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Hypovitaminosis D is associated with cognitive decline in the elderly, but the issue of causality remains unresolved. Definitive evidence would include the visualization of brain lesions resulting from hypovitaminosis D. The aim of the present article is to determine, through a literature review, the location and nature of possible brain disorders in hypovitaminosis D. We found limited brain-imaging data, which reported ischemic infarcts and white matter hyperintensities in hypovitaminosis D, though did not provide their specific location or report any focal atrophy. Based on the finding of executive dysfunctions (i.e., mental shifting and information updating impairments) in the presence of hypovitaminosis D, we suggest that hypovitaminosis D is associated with a dysfunction of the frontal-subcortical neuronal circuits, particularly the dorsolateral circuit. Further imaging studies are required to corroborate this assumption and to determine whether hypovitaminosis D results in degenerative and / or vascular lesions.

We examined ERP responses during the generation of word associates or mental images in response to concrete and abstract concepts. Of interest were the predictions of dual coding theory (DCT), which proposes that processing lexical concepts depends on functionally independent but interconnected verbal and nonverbal systems. ERP responses were time-locked to either stimulus onset or response to compensate for potential latency differences across conditions. During word associate generation, but not mental imagery, concrete items elicited a greater N400 than abstract items. A concreteness effect emerged at a later time point during the mental imagery task. Data were also analyzed using time-frequency analysis that investigated synchronization of neuronal populations over time during processing. Concrete words elicited an enhanced late going desynchronization of theta-band power (723-938 ms post stimulus onset) during associate generation. During mental imagery, abstract items elicited greater delta-band power from 800 to 1,000 ms following stimulus onset, theta-band power from 350 to 205 ms before response, and alpha-band power from 900 to 800 ms before response. Overall, the findings support DCT in suggesting that lexical concepts are not amodal and that concreteness effects are modulated by tasks that focus participants on verbal versus nonverbal, imagery-based knowledge.

AbstractModels of large-scale brain networks that are informed by the underlying anatomical connectivity contribute to our understanding of the mapping between the structure of the brain and its dynamical function. Connectome-based modelling is a promising approach to a more comprehensive understanding of brain function across spatial and temporal scales, but it must be constrained by multi-scale empirical data from animal models. Here we describe the construction of a macaque (Macaca mulatta and Macaca fascicularis) connectome for whole-cortex simulations in TheVirtualBrain, an open-source simulation platform. We take advantage of available axonal tract-tracing datasets and enhance the existing connectome data using diffusion-based tractography in macaques. We illustrate the utility of the connectome as an extension of TheVirtualBrain by simulating resting-state BOLD-fMRI data and fitting it to empirical resting-state data.

In recent years, rapid technological developments in the field of neuroimaging have provided new methods for assessing residual cognition, detecting consciousness, and even communicating with patients who clinically appear to be in a vegetative state. Here, I highlight some of the major implications of these developments, discuss their scientific, clinical, legal, and ethical relevance, and make my own recommendations for future directions in this field.

AbstractObjectives: Functional magnetic resonance imaging (fMRI) may be adopted as a complementary tool for bedside observation in the disorders of consciousness (DOC). However, the diagnostic value of this technique is still debated because of the lack of accuracy in determining levels of consciousness within a single patient. Recently, Giacino and colleagues (2014) hypothesized that a longitudinal fMRI evaluation may provide a more informative assessment in the detection of residual awareness. The aim of this study was to measure the correspondence between clinically defined level of awareness and neural responses within a single DOC patient. Methods: We used a follow-up fMRI design in combination with a passive speech-processing task. Patient’s consciousness was measured through time by using the Coma Recovery Scale. Results: The patient progressed from a vegetative state (VS) to a minimally conscious state (MCS). Patient’s task-related neural responses mirrored the clinical change from a VS to an MCS. Specifically, while in an MCS, but not a VS, the patient showed a selective recruitment of the left angular gyrus when he listened to a native speech narrative, as compared to the reverse presentation of the same stimulus. Furthermore, the patient showed an increased response in the language-related brain network and a greater deactivation in the default mode network following his progression to an MCS. Conclusions: Our findings indicate that longitudinal assessment of brain responses to passive stimuli can contribute to the definition of the clinical status in individual patients with DOC and represents an adequate counterpart of the bedside assessment during the diagnostic decision-making process. (JINS, 2016, 22, 620–630)

International audience; The technological development and economic of scale for solar photovoltaic (PV), batteries and combined heat and power (CHP) have led to the technical potential for a mass-scale transition to off-grid home electricity production for a significant number of utility customers. However, economic projections on complex hybrid systems utilizing these three technologies is challenging and no comprehensive method is available for guiding decision makers. This paper provides a new method of quantifying the economic viability of off-grid PV+battery+CHP systems by calculating the levelized cost of electricity (LCOE) of the technology to be compared to centralized grid electricity. The analysis is inherently conservative as it does not include the additional value of the heat form the CHP unit. A case study for residential electricity and thermal demand in an extreme worst case environment (Houghton, Michigan) is provided to demonstrate the methodology. The results of this case study show that with reasonable economic assumptions and current costs, PV+battery+CHP systems already provide a potential source of profit for some consumers to leave the grid. A sensitivity analysis for LCOE of such a hybrid system was then carried out on the capital cost of the three energy subsystems , capacity factor of PV and CHP, efficiency of the CHP, natural gas rates, and fuel consumption of the CHP. The results of the sensitivity provide decision makers with clear guides to the LCOE of distributed generation with off-grid PV+battery+CHP systems and offer support to preliminary analysis that indicated a potential increase in grid defection in the U.S. in the near future.

PurposeTo develop and evaluate a local frequency shift (LFS) mapping method specifically designed for multi‐echo acquisitions and multi‐channel receive coils.MethodsThe proposed method uses the pixel‐by‐pixel inter‐echo variance (IEV) as a weighting factor during channel‐combination. Five healthy volunteers were scanned at 7 T. The IEV‐weighted method was quantitatively compared to established (adaptive and Hermitian product) channel‐combination methods with respect to IEV of LFS over the entire brain.ResultsIn all experiments, the IEV‐weighted method generated LFS maps free of artifacts caused by unwrapping errors. Based on measurements of the inter‐echo frequency variance throughout the whole brain, the IEV‐weighted method produced the lowest variation and the best contrast at the edge of the brain.ConclusionThe primary finding of the present study is that accurate LFS maps are achievable if the data from each channel is processed independently prior to combination followed by a weighted combination using IEV as the weighting term. The software is freely available to the scientific community. Magn Reson Med 73:1654–1661, 2015. © 2014 Wiley Periodicals, Inc.