A unified view on beamformers for M/EEG source reconstruction

Beamforming is a popular method for functional source reconstruction using magnetoencephalography (MEG) and electroencephalography (EEG) data. Beamformers, which were first proposed for MEG more than two decades ago, have since been applied in hundreds of studies, demonstrating that they are a versatile and robust tool for neuroscience. However, certain characteristics of beamformers remain somewhat elusive and there currently does not exist a unified documentation of the mathematical underpinnings and computational subtleties of beamformers as implemented in the most widely used academic open source software packages for MEG analysis (Brainstorm, FieldTrip, MNE, and SPM). Here, we provide such documentation that aims at providing the mathematical background of beamforming and unifying the terminology. Beamformer implementations are compared across toolboxes and pitfalls of beamforming analyses are discussed. Specifically, we provide details on handling rank deficient covariance matrices, prewhitening, the rank reduction of forward fields, and on the combination of heterogeneous sensor types, such as magnetometers and gradiometers. The overall aim of this paper is to contribute to contemporary efforts towards higher levels of computational transparency in functional neuroimaging

Inverse Modeling for MEG/EEG data

We provide an overview of the state-of-the-art for mathematical methods that are used to reconstruct brain activity from neurophysiological data. After a brief introduction on the mathematics of the forward problem, we discuss standard and recently proposed regularization methods, as well as Monte Carlo techniques for Bayesian inference. We classify the inverse methods based on the underlying source model, and discuss advantages and disadvantages. Finally we describe an application to the pre-surgical evaluation of epileptic patients.Comment: 15 pages, 1 figur

Effects of dipole position, orientation and noise on the accuracy of EEG source localization

BACKGROUND: The electroencephalogram (EEG) reflects the electrical activity in the brain on the surface of scalp. A major challenge in this field is the localization of sources in the brain responsible for eliciting the EEG signal measured at the scalp. In order to estimate the location of these sources, one must correctly model the sources, i.e., dipoles, as well as the volume conductor in which the resulting currents flow. In this study, we investigate the effects of dipole depth and orientation on source localization with varying sets of simulated random noise in 4 realistic head models. METHODS: Dipole simulations were performed using realistic head models and using the boundary element method (BEM). In all, 92 dipole locations placed in temporal and parietal regions of the head with varying depth and orientation were investigated along with 6 different levels of simulated random noise. Localization errors due to dipole depth, orientation and noise were investigated. RESULTS: The results indicate that there are no significant differences in localization error due tangential and radial dipoles. With high levels of simulated Gaussian noise, localization errors are depth-dependant. For low levels of added noise, errors are similar for both deep and superficial sources. CONCLUSION: It was found that if the signal-to-noise ratio is above a certain threshold, localization errors in realistic head models are, on average the same for deep and superficial sources. As the noise increases, localization errors increase, particularly for deep sources

Electrophysiological modeling in generalized epilepsy using surface EEG and anatomical brain structures

Deep brain structures involve significantly in the pathology of brain diseases such as epilepsy, Alzheimer, and Parkinson. Physiological brain modeling has become an emerging approach to investigate the coupling dynamics of the brain activity ofthese diseases. We propose a method using the surface EEG signals integrated with the anatomical individual brain to build the electrophysiological model of the epileptic patient’s brain. The EEG-driven model is used to investigate the deep brain activities of 23 patients diagnosed with generalized epilepsy from CHB-MIT Scalp EEG Database. Significant changes in the electrical activities in hippocampus, accumbens, amygdala, provide us insights into the dynamics ofactive brain regions during epilepsy. All of these brain regions show the significant energy variation defined by 5 features (Mean, Max, Min, Standard deviation, Power spectral density) with the p-value < 0.05 in both pre-ictal vs ictal and ictal vs post-ictal. Such result shows the potential of using EEG as a tool to capture the deep brain activity of epilepsy and other diseases that alter deep brain structures. The proposed model may be used to enhance the sensitivity of detecting and predicting epilepsy, detect the progression of the brain lesion, and support the decision-making for a brain medical intervention

Regional Differences in the Sensitivity of MEG for Interictal Spikes in Epilepsy

MEG interictal spikes as recorded in epilepsy patients are a reflection of intracranial interictal activity. This study investigates the relationship between the estimated sources of MEG spikes and the location, distribution and size of interictal spikes in the invasive ECoG of a group of 38 epilepsy patients that are monitored for pre-surgical evaluation. An amplitude/surface area measure is defined to quantify and rank ECoG spikes. It is found that all MEG spikes are associated with an ECoG spike that is among the three highest ranked in a patient. Among the different brain regions considered, the fronto-orbital, inter-hemispheric, tempero-lateral and central regions stand out. In an accompanying simulation study it is shown that for hypothesized extended sources of larger sizes, as suggested by the data, source location, orientation and curvature can partly explain the observed sensitivity of MEG for interictal spikes

Modification of EGF-Like Module 1 of Thrombospondin-1, an Animal Extracellular Protein, by O-Linked N-Acetylglucosamine

Thrombospondin-1 (TSP-1) is known to be subject to three unusual carbohydrate modifications: C-mannosylation, O-fucosylation, and O-glucosylation. We now describe a fourth: O-β-N-acetylglucosaminylation. Previously, O-β-N-acetylglucosamine (O-β-GlcNAc) was found on a threonine in the loop between the fifth and sixth cysteines of the 20th epidermal growth factor (EGF)-like module of Drosophila Notch. A BLAST search based on the Drosophila Notch loop sequence identified a number of human EGF-like modules that contain a similar sequence, including EGF-like module 1 of TSP-1 and its homolog, TSP-2. TSP-1, which has a potentially modifiable serine in the loop, reacted in immuno-blots with the CTD110.6 anti-O-GlcNAc antibody. Antibody reactivity was diminished by treatment of TSP-1 with β-N-acetylhexosaminidase. TSP-2, which lacks a potentially modifiable serine/threonine in the loop, did not react with CTD110.6. Analysis of tandem modules of TSP-1 localized reactivity of CTD110.6 to EGF-like module 1. Top-down mass spectrometric analysis of EGF-like module 1 demonstrated the expected modifications with glucose (+162 Da) and xylose (+132 Da) separately from modification with N-acetyl hexosamine (+203 Da). Mass spectrometric sequence analysis localized the +203-Da modification to Ser580 in the sequence 575CPPGYSGNGIQC586. These results demonstrate that O-β-N-acetylglucosaminylation can occur on secreted extracellular matrix proteins as well as on cell surface proteins

Androgenic dependence of exophytic tumor growth in a transgenic mouse model of bladder cancer: a role for thrombospondin-1

<p>Abstract</p> <p>Background</p> <p>Steroid hormones influence mitogenic signaling pathways, apoptosis, and cell cycle checkpoints, and it has long been known that incidence of bladder cancer (BC) in men is several times greater than in women, a difference that cannot be attributed to environmental or lifestyle factors alone. Castration reduces incidence of chemically-induced BC in rodents. It is unclear if this effect is due to hormonal influences on activation/deactivation of carcinogens or a direct effect on urothelial cell proliferation or other malignant processes. We examined the effect of castration on BC growth in UPII-SV40T transgenic mice, which express SV40 T antigen specifically in urothelium and reliably develop BC. Furthermore, because BC growth in UPII-SV40T mice is exophytic, we speculated BC growth was dependent on angiogenesis and angiogenesis was, in turn, androgen responsive.</p> <p>Methods</p> <p>Flat panel detector-based cone beam computed tomography (FPDCT) was used to longitudinally measure exophytic BC growth in UPII-SV40T male mice sham-operated, castrated, or castrated and supplemented with dihydrotestosterone (DHT). Human normal bladder and BC biopsies and mouse bladder were examined quantitatively for thrombospondin-1 (TSP1) protein expression.</p> <p>Results</p> <p>Mice castrated at 24 weeks of age had decreased BC volumes at 32 weeks compared to intact mice (p = 0.0071) and castrated mice administered DHT (p = 0.0233; one-way ANOVA, JMP 6.0.3, SAS Institute, Inc.). Bladder cancer cell lines responded to DHT treatment with increased proliferation, regardless of androgen receptor expression levels. TSP1, an anti-angiogenic factor whose expression is inhibited by androgens, had decreased expression in bladders of UPII-SV40T mice compared to wild-type. Castration increased TSP1 levels in UPII-SV40T mice compared to intact mice. TSP1 protein expression was higher in 8 of 10 human bladder biopsies of normal versus malignant tissue from the same patients.</p> <p>Conclusion</p> <p>FPDCT allows longitudinal monitoring of exophytic tumor growth in the UPII-SV40T model of BC that bypasses need for chemical carcinogens, which confound analysis of androgen effects. Androgens increase tumor cell growth <it>in vitro </it>and <it>in vivo </it>and decrease TSP1 expression, possibly explaining the therapeutic effect of castration. This effect may, in part, explain gender differences in BC incidence and implies anti-androgenic therapies may be effective in preventing and treating BC.</p

A genome-wide SNP-association study confirms a sequence variant (g.66493737C>T) in the equine myostatin (MSTN) gene as the most powerful predictor of optimum racing distance for Thoroughbred racehorses

<p>Abstract</p> <p>Background</p> <p>Thoroughbred horses have been selected for traits contributing to speed and stamina for centuries. It is widely recognized that inherited variation in physical and physiological characteristics is responsible for variation in individual aptitude for race distance, and that muscle phenotypes in particular are important.</p> <p>Results</p> <p>A genome-wide SNP-association study for optimum racing distance was performed using the EquineSNP50 Bead Chip genotyping array in a cohort of <it>n </it>= 118 elite Thoroughbred racehorses divergent for race distance aptitude. In a cohort-based association test we evaluated genotypic variation at 40,977 SNPs between horses suited to short distance (≤ 8 f) and middle-long distance (> 8 f) races. The most significant SNP was located on chromosome 18: BIEC2-417495 ~690 kb from the gene encoding myostatin (<it>MSTN</it>) [<it>P</it>_unadj.= 6.96 × 10^-6]. Considering best race distance as a quantitative phenotype, a peak of association on chromosome 18 (chr18:65809482-67545806) comprising eight SNPs encompassing a 1.7 Mb region was observed. Again, similar to the cohort-based analysis, the most significant SNP was BIEC2-417495 (<it>P</it>_unadj.= 1.61 × 10^-9; <it>P</it>_Bonf.= 6.58 × 10^-5). In a candidate gene study we have previously reported a SNP (g.66493737C>T) in <it>MSTN </it>associated with best race distance in Thoroughbreds; however, its functional and genome-wide relevance were uncertain. Additional re-sequencing in the flanking regions of the <it>MSTN </it>gene revealed four novel 3' UTR SNPs and a 227 bp SINE insertion polymorphism in the 5' UTR promoter sequence. Linkage disequilibrium was highest between g.66493737C>T and BIEC2-417495 (<it>r</it>²= 0.86).</p> <p>Conclusions</p> <p>Comparative association tests consistently demonstrated the g.66493737C>T SNP as the superior variant in the prediction of distance aptitude in racehorses (g.66493737C>T, <it>P </it>= 1.02 × 10^-10; BIEC2-417495, <it>P</it>_unadj.= 1.61 × 10^-9). Functional investigations will be required to determine whether this polymorphism affects putative transcription-factor binding and gives rise to variation in gene and protein expression. Nonetheless, this study demonstrates that the g.66493737C>T SNP provides the most powerful genetic marker for prediction of race distance aptitude in Thoroughbreds.</p

Seafloor character and sedimentary processes in eastern Long Island Sound and western Block Island Sound

Author Posting. © The Author(s), 2006. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Geo-Marine Letters 26 (2006): 59-68, doi: 10.1007/s00367-006-0016-4.Multibeam bathymetric data and seismic-reflection profiles collected in eastern Long Island and western Block Island Sounds reveal previously unrecognized glacial features and modern bedforms. Glacial features include an ice-sculptured bedrock surface, a newly identified recessional moraine, exposed glaciolacustrine sediments, and remnants of stagnant-ice-contact deposits. Modern bedforms include fields of transverse sand waves, barchanoid waves, giant scour depressions, and pockmarks. Bedform asymmetry and scour around obstructions indicate that net sediment transport is westward across the northern par of the study area near Fishers Island and eastward across the southern par near Great Gull Island.This work was supported by the Coastal and Marine Geology Program of the U.S. Geological Survey, the Connecticut Department of Environmental Protection, and the Atlantic Hydrographic Branch of the National Oceanic and Atmospheric Administration

Sensitivity of MEG and EEG to Source Orientation

An important difference between magnetoencephalography (MEG) and electroencephalography (EEG) is that MEG is insensitive to radially oriented sources. We quantified computationally the dependency of MEG and EEG on the source orientation using a forward model with realistic tissue boundaries. Similar to the simpler case of a spherical head model, in which MEG cannot see radial sources at all, for most cortical locations there was a source orientation to which MEG was insensitive. The median value for the ratio of the signal magnitude for the source orientation of the lowest and the highest sensitivity was 0.06 for MEG and 0.63 for EEG. The difference in the sensitivity to the source orientation is expected to contribute to systematic differences in the signal-to-noise ratio between MEG and EEG.National Institutes of Health (U.S.) (Grant NS057500)National Institutes of Health (U.S.) (Grant NS037462)National Institutes of Health (U.S.) (Grant HD040712)National Center for Research Resources (U.S.) (P41RR14075)Mind Research Networ