obesity, MDD, and known risk genotypes might interact in the brain. Subjects were 81 patients with MDD (mean age 48.6 years) and 69 matched healthy controls (mean age 51.2 years). Subjects underwent 1.5T magnetic resonance imaging, genotyping for the fat mass and obesity associated (FTO) gene rs3751812 polymorphism, and measurements for body mass index (BMI). We conducted a whole brain voxelwise analysis using tensor-based morphometry (TBM) to examine the main and interaction effects of diagnosis, BMI and FTO genotype. Significant effects of BMI were observed across widespread brain regions, indicating reductions in predominantly subcortical and white matter areas associated with increased BMI, but there was no influence of MDD or FTO rs3751812 genotype. There were no significant interaction effects. Within MDD patients, there was no effect of current depressive symptoms; however the use of antidepressant medication was associated with reductions in brain volume in the frontal lobe and cerebellum. Obesity affects brain structure in both healthy participants and MDD patients; this influence may account for some of the brain changes previously associated with MDD. BMI and the use of medication should ideally be measured and controlled for when conducting structural brain imaging research in MDD.

High spatial and temporal resolution wide-field imaging of neuron activity using quantum NV-diamond.

A quantitative understanding of the dynamics of biological neural networks is fundamental to gaining insight into information processing in the brain. While techniques exist to measure spatial or temporal properties of these networks, it remains a significant challenge to resolve the neural dynamics with subcellular spatial resolution. In this work we consider a fundamentally new form of wide-field imaging for neuronal networks based on the nanoscale magnetic field sensing properties of optically active spins in a diamond substrate. We analyse the sensitivity of the system to the magnetic field generated by an axon transmembrane potential and confirm these predictions experimentally using electronically-generated neuron signals. By numerical simulation of the time dependent transmembrane potential of a morphologically reconstructed hippocampal CA1 pyramidal neuron, we show that the imaging system is capable of imaging planar neuron activity non-invasively at millisecond temporal resolution and micron spatial resolution over wide-fields.

Acoustic sensitivity of single-mode optical power dividers.

The acoustic sensitivity of previously reported evanescent-field fiber couplers has been measured. The measured values were substantially larger than the values calculated from our theoretical model. A qualitative explanation of this discrepancy is presented.

Microbend fiber-optic sensor.

Intensity modulation induced by microbending in multimode fibers is considered as a transduction mechanism for detecting environmental changes such as pressure, temperature, acceleration, and magnetic and electric fields. A generic microbend sensor has been defined and studied, and its components, such as sensing fiber, light source, optical fiber leads, and detector, have been examined and optimized. Finally, the generic microbend sensor has been tested demonstrating good performance.

Sensitive, high-speed thermometry using optical fibers.

The use of aluminum-jacketed optical fibers for sensitive, high-speed thermometry is demonstrated. Sensitivity of the fiber to thermal variations is observed at frequencies up to 30 kHz. Although the presence of configurationdependent mechanical resonances between 10 and 22 kHz precludes a simple analysis of the thermal response at these frequencies, the response between 5 Hz and 4 kHz is in reasonable agreement with analytic results. Assuming a minimum-detectable phase change of 10(-6) rad, the observed sensitivity at 4 kHz corresponds to a minimum detectable temperature variation of 1 microK for a 1-cm length of fiber. This performance represents orders-of-magnitude improvement in both sensitivity and frequency response relative to those of commercially available temperature-smeasuring systems.