Functional magnetic resonance imaging (fMRI) often involves long scanning durations to ensure the associated brain activity can be detected. However, excessive experimentation can lead to many ...undesirable effects, such as from learning and/or fatigue effects, discomfort for the subject, excessive motion artifacts and loss of sustained attention on task. Overly long experimentation can thus have a detrimental effect on signal quality and accurate voxel activation detection. Here, we propose dynamic experimentation with real-time fMRI using a novel statistically driven approach that invokes early stopping when sufficient statistical evidence for assessing the task-related activation is observed.
Voxel-level sequential probability ratio test (SPRT) statistics based on general linear models (GLMs) were implemented on fMRI scans of a mathematical 1-back task from 12 healthy teenage subjects and 11 teenage subjects born extremely preterm (EPT). This approach is based on likelihood ratios and allows for systematic early stopping based on target statistical error thresholds. We adopt a two-stage estimation approach that allows for accurate estimates of GLM parameters before stopping is considered. Early stopping performance is reported for different first stage lengths, and activation results are compared with full durations. Finally, group comparisons are conducted with both early stopped and full duration scan data. Numerical parallelization was employed to facilitate completion of computations involving a new scan within every repetition time (TR).
Use of SPRT demonstrates the feasibility and efficiency gains of automated early stopping, with comparable activation detection as with full protocols. Dynamic stopping of stimulus administration was achieved in around half of subjects, with typical time savings of up to 33% (4 min on a 12 min scan). A group analysis produced similar patterns of activity for control subjects between early stopping and full duration scans. The EPT group, individually, demonstrated more variability in location and extent of the activations compared to the normal term control group. This was apparent in the EPT group results, reflected by fewer and smaller clusters.
A systematic statistical approach for early stopping with real-time fMRI experimentation has been implemented. This dynamic approach has promise for reducing subject burden and fatigue effects.
Objective: The Cognition Battery of the National Institutes of Heath Toolbox is a commonly utilized set of assessments of neuropsychological abilities, evaluating executive function, attention, ...working memory, processing speed, and episodic memory. We highlight the utility of an advanced statistical model in providing nuanced characterization of neurocognition in an adolescent population. We propose that partially ordered set (POSET) models are well suited to analyze polyfactorial tasks and identify distinct profiles of cognitive functioning. Method: Two models were considered using POSET classification. The first modeled 5 distinct cognitive functions and allowed for multiple functions to contribute to task performance. The second simpler model involved only 2 broader-based functions without polyfactorial task specifications. Existing performance data from 745 adolescents aged 14-17 years were analyzed. Posterior probabilities of classification performance and the discriminatory properties of the estimated response distributions indicated how well the modeling approaches fit the data. Results: The larger first model resulted in 8 profiles or states characterized by combinations of high or low functioning in 5 distinct functions. The simpler second model involved 2 broader-based functions that resulted in 4 states. Comparing model fit criteria, we believe that the finer-grained first model may better reflect the cognitive constructs associated with the tasks. Notably, POSET modeling did not always provide adequate classification of working memory because of the limited design of the Cognition Battery. Conclusions: We demonstrate that the use of POSET models is a feasible approach for detailed analysis of neurocognitive data that can extract information on cognitive functions, even when provided with limited task batteries.
General Scientific Summary
Our study highlights the utility and importance of advanced statistical modeling methods that systematically account for the multifactorial nature of neuropsychological tasks. Such modeling has the potential to reveal individual profiles of cognitive strengths and weaknesses that account for performance across tests. These profiles can then be examined in association with findings from neuroimaging studies or in guiding individually tailoring educational approaches. Importantly, this analysis illustrates how open-source resources such as the National Institutes of Heath Toolbox can enable application of neuropsychological modeling approaches that require moderate to large samples of test response data, such as POSET modeling.
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A key area of research in epilepsy neurological disorder is the characterization of epileptic networks as they form and evolve during seizure events. In this paper, we describe the development and ...application of an integrative workflow to analyze functional and structural connectivity measures during seizure events using stereotactic electroencephalogram (SEEG) and diffusion weighted imaging data (DWI). We computed structural connectivity measures using electrode locations involved in recording SEEG signal data as reference points to filter fiber tracts. We used a new workflow-based tool to compute functional connectivity measures based on non-linear correlation coefficient, which allows the derivation of directed graph structures to represent coupling between signal data. We applied a hierarchical clustering based network analysis method over the functional connectivity data to characterize the organization of brain network into modules using data from 27 events across 8 seizures in a patient with refractory left insula epilepsy. The visualization of hierarchical clustering values as dendrograms shows the formation of connected clusters first within each insulae followed by merging of clusters across the two insula; however, there are clear differences between the network structures and clusters formed across the 8 seizures of the patient. The analysis of structural connectivity measures showed strong connections between contacts of certain electrodes within the same brain hemisphere with higher prevalence in the perisylvian/opercular areas. The combination of imaging and signal modalities for connectivity analysis provides information about a patient-specific dynamical functional network and examines the underlying structural connections that potentially influences the properties of the epileptic network. We also performed statistical analysis of the absolute changes in correlation values across all 8 seizures during a baseline normative time period and different seizure events, which showed decreased correlation values during seizure onset; however, the changes during ictal phases were varied.
The presence of brain amyloid-beta positivity is associated with cognitive impairment and dementia, but whether there are specific aspects of cognition that are most linked to amyloid-beta is ...unclear. Analysis of neuropsychological test data presents challenges since a single test often requires drawing upon multiple cognitive functions to perform well. It can thus be imprecise to link performance on a given test to a specific cognitive function. Our objective was to provide insight into how cognitive functions are associated with brain amyloid-beta positivity among samples consisting of cognitively normal and mild cognitively impaired (MCI) subjects, by using partially ordered set models (POSETs).
We used POSET classification models of neuropsychological test data to classify samples to detailed cognitive profiles using ADNI2 and AIBL data. We considered 3 gradations of episodic memory, cognitive flexibility, verbal fluency, attention and perceptual motor speed, and performed group comparisons of cognitive functioning stratified by amyloid positivity (yes/no) and age (<70, 70-80, 81-90 years). We also employed random forest methods stratified by age to assess the effectiveness of cognitive testing in predicting amyloid positivity, in addition to demographic variables, and
4 allele count.
In ADNI2, differences in episodic memory and attention by amyloid were found for <70, and 70-80 years groups. In AIBL, episodic memory differences were found in the 70-80 years age group. In both studies, no cognitive differences were found in the 81-90 years group. The random forest analysis indicates that variable importance in classification depends on age. Cognitive testing that targets an intermediate level of episodic memory and delayed recall, in addition to
4 allele count, are the most important variables in both studies.
In the ADNI2 and AIBL samples, the associations between specific cognitive abilities and brain amyloid-beta positivity depended on age, but in general episodic memory was most consistently predictive of brain amyloid-beta positivity. Random forest methods and OOB error rates establish the feasibility of predicting the presence of brain beta-amyloid using cognitive testing,
4 genotyping and demographic variables.
The concept of ecological integrity has been applied widely to management of aquatic systems, but still is considered by many to be too vague and difficult to quantify to be useful for managing ...terrestrial systems, particularly across broad areas. Extensive public lands in the western United States are managed for diverse uses such as timber harvest, livestock grazing, energy development, and wildlife conservation, some of which may degrade ecological integrity. We propose a method for assessing ecological integrity on multiple-use lands that identifies the components of integrity and levels in the ecological hierarchy where the assessment will focus, and considers existing policies and management objectives. Both natural reference and societally desired environmental conditions are relevant comparison points. We applied the method to evaluate the ecological integrity of shrublands in Nevada, yielding an assessment based on six indicators of ecosystem structure, function, and composition, including resource- and stressor-based indicators measured at multiple scales. Results varied spatially and among indicators. Invasive plant cover and surface development were highest in shrublands in northwest and southeast Nevada. Departure from reference conditions of shrubland area, composition, patch size, and connectivity was highest in central and northern Nevada. Results may inform efforts to control invasive species and restore shrublands on federal lands in Nevada. We suggest that ecological integrity assessments for multiple-use lands be grounded in existing policies and monitoring programs, incorporate resource- and stressor-based metrics, rely on publicly available data collected at multiple spatial scales, and quantify both natural reference and societally desired resource conditions.
The human leukocyte antigen class II genes
DRB1, DQB1, and
DQA1 are associated with Graves disease (GD), but, because of strong linkage disequilibrium within this region, the primary etiological ...variant(s) remains unknown. In the present study, 871 patients with GD and 621 control subjects were genotyped at the
DRB1, DQB1, and
DQA1 loci. All three loci were associated with GD (
P
=
1.45×
10
−12,
P
=
3.20×
10
−5, and
P
=
9.26×
10
−12, respectively). Stepwise logistic-regression analysis showed that the association could be explained by either
DRB1 or
DQA1 but not by
DQB1. To extend previous results, the amino acid sequence of the exon 2–encoded peptide-binding domain of
DRB1 was predicted for each subject, and, by use of logistic regression, each position was analyzed for association with GD. Of 102 amino acids, 70 were uninformative; of the remaining 32 amino acids, 13 were associated with GD (
P values ranged from
2.20×
10
−4 to
1.2×
10
−12). The strongest association was at position β74. This analysis is consistent with the possibility that position β74 of exon 2 of the DRB1 molecule may have a specific and central role in autoantigen presentation by DRB1 to T lymphocytes. However, we cannot yet exclude a primary role for
DQA1 or for other polymorphisms that affect DRB1 function or expression.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate ...patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre sample of adult epilepsy patients. Diffusion-weighted MRI data were analysed from 1069 healthy controls and 1249 patients: temporal lobe epilepsy with hippocampal sclerosis (n = 599), temporal lobe epilepsy with normal MRI (n = 275), genetic generalized epilepsy (n = 182) and non-lesional extratemporal epilepsy (n = 193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fibre tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at P < 0.001). Across 'all epilepsies' lower fractional anisotropy was observed in most fibre tracts with small to medium effect sizes, especially in the corpus callosum, cingulum and external capsule. There were also less robust increases in mean diffusivity. Syndrome-specific fractional anisotropy and mean diffusivity differences were most pronounced in patients with hippocampal sclerosis in the ipsilateral parahippocampal cingulum and external capsule, with smaller effects across most other tracts. Individuals with temporal lobe epilepsy and normal MRI showed a similar pattern of greater ipsilateral than contralateral abnormalities, but less marked than those in patients with hippocampal sclerosis. Patients with generalized and extratemporal epilepsies had pronounced reductions in fractional anisotropy in the corpus callosum, corona radiata and external capsule, and increased mean diffusivity of the anterior corona radiata. Earlier age of seizure onset and longer disease duration were associated with a greater extent of diffusion abnormalities in patients with hippocampal sclerosis. We demonstrate microstructural abnormalities across major association, commissural, and projection fibres in a large multicentre study of epilepsy. Overall, patients with epilepsy showed white matter abnormalities in the corpus callosum, cingulum and external capsule, with differing severity across epilepsy syndromes. These data further define the spectrum of white matter abnormalities in common epilepsy syndromes, yielding more detailed insights into pathological substrates that may explain cognitive and psychiatric co-morbidities and be used to guide biomarker studies of treatment outcomes and/or genetic research.
The Sloan Digital Sky Survey III (SDSS-III) presents the first spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS). This ninth data release (DR9) of the SDSS project includes ...535,995 new galaxy spectra (median z ~ 0.52), 102,100 new quasar spectra (median z ~ 2.32), and 90,897 new stellar spectra, along with the data presented in previous data releases. These spectra were obtained with the new BOSS spectrograph and were taken between 2009 December and 2011 July. In addition, the stellar parameters pipeline, which determines radial velocities, surface temperatures, surface gravities, and metallicities of stars, has been updated and refined with improvements in temperature estimates for stars with T sub(eff) < 5000 K and in metallicity estimates for stars with Fe/H > -0.5. DR9 includes new stellar parameters for all stars presented in DR8, including stars from SDSS-I and II, as well as those observed as part of the SEGUE-2. The astrometry error introduced in the DR8 imaging catalogs has been corrected in the DR9 data products. The next data release for SDSS-III will be in Summer 2013, which will present the first data from the APOGEE along with another year of data from BOSS, followed by the final SDSS-III data release in 2014 December.
The regulatory mechanisms involved in tendon homeostasis and repair are not fully understood. Accumulating data, however, demonstrate that the nervous system, in addition to afferent (sensory) ...functions, through efferent pathways plays an active role in regulating pain, inflammation, and tissue repair. In normal-, healing- and tendinopathic tendons three neurosignalling pathways consisting of autonomic, sensory and glutamatergic neuromediators have been established. In healthy tendons, neuromediators are found in the paratenon, whereas the proper tendon is practically devoid of nerves, reflecting that normal tendon homeostasis is regulated by pro- and anti-inflammatory mediators from the tendon surroundings. During tendon repair, however, there is extensive nerve ingrowth into the tendon proper and subsequent time-dependent appearance of sensory, autonomic and glutamatergic mediators, which amplify and fine-tune inflammation and tendon regeneration. In tendinopathy, excessive and protracted sensory and glutamatergic signalling may be involved in inflammatory, painful and hypertrophic tissue reactions. As our understanding of these processes improves, neuronal mediators may prove to be useful in the development of targeted pharmacotherapy and tissue engineering approaches to painful, degenerative and traumatic tendon disorders.
Genome-wide linkage disequilibrium (LD) mapping of common disease genes could be more powerful than linkage analysis if the appropriate density of polymorphic markers were known and if the genotyping ...effort and cost of producing such an LD map could be reduced. Although different metrics that measure the extent of LD have been evaluated, even the most recent studies have not placed significant emphasis on the most informative and cost-effective method of LD mapping-that based on haplotypes. We have scanned 135 kb of DNA from nine genes, genotyped 122 single-nucleotide polymorphisms (SNPs; approximately 184,000 genotypes) and determined the common haplotypes in a minimum of 384 European individuals for each gene. Here we show how knowledge of the common haplotypes and the SNPs that tag them can be used to (i) explain the often complex patterns of LD between adjacent markers, (ii) reduce genotyping significantly (in this case from 122 to 34 SNPs), (iii) scan the common variation of a gene sensitively and comprehensively and (iv) provide key fine-mapping data within regions of strong LD. Our results also indicate that, at least for the genes studied here, the current version of dbSNP would have been of limited utility for LD mapping because many common haplotypes could not be defined. A directed re-sequencing effort of the approximately 10% of the genome in or near genes in the major ethnic groups would aid the systematic evaluation of the common variant model of common disease.
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