EEG Microstates During Resting Represent Personality Differences

We investigated the spontaneous brain electric activity of 13 skeptics and 16 believers in paranormal phenomena; they were university students assessed with a self-report scale about paranormal beliefs. 33-channel EEG recordings during no-task resting were processed as sequences of momentary potential distribution maps. Based on the maps at peak times of Global Field Power, the sequences were parsed into segments of quasi-stable potential distribution, the ‘microstates'. The microstates were clustered into four classes of map topographies (A-D). Analysis of the microstate parameters time coverage, occurrence frequency and duration as well as the temporal sequence (syntax) of the microstate classes revealed significant differences: Believers had a higher coverage and occurrence of class B, tended to decreased coverage and occurrence of class C, and showed a predominant sequence of microstate concatenations from A to C to B to A that was reversed in skeptics (A to B to C to A). Microstates of different topographies, putative "atoms of thought”, are hypothesized to represent different types of information processing.The study demonstrates that personality differences can be detected in resting EEG microstate parameters and microstate syntax. Microstate analysis yielded no conclusive evidence for the hypothesized relation between paranormal belief and schizophreni

Research Design, Soil and Biodiversity Baseline for Long-term Farming Systems Comparison of Full Sun and Shaded Agroforestry Cocoa Production under Conventional and Organic Management in Alto Beni, Bolivia

Cocoa, mainly produced by 5 to 6 millions of smallholder farmers, is considered as one of the most sustainable production system in the humid tropics. Little is known about the sustainability of different cocoa production systems. A long-term experiment is set up in Alto Beni at 400m above sea level with a humid winter dry climate, 1’540 mm annual rainfall. The trial assesses the sustainability of five cocoa (Theobroma cacao) production systems with the parameters of yield and yield stability, input-output efficiency of nutrients and energy, soil fertility, biodiversity, economic result, climate change mitigation and adaptation. The two-factorial experiment is arranged in an completely randomised block design; the five cocoa treatments, based on local and international practices, are four times repeated. The production systems are differentiated by the diversity of shade canopy and by crops, from mono culture full sun cocoa to a agroforestry cocoa with leguminous species (Inga edulis, Erythrina poeppigiana) shade canopy, including fruits (e.g. Euterpe precatoria, Theobroma grandiflorum) and timber (e.g. Centrolobium ochroxylum, Swietenia macrophylla) species, and a higher diversified agroforestry system based on the natural successions of species. The management of the cocoa is conventional and organic. The five treatments are: mono culture full sun cocoa conventional, mono culture full sun organic, agroforestry conventional, agroforestry organic and successional agroforestry organic. Fallow plots and nearby forests plots are monitored for soil fertility and biodiversity. Field clearing started in 2007 followed by maize (Zea mays) crop and end of 2008 the cocoa plots (48m×48 m) were established. The results of the baseline studies concerning soil fertility show good nutrient level for cocoa production; the variance of soil parameters is documented in a soil map. According the FAO soil classification (2006) the soils are Lixisole and Luvisole with high base saturation

The resting microstate networks (RMN): cortical distributions, dynamics, and frequency specific information flow

A brain microstate is characterized by a unique, fixed spatial distribution of electrically active neurons with time varying amplitude. It is hypothesized that a microstate implements a functional/physiological state of the brain during which specific neural computations are performed. Based on this hypothesis, brain electrical activity is modeled as a time sequence of non-overlapping microstates with variable, finite durations (Lehmann and Skrandies 1980, 1984; Lehmann et al 1987). In this study, EEG recordings from 109 participants during eyes closed resting condition are modeled with four microstates. In a first part, a new confirmatory statistics method is introduced for the determination of the cortical distributions of electric neuronal activity that generate each microstate. All microstates have common posterior cingulate generators, while three microstates additionally include activity in the left occipital/parietal, right occipital/parietal, and anterior cingulate cortices. This appears to be a fragmented version of the metabolically (PET/fMRI) computed default mode network (DMN), supporting the notion that these four regions activate sequentially at high time resolution, and that slow metabolic imaging corresponds to a low-pass filtered version. In the second part of this study, the microstate amplitude time series are used as the basis for estimating the strength, directionality, and spectral characteristics (i.e., which oscillations are preferentially transmitted) of the connections that are mediated by the microstate transitions. The results show that the posterior cingulate is an important hub, sending alpha and beta oscillatory information to all other microstate generator regions. Interestingly, beyond alpha, beta oscillations are essential in the maintenance of the brain during resting state.Comment: pre-print, technical report, The KEY Institute for Brain-Mind Research (Zurich), Kansai Medical University (Osaka

Innovations orthogonalization: a solution to the major pitfalls of EEG/MEG "leakage correction"

The problem of interest here is the study of brain functional and effective connectivity based on non-invasive EEG-MEG inverse solution time series. These signals generally have low spatial resolution, such that an estimated signal at any one site is an instantaneous linear mixture of the true, actual, unobserved signals across all cortical sites. False connectivity can result from analysis of these low-resolution signals. Recent efforts toward "unmixing" have been developed, under the name of "leakage correction". One recent noteworthy approach is that by Colclough et al (2015 NeuroImage, 117:439-448), which forces the inverse solution signals to have zero cross-correlation at lag zero. One goal is to show that Colclough's method produces false human connectomes under very broad conditions. The second major goal is to develop a new solution, that appropriately "unmixes" the inverse solution signals, based on innovations orthogonalization. The new method first fits a multivariate autoregression to the inverse solution signals, giving the mixed innovations. Second, the mixed innovations are orthogonalized. Third, the mixed and orthogonalized innovations allow the estimation of the "unmixing" matrix, which is then finally used to "unmix" the inverse solution signals. It is shown that under very broad conditions, the new method produces proper human connectomes, even when the signals are not generated by an autoregressive model.Comment: preprint, technical report, under license "Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)", https://creativecommons.org/licenses/by-nc-nd/4.0

Cocoa in Full-sun Monocultures vs. Shaded Agroforestry Systems under Conventional and Organic Management in Bolivia

Cocoa is a crucial export commodity for many developing countries and provides income for millions of smallholders. However, cocoa cultivation has resulted in habitat destruction, biodiversity loss and soil degradation. While much of the world’s cocoa is produced in arguably unsustainable full-sun monoculture systems, shaded agroforestry systems may be an alternative for sustainable cocoa production. However, data-based information on advantages and limitations of different cocoa production systems are limited and pairwise comparisons on the long-term performance of cocoa monocultures and agroforestry systems under conventional and organic management are literally inexistent. The Research Institute of Organic Agriculture (FiBL) is pioneering to fill this knowledge gap with a unique long term field trial in tropical Bolivia. The trial was established in 2008 and consists of six systems: two monocultures (MONO CONV/ORG) and two agroforestry systems (AF CONV/ORG) under conventional and organic management, one successional agroforestry system (SAFS, organic only) with dynamic shade management, and a fallow system of the same age serving as a reference for biodiversity and soil fertility studies. The systems aim to represent current smallholder cocoa farmers’ practices. Parameters such as the tree development, yield of cocoa and by-crops, incidences of pests and diseases, soil fertility, carbon stocks, nutrient balances, economic data and biodiversity are regularly assessed. Five years after planting, results showed significantly shorter tree circumference (18% and 33 %) in AF systems and SAFS, respectively, compared to MONO systems. Tree circumference correlated strongly with cocoa dry bean yield which was, as expected, highest in MONO CONV (603 kg ha−1). By-crops such as plantain, cassava, pineapple, etc. were harvested in AF systems and SAFS, which may compensate for lower cocoa yields in the first years. Future research will investigate cocoa performance after the establishment phase and thus provide indications on the long-term sustainability of the different systems

Functionally aberrant electrophysiological cortical connectivities in first episode medication-naive schizophrenics from three psychiatry centers

Functional dissociation between brain processes is widely hypothesized to account for aberrations of thought and emotions in schizophrenic patients. The typically small groups of analyzed schizophrenic patients yielded different neurophysiological findings, probably because small patient groups are likely to comprise different schizophrenia subtypes. We analyzed multichannel eyes- closed resting EEG from three small groups of acutely ill, first episode productive schizophrenic patients before start of medication (from three centers: Bern N = 9; Osaka N = 9; Berlin N = 12) and their controls. Low resolution brain electromagnetic tomography (LORETA) was used to compute intracortical source model-based lagged functional connectivity not biased by volume conduction effects between 19 cortical regions of interest (ROIs). The connectivities were compared between controls and patients of each group. Conjunction analysis determined six aberrant cortical functional connectivities that were the same in the three patient groups. Four of these six concerned the facilitating EEG alpha-1 frequency activity; they were decreased in the patients. Another two of these six connectivities concerned the inhibiting EEG delta frequency activity; they were increased in the patients. The principal orientation of the six aberrant cortical functional connectivities was sagittal; five of them involved both hemispheres. In sum, activity in the posterior brain areas of preprocessing functions and the anterior brain areas of evaluation and behavior control functions were compromised by either decreased coupled activation or increased coupled inhibition, common across schizophrenia subtypes in the three patient groups. These results of the analyzed three independent groups of schizophrenics support the concept of functional dissociation

Transethnic meta-analysis of rare coding variants in PLCG2, ABI3, and TREM2 supports their general contribution to Alzheimer’s disease

Rare coding variants in TREM2, PLCG2, and ABI3 were recently associated with the susceptibility to Alzheimer’s disease (AD) in Caucasians. Frequencies and AD-associated effects of variants differ across ethnicities. To start filling the gap on AD genetics in South America and assess the impact of these variants across ethnicity, we studied these variants in Argentinian population in association with ancestry. TREM2 (rs143332484 and rs75932628), PLCG2 (rs72824905), and ABI3 (rs616338) were genotyped in 419 AD cases and 486 controls. Meta-analysis with European population was performed. Ancestry was estimated from genome-wide genotyping results. All variants show similar frequencies and odds ratios to those previously reported. Their association with AD reach statistical significance by meta-analysis. Although the Argentinian population is an admixture, variant carriers presented mainly Caucasian ancestry. Rare coding variants in TREM2, PLCG2, and ABI3 also modulate susceptibility to AD in populations from Argentina, and they may have a European heritage.International Society for Neurochemistry (ISN) and Alexander von Humboldt Foundation (to M.C.D.); Agencia Nacional de Promoción Científica y Tecnológica (PBIT/09 2013, PICT2015-0285 and PICT-2016-4647 to L.M.; PICT-2014-1537 to M.C.D.

The individuality index: a measure to quantify the degree of inter-individual, spatial variability in intra-cerebral brain electric and metabolic activity

Contemporary neuroscience research primarily focuses on the identification of brain activation patterns commonly deviant across participant groups or experimental conditions. This approach inherently underestimates potentially meaningful intra- and inter-individual variability present in brain physiological measures. We propose a parameter referred to as ‘individuality index (II)’ that takes individual variability into account. It quantifies the degree of individual variance of brain activation patterns for different brain regions and participants. IIs can be computed based on intra-cerebral source strength values such as the ones derived from the exact low resolution electromagnetic tomography source localization software. We exemplary estimated IIs for simulated datasets. Our results illustrate how IIs are affected by different spatial activation patterns across participants and quantify their distributional properties. They suggest that the proposed indices can meaningfully quantify inter- and intra-individuality of brain activation patterns. Their application to realistic datasets will allow the identification of (1) those brain regions that show particularly heterogeneous activation patterns, the contribution of which is particularly likely to be underestimated by conventional group statistics, (2) those brain regions that can alternatively be recruited by different participants for the same tasks, and (3) their associations with potentially decisive behavioral variables such as individually applied mental strategy