GraphVar 2.0: A user-friendly toolbox for machine learning on functional connectivity measures.

BACKGROUND: We previously presented GraphVar as a user-friendly MATLAB toolbox for comprehensive graph analyses of functional brain connectivity. Here we introduce a comprehensive extension of the toolbox allowing users to seamlessly explore easily customizable decoding models across functional connectivity measures as well as additional features. NEW METHOD: GraphVar 2.0 provides machine learning (ML) model construction, validation and exploration. Machine learning can be performed across any combination of graph measures and additional variables, allowing for a flexibility in neuroimaging applications. RESULTS: In addition to previously integrated functionalities, such as network construction and graph-theoretical analyses of brain connectivity with a high-speed general linear model (GLM), users can now perform customizable ML across connectivity matrices, graph measures and additionally imported variables. The new extension also provides parametric and nonparametric testing of classifier and regressor performance, data export, figure generation and high quality export. COMPARISON WITH EXISTING METHODS: Compared to other existing toolboxes, GraphVar 2.0 offers (1) comprehensive customization, (2) an all-in-one user friendly interface, (3) customizable model design and manual hyperparameter entry, (4) interactive results exploration and data export, (5) automated queue system for modelling multiple outcome variables within the same session, (6) an easy to follow introductory review. CONCLUSIONS: GraphVar 2.0 allows comprehensive, user-friendly exploration of encoding (GLM) and decoding (ML) modelling approaches on functional connectivity measures making big data neuroscience readily accessible to a broader audience of neuroimaging investigators.

General, crystallized and fluid intelligence are not associated with functional global network efficiency: A replication study with the human connectome project 1200 data set.

One hallmark example of a link between global topological network properties of complex functional brain connectivity and cognitive performance is the finding that general intelligence may depend on the efficiency of the brain's intrinsic functional network architecture. However, although this association has been featured prominently over the course of the last decade, the empirical basis for this broad association of general intelligence and global functional network efficiency is quite limited. In the current study, we set out to replicate the previously reported association between general intelligence and global functional network efficiency using the large sample size and high quality data of the Human Connectome Project, and extended the original study by testing for separate association of crystallized and fluid intelligence with global efficiency, characteristic path length, and global clustering coefficient. We were unable to provide evidence for the proposed association between general intelligence and functional brain network efficiency, as was demonstrated by van den Heuvel et al. (2009), or for any other association with the global network measures employed. More specifically, across multiple network definition schemes, ranging from voxel-level networks to networks of only 100 nodes, no robust associations and only very weak non-significant effects with a maximal R2 of 0.01 could be observed. Notably, the strongest (non-significant) effects were observed in voxel-level networks. We discuss the possibility that the low power of previous studies and publication bias may have led to false positive results fostering the widely accepted notion of general intelligence being associated to functional global network efficiency.

GraphVar: a user-friendly toolbox for comprehensive graph analyses of functional brain connectivity.

BACKGROUND: Graph theory provides a powerful and comprehensive formalism of global and local topological network properties of complex structural or functional brain connectivity. Software packages such as the Brain-Connectivity-Toolbox have contributed to graph theory's increasing popularity for characterization of brain networks. However, comparably comprehensive packages are command-line based and require programming experience; this precludes their use by users without a computational background, whose research would otherwise benefit from graph-theoretical methods. NEW METHOD: "GraphVar" is a user-friendly GUI-based toolbox for comprehensive graph-theoretical analyses of brain connectivity, including network construction and characterization, statistical analysis on network topological measures, network based statistics, and interactive exploration of results. RESULTS: GraphVar provides a comprehensive collection of graph analysis routines for analyses of functional brain connectivity in one single toolbox by combining features across multiple currently available toolboxes, such as the Brain Connectivity Toolbox, the Graph Analysis Toolbox, and the Network Based Statistic Toolbox (BCT, Rubinov and Sporns, 2010; GAT, Hosseini et al., 2012; NBS, Zalesky et al., 2010). GraphVar was developed under the GNU General Public License v3.0 and can be downloaded at www.rfmri.org/graphvar or www.nitrc.org/projects/graphvar. COMPARISON WITH EXISTING METHODS: By combining together features across multiple toolboxes, GraphVar will allow comprehensive graph-theoretical analyses in one single toolbox without resorting to code. CONCLUSIONS: GraphVar will make graph theoretical methods more accessible for a broader audience of neuroimaging researchers.

5-HTTLPR/rs25531 polymorphism and neuroticism are linked by resting state functional connectivity of amygdala and fusiform gyrus.

The s/s-genotype of the 5-HTTLPR polymorphism and the personality trait of neuroticism have both been associated with experiences of negative affect, anxiety and mood disorders, as well as an emotional processing bias towards negative facial emotions. On a neural level, this bias can be characterized by altered amygdala and fusiform gyrus (FFG) activity during perception of negative facial expressions. Using resting-state functional magnetic resonance imaging in a multi-center-sample of 178 healthy subjects of European descent, this study investigated the association of 5-HTTLPR (short s- and long l-allele) including the genotype of the single nucleotide polymorphism (SNP) rs25531 (A/G) within this region polymorphism, and trait neuroticism on resting-state functional connectivity (rs-FC) between amygdala and the FFG. Moreover, we aimed to identify additional brain regions with associations of 5-HTTLPR/rs25531 (combined according to its expression; low: s/s; high: l(A)/l(A); intermediate: s/l(A), s/l(G), l(G)/l(G), l(A)/l(G)) and trait neuroticism to amygdala rs-FC. Separate analyses for 5-HTTLPR/rs25531 and neuroticism (controlling for age, gender, handedness, and research site) revealed that s/s-homozygotes and individuals high in neuroticism obtained altered amygdala rs-FC in the right occipital face area, which is considered to be a "core component" of the face processing system. Importantly, effects of neuroticism were replicated across three independent research sites. Additionally, associations of 5-HTTLPR/rs25531 genotype and amygdala rs-FC were observed in the anterior and posterior cingulate cortex, whereas neuroticism was not related to rs-FC in these areas. The presented data implies that 5-HTTLPR/rs25531 variants and neuroticism are linked by resting state functional connectivity of amygdala and fusiform gyrus and suggests that variants of 5-HTTLPR/rs25531 genotype and different levels of neuroticism may partly account for altered processing of negative facial emotions.

High Thrill and adventure seeking is associated with reduced interoceptive sensitivity: evidence for an altered sex-specific homeostatic processing in high sensation seekers.

OBJECTIVE: The personality trait of sensation seeking (SS) has been traditionally linked to the construct of exteroception, i.e. sensing of the outside world. Little is known about the relationship between SS and interoception, i.e. sensing originating in the body. Interoceptive sensations have strong affective and motivational components that may influence behaviors such as risk-taking in SS. This investigation examined whether interoceptive differences contribute to different behavioral characteristics in SS. METHOD: Using an inspiratory resistive load breathing task, the response to an aversive interoceptive stimulus as a basic homeostatic process was studied in 112 subjects (n=74 females, 38 males). A linear-mixed model approach was used to examine the influence of thrill and adventure seeking (TAS) on the interoceptive response across three levels of breathing resistances (10, 20, 40 cmH2O/L/sec). RESULTS: High relative to low TAS individuals were less responsive in evaluating intensities of perceived choking with increasing inspiratory resistive loads. This effect was driven by male, but not female high TAS individuals and was particularly associated with reduced interoceptive sensitivity in males. CONCLUSION: The conceptualization of SS as primarily driven by exteroceptive stimuli can be expanded to a view of an altered homeostasis in SS, specifically in males.

Bandwidth reduction technique for multilayer wavelength division multiplexing (WDM) bandpass filters.

The push to develop 100 GHz and smaller bandwidth WDM filters is at demanding levels. Currently, 200 GHz is the standard bandwidth for multilayer interference coatings with high efficiencies, and enormous processing effort is going into the development of standard 100 GHz filters. This paper outlines a simple design that will reduce bandwidth up to 40% when applied to 200 GHz bandpass filters. This design method can also be used in existing 100 GHz designs to achieve even smaller bandwidths.

Optical and durability properties of infrared transmitting thin films.

Refractive indices and extinction coefficients have been calculated for 14 oxide and fluoride thin films over a wavelength range of 0.6-12 mum. Results from adhesion, abrasion, and humidity testing have been included to characterize the durability of each film. The data allow selection of the best oxide and fluoride materials for IR antireflection coatings, and detailed optical constants are provided for the coating design.