HERMES: Towards an Integrated Toolbox to Characterize Functional and Effective Brain Connectivity

The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ‘traditional’ set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified-easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.

HERMES: towards an integrated toolbox to characterize functional and effective brain connectivity

The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ?traditional? set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified, easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.

Prediction of high-pressure adsorption equilibrium of supercritical gases using density functional theory

In this paper, we present the results of the prediction of the high-pressure adsorption equilibrium of supercritical. gases (Ar, N-2, CH4, and CO2) on various activated carbons (BPL, PCB, and Norit R1 extra) at various temperatures using a density-functional-theory-based finite wall thickness (FWT) model. Pore size distribution results of the carbons are taken from our recent previous work 1,2 using this approach for characterization. To validate the model, isotherms calculated from the density functional theory (DFT) approach are comprehensively verified against those determined by grand canonical Monte Carlo (GCMC) simulation, before the theoretical adsorption isotherms of these investigated carbons calculated by the model are compared with the experimental adsorption measurements of the carbons. We illustrate the accuracy and consistency of the FWT model for the prediction of adsorption isotherms of the all investigated gases. The pore network connectivity problem occurring in the examined carbons is also discussed, and on the basis of the success of the predictions assuming a similar pore size distribution for accessible and inaccessible regions, it is suggested that this is largely related to the disordered nature of the carbon.

A multimodal investigation of dynamic face perception using functional magnetic resonance imaging and magnetoencephalography

Motion is an important aspect of face perception that has been largely neglected to date. Many of the established findings are based on studies that use static facial images, which do not reflect the unique temporal dynamics available from seeing a moving face. In the present thesis a set of naturalistic dynamic facial emotional expressions was purposely created and used to investigate the neural structures involved in the perception of dynamic facial expressions of emotion, with both functional Magnetic Resonance Imaging (fMRI) and Magnetoencephalography (MEG). Through fMRI and connectivity analysis, a dynamic face perception network was identified, which is demonstrated to extend the distributed neural system for face perception (Haxby et al.,2000). Measures of effective connectivity between these regions revealed that dynamic facial stimuli were associated with specific increases in connectivity between early visual regions, such as inferior occipital gyri and superior temporal sulci, along with coupling between superior temporal sulci and amygdalae, as well as with inferior frontal gyri. MEG and Synthetic Aperture Magnetometry (SAM) were used to examine the spatiotemporal profile of neurophysiological activity within this dynamic face perception network. SAM analysis revealed a number of regions showing differential activation to dynamic versus static faces in the distributed face network, characterised by decreases in cortical oscillatory power in the beta band, which were spatially coincident with those regions that were previously identified with fMRI. These findings support the presence of a distributed network of cortical regions that mediate the perception of dynamic facial expressions, with the fMRI data providing information on the spatial co-ordinates paralleled by the MEG data, which indicate the temporal dynamics within this network. This integrated multimodal approach offers both excellent spatial and temporal resolution, thereby providing an opportunity to explore dynamic brain activity and connectivity during face processing.

Network construction and graph theoretical analysis of functional language networks in pediatric epilepsy

This dissertation introduces a new approach for assessing the effects of pediatric epilepsy on the language connectome. Two novel data-driven network construction approaches are presented. These methods rely on connecting different brain regions using either extent or intensity of language related activations as identified by independent component analysis of fMRI data. An auditory description decision task (ADDT) paradigm was used to activate the language network for 29 patients and 30 controls recruited from three major pediatric hospitals. Empirical evaluations illustrated that pediatric epilepsy can cause, or is associated with, a network efficiency reduction. Patients showed a propensity to inefficiently employ the whole brain network to perform the ADDT language task; on the contrary, controls seemed to efficiently use smaller segregated network components to achieve the same task. To explain the causes of the decreased efficiency, graph theoretical analysis was carried out. The analysis revealed no substantial global network feature differences between the patient and control groups. It also showed that for both subject groups the language network exhibited small-world characteristics; however, the patient's extent of activation network showed a tendency towards more random networks. It was also shown that the intensity of activation network displayed ipsilateral hub reorganization on the local level. The left hemispheric hubs displayed greater centrality values for patients, whereas the right hemispheric hubs displayed greater centrality values for controls. This hub hemispheric disparity was not correlated with a right atypical language laterality found in six patients. Finally it was shown that a multi-level unsupervised clustering scheme based on self-organizing maps, a type of artificial neural network, and k-means was able to fairly and blindly separate the subjects into their respective patient or control groups. The clustering was initiated using the local nodal centrality measurements only. Compared to the extent of activation network, the intensity of activation network clustering demonstrated better precision. This outcome supports the assertion that the local centrality differences presented by the intensity of activation network can be associated with focal epilepsy.^

Current knowledge on the role of the inferior frontal gyrus in Theory of Mind - a commentary on Schurz and Tholen (2016)

Schurz and Tholen (2016) argue that common approaches to studying the neural basis of “theory of mind” (ToM) obscure a potentially important role for inferior frontal gyrus (IFG) in managing conflict between perspectives, and urge new work to address this question: “to gain a full understanding of the IFG's role in ToM, we encourage future imaging studies to use a wider range of control conditions.” (p332). We wholeheartedly agree, but note that this observation has been made before, and has already led to a programme of work that provides evidence from fMRI, EEG, and TMS on the role of IFG in managing conflict between self and other perspectives in ToM. We highlight these works, and in particular we demonstrate how careful manipulation within ToM tasks has been used to act as an internal control condition, wherein conflict has been manipulated within-subject. We further add to the discussion by framing key questions that remain regarding IFG in the context of these. Using limitations in the existing research, we outline how best researchers can proceed with the challenge set by Schurz and Tholen (2016).

Homo- and heteronuclear meso,meso-(E)-Ethene-1,2-diyl-Linked Diporphyrins : preparation, X-ray crystal structure, electronic absorption and emission spectra and density functional theory calculations

Homo-and heteronuclear meso,meso-(E)-ethene-1,2-diyl-linked diporphyrins have been prepared by the Suzuki coupling of porphyrinylboronates and iodovinylporphyrins. Combinations comprising 5,10,15-triphenylporphyrin (TriPP) on both ends of the ethene-1,2-diyl bridge M 210 (M 2=H 2/Ni, Ni 2, Ni/Zn, H 4, H 2Zn, Zn 2) and 5,15-bis(3,5-di-tert-butylphenyl)porphyrinato-nickel(II) on one end and H 2, Ni, and ZnTriPP on the other (M 211), enable the first studies of this class of compounds possessing intrinsic polarity. The compounds were characterized by electronic absorption and steady state emission spectra, 1H NMR spectra, and for the Ni 2 bis(TriPP) complex Ni 210, single crystal X-ray structure determination. The crystal structure shows ruffled distortions of the porphyrin rings, typical of Ni II porphyrins, and the (E)-C 2H 2 bridge makes a dihedral angle of 50° with the mean planes of the macrocycles. The result is a stepped parallel arrangement of the porphyrin rings. The dihedral angles in the solid state reflect the interplay of steric and electronic effects of the bridge on interporphyrin communication. The emission spectra in particular, suggest energy transfer across the bridge is fast in conformations in which the bridge is nearly coplanar with the rings. Comparisons of the fluorescence behaviour of H 410 and H 2Ni10 show strong quenching of the free base fluorescence when the complex is excited at the lower energy component of the Soret band, a feature associated in the literature with more planar conformations. TDDFT calculations on the gas-phase optimized geometry of Ni 210 reproduce the features of the experimental electronic absorption spectrum within 0.1 eV. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Methane activation on Fe4 cluster : a density functional theory study

We report a comprehensive theoretical study on reaction of methane by Fe4 cluster. This Letter gains insight into the mechanism of the reaction and indicate the Fe4 cluster has strong catalytic effect on the activation reaction of methane. In detail, the results show the cleavage of the first C–H bond is both an energetically and kinetically favourable process and the breaking of the second C–H is the rate-determining step. Moreover, our Letter demonstrates that the different cluster size of iron can not only determine the catalytic activity of methane but also control the product selectivity.

How to achieve maximum charge carrier loading on heteroatom-substituted graphene nanoribbon edges: density functional theory study

The practical number of charge carriers loaded is crucial to the evaluation of the capacity performance of carbon-based electrodes in service, and cannot be easily addressed experimentally. In this paper, we report a density functional theory study of charge carrier adsorption onto zigzag edge-shaped graphene nanoribbons (ZGNRs), both pristine and incorporating edge substitution with boron, nitrogen or oxygen atoms. All edge substitutions are found to be energetically favorable, especially in oxidized environments. The maximal loading of protons onto the substituted ZGNR edges obeys a rule of [8-n-1], where n is the number of valence electrons of the edge-site atom constituting the adsorption site. Hence, a maximum charge loading is achieved with boron substitution. This result correlates in a transparent manner with the electronic structure characteristics of the edge atom. The boron edge atom, characterized by the most empty p band, facilitates more than the other substitutional cases the accommodation of valence electrons transferred from the ribbon, induced by adsorption of protons. This result not only further confirms the possibility of enhancing charge storage performance of carbon-based electrochemical devices through chemical functionalization but also, more importantly, provides the physical rationale for further design strategies.

Charge carrier exchange at chemically modified graphene edges: A density functional theory study

Heteroatom doping on the edge of graphene may serve as an effective way to tune chemical activity of carbon-based electrodes with respect to charge carrier transfer in an aqueous environment. In a step towards developing mechanistic understanding of this phenomenon, we explore herein mechanisms of proton transfer from aqueous solution to pristine and doped graphene edges utilizing density functional theory. Atomic B-, N-, and O- doped edges as well as the native graphene are examined, displaying varying proton affinities and effective interaction ranges with the H3O+ charge carrier. Our study shows that the doped edges characterized by more dispersive orbitals, namely boron and nitrogen, demonstrate more energetically favourable charge carrier exchange compared with oxygen, which features more localized orbitals. Extended calculations are carried out to examine proton transfer from the hydronium ion in the presence of explicit water, with results indicating that the basic mechanistic features of the simpler model are unchanged.

Adsorption and dissociation of ammonia borane outside and inside single-walled carbon nanotubes : A density functional theory study

Amonia borane (AB) has been identified as a potential candidate highcapacity hydrogen storage material. This work probes the adsorption and dissociation of AB inside and outside single-walled carbon nanotubes (SWCNTs) within the framework of density functional theory. The dissociation barriers of AB have been calculated and compared with that of the isolated AB molecule. On the basis of the present calculations, no notable improvement results from SWCNT confinement; on the contrary, the dissociation barrier slightly increases with respect to isolated AB.

A density functional theory study on CO2 capture and activation by graphene-like boron nitride with boron vacancy

First principle calculations for a hexagonal (graphene-like) boron nitride (g-BN) monolayer sheet in the presence of a boron-atom vacancy show promising properties for capture and activation of carbon dioxide. CO2 is found to decompose to produce an oxygen molecule via an intermediate chemisorption state on the defect g-BN sheet. The three stationary states and two transition states in the reaction pathway are confirmed by minimum energy pathway search and frequency analysis. The values computed for the two energy barriers involved in this catalytic reaction after enthalpy correction indicate that the catalytic reaction should proceed readily at room temperature.

A density functional theory study of CO2 and N2 adsorption on aluminium nitride single walled nanotubes

Strong binding of isolated carbon dioxide (CO2) on aluminium nitride (AlN) single walled nanotubes is verified using two different functionals. Two optimized configurations corresponding to physisorption and chemisorption are linked by a low energy barrier, such that the chemisorbed state is accessible and thermodynamically favored at low temperatures. In contrast, N2 is found only to form a physisorbed complex with the AlN nanotube, suggesting the potential application of aluminium nitride based materials for CO2 fixation. The effect of nanotube diameter on gas adsorption properties is also discussed. The diameter is found to have an important effect on the chemisorption of CO2, but has little effect on the physisorption of either CO2 or N2.

Adsorption of carbon dioxide and nitrogen on single-layer aluminum nitride nanostructures studied by density functional theory

The adsorption of carbon dioxide and nitrogen molecules on aluminum nitride (AlN) nanostructures has been explored using first-principle computational methods. Optimized configurations corresponding to physisorption and, subsequentially, chemisorption of CO2 are identified, in contrast to N2, for which only a physisorption structure is found. Transition-state searches imply a low energy barrier between the physisorption and chemisorption states for CO2 such that the latter is accessible and thermodynamically favored at room temperature. The effective binding energy of the optimized chemisorption structure is apparently larger than those for other CO2 adsorptive materials, suggesting the potential for application of aluminum nitride nanostructures for carbon dioxide capture and storage.

The effect of Fe doping on adsorption of CO2/N2within carbon nanotubes : a density functional theory study with dispersion corrections

An ab initio density functional theory (DFT) study with correction for dispersive interactions was performed to study the adsorption of N2 and CO2 inside an (8, 8) single-walled carbon nanotube. We find that the approach of combining DFT and van der Waals correction is very effective for describing the long-range interaction between N2/CO2 and the carbon nanotube (CNT). Surprisingly, exohedral doping of an Fe atom onto the CNT surface will only affect the adsorption energy of the quadrupolar CO2 molecule inside the CNT (20–30%), and not that of molecular N2. Our results suggest the feasibility of enhancement of CO2/N2 separation in CNT-based membranes by using exohedral doping of metal atoms.