Towards a model-based integration of co-registered electroencephalography/functional magnetic resonance imaging data with realistic neural population meshes

Brain activity can be measured with several non-invasive neuroimaging modalities, but each modality has inherent limitations with respect to resolution, contrast and interpretability. It is hoped that multimodal integration will address these limitations by using the complementary features of already available data. However, purely statistical integration can prove problematic owing to the disparate signal sources. As an alternative, we propose here an advanced neural population model implemented on an anatomically sound cortical mesh with freely adjustable connectivity, which features proper signal expression through a realistic head model for the electroencephalogram (EEG), as well as a haemodynamic model for functional magnetic resonance imaging based on blood oxygen level dependent contrast (fMRI BOLD). It hence allows simultaneous and realistic predictions of EEG and fMRI BOLD from the same underlying model of neural activity. As proof of principle, we investigate here the influence on simulated brain activity of strengthening visual connectivity. In the future we plan to fit multimodal data with this neural population model. This promises novel, model-based insights into the brain's activity in sleep, rest and task conditions.

Analysis of diffusion tensor magnetic resonance imaging data using principal component analysis

An analysis method for diffusion tensor (DT) magnetic resonance imaging data is described, which, contrary to the standard method (multivariate fitting), does not require a specific functional model for diffusion-weighted (DW) signals. The method uses principal component analysis (PCA) under the assumption of a single fibre per pixel. PCA and the standard method were compared using simulations and human brain data. The two methods were equivalent in determining fibre orientation. PCA-derived fractional anisotropy and DT relative anisotropy had similar signal-to-noise ratio (SNR) and dependence on fibre shape. PCA-derived mean diffusivity had similar SNR to the respective DT scalar, and it depended on fibre anisotropy. Appropriate scaling of the PCA measures resulted in very good agreement between PCA and DT maps. In conclusion, the assumption of a specific functional model for DW signals is not necessary for characterization of anisotropic diffusion in a single fibre.

Magnetic resonance imaging of a randomized controlled trial investigating predictors of recovery following psychological treatment in adolescents with moderate to severe unipolar depression: study protocol for Magnetic Resonance - Improving Mood with Psychoanalytic and Cognitive Therapies (MR-IMPACT)

Background Major depressive disorders (MDD) are a debilitating and pervasive group of mental illnesses afflicting many millions of people resulting in the loss of 110 million working days and more than 2,500 suicides per annum. Adolescent MDD patients attending NHS clinics show high rates of recurrence into adult life. A meta-analysis of recent research shows that psychological treatments are not as efficacious as previously thought. Modest treatment outcomes of approximately 65% of cases responding suggest that aetiological and clinical heterogeneity may hamper the better use of existing therapies and discovery of more effective treatments. Information with respect to optimal treatment choice for individuals is lacking, with no validated biomarkers to aid therapeutic decision-making. Methods/Design Magnetic resonance-Improving Mood with Psychoanalytic and Cognitive Therapies, the MR-IMPACT study, plans to identify brain regions implicated in the pathophysiology of depressions and examine whether there are specific behavioural or neural markers predicting remission and/or subsequent relapse in a subsample of depressed adolescents recruited to the IMPACT randomised controlled trial (Registration # ISRCTN83033550). Discussion MR-IMPACT is an investigative biomarker component of the IMPACT pragmatic effectiveness trial. The aim of this investigation is to identify neural markers and regional indicators of the pathophysiology of and treatment response for MDD in adolescents. We anticipate that these data may enable more targeted treatment delivery by identifying those patients who may be optimal candidates for therapeutic response.

Transmission of wireless power by magnetic resonance

The work involves investigation of a type of wireless power system wherein its analysis will yield the construction of a prototype modeled as a singular technological artifact. It is through exploration of the artifact that forms the intellectual basis for not only its prototypical forms, but suggestive of variant forms not yet discovered. Through the process it is greatly clarified the role of the artifact, its most suitable application given the constraints on the delivery problem, and optimization strategies to improve it. In order to improve maturity and contribute to a body of knowledge, this document proposes research utilizing mid-field region, efficient inductive-transfer for the purposes of removing wired connections and electrical contacts. While the description seems enough to state the purpose of this work, it does not convey the compromises of having to redraw the lines of demarcation between near and far-field in the traditional method of broadcasting. Two striking scenarios are addressed in this thesis: Firstly, the mathematical explanation of wireless power is due to J.C. Maxwell's original equations, secondly, the behavior of wireless power in the circuit is due to Joseph Larmor's fundamental works on the dynamics of the field concept. A model of propagation will be presented which matches observations in experiments. A modified model of the dipole will be presented to address the phenomena observed in the theory and experiments. Two distinct sets of experiments will test the concept of single and two coupled-modes. In a more esoteric context of the zero and first-order magnetic field, the suggestion of a third coupled-mode is presented. Through the remaking of wireless power in this context, it is the intention of the author to show the reader that those things lost to history, bound to a path of complete obscurity, are once again innovative and useful ideas.

Neonatal environment exerts a sustained influence on the development of the intestinal microbiota and metabolic phenotype

The postnatal environment, including factors such as weaning and acquisition of the gut microbiota, has been causally linked to the development of later immunological diseases such as allergy and autoimmunity, and has also been associated with a predisposition to metabolic disorders. We show that the very early-life environment influences the development of both the gut microbiota and host metabolic phenotype in a porcine model of human infants. Farmpiglets were nursed by their mothers for 1 day, before removal to highly controlled, individual isolators where they received formula milk until weaning at 21 days. The experiment was repeated, to create two batches, which differed only in minor environmental fluctuations during the first day. At day 1 after birth, metabolic profiling of serum by 1H nuclear magnetic resonance spectroscopy demonstrated significant, systemic, inter-batch variation which persisted until weaning. However, the urinary metabolic profiles demonstrated that significant inter-batch effects on 3-hydroxyisovalerate, trimethylamine-N-oxide and mannitol persisted beyond weaning to at least 35 days. Batch effects were linked to significant differences in the composition of colonic microbiota at 35 days, determined by 16 S pyrosequencing. Different weaning diets modulated both the microbiota and metabolic phenotype independently of the persistent batch effects. We demonstrate that the environment during the first day of life influences development of the microbiota and metabolic phenotype and thus should be taken into account when interrogating experimental outcomes. In addition, we suggest that intervention at this early time could provide ‘metabolic rescue’ for at-risk infants who have undergone aberrant patterns of initial intestinal colonisation.

Evaluation of optical techniques for characterising soil organic matter quality in agricultural soils

Soil organic matter (SOM) is one of the main global carbon pools. It is a measure of soil quality as its presence increases carbon sequestration and improves physical and chemical soil properties. The determination and characterisation of humic substances gives essential information of the maturity and stresses of soils as well as of their health. However, the determination of the exact nature and molecular structure of these substances has been proven difficult. Several complex techniques exist to characterise SOM and mineralisation and humification processes. One of the more widely accepted for its accuracy is nuclear magnetic resonance (NMR) spectroscopy. Despite its efficacy, NMR needs significant economic resources, equipment, material and time. Proxy measures like the fluorescence index (FI), cold and hot-water extractable carbon (CWC and HWC) and SUVA-254 have the potential to characterise SOM and, in combination, provide qualitative and quantitative data of SOM and its processes. Spanish and British agricultural cambisols were used to measure SOM quality and determine whether similarities were found between optical techniques and 1H NMR results in these two regions with contrasting climatic conditions. High correlations (p < 0.001) were found between the specific aromatic fraction measured with 1H NMR and SUVA-254 (Rs = 0.95) and HWC (Rs = 0.90), which could be described using a linear model. A high correlation between FI and the aromatics fraction measured with 1H NMR (Rs = −0.976) was also observed. In view of our results, optical measures have a potential, in combination, to predict the aromatic fraction of SOM without the need of expensive and time consuming techniques.

Soil phosphorus dynamics and phytoavailability from sewage sludge at different stages in a treatment stream

The effect of different stages of sewage sludge treatment on phosphorus (P) dynamics in amended soils was determined using samples of undigested liquid (UL), anaerobically digested liquid (AD) and dewatered anaerobically digested (DC) sludge. Sludges were taken from three points in the same treatment stream and applied to a sandy loam soil in field-based mesocosms at 4, 8 and 16t ha−1 dry solids. Mesocosms were sown with perennial ryegrass (Lolium perenne cv. Melle), and the sward was harvested after 35 and 70 days to determine yield and foliar P concentration. Soils were also sampled during this period to measure P transformations and the activities of acid phosphomonoesterase and phosphodiesterase. Data show that the AD amended soils had the greatest plant-available and foliar P content up to the second harvest, but the UL amended soils had the greatest enzyme activity. Characterisation of control and 16t ha−1 soils and sludge using solution 31P nuclear magnetic resonance (NMR) spectroscopy after NaOH–EDTA extraction revealed that P was predominantly in the inorganic pool in all three sludge samples, with the highest proportion (of the total extracted P) as inorganic P in the anaerobically digested liquid sludge. After sludge incorporation, P was immobilised to organic species. The majority of organic P was in monoester-P forms, while the remainder of organic P (diester P and phosphonate P) was more susceptible to transformations through time and showed variation with sludge type. These results show that application of sewage sludge at rates as low as 4t ha−1 can have a significant nutritional benefit to ryegrass over an initial 35-day growth and subsequent 35-day re-growth periods. Differences in P transformation, and hence nutritional benefit, between sludge types were evident throughout the experiment. Thus, differences in sludge treatment process alter the edaphic mineralisation characteristics of biosolids derived from the same source material.