Crystallized and fluid intelligence are predicted by microstructure of specific white-matter tracts

Studies of the neural basis of intelligence have focused on comparing brain imaging variables with global scales instead of the cognitive domains integrating these scales or quotients. Here, the relation between mean tract‐based fractional anisotropy (mTBFA) and intelligence indices was explored. Deterministic tractography was performed using a regions of interest approach for 10 white‐matter fascicles along which the mTBFA was calculated. The study sample included 83 healthy individuals from the second wave of the Cuban Human Brain Mapping Project, whose WAIS‐III intelligence quotients and indices were obtained. Inspired by the “Watershed model” of intelligence, we employed a regularized hierarchical Multiple Indicator, Multiple Causes model (MIMIC), to assess the association of mTBFA with intelligence scores, as mediated by latent variables summarizing the indices. Regularized MIMIC, used due to the limited sample size, selected relevant mTBFA by means of an elastic net penalty and achieved good fits to the data. Two latent variables were necessary to describe the indices: Fluid intelligence (Perceptual Organization and Processing Speed indices) and Crystallized Intelligence (Verbal Comprehension and Working Memory indices). Regularized MIMIC revealed effects of the forceps minor tract on crystallized intelligence and of the superior longitudinal fasciculus on fluid intelligence. The model also detected the significant effect of age on both latent variables

Mathematical modeling and forecasting of COVID-19: experience in Santiago de Cuba province

In the province of Santiago de Cuba, Cuba, the COVID-19 epidemic has a limited progression that shows an early small-number peak of infections. Most published mathematical models fit data with high numbers of confirmed cases. In contrast, small numbers of cases make it difficult to predict the course of the epidemic. We present two known models adapted to capture the noisy dynamics of COVID-19 in the Santiago de Cuba province. Parameters of both models were estimated using the approximate-Bayesian-computation framework with dedicated error laws. One parameter of each model was updated on key dates of travel restrictions. Both models approximately predicted the infection peak and the end of the COVID-19 epidemic in Santiago de Cuba. The first model predicted 57 reported cases and 16 unreported cases. Additionally, it estimated six initially exposed persons. The second model forecasted 51 confirmed cases at the end of the epidemic. In conclusion, an opportune epidemiological investigation, along with the low number of initially exposed individuals, might partly explain the favorable evolution of the COVID-19 epidemic in Santiago de Cuba. With the available data, the simplest model predicted the epidemic evolution with greater precision, and the more complex model helped to explain the epidemic phenomenology

Finding electrophysiological sources of aging-related processes using penalized least squares with Modified Newton-Raphson algorithm

In this work, we evaluate the flexibility of a modified Newton-Raphson (MNR) algorithm for finding electrophysiological sources in both simulated and real data, and then apply it to different penalized models in order to compare the sources of the EEG theta rhythm in two groups of elderly subjects with different levels of declined physical performance. As a first goal, we propose the MNR algorithm for estimating general multiple penalized least squares (MPLS) models and show that it is capable to find solutions that are simultaneously sparse and smooth. This algorithm allowed to address known and novel models such as the Smooth Non-negative Garrote and the Non-negative Smooth LASSO. We test its ability to solve the EEG inverse problem with multiple penalties -using simulated data- in terms of localization error, blurring and visibility, as compared with traditional algorithms. As a second goal, we explore the electrophysiological sources of the theta activity extracted from resting-state EEG recorded in two groups of older adults, which belong to a longitudinal study to assess the relationship between measures of physical performance (gait speed) decline and normal cognition. The groups contained subjects with good and bad physical performance in the two evaluations (6 years apart). In accordance to clinical studies, we found differences in EEG theta sources for the two groups, specifically, subjects with declined physical performance presented decreased temporal sources while increased prefrontal sources that seem to reflect compensating mechanisms to ensure a stable walking

Regularized logistic regression and multi-objective variable selection for classifying MEG data

This paper addresses the question of maximizing classifier accuracy for classifying task-related mental activity from Magnetoencelophalography (MEG) data. We propose the use of different sources of information and introduce an automatic channel selection procedure. To determine an informative set of channels, our approach combines a variety of machine learning algorithms: feature subset selection methods, classifiers based on regularized logistic regression, information fusion, and multiobjective optimization based on probabilistic modeling of the search space. The experimental results show that our proposal is able to improve classification accuracy compared to approaches whose classifiers use only one type of MEG information or for which the set of channels is fixed a priori

Documento de posición sobre las necesidades y niveles óptimos de vitamina D

IntroducciónEn los últimos años se ha producido un notable interés por la vitamina D, no sólo por su importancia crucial en el metabolismo mineral óseo, sino también por los efectos extraóseos, cada vez mejor conocidos. Asi mismo, se ha constatado la existencia de valores séricos bajos de vitamina D, por debajo de lo deseable, en diferentes poblaciones, tanto sanas como enfermas, y se discute cuáles serían los niveles óptimos de vitamina D en sangre. Por todo ello, la Sociedad Española de Investigación Ósea y Metabolismo Mineral (SEIOMM), conjuntamente con todas las Sociedades Científicas implicadas en el estudio del metabolismo óseo, han elaborado el presente documento de posición sobre las necesidades y niveles óptimos de vitamina D

New approaches to the study of human brain networks underlying spatial attention and related processes

Cognitive processes, such as spatial attention, are thought to rely on extended networks in the human brain. Both clinical data from lesioned patients and fMRI data acquired when healthy subjects perform particular cognitive tasks typically implicate a wide expanse of potentially contributing areas, rather than just a single brain area. Conversely, evidence from more targeted interventions, such as transcranial magnetic stimulation (TMS) or invasive microstimulation of the brain, or selective study of patients with highly focal brain damage, can sometimes indicate that a single brain area may make a key contribution to a particular cognitive process. But this in turn raises questions about how such a brain area may interface with other interconnected areas within a more extended network to support cognitive processes. Here, we provide a brief overview of new approaches that seek to characterise the causal role of particular brain areas within networks of several interacting areas, by measuring the effects of manipulations for a targeted area on function in remote interconnected areas. In human participants, these approaches include concurrent TMS-fMRI and TMS-EEG, as well as combination of the focal lesion method in selected patients with fMRI and/or EEG measures of the functional impact from the lesion on interconnected intact brain areas. Such approaches shed new light on how frontal cortex and parietal cortex modulate sensory areas in the service of attention and cognition, for the normal and damaged human brain

To the Cloud! A Grassroots Proposal to Accelerate Brain Science Discovery

The revolution in neuroscientific data acquisition is creating an analysis challenge. We propose leveraging cloud-computing technologies to enable large-scale neurodata storing, exploring, analyzing, and modeling. This utility will empower scientists globally to generate and test theories of brain function and dysfunctio

Country-level gender inequality is associated with structural differences in the brains of women and men

Gender inequality across the world has been associated with a higher risk to mental health problems and lower academic achievement in women compared to men. We also know that the brain is shaped by nurturing and adverse socio-environmental experiences. Therefore, unequal exposure to harsher conditions for women compared to men in gender-unequal countries might be reflected in differences in their brain structure, and this could be the neural mechanism partly explaining women's worse outcomes in gender-unequal countries. We examined this through a random-effects meta-analysis on cortical thickness and surface area differences between adult healthy men and women, including a meta-regression in which country-level gender inequality acted as an explanatory variable for the observed differences. A total of 139 samples from 29 different countries, totaling 7,876 MRI scans, were included. Thickness of the right hemisphere, and particularly the right caudal anterior cingulate, right medial orbitofrontal, and left lateral occipital cortex, presented no differences or even thicker regional cortices in women compared to men in gender-equal countries, reversing to thinner cortices in countries with greater gender inequality. These results point to the potentially hazardous effect of gender inequality on women's brains and provide initial evidence for neuroscience-informed policies for gender equality

Understanding the role of the perivascular space in cerebral small vessel disease

Small vessel diseases are a group of disorders that result from pathological alteration of the small blood vessels in the brain, including the small arteries, capillaries and veins. Of the 35-36 million people that are estimated to suffer from dementia worldwide, up to 65% have an SVD component. Furthermore, SVD causes 20-25% of strokes, worsens outcome after stroke and is a leading cause of disability, cognitive impairment and poor mobility. Yet the underlying cause(s) of SVD are not fully understood.Magnetic resonance imaging (MRI) has confirmed enlarged perivascular spaces (PVS) as a hallmark feature of SVD. In healthy tissue, these spaces are proposed to form part of a complex brain fluid drainage system which supports interstitial fluid exchange and may also facilitate clearance of waste products from the brain. The pathophysiological signature of PVS, and what this infers about their function and interaction with cerebral microcirculation, plus subsequent downstream effects on lesion development in the brain has not been established. Here we discuss the potential of enlarged PVS to be a unique biomarker for SVD and related brain disorders with a vascular component. We propose that widening of PVS suggests presence of peri-vascular cell debris and other waste products that forms part of a vicious cycle involving impaired cerebrovascular reactivity (CVR), blood-brain barrier (BBB) dysfunction, perivascular inflammation and ultimately impaired clearance of waste proteins from the interstitial fluid (ISF) space, leading to accumulation of toxins, hypoxia and tissue damage.Here, we outline current knowledge, questions and hypotheses regarding understanding the brain fluid dynamics underpinning dementia and stroke through the common denominator of SVD

Effectiveness of an intervention for improving drug prescription in primary care patients with multimorbidity and polypharmacy:Study protocol of a cluster randomized clinical trial (Multi-PAP project)

This study was funded by the Fondo de Investigaciones Sanitarias ISCIII (Grant Numbers PI15/00276, PI15/00572, PI15/00996), REDISSEC (Project Numbers RD12/0001/0012, RD16/0001/0005), and the European Regional Development Fund ("A way to build Europe").Background: Multimorbidity is associated with negative effects both on people's health and on healthcare systems. A key problem linked to multimorbidity is polypharmacy, which in turn is associated with increased risk of partly preventable adverse effects, including mortality. The Ariadne principles describe a model of care based on a thorough assessment of diseases, treatments (and potential interactions), clinical status, context and preferences of patients with multimorbidity, with the aim of prioritizing and sharing realistic treatment goals that guide an individualized management. The aim of this study is to evaluate the effectiveness of a complex intervention that implements the Ariadne principles in a population of young-old patients with multimorbidity and polypharmacy. The intervention seeks to improve the appropriateness of prescribing in primary care (PC), as measured by the medication appropriateness index (MAI) score at 6 and 12months, as compared with usual care. Methods/Design: Design:pragmatic cluster randomized clinical trial. Unit of randomization: family physician (FP). Unit of analysis: patient. Scope: PC health centres in three autonomous communities: Aragon, Madrid, and Andalusia (Spain). Population: patients aged 65-74years with multimorbidity (≥3 chronic diseases) and polypharmacy (≥5 drugs prescribed in ≥3months). Sample size: n=400 (200 per study arm). Intervention: complex intervention based on the implementation of the Ariadne principles with two components: (1) FP training and (2) FP-patient interview. Outcomes: MAI score, health services use, quality of life (Euroqol 5D-5L), pharmacotherapy and adherence to treatment (Morisky-Green, Haynes-Sackett), and clinical and socio-demographic variables. Statistical analysis: primary outcome is the difference in MAI score between T0 and T1 and corresponding 95% confidence interval. Adjustment for confounding factors will be performed by multilevel analysis. All analyses will be carried out in accordance with the intention-to-treat principle. Discussion: It is essential to provide evidence concerning interventions on PC patients with polypharmacy and multimorbidity, conducted in the context of routine clinical practice, and involving young-old patients with significant potential for preventing negative health outcomes. Trial registration: Clinicaltrials.gov, NCT02866799Publisher PDFPeer reviewe