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1.  The active site of hen egg-white lysozyme: flexibility and chemical bonding 
Chemical bonding at the active site of lysozyme is analyzed on the basis of a multipole model employing transferable multipole parameters from a database. Large B factors at low temperatures reflect frozen-in disorder, but therefore prevent a meaningful free refinement of multipole parameters.
Chemical bonding at the active site of hen egg-white lysozyme (HEWL) is analyzed on the basis of Bader’s quantum theory of atoms in molecules [QTAIM; Bader (1994 ▶), Atoms in Molecules: A Quantum Theory. Oxford University Press] applied to electron-density maps derived from a multipole model. The observation is made that the atomic displacement parameters (ADPs) of HEWL at a temperature of 100 K are larger than ADPs in crystals of small biological molecules at 298 K. This feature shows that the ADPs in the cold crystals of HEWL reflect frozen-in disorder rather than thermal vibrations of the atoms. Directly generalizing the results of multipole studies on small-molecule crystals, the important consequence for electron-density analysis of protein crystals is that multipole parameters cannot be independently varied in a meaningful way in structure refinements. Instead, a multipole model for HEWL has been developed by refinement of atomic coordinates and ADPs against the X-ray diffraction data of Wang and coworkers [Wang et al. (2007), Acta Cryst. D63, 1254–1268], while multipole parameters were fixed to the values for transferable multipole parameters from the ELMAM2 database [Domagala et al. (2012), Acta Cryst. A68, 337–351] . Static and dynamic electron densities based on this multipole model are presented. Analysis of their topological properties according to the QTAIM shows that the covalent bonds possess similar properties to the covalent bonds of small molecules. Hydrogen bonds of intermediate strength are identified for the Glu35 and Asp52 residues, which are considered to be essential parts of the active site of HEWL. Furthermore, a series of weak C—H⋯O hydrogen bonds are identified by means of the existence of bond critical points (BCPs) in the multipole electron density. It is proposed that these weak interactions might be important for defining the tertiary structure and activity of HEWL. The deprotonated state of Glu35 prevents a distinction between the Phillips and Koshland mechanisms.
PMCID: PMC3975892  PMID: 24699657
hen egg-white lysozyme; multipole model; multipole parameters
2.  Topological Properties of Chemical Bonds from Static and Dynamic Electron Densities 
Dynamic and static electron densities (EDs) based on the independent spherical atom model (IAM) and multipole (MP) models of crambin were successfully computed, holding no series-termination effects. The densities are compared to EDs of small biological molecules at diverse temperatures. It is outlined that proteins exhibit an intrinsic flexibility, present as frozen disorder at 100 K, in contrast to small molecules. The flexibility of the proteins is reflected by atomic displacement parameters (B-factors), which are considerably larger than for small molecules at 298 K. Thus, an optimal deconvolution of deformation density and thermal motion is not guaranteed, which prevents a free refinement of MP parameters but allows an application of transferable, fixed MP parameters. The analysis of the topological properties, such as the density at bond critical points (BCPs) and the Laplacian, reveals systematic differences between static and dynamic EDs. Zero-point-vibrations, yet present in dynamic EDs at low temperature, affect but marginally the EDs of small molecules. The zero-point-vibrations cause a smearing of the ED, which becomes more pronounced with increasing temperature. Topological properties, primarily the Laplacian, of covalent bonds appear to be more sensitive to effects by temperature and the polarity of the bonds. However, dynamic EDs at ca. 20 K based on MP models provide a good characterization of chemical bonding. Both the density at BCPs and the Laplacian of hydrogen bonds constitute similar values from static and dynamic EDs for all studied temperatures. Deformation densities demonstrate the necessity of the employment of MP parameters in order to comprise the nature of covalent bonds. The character of hydrogen bonds can be roughly pictured by IAM, whereas MP parameters are recommended for a classification of hydrogen bonds beyond a solely interpretation of topological properties.
PMCID: PMC4431502  PMID: 25995522
Amino acids; Electron densities; Chemical bonding; Proteins; X-ray diffraction
3.  Atomic Forces for Geometry-Dependent Point Multipole and Gaussian Multipole Models 
Journal of computational chemistry  2010;31(15):2702-2713.
In standard treatments of atomic multipole models, interaction energies, total molecular forces, and total molecular torques are given for multipolar interactions between rigid molecules. However, if the molecules are assumed to be flexible, two additional multipolar atomic forces arise due to 1) the transfer of torque between neighboring atoms, and 2) the dependence of multipole moment on internal geometry (bond lengths, bond angles, etc.) for geometry-dependent multipole models. In the current study, atomic force expressions for geometry-dependent multipoles are presented for use in simulations of flexible molecules. The atomic forces are derived by first proposing a new general expression for Wigner function derivatives ∂Dlm′m/∂Ω. The force equations can be applied to electrostatic models based on atomic point multipoles or Gaussian multipole charge density. Hydrogen bonded dimers are used to test the inter-molecular electrostatic energies and atomic forces calculated by geometry-dependent multipoles fit to the ab initio electrostatic potential (ESP). The electrostatic energies and forces are compared to their reference ab initio values. It is shown that both static and geometry-dependent multipole models are able to reproduce total molecular forces and torques with respect to ab initio, while geometry-dependent multipoles are needed to reproduce ab initio atomic forces. The expressions for atomic force can be used in simulations of flexible molecules with atomic multipoles. In addition, the results presented in this work should lead to further development of next generation force fields composed of geometry-dependent multipole models.
PMCID: PMC2941241  PMID: 20839297
Multipole; Gaussian Multipole; Force; Torque; Wigner Function
4.  Quantum crystallographic charge density of urea 
IUCrJ  2016;3(Pt 4):237-246.
A charge-density model of urea was calculated using quantum theory and was refined against publicly available ultra-high-resolution X-ray diffraction data. The quantum model differs from a multipole model but agrees comparably with the data; quantum crystallography therefore can provide unique and accurate charge density models.
Standard X-ray crystallography methods use free-atom models to calculate mean unit-cell charge densities. Real molecules, however, have shared charge that is not captured accurately using free-atom models. To address this limitation, a charge density model of crystalline urea was calculated using high-level quantum theory and was refined against publicly available ultra-high-resolution experimental Bragg data, including the effects of atomic displacement parameters. The resulting quantum crystallographic model was compared with models obtained using spherical atom or multipole methods. Despite using only the same number of free parameters as the spherical atom model, the agreement of the quantum model with the data is comparable to the multipole model. The static, theoretical crystalline charge density of the quantum model is distinct from the multipole model, indicating the quantum model provides substantially new information. Hydrogen thermal ellipsoids in the quantum model were very similar to those obtained using neutron crystallography, indicating that quantum crystallography can increase the accuracy of the X-ray crystallographic atomic displacement parameters. The results demonstrate the feasibility and benefits of integrating fully periodic quantum charge density calculations into ultra-high-resolution X-ray crystallographic model building and refinement.
PMCID: PMC4937779  PMID: 27437111
charge density; quantum theory; spherical atom model
5.  HPAM: Hirshfeld Partitioned Atomic Multipoles 
Computer physics communications  2012;183(2):390-397.
An implementation of the Hirshfeld (HD) and Hirshfeld-Iterated (HD-I) atomic charge density partitioning schemes is described. Atomic charges and atomic multipoles are calculated from the HD and HD-I atomic charge densities for arbitrary atomic multipole rank lmax on molecules of arbitrary shape and size. The HD and HD-I atomic charges/multipoles are tested by comparing molecular multipole moments and the electrostatic potential (ESP) surrounding a molecule with their reference ab initio values. In general, the HD-I atomic charges/multipoles are found to better reproduce ab initio electrostatic properties over HD atomic charges/multipoles. A systematic increase in precision for reproducing ab initio electrostatic properties is demonstrated by increasing the atomic multipole rank from lmax = 0 (atomic charges) to lmax = 4 (atomic hexadecapoles). Both HD and HD-I atomic multipoles up to rank lmax are shown to exactly reproduce ab initio molecular multipole moments of rank L for L ≤ lmax. In addition, molecular dipole moments calculated by HD, HD-I, and ChelpG atomic charges only (lmax = 0) are compared with reference ab initio values. Significant errors in reproducing ab initio molecular dipole moments are found if only HD or HD-I atomic charges used.
PMCID: PMC3225920  PMID: 22140274
Atomic multipoles; Hirshfeld charges; dipole; quadrupole
6.  Polarizable atomic multipole X-ray refinement: application to peptide crystals 
A method to accelerate the computation of structure factors from an electron density described by anisotropic and aspherical atomic form factors via fast Fourier transformation is described for the first time.
Recent advances in computational chemistry have produced force fields based on a polarizable atomic multipole description of biomolecular electrostatics. In this work, the Atomic Multipole Optimized Energetics for Biomolecular Applications (AMOEBA) force field is applied to restrained refinement of molecular models against X-ray diffraction data from peptide crystals. A new formalism is also developed to compute anisotropic and aspherical structure factors using fast Fourier transformation (FFT) of Cartesian Gaussian multipoles. Relative to direct summation, the FFT approach can give a speedup of more than an order of magnitude for aspherical refinement of ultrahigh-resolution data sets. Use of a sublattice formalism makes the method highly parallelizable. Application of the Cartesian Gaussian multipole scattering model to a series of four peptide crystals using multipole coefficients from the AMOEBA force field demonstrates that AMOEBA systematically underestimates electron density at bond centers. For the trigonal and tetrahedral bonding geometries common in organic chemistry, an atomic multipole expansion through hexadecapole order is required to explain bond electron density. Alternatively, the addition of inter­atomic scattering (IAS) sites to the AMOEBA-based density captured bonding effects with fewer parameters. For a series of four peptide crystals, the AMOEBA–IAS model lowered R free by 20–40% relative to the original spherically symmetric scattering model.
PMCID: PMC2733883  PMID: 19690373
scattering factors; aspherical; anisotropic; force fields; multipole; polarization; AMOEBA; bond density; direct summation; FFT; SGFFT; Ewald; PME
7.  Modeling Organochlorine Compounds and the σ-Hole Effect Using a Polarizable Multipole Force Field 
The journal of physical chemistry. B  2014;118(24):6456-6465.
The charge distribution of halogen atoms on organochlorine compounds can be highly anisotropic and even display a so-called σ-hole, which leads to strong halogen bonds with electron donors. In this paper, we have systematically investigated a series of chloromethanes with one to four chloro substituents using a polarizable multipole-based molecular mechanics model. The atomic multipoles accurately reproduced the ab initio electrostatic potential around chloromethanes, including CCl4, which has a prominent σ-hole on the Cl atom. The van der Waals parameters for Cl were fitted to the experimental density and heat of vaporization. The calculated hydration free energy, solvent reaction fields, and interaction energies of several homo- and heterodimer of chloromethanes are in good agreement with experimental and ab initio data. This study suggests that sophisticated electrostatic models, such as polarizable atomic multipoles, are needed for accurate description of electrostatics in organochlorine compounds and halogen bonds, although further improvement is necessary for better transferability.
PMCID: PMC4065202  PMID: 24484473
molecular mechanics simulation; halogen bond; ab initio quantum mechanics; hydration free energy; parameter optimization
8.  An optimized intermolecular force field for hydrogen-bonded organic molecular crystals using atomic multipole electrostatics 
An empirically parameterized intermolecular force field is developed for crystal structure modelling and prediction. The model is optimized for use with an atomic multipole description of electrostatic interactions.
We present a re-parameterization of a popular intermolecular force field for describing intermolecular interactions in the organic solid state. Specifically we optimize the performance of the exp-6 force field when used in conjunction with atomic multipole electrostatics. We also parameterize force fields that are optimized for use with multipoles derived from polarized molecular electron densities, to account for induction effects in molecular crystals. Parameterization is performed against a set of 186 experimentally determined, low-temperature crystal structures and 53 measured sublimation enthalpies of hydrogen-bonding organic molecules. The resulting force fields are tested on a validation set of 129 crystal structures and show improved reproduction of the structures and lattice energies of a range of organic molecular crystals compared with the original force field with atomic partial charge electrostatics. Unit-cell dimensions of the validation set are typically reproduced to within 3% with the re-parameterized force fields. Lattice energies, which were all included during parameterization, are systematically underestimated when compared with measured sublimation enthalpies, with mean absolute errors of between 7.4 and 9.0%.
PMCID: PMC4971546  PMID: 27484370
lattice energy; crystal structure prediction; multipoles; polarization; electrostatics
9.  Gaussian Multipole Model (GMM) 
An electrostatic model based on charge density is proposed as a model for future force fields. The model is composed of a nucleus and a single Slater-type contracted Gaussian multipole charge density on each atom. The Gaussian multipoles are fit to the electrostatic potential (ESP) calculated at the B3LYP/6-31G* and HF/aug-cc-pVTZ levels of theory and tested by comparing electrostatic dimer energies, inter-molecular density overlap integrals, and permanent molecular multipole moments with their respective ab initio values. For the case of water, the atomic Gaussian multipole moments Qlm are shown to be a smooth function of internal geometry (bond length and bond angle), which can be approximated by a truncated linear Taylor series. In addition, results are given when the Gaussian multipole charge density is applied to a model for exchange-repulsion energy based on the inter-molecular density overlap.
PMCID: PMC2832208  PMID: 20209077
Gaussian multipoles; charge density; electrostatic model; multipole; overlap
10.  Modulated anharmonic ADPs are intrinsic to aperiodic crystals: a case study on incommensurate Rb2ZnCl4  
The superspace maximum entropy method (MEM) density in combination with structure refinements has been used to uncover the modulation in incommensurate Rb2ZnCl4 close to the lock-in transition. Modulated atomic displacement parameters (ADPs) and modulated anharmonic ADPs are found to form an intrinsic part of the modulation. Refined values for the displacement modulation function depend on the presence or absence of modulated ADPs in the model.
A combination of structure refinements, analysis of the superspace MEM density and interpretation of difference-Fourier maps has been used to characterize the incommensurate modulation of rubidium tetrachlorozincate, Rb2ZnCl4, at a temperature of T = 196 K, close to the lock-in transition at T lock-in = 192 K. The modulation is found to consist of a combination of displacement modulation functions, modulated atomic displacement parameters (ADPs) and modulated third-order anharmonic ADPs. Up to fifth-order Fourier coefficients could be refined against diffraction data containing up to fifth-order satellite reflections. The center-of-charge of the atomic basins of the MEM density and the displacive modulation functions of the structure model provide equivalent descriptions of the displacive modulation. Modulations of the ADPs and anharmonic ADPs are visible in the MEM density, but extracting quantitative information about these modulations appears to be difficult. In the structure refinements the modulation parameters of the ADPs form a dependent set, and ad hoc restrictions had to be introduced in the refinements. It is suggested that modulated harmonic ADPs and modulated third-order anharmonic ADPs form an intrinsic part, however small, of incommensurately modulated structures in general. Refinements of alternate models with and without parameters for modulated ADPs lead to significant differences between the parameters of the displacement modulation in these two types of models, thus showing the modulation of ADPs to be important for a correct description of the displacive modulation. The resulting functions do not provide evidence for an interpretation of the modulation by a soliton model.
PMCID: PMC3098556  PMID: 21586828
aperiodic crystals; incommensurate modulated structures; MEM density; ADPs
11.  High-Resolution Crystal Structures of Protein Helices Reconciled with Three-Centered Hydrogen Bonds and Multipole Electrostatics 
PLoS ONE  2015;10(4):e0123146.
Theoretical and experimental evidence for non-linear hydrogen bonds in protein helices is ubiquitous. In particular, amide three-centered hydrogen bonds are common features of helices in high-resolution crystal structures of proteins. These high-resolution structures (1.0 to 1.5 Å nominal crystallographic resolution) position backbone atoms without significant bias from modeling constraints and identify Φ = -62°, ψ = -43 as the consensus backbone torsional angles of protein helices. These torsional angles preserve the atomic positions of α-β carbons of the classic Pauling α-helix while allowing the amide carbonyls to form bifurcated hydrogen bonds as first suggested by Némethy et al. in 1967. Molecular dynamics simulations of a capped 12-residue oligoalanine in water with AMOEBA (Atomic Multipole Optimized Energetics for Biomolecular Applications), a second-generation force field that includes multipole electrostatics and polarizability, reproduces the experimentally observed high-resolution helical conformation and correctly reorients the amide-bond carbonyls into bifurcated hydrogen bonds. This simple modification of backbone torsional angles reconciles experimental and theoretical views to provide a unified view of amide three-centered hydrogen bonds as crucial components of protein helices. The reason why they have been overlooked by structural biologists depends on the small crankshaft-like changes in orientation of the amide bond that allows maintenance of the overall helical parameters (helix pitch (p) and residues per turn (n)). The Pauling 3.613 α-helix fits the high-resolution experimental data with the minor exception of the amide-carbonyl electron density, but the previously associated backbone torsional angles (Φ, Ψ) needed slight modification to be reconciled with three-atom centered H-bonds and multipole electrostatics. Thus, a new standard helix, the 3.613/10-, Némethy- or N-helix, is proposed. Due to the use of constraints from monopole force fields and assumed secondary structures used in low-resolution refinement of electron density of proteins, such structures in the PDB often show linear hydrogen bonding.
PMCID: PMC4403875  PMID: 25894612
12.  Directional Dependence of Hydrogen Bonds: a Density-based Energy Decomposition Analysis and Its Implications on Force Field Development 
One well-known shortcoming of widely-used biomolecular force fields is the description of the directional dependence of hydrogen bonding (HB). Here we aim to better understand the origin of this difficulty and thus provide some guidance for further force field development. Our theoretical approaches center on a novel density-based energy decomposition analysis (DEDA) method [J. Chem. Phys., 131, 164112 (2009)], in which the frozen density energy is variationally determined through constrained search. This unique and most significant feature of DEDA enables us to find that the frozen density interaction term is the key factor in determining the HB orientation, while the sum of polarization and charge-transfer components shows very little HB directional dependence. This new insight suggests that the difficulty for current non-polarizable force fields to describe the HB directional dependence is not due to the lack of explicit polarization or charge-transfer terms. Using the DEDA results as reference, we further demonstrate that the main failure coming from the atomic point charge model can be overcome largely by introducing extra charge sites or higher order multipole moments. Among all the electrostatic models explored, the smeared charge distributed multipole model (up to quadrupole), which also takes account of charge penetration effects, gives the best agreement with the corresponding DEDA results. Meanwhile, our results indicate that the van der Waals interaction term needs to be further improved to better model directional hydrogen bonding.
PMCID: PMC3259744  PMID: 22267958
13.  Solid-state tautomeric structure and invariom refinement of a novel and potent HIV integrase inhibitor 
The conformation and tautomeric structure of (Z)-4-[5-(2,6-difluoro­benzyl)-1-(2-fluoro­benzyl)-2-oxo-1,2-dihydro­pyridin-3-yl]-4-hy­droxy-2-oxo-N-(2-oxopyrrolidin-1-yl)but-3-enamide, C27H22F3N3O5, in the solid state has been resolved by single-crystal X-ray crystallography. The electron distribution in the mol­ecule was evaluated by refinements with invarioms, aspherical scattering factors by the method of Dittrich et al. [Acta Cryst. (2005), A61, 314–320] that are based on the Hansen–Coppens multipole model [Hansen & Coppens (1978 ▶). Acta Cryst. A34, 909–921]. The β-diketo portion of the mol­ecule exists in the enol form. The enol –OH hydrogen forms a strong asymmetric hydrogen bond with the carbonyl O atom on the β-C atom of the chain. Weak intra­molecular hydrogen bonds exist between the weakly acidic α-CH hydrogen of the keto–enol group and the pyridinone carbonyl O atom, and also between the hydrazine N—H group and the carbonyl group in the β-position from the hydrazine N—H group. The electrostatic properties of the mol­ecule were derived from the mol­ecular charge density. The mol­ecule is in a lengthened conformation and the rings of the two benzyl groups are nearly orthogonal. Results from a high-field 1H and 13C NMR correlation spectroscopy study confirm that the same tautomer exists in solution as in the solid state.
PMCID: PMC3589111  PMID: 23459357
14.  Polarizable Atomic Multipole-based Molecular Mechanics for Organic Molecules 
An empirical potential based on permanent atomic multipoles and atomic induced dipoles is reported for alkanes, alcohols, amines, sulfides, aldehydes, carboxylic acids, amides, aromatics and other small organic molecules. Permanent atomic multipole moments through quadrupole moments have been derived from gas phase ab initio molecular orbital calculations. The van der Waals parameters are obtained by fitting to gas phase homodimer QM energies and structures, as well as experimental densities and heats of vaporization of neat liquids. As a validation, the hydrogen bonding energies and structures of gas phase heterodimers with water are evaluated using the resulting potential. For 32 homo- and heterodimers, the association energy agrees with ab initio results to within 0.4 kcal/mol. The RMS deviation of hydrogen bond distance from QM optimized geometry is less than 0.06 Å. In addition, liquid self-diffusion and static dielectric constants computed from molecular dynamics simulation are consistent with experimental values. The force field is also used to compute the solvation free energy of 27 compounds not included in the parameterization process, with a RMS error of 0.69 kcal/mol. The results obtained in this study suggest the AMOEBA force field performs well across different environments and phases. The key algorithms involved in the electrostatic model and a protocol for developing parameters are detailed to facilitate extension to additional molecular systems.
PMCID: PMC3196664  PMID: 22022236
15.  Anharmonicity and isomorphic phase transition: a multi-temperature X-ray single-crystal and powder diffraction study of 1-(2′-aminophenyl)-2-methyl-4-nitroimidazole 
Iucrj  2014;1(Pt 2):110-118.
Multi-temperature single-crystal and powder diffraction experiments on 1-(2′-aminophenyl)-2-methyl-4-nitroimidazole show that this crystal undergoes an isomorphic phase transition with the coexistence of two phase domains over a wide temperature range. The anharmonic approach was the only way to model the resulting disorder.
The harmonic model of atomic nuclear motions is usually enough for multipole modelling of high-resolution X-ray diffraction data; however, in some molecular crystals, such as 1-(2′-aminophenyl)-2-methyl-4-nitro-1H-imidazole [Paul, Kubicki, Jelsch et al. (2011 ▶). Acta Cryst. B67, 365–378], it may not be sufficient for a correct description of the charge-density distribution. Multipole refinement using harmonic atom vibrations does not lead to the best electron density model in this case and the so-called ‘shashlik-like’ pattern of positive and negative residual electron density peaks is observed in the vicinity of some atoms. This slight disorder, which cannot be modelled by split atoms, was solved using third-order anharmonic nuclear motion (ANM) parameters. Multipole refinement of the experimental high-resolution X-ray diffraction data of 1-(2′-aminophenyl)-2-methyl-4-nitro-1H-imidazole at three different temperatures (10, 35 and 70 K) and a series of powder diffraction experiments (20 ≤ T ≤ 300 K) were performed to relate this anharmonicity observed for several light atoms (N atoms of amino and nitro groups, and O atoms of nitro groups) to an isomorphic phase transition reflected by a change in the b cell parameter around 65 K. The observed disorder may result from the coexistence of domains of two phases over a large temperature range, as shown by low-temperature powder diffraction.
PMCID: PMC4062092  PMID: 25075327
anharmonicity; isomorphic phase transition; experimental charge density; X-ray closed-circuit helium cryostat; Hansen–Coppens model; multiple-temperature powder diffraction
16.  Point Charges Optimally Placed to Represent the Multipole Expansion of Charge Distributions 
PLoS ONE  2013;8(7):e67715.
We propose an approach for approximating electrostatic charge distributions with a small number of point charges to optimally represent the original charge distribution. By construction, the proposed optimal point charge approximation (OPCA) retains many of the useful properties of point multipole expansion, including the same far-field asymptotic behavior of the approximate potential. A general framework for numerically computing OPCA, for any given number of approximating charges, is described. We then derive a 2-charge practical point charge approximation, PPCA, which approximates the 2-charge OPCA via closed form analytical expressions, and test the PPCA on a set of charge distributions relevant to biomolecular modeling. We measure the accuracy of the new approximations as the RMS error in the electrostatic potential relative to that produced by the original charge distribution, at a distance the extent of the charge distribution–the mid-field. The error for the 2-charge PPCA is found to be on average 23% smaller than that of optimally placed point dipole approximation, and comparable to that of the point quadrupole approximation. The standard deviation in RMS error for the 2-charge PPCA is 53% lower than that of the optimal point dipole approximation, and comparable to that of the point quadrupole approximation. We also calculate the 3-charge OPCA for representing the gas phase quantum mechanical charge distribution of a water molecule. The electrostatic potential calculated by the 3-charge OPCA for water, in the mid-field (2.8 Å from the oxygen atom), is on average 33.3% more accurate than the potential due to the point multipole expansion up to the octupole order. Compared to a 3 point charge approximation in which the charges are placed on the atom centers, the 3-charge OPCA is seven times more accurate, by RMS error. The maximum error at the oxygen-Na distance (2.23 Å ) is half that of the point multipole expansion up to the octupole order.
PMCID: PMC3701554  PMID: 23861790
17.  A Transferable Coarse-Grained Model for Hydrogen Bonding Liquids 
We present here a recent development of a generalized coarse-grained model for use in molecular simulations. In this model, interactions between coarse-grained particles consist of both van der Waals and explicit electrostatic components. As a result, the coarse-grained model offers the transferability that is lacked by most current effectivepotential based approaches. The previous center-of-mass framework1 is generalized here to include arbitrary off-center interaction sites for both Gay-Berne and multipoles. The new model has been applied to molecular dynamic simulations of neat methanol liquid. By placing a single point multipole at the oxygen atom rather than at the center of mass of methanol, there is a significant improvement in the ability to capture hydrogen-bonding. The critical issue of transferability of the coarse-grained model is verified on methanol-water mixtures, using parameters derived from neat liquids without any modification. The mixture density and internal energy from coarse-grained molecular dynamics simulations show good agreement with experimental measurements, on a par with what has been obtained from more detailed atomic models. By mapping the dynamics trajectory from the coarse-grained simulation into the all-atom counterpart, we are able to investigate atomic .level structure and interaction. Atomic radial distribution functions of neat methanol, neat water and mixtures compare favorably to experimental measurements. Furthermore, hydrogen-bonded 6- and 7-molecule chains of water and methanol observed in the mixture are in agreement with previous atomic simulations.
PMCID: PMC2443098  PMID: 18688358
18.  Restrained electrostatic potential atomic partial charges for condensed-phase simulations of carbohydrates* 
Theochem  2000;527(1-3):149-156.
Charges derived from fitting a classical Coulomb model to quantum mechanical molecular electrostatic potentials (so called ESP-charges) are frequently used in simulations of macromolecules. Simulational methods that use ESP-charges generally reproduce the geometries of hydrogen bonded complexes, despite the fact that these charges are known to overestimate the strengths of these interactions. Through the use of a restraint function during the fitting of the partial charges to the electrostatic potentials the magnitudes of the charges may be attenuated (so called RESP-charges). For the AMBER force field RESP-charges have been proposed for proteins and nucleic acids. Here we examine a novel approach for determining the RESP-charges for carbohydrates based on molecular dynamics (MD) simulations of crystal structures. During a simulation, the crystallographic unit cell geometry is sensitive to both inter-molecular non-bonded forces and internal torsional rotations. However, for polar molecules, and specifically carbohydrates, the crystal geometries are particularly sensitive to the set of partial atomic charges employed in the simulation. Thus, given a force field in which the van der Waals and torsion terms are well parameterized, it is possible to assess the suitability of a set of partial charges by monitoring the properties of the crystal during an MD simulation. We have examined several charge sets for use with the GLYCAM parameters for carbohydrate and glycoprotein simulations and found that a restraint weight of 0.01 gives the best agreement with the neutron diffraction structure of α-d-glucopyranose. Unrestrained ESP-charges performed poorly as did the charges obtained from Mulliken and distributed multipole analyses of the quantum mechanical HF/6-31G* wavefunctions.
PMCID: PMC4191892  PMID: 25309012
AMBER; Carbohydrate; Electrostatic potential; GLYCAM; Molecular dynamics simulations; Restrained electrostatic charges
19.  A variational linear-scaling framework to build practical, efficient next-generation orbital-based quantum force fields 
We introduce a new hybrid molecular orbital/density-functional modified divide-and-conquer (mDC) approach that allows the linear-scaling calculation of very large quantum systems. The method provides a powerful framework from which linear-scaling force fields for molecular simulations can be developed. The method is variational in the energy, and has simple, analytic gradients and essentially no break-even point with respect to the corresponding full electronic structure calculation. Furthermore, the new approach allows intermolecular forces to be properly balanced such that non-bonded interactions can be treated, in some cases, to much higher accuracy than the full calculation. The approach is illustrated using the second-order self-consistent charge density-functional tight-binding model (DFTB2). Using this model as a base Hamiltonian, the new mDC approach is applied to a series of water systems, where results show that geometries and interaction energies between water molecules are greatly improved relative to full DFTB2. In order to achieve substantial improvement in the accuracy of intermolecular binding energies and hydrogen bonded cluster geometries, it was necessary to extend the DFTB2 model to higher-order atom-centered multipoles for the second-order self-consistent intermolecular electrostatic term. Using generalized, linear-scaling electrostatic methods, timings demonstrate that the method is able to calculate a water system of 3000 atoms in less than half of a second, and systems of up to one million atoms in only a few minutes using a conventional desktop workstation.
PMCID: PMC3694615  PMID: 23814506
20.  Theoretical description of halogen bonding – an insight based on the natural orbitals for chemical valence combined with the extended-transition-state method (ETS-NOCV) 
Journal of Molecular Modeling  2012;19(11):4681-4688.
In the present study we have characterized the halogen bonding in selected molecules H3N–ICF3 (1-NH3), (PH3)2C–ICF3 (1-CPH3), C3H7Br–(IN2H2C3)2C6H4 (2-Br), H2–(IN2H2C3)2C6H4 (2-H2) and Cl–(IC6F5)2C7H10N2O5 (3-Cl), containing from one halogen bond (1-NH3, 1-CPH3) up to four connections in 3-Cl (the two Cl–HN and two Cl–I), based on recently proposed ETS-NOCV analysis. It was found based on the NOCV-deformation density components that the halogen bonding C–X…B (X-halogen atom, B-Lewis base), contains a large degree of covalent contribution (the charge transfer to X…B inter-atomic region) supported further by the electron donation from base atom B to the empty σ*(C–X) orbital. Such charge transfers can be of similar importance compared to the electrostatic stabilization. Further, the covalent part of halogen bonding is due to the presence of σ-hole at outer part of halogen atom (X). ETS-NOCV approach allowed to visualize formation of the σ-hole at iodine atom of CF3I molecule. It has also been demonstrated that strongly electrophilic halogen bond donor, [C6H4(C3H2N2I)2][OTf]2, can activate chemically inert isopropyl bromide (2-Br) moiety via formation of Br–I bonding and bind the hydrogen molecule (2-H2). Finally, ETS-NOCV analysis performed for 3-Cl leads to the conclusion that, in terms of the orbital-interaction component, the strength of halogen (Cl–I) bond is roughly three times more important than the hydrogen bonding (Cl–HN).
FigureETS-NOCV reprezentation of σ-hole at iodine together with the molecular electrostatic potential picture
PMCID: PMC3825488  PMID: 22669533
Covalency; ETS-NOCV; Halogen bonding
21.  Ultrahigh-resolution crystallography and related electron density and electrostatic properties in proteins 
Journal of Synchrotron Radiation  2008;15(Pt 3):202-203.
Ultrahigh-resolution protein diffraction data allow valence electron density modelling and calculations of experimental electrostatic properties. Protein–ligand interaction energy may therefore be estimated.
With an increasing number of biological macromolecular crystal structures measured at ultrahigh resolution (1 Å or better), it is necessary to extend to large systems the experimental valence electron density modelling that is applied to small molecules. A database of average multipole populations has been built, describing the electron density of chemical groups in all 20 amino acids found in proteins. It allows calculation of atomic aspherical scattering factors, which are the starting point for refinement of the protein electron density, using the MoPro software. It is shown that the use of non-spherical scattering factors has a major impact on crystallographic statistics and results in a more accurate crystal structure, notably in terms of thermal displacement parameters and bond distances involving H atoms. It is also possible to obtain a realistic valence electron density model, which is used in the calculation of the electrostatic potential and energetic properties of proteins.
PMCID: PMC2394818  PMID: 18421138
electron density; protein refinement; high-resolution crystallography
22.  25th Annual Computational Neuroscience Meeting: CNS-2016 
Sharpee, Tatyana O. | Destexhe, Alain | Kawato, Mitsuo | Sekulić, Vladislav | Skinner, Frances K. | Wójcik, Daniel K. | Chintaluri, Chaitanya | Cserpán, Dorottya | Somogyvári, Zoltán | Kim, Jae Kyoung | Kilpatrick, Zachary P. | Bennett, Matthew R. | Josić, Kresimir | Elices, Irene | Arroyo, David | Levi, Rafael | Rodriguez, Francisco B. | Varona, Pablo | Hwang, Eunjin | Kim, Bowon | Han, Hio-Been | Kim, Tae | McKenna, James T. | Brown, Ritchie E. | McCarley, Robert W. | Choi, Jee Hyun | Rankin, James | Popp, Pamela Osborn | Rinzel, John | Tabas, Alejandro | Rupp, André | Balaguer-Ballester, Emili | Maturana, Matias I. | Grayden, David B. | Cloherty, Shaun L. | Kameneva, Tatiana | Ibbotson, Michael R. | Meffin, Hamish | Koren, Veronika | Lochmann, Timm | Dragoi, Valentin | Obermayer, Klaus | Psarrou, Maria | Schilstra, Maria | Davey, Neil | Torben-Nielsen, Benjamin | Steuber, Volker | Ju, Huiwen | Yu, Jiao | Hines, Michael L. | Chen, Liang | Yu, Yuguo | Kim, Jimin | Leahy, Will | Shlizerman, Eli | Birgiolas, Justas | Gerkin, Richard C. | Crook, Sharon M. | Viriyopase, Atthaphon | Memmesheimer, Raoul-Martin | Gielen, Stan | Dabaghian, Yuri | DeVito, Justin | Perotti, Luca | Kim, Anmo J. | Fenk, Lisa M. | Cheng, Cheng | Maimon, Gaby | Zhao, Chang | Widmer, Yves | Sprecher, Simon | Senn, Walter | Halnes, Geir | Mäki-Marttunen, Tuomo | Keller, Daniel | Pettersen, Klas H. | Andreassen, Ole A. | Einevoll, Gaute T. | Yamada, Yasunori | Steyn-Ross, Moira L. | Alistair Steyn-Ross, D. | Mejias, Jorge F. | Murray, John D. | Kennedy, Henry | Wang, Xiao-Jing | Kruscha, Alexandra | Grewe, Jan | Benda, Jan | Lindner, Benjamin | Badel, Laurent | Ohta, Kazumi | Tsuchimoto, Yoshiko | Kazama, Hokto | Kahng, B. | Tam, Nicoladie D. | Pollonini, Luca | Zouridakis, George | Soh, Jaehyun | Kim, DaeEun | Yoo, Minsu | Palmer, S. E. | Culmone, Viviana | Bojak, Ingo | Ferrario, Andrea | Merrison-Hort, Robert | Borisyuk, Roman | Kim, Chang Sub | Tezuka, Taro | Joo, Pangyu | Rho, Young-Ah | Burton, Shawn D. | Bard Ermentrout, G. | Jeong, Jaeseung | Urban, Nathaniel N. | Marsalek, Petr | Kim, Hoon-Hee | Moon, Seok-hyun | Lee, Do-won | Lee, Sung-beom | Lee, Ji-yong | Molkov, Yaroslav I. | Hamade, Khaldoun | Teka, Wondimu | Barnett, William H. | Kim, Taegyo | Markin, Sergey | Rybak, Ilya A. | Forro, Csaba | Dermutz, Harald | Demkó, László | Vörös, János | Babichev, Andrey | Huang, Haiping | Verduzco-Flores, Sergio | Dos Santos, Filipa | Andras, Peter | Metzner, Christoph | Schweikard, Achim | Zurowski, Bartosz | Roach, James P. | Sander, Leonard M. | Zochowski, Michal R. | Skilling, Quinton M. | Ognjanovski, Nicolette | Aton, Sara J. | Zochowski, Michal | Wang, Sheng-Jun | Ouyang, Guang | Guang, Jing | Zhang, Mingsha | Michael Wong, K. Y. | Zhou, Changsong | Robinson, Peter A. | Sanz-Leon, Paula | Drysdale, Peter M. | Fung, Felix | Abeysuriya, Romesh G. | Rennie, Chris J. | Zhao, Xuelong | Choe, Yoonsuck | Yang, Huei-Fang | Mi, Yuanyuan | Lin, Xiaohan | Wu, Si | Liedtke, Joscha | Schottdorf, Manuel | Wolf, Fred | Yamamura, Yoriko | Wickens, Jeffery R. | Rumbell, Timothy | Ramsey, Julia | Reyes, Amy | Draguljić, Danel | Hof, Patrick R. | Luebke, Jennifer | Weaver, Christina M. | He, Hu | Yang, Xu | Ma, Hailin | Xu, Zhiheng | Wang, Yuzhe | Baek, Kwangyeol | Morris, Laurel S. | Kundu, Prantik | Voon, Valerie | Agnes, Everton J. | Vogels, Tim P. | Podlaski, William F. | Giese, Martin | Kuravi, Pradeep | Vogels, Rufin | Seeholzer, Alexander | Podlaski, William | Ranjan, Rajnish | Vogels, Tim | Torres, Joaquin J. | Baroni, Fabiano | Latorre, Roberto | Gips, Bart | Lowet, Eric | Roberts, Mark J. | de Weerd, Peter | Jensen, Ole | van der Eerden, Jan | Goodarzinick, Abdorreza | Niry, Mohammad D. | Valizadeh, Alireza | Pariz, Aref | Parsi, Shervin S. | Warburton, Julia M. | Marucci, Lucia | Tamagnini, Francesco | Brown, Jon | Tsaneva-Atanasova, Krasimira | Kleberg, Florence I. | Triesch, Jochen | Moezzi, Bahar | Iannella, Nicolangelo | Schaworonkow, Natalie | Plogmacher, Lukas | Goldsworthy, Mitchell R. | Hordacre, Brenton | McDonnell, Mark D. | Ridding, Michael C. | Zapotocky, Martin | Smit, Daniel | Fouquet, Coralie | Trembleau, Alain | Dasgupta, Sakyasingha | Nishikawa, Isao | Aihara, Kazuyuki | Toyoizumi, Taro | Robb, Daniel T. | Mellen, Nick | Toporikova, Natalia | Tang, Rongxiang | Tang, Yi-Yuan | Liang, Guangsheng | Kiser, Seth A. | Howard, James H. | Goncharenko, Julia | Voronenko, Sergej O. | Ahamed, Tosif | Stephens, Greg | Yger, Pierre | Lefebvre, Baptiste | Spampinato, Giulia Lia Beatrice | Esposito, Elric | et Olivier Marre, Marcel Stimberg | Choi, Hansol | Song, Min-Ho | Chung, SueYeon | Lee, Dan D. | Sompolinsky, Haim | Phillips, Ryan S. | Smith, Jeffrey | Chatzikalymniou, Alexandra Pierri | Ferguson, Katie | Alex Cayco Gajic, N. | Clopath, Claudia | Angus Silver, R. | Gleeson, Padraig | Marin, Boris | Sadeh, Sadra | Quintana, Adrian | Cantarelli, Matteo | Dura-Bernal, Salvador | Lytton, William W. | Davison, Andrew | Li, Luozheng | Zhang, Wenhao | Wang, Dahui | Song, Youngjo | Park, Sol | Choi, Ilhwan | Shin, Hee-sup | Choi, Hannah | Pasupathy, Anitha | Shea-Brown, Eric | Huh, Dongsung | Sejnowski, Terrence J. | Vogt, Simon M. | Kumar, Arvind | Schmidt, Robert | Van Wert, Stephen | Schiff, Steven J. | Veale, Richard | Scheutz, Matthias | Lee, Sang Wan | Gallinaro, Júlia | Rotter, Stefan | Rubchinsky, Leonid L. | Cheung, Chung Ching | Ratnadurai-Giridharan, Shivakeshavan | Shomali, Safura Rashid | Ahmadabadi, Majid Nili | Shimazaki, Hideaki | Nader Rasuli, S. | Zhao, Xiaochen | Rasch, Malte J. | Wilting, Jens | Priesemann, Viola | Levina, Anna | Rudelt, Lucas | Lizier, Joseph T. | Spinney, Richard E. | Rubinov, Mikail | Wibral, Michael | Bak, Ji Hyun | Pillow, Jonathan | Zaho, Yuan | Park, Il Memming | Kang, Jiyoung | Park, Hae-Jeong | Jang, Jaeson | Paik, Se-Bum | Choi, Woochul | Lee, Changju | Song, Min | Lee, Hyeonsu | Park, Youngjin | Yilmaz, Ergin | Baysal, Veli | Ozer, Mahmut | Saska, Daniel | Nowotny, Thomas | Chan, Ho Ka | Diamond, Alan | Herrmann, Christoph S. | Murray, Micah M. | Ionta, Silvio | Hutt, Axel | Lefebvre, Jérémie | Weidel, Philipp | Duarte, Renato | Morrison, Abigail | Lee, Jung H. | Iyer, Ramakrishnan | Mihalas, Stefan | Koch, Christof | Petrovici, Mihai A. | Leng, Luziwei | Breitwieser, Oliver | Stöckel, David | Bytschok, Ilja | Martel, Roman | Bill, Johannes | Schemmel, Johannes | Meier, Karlheinz | Esler, Timothy B. | Burkitt, Anthony N. | Kerr, Robert R. | Tahayori, Bahman | Nolte, Max | Reimann, Michael W. | Muller, Eilif | Markram, Henry | Parziale, Antonio | Senatore, Rosa | Marcelli, Angelo | Skiker, K. | Maouene, M. | Neymotin, Samuel A. | Seidenstein, Alexandra | Lakatos, Peter | Sanger, Terence D. | Menzies, Rosemary J. | McLauchlan, Campbell | van Albada, Sacha J. | Kedziora, David J. | Neymotin, Samuel | Kerr, Cliff C. | Suter, Benjamin A. | Shepherd, Gordon M. G. | Ryu, Juhyoung | Lee, Sang-Hun | Lee, Joonwon | Lee, Hyang Jung | Lim, Daeseob | Wang, Jisung | Lee, Heonsoo | Jung, Nam | Anh Quang, Le | Maeng, Seung Eun | Lee, Tae Ho | Lee, Jae Woo | Park, Chang-hyun | Ahn, Sora | Moon, Jangsup | Choi, Yun Seo | Kim, Juhee | Jun, Sang Beom | Lee, Seungjun | Lee, Hyang Woon | Jo, Sumin | Jun, Eunji | Yu, Suin | Goetze, Felix | Lai, Pik-Yin | Kim, Seonghyun | Kwag, Jeehyun | Jang, Hyun Jae | Filipović, Marko | Reig, Ramon | Aertsen, Ad | Silberberg, Gilad | Bachmann, Claudia | Buttler, Simone | Jacobs, Heidi | Dillen, Kim | Fink, Gereon R. | Kukolja, Juraj | Kepple, Daniel | Giaffar, Hamza | Rinberg, Dima | Shea, Steven | Koulakov, Alex | Bahuguna, Jyotika | Tetzlaff, Tom | Kotaleski, Jeanette Hellgren | Kunze, Tim | Peterson, Andre | Knösche, Thomas | Kim, Minjung | Kim, Hojeong | Park, Ji Sung | Yeon, Ji Won | Kim, Sung-Phil | Kang, Jae-Hwan | Lee, Chungho | Spiegler, Andreas | Petkoski, Spase | Palva, Matias J. | Jirsa, Viktor K. | Saggio, Maria L. | Siep, Silvan F. | Stacey, William C. | Bernar, Christophe | Choung, Oh-hyeon | Jeong, Yong | Lee, Yong-il | Kim, Su Hyun | Jeong, Mir | Lee, Jeungmin | Kwon, Jaehyung | Kralik, Jerald D. | Jahng, Jaehwan | Hwang, Dong-Uk | Kwon, Jae-Hyung | Park, Sang-Min | Kim, Seongkyun | Kim, Hyoungkyu | Kim, Pyeong Soo | Yoon, Sangsup | Lim, Sewoong | Park, Choongseok | Miller, Thomas | Clements, Katie | Ahn, Sungwoo | Ji, Eoon Hye | Issa, Fadi A. | Baek, JeongHun | Oba, Shigeyuki | Yoshimoto, Junichiro | Doya, Kenji | Ishii, Shin | Mosqueiro, Thiago S. | Strube-Bloss, Martin F. | Smith, Brian | Huerta, Ramon | Hadrava, Michal | Hlinka, Jaroslav | Bos, Hannah | Helias, Moritz | Welzig, Charles M. | Harper, Zachary J. | Kim, Won Sup | Shin, In-Seob | Baek, Hyeon-Man | Han, Seung Kee | Richter, René | Vitay, Julien | Beuth, Frederick | Hamker, Fred H. | Toppin, Kelly | Guo, Yixin | Graham, Bruce P. | Kale, Penelope J. | Gollo, Leonardo L. | Stern, Merav | Abbott, L. F. | Fedorov, Leonid A. | Giese, Martin A. | Ardestani, Mohammad Hovaidi | Faraji, Mohammad Javad | Preuschoff, Kerstin | Gerstner, Wulfram | van Gendt, Margriet J. | Briaire, Jeroen J. | Kalkman, Randy K. | Frijns, Johan H. M. | Lee, Won Hee | Frangou, Sophia | Fulcher, Ben D. | Tran, Patricia H. P. | Fornito, Alex | Gliske, Stephen V. | Lim, Eugene | Holman, Katherine A. | Fink, Christian G. | Kim, Jinseop S. | Mu, Shang | Briggman, Kevin L. | Sebastian Seung, H. | Wegener, Detlef | Bohnenkamp, Lisa | Ernst, Udo A. | Devor, Anna | Dale, Anders M. | Lines, Glenn T. | Edwards, Andy | Tveito, Aslak | Hagen, Espen | Senk, Johanna | Diesmann, Markus | Schmidt, Maximilian | Bakker, Rembrandt | Shen, Kelly | Bezgin, Gleb | Hilgetag, Claus-Christian | van Albada, Sacha Jennifer | Sun, Haoqi | Sourina, Olga | Huang, Guang-Bin | Klanner, Felix | Denk, Cornelia | Glomb, Katharina | Ponce-Alvarez, Adrián | Gilson, Matthieu | Ritter, Petra | Deco, Gustavo | Witek, Maria A. G. | Clarke, Eric F. | Hansen, Mads | Wallentin, Mikkel | Kringelbach, Morten L. | Vuust, Peter | Klingbeil, Guido | De Schutter, Erik | Chen, Weiliang | Zang, Yunliang | Hong, Sungho | Takashima, Akira | Zamora, Criseida | Gallimore, Andrew R. | Goldschmidt, Dennis | Manoonpong, Poramate | Karoly, Philippa J. | Freestone, Dean R. | Soundry, Daniel | Kuhlmann, Levin | Paninski, Liam | Cook, Mark | Lee, Jaejin | Fishman, Yonatan I. | Cohen, Yale E. | Roberts, James A. | Cocchi, Luca | Sweeney, Yann | Lee, Soohyun | Jung, Woo-Sung | Kim, Youngsoo | Jung, Younginha | Song, Yoon-Kyu | Chavane, Frédéric | Soman, Karthik | Muralidharan, Vignesh | Srinivasa Chakravarthy, V. | Shivkumar, Sabyasachi | Mandali, Alekhya | Pragathi Priyadharsini, B. | Mehta, Hima | Davey, Catherine E. | Brinkman, Braden A. W. | Kekona, Tyler | Rieke, Fred | Buice, Michael | De Pittà, Maurizio | Berry, Hugues | Brunel, Nicolas | Breakspear, Michael | Marsat, Gary | Drew, Jordan | Chapman, Phillip D. | Daly, Kevin C. | Bradle, Samual P. | Seo, Sat Byul | Su, Jianzhong | Kavalali, Ege T. | Blackwell, Justin | Shiau, LieJune | Buhry, Laure | Basnayake, Kanishka | Lee, Sue-Hyun | Levy, Brandon A. | Baker, Chris I. | Leleu, Timothée | Philips, Ryan T. | Chhabria, Karishma
BMC Neuroscience  2016;17(Suppl 1):54.
Table of contents
A1 Functional advantages of cell-type heterogeneity in neural circuits
Tatyana O. Sharpee
A2 Mesoscopic modeling of propagating waves in visual cortex
Alain Destexhe
A3 Dynamics and biomarkers of mental disorders
Mitsuo Kawato
F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons
Vladislav Sekulić, Frances K. Skinner
F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains
Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári
F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks.
Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić
O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators
Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona
O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain
Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi
O3 Modeling auditory stream segregation, build-up and bistability
James Rankin, Pamela Osborn Popp, John Rinzel
O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields
Alejandro Tabas, André Rupp, Emili Balaguer-Ballester
O5 A simple model of retinal response to multi-electrode stimulation
Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin
O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task
Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer
O7 Input-location dependent gain modulation in cerebellar nucleus neurons
Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Nielsen, Volker Steuber
O8 Analytic solution of cable energy function for cortical axons and dendrites
Huiwen Ju, Jiao Yu, Michael L. Hines, Liang Chen, Yuguo Yu
O9 C. elegans interactome: interactive visualization of Caenorhabditis elegans worm neuronal network
Jimin Kim, Will Leahy, Eli Shlizerman
O10 Is the model any good? Objective criteria for computational neuroscience model selection
Justas Birgiolas, Richard C. Gerkin, Sharon M. Crook
O11 Cooperation and competition of gamma oscillation mechanisms
Atthaphon Viriyopase, Raoul-Martin Memmesheimer, Stan Gielen
O12 A discrete structure of the brain waves
Yuri Dabaghian, Justin DeVito, Luca Perotti
O13 Direction-specific silencing of the Drosophila gaze stabilization system
Anmo J. Kim, Lisa M. Fenk, Cheng Lyu, Gaby Maimon
O14 What does the fruit fly think about values? A model of olfactory associative learning
Chang Zhao, Yves Widmer, Simon Sprecher,Walter Senn
O15 Effects of ionic diffusion on power spectra of local field potentials (LFP)
Geir Halnes, Tuomo Mäki-Marttunen, Daniel Keller, Klas H. Pettersen,Ole A. Andreassen, Gaute T. Einevoll
O16 Large-scale cortical models towards understanding relationship between brain structure abnormalities and cognitive deficits
Yasunori Yamada
O17 Spatial coarse-graining the brain: origin of minicolumns
Moira L. Steyn-Ross, D. Alistair Steyn-Ross
O18 Modeling large-scale cortical networks with laminar structure
Jorge F. Mejias, John D. Murray, Henry Kennedy, Xiao-Jing Wang
O19 Information filtering by partial synchronous spikes in a neural population
Alexandra Kruscha, Jan Grewe, Jan Benda, Benjamin Lindner
O20 Decoding context-dependent olfactory valence in Drosophila
Laurent Badel, Kazumi Ohta, Yoshiko Tsuchimoto, Hokto Kazama
P1 Neural network as a scale-free network: the role of a hub
B. Kahng
P2 Hemodynamic responses to emotions and decisions using near-infrared spectroscopy optical imaging
Nicoladie D. Tam
P3 Phase space analysis of hemodynamic responses to intentional movement directions using functional near-infrared spectroscopy (fNIRS) optical imaging technique
Nicoladie D.Tam, Luca Pollonini, George Zouridakis
P4 Modeling jamming avoidance of weakly electric fish
Jaehyun Soh, DaeEun Kim
P5 Synergy and redundancy of retinal ganglion cells in prediction
Minsu Yoo, S. E. Palmer
P6 A neural field model with a third dimension representing cortical depth
Viviana Culmone, Ingo Bojak
P7 Network analysis of a probabilistic connectivity model of the Xenopus tadpole spinal cord
Andrea Ferrario, Robert Merrison-Hort, Roman Borisyuk
P8 The recognition dynamics in the brain
Chang Sub Kim
P9 Multivariate spike train analysis using a positive definite kernel
Taro Tezuka
P10 Synchronization of burst periods may govern slow brain dynamics during general anesthesia
Pangyu Joo
P11 The ionic basis of heterogeneity affects stochastic synchrony
Young-Ah Rho, Shawn D. Burton, G. Bard Ermentrout, Jaeseung Jeong, Nathaniel N. Urban
P12 Circular statistics of noise in spike trains with a periodic component
Petr Marsalek
P14 Representations of directions in EEG-BCI using Gaussian readouts
Hoon-Hee Kim, Seok-hyun Moon, Do-won Lee, Sung-beom Lee, Ji-yong Lee, Jaeseung Jeong
P15 Action selection and reinforcement learning in basal ganglia during reaching movements
Yaroslav I. Molkov, Khaldoun Hamade, Wondimu Teka, William H. Barnett, Taegyo Kim, Sergey Markin, Ilya A. Rybak
P17 Axon guidance: modeling axonal growth in T-Junction assay
Csaba Forro, Harald Dermutz, László Demkó, János Vörös
P19 Transient cell assembly networks encode persistent spatial memories
Yuri Dabaghian, Andrey Babichev
P20 Theory of population coupling and applications to describe high order correlations in large populations of interacting neurons
Haiping Huang
P21 Design of biologically-realistic simulations for motor control
Sergio Verduzco-Flores
P22 Towards understanding the functional impact of the behavioural variability of neurons
Filipa Dos Santos, Peter Andras
P23 Different oscillatory dynamics underlying gamma entrainment deficits in schizophrenia
Christoph Metzner, Achim Schweikard, Bartosz Zurowski
P24 Memory recall and spike frequency adaptation
James P. Roach, Leonard M. Sander, Michal R. Zochowski
P25 Stability of neural networks and memory consolidation preferentially occur near criticality
Quinton M. Skilling, Nicolette Ognjanovski, Sara J. Aton, Michal Zochowski
P26 Stochastic Oscillation in Self-Organized Critical States of Small Systems: Sensitive Resting State in Neural Systems
Sheng-Jun Wang, Guang Ouyang, Jing Guang, Mingsha Zhang, K. Y. Michael Wong, Changsong Zhou
P27 Neurofield: a C++ library for fast simulation of 2D neural field models
Peter A. Robinson, Paula Sanz-Leon, Peter M. Drysdale, Felix Fung, Romesh G. Abeysuriya, Chris J. Rennie, Xuelong Zhao
P28 Action-based grounding: Beyond encoding/decoding in neural code
Yoonsuck Choe, Huei-Fang Yang
P29 Neural computation in a dynamical system with multiple time scales
Yuanyuan Mi, Xiaohan Lin, Si Wu
P30 Maximum entropy models for 3D layouts of orientation selectivity
Joscha Liedtke, Manuel Schottdorf, Fred Wolf
P31 A behavioral assay for probing computations underlying curiosity in rodents
Yoriko Yamamura, Jeffery R. Wickens
P32 Using statistical sampling to balance error function contributions to optimization of conductance-based models
Timothy Rumbell, Julia Ramsey, Amy Reyes, Danel Draguljić, Patrick R. Hof, Jennifer Luebke, Christina M. Weaver
P33 Exploration and implementation of a self-growing and self-organizing neuron network building algorithm
Hu He, Xu Yang, Hailin Ma, Zhiheng Xu, Yuzhe Wang
P34 Disrupted resting state brain network in obese subjects: a data-driven graph theory analysis
Kwangyeol Baek, Laurel S. Morris, Prantik Kundu, Valerie Voon
P35 Dynamics of cooperative excitatory and inhibitory plasticity
Everton J. Agnes, Tim P. Vogels
P36 Frequency-dependent oscillatory signal gating in feed-forward networks of integrate-and-fire neurons
William F. Podlaski, Tim P. Vogels
P37 Phenomenological neural model for adaptation of neurons in area IT
Martin Giese, Pradeep Kuravi, Rufin Vogels
P38 ICGenealogy: towards a common topology of neuronal ion channel function and genealogy in model and experiment
Alexander Seeholzer, William Podlaski, Rajnish Ranjan, Tim Vogels
P39 Temporal input discrimination from the interaction between dynamic synapses and neural subthreshold oscillations
Joaquin J. Torres, Fabiano Baroni, Roberto Latorre, Pablo Varona
P40 Different roles for transient and sustained activity during active visual processing
Bart Gips, Eric Lowet, Mark J. Roberts, Peter de Weerd, Ole Jensen, Jan van der Eerden
P41 Scale-free functional networks of 2D Ising model are highly robust against structural defects: neuroscience implications
Abdorreza Goodarzinick, Mohammad D. Niry, Alireza Valizadeh
P42 High frequency neuron can facilitate propagation of signal in neural networks
Aref Pariz, Shervin S. Parsi, Alireza Valizadeh
P43 Investigating the effect of Alzheimer’s disease related amyloidopathy on gamma oscillations in the CA1 region of the hippocampus
Julia M. Warburton, Lucia Marucci, Francesco Tamagnini, Jon Brown, Krasimira Tsaneva-Atanasova
P44 Long-tailed distributions of inhibitory and excitatory weights in a balanced network with eSTDP and iSTDP
Florence I. Kleberg, Jochen Triesch
P45 Simulation of EMG recording from hand muscle due to TMS of motor cortex
Bahar Moezzi, Nicolangelo Iannella, Natalie Schaworonkow, Lukas Plogmacher, Mitchell R. Goldsworthy, Brenton Hordacre, Mark D. McDonnell, Michael C. Ridding, Jochen Triesch
P46 Structure and dynamics of axon network formed in primary cell culture
Martin Zapotocky, Daniel Smit, Coralie Fouquet, Alain Trembleau
P47 Efficient signal processing and sampling in random networks that generate variability
Sakyasingha Dasgupta, Isao Nishikawa, Kazuyuki Aihara, Taro Toyoizumi
P48 Modeling the effect of riluzole on bursting in respiratory neural networks
Daniel T. Robb, Nick Mellen, Natalia Toporikova
P49 Mapping relaxation training using effective connectivity analysis
Rongxiang Tang, Yi-Yuan Tang
P50 Modeling neuron oscillation of implicit sequence learning
Guangsheng Liang, Seth A. Kiser, James H. Howard, Jr., Yi-Yuan Tang
P51 The role of cerebellar short-term synaptic plasticity in the pathology and medication of downbeat nystagmus
Julia Goncharenko, Neil Davey, Maria Schilstra, Volker Steuber
P52 Nonlinear response of noisy neurons
Sergej O. Voronenko, Benjamin Lindner
P53 Behavioral embedding suggests multiple chaotic dimensions underlie C. elegans locomotion
Tosif Ahamed, Greg Stephens
P54 Fast and scalable spike sorting for large and dense multi-electrodes recordings
Pierre Yger, Baptiste Lefebvre, Giulia Lia Beatrice Spampinato, Elric Esposito, Marcel Stimberg et Olivier Marre
P55 Sufficient sampling rates for fast hand motion tracking
Hansol Choi, Min-Ho Song
P56 Linear readout of object manifolds
SueYeon Chung, Dan D. Lee, Haim Sompolinsky
P57 Differentiating models of intrinsic bursting and rhythm generation of the respiratory pre-Bötzinger complex using phase response curves
Ryan S. Phillips, Jeffrey Smith
P58 The effect of inhibitory cell network interactions during theta rhythms on extracellular field potentials in CA1 hippocampus
Alexandra Pierri Chatzikalymniou, Katie Ferguson, Frances K. Skinner
P59 Expansion recoding through sparse sampling in the cerebellar input layer speeds learning
N. Alex Cayco Gajic, Claudia Clopath, R. Angus Silver
P60 A set of curated cortical models at multiple scales on Open Source Brain
Padraig Gleeson, Boris Marin, Sadra Sadeh, Adrian Quintana, Matteo Cantarelli, Salvador Dura-Bernal, William W. Lytton, Andrew Davison, R. Angus Silver
P61 A synaptic story of dynamical information encoding in neural adaptation
Luozheng Li, Wenhao Zhang, Yuanyuan Mi, Dahui Wang, Si Wu
P62 Physical modeling of rule-observant rodent behavior
Youngjo Song, Sol Park, Ilhwan Choi, Jaeseung Jeong, Hee-sup Shin
P64 Predictive coding in area V4 and prefrontal cortex explains dynamic discrimination of partially occluded shapes
Hannah Choi, Anitha Pasupathy, Eric Shea-Brown
P65 Stability of FORCE learning on spiking and rate-based networks
Dongsung Huh, Terrence J. Sejnowski
P66 Stabilising STDP in striatal neurons for reliable fast state recognition in noisy environments
Simon M. Vogt, Arvind Kumar, Robert Schmidt
P67 Electrodiffusion in one- and two-compartment neuron models for characterizing cellular effects of electrical stimulation
Stephen Van Wert, Steven J. Schiff
P68 STDP improves speech recognition capabilities in spiking recurrent circuits parameterized via differential evolution Markov Chain Monte Carlo
Richard Veale, Matthias Scheutz
P69 Bidirectional transformation between dominant cortical neural activities and phase difference distributions
Sang Wan Lee
P70 Maturation of sensory networks through homeostatic structural plasticity
Júlia Gallinaro, Stefan Rotter
P71 Corticothalamic dynamics: structure, number of solutions and stability of steady-state solutions in the space of synaptic couplings
Paula Sanz-Leon, Peter A. Robinson
P72 Optogenetic versus electrical stimulation of the parkinsonian basal ganglia. Computational study
Leonid L. Rubchinsky, Chung Ching Cheung, Shivakeshavan Ratnadurai-Giridharan
P73 Exact spike-timing distribution reveals higher-order interactions of neurons
Safura Rashid Shomali, Majid Nili Ahmadabadi, Hideaki Shimazaki, S. Nader Rasuli
P74 Neural mechanism of visual perceptual learning using a multi-layered neural network
Xiaochen Zhao, Malte J. Rasch
P75 Inferring collective spiking dynamics from mostly unobserved systems
Jens Wilting, Viola Priesemann
P76 How to infer distributions in the brain from subsampled observations
Anna Levina, Viola Priesemann
P77 Influences of embedding and estimation strategies on the inferred memory of single spiking neurons
Lucas Rudelt, Joseph T. Lizier, Viola Priesemann
P78 A nearest-neighbours based estimator for transfer entropy between spike trains
Joseph T. Lizier, Richard E. Spinney, Mikail Rubinov, Michael Wibral, Viola Priesemann
P79 Active learning of psychometric functions with multinomial logistic models
Ji Hyun Bak, Jonathan Pillow
P81 Inferring low-dimensional network dynamics with variational latent Gaussian process
Yuan Zaho, Il Memming Park
P82 Computational investigation of energy landscapes in the resting state subcortical brain network
Jiyoung Kang, Hae-Jeong Park
P83 Local repulsive interaction between retinal ganglion cells can generate a consistent spatial periodicity of orientation map
Jaeson Jang, Se-Bum Paik
P84 Phase duration of bistable perception reveals intrinsic time scale of perceptual decision under noisy condition
Woochul Choi, Se-Bum Paik
P85 Feedforward convergence between retina and primary visual cortex can determine the structure of orientation map
Changju Lee, Jaeson Jang, Se-Bum Paik
P86 Computational method classifying neural network activity patterns for imaging data
Min Song, Hyeonsu Lee, Se-Bum Paik
P87 Symmetry of spike-timing-dependent-plasticity kernels regulates volatility of memory
Youngjin Park, Woochul Choi, Se-Bum Paik
P88 Effects of time-periodic coupling strength on the first-spike latency dynamics of a scale-free network of stochastic Hodgkin-Huxley neurons
Ergin Yilmaz, Veli Baysal, Mahmut Ozer
P89 Spectral properties of spiking responses in V1 and V4 change within the trial and are highly relevant for behavioral performance
Veronika Koren, Klaus Obermayer
P90 Methods for building accurate models of individual neurons
Daniel Saska, Thomas Nowotny
P91 A full size mathematical model of the early olfactory system of honeybees
Ho Ka Chan, Alan Diamond, Thomas Nowotny
P92 Stimulation-induced tuning of ongoing oscillations in spiking neural networks
Christoph S. Herrmann, Micah M. Murray, Silvio Ionta, Axel Hutt, Jérémie Lefebvre
P93 Decision-specific sequences of neural activity in balanced random networks driven by structured sensory input
Philipp Weidel, Renato Duarte, Abigail Morrison
P94 Modulation of tuning induced by abrupt reduction of SST cell activity
Jung H. Lee, Ramakrishnan Iyer, Stefan Mihalas
P95 The functional role of VIP cell activation during locomotion
Jung H. Lee, Ramakrishnan Iyer, Christof Koch, Stefan Mihalas
P96 Stochastic inference with spiking neural networks
Mihai A. Petrovici, Luziwei Leng, Oliver Breitwieser, David Stöckel, Ilja Bytschok, Roman Martel, Johannes Bill, Johannes Schemmel, Karlheinz Meier
P97 Modeling orientation-selective electrical stimulation with retinal prostheses
Timothy B. Esler, Anthony N. Burkitt, David B. Grayden, Robert R. Kerr, Bahman Tahayori, Hamish Meffin
P98 Ion channel noise can explain firing correlation in auditory nerves
Bahar Moezzi, Nicolangelo Iannella, Mark D. McDonnell
P99 Limits of temporal encoding of thalamocortical inputs in a neocortical microcircuit
Max Nolte, Michael W. Reimann, Eilif Muller, Henry Markram
P100 On the representation of arm reaching movements: a computational model
Antonio Parziale, Rosa Senatore, Angelo Marcelli
P101 A computational model for investigating the role of cerebellum in acquisition and retention of motor behavior
Rosa Senatore, Antonio Parziale, Angelo Marcelli
P102 The emergence of semantic categories from a large-scale brain network of semantic knowledge
K. Skiker, M. Maouene
P103 Multiscale modeling of M1 multitarget pharmacotherapy for dystonia
Samuel A. Neymotin, Salvador Dura-Bernal, Alexandra Seidenstein, Peter Lakatos, Terence D. Sanger, William W. Lytton
P104 Effect of network size on computational capacity
Salvador Dura-Bernal, Rosemary J. Menzies, Campbell McLauchlan, Sacha J. van Albada, David J. Kedziora, Samuel Neymotin, William W. Lytton, Cliff C. Kerr
P105 NetPyNE: a Python package for NEURON to facilitate development and parallel simulation of biological neuronal networks
Salvador Dura-Bernal, Benjamin A. Suter, Samuel A. Neymotin, Cliff C. Kerr, Adrian Quintana, Padraig Gleeson, Gordon M. G. Shepherd, William W. Lytton
P107 Inter-areal and inter-regional inhomogeneity in co-axial anisotropy of Cortical Point Spread in human visual areas
Juhyoung Ryu, Sang-Hun Lee
P108 Two bayesian quanta of uncertainty explain the temporal dynamics of cortical activity in the non-sensory areas during bistable perception
Joonwon Lee, Sang-Hun Lee
P109 Optimal and suboptimal integration of sensory and value information in perceptual decision making
Hyang Jung Lee, Sang-Hun Lee
P110 A Bayesian algorithm for phoneme Perception and its neural implementation
Daeseob Lim, Sang-Hun Lee
P111 Complexity of EEG signals is reduced during unconsciousness induced by ketamine and propofol
Jisung Wang, Heonsoo Lee
P112 Self-organized criticality of neural avalanche in a neural model on complex networks
Nam Jung, Le Anh Quang, Seung Eun Maeng, Tae Ho Lee, Jae Woo Lee
P113 Dynamic alterations in connection topology of the hippocampal network during ictal-like epileptiform activity in an in vitro rat model
Chang-hyun Park, Sora Ahn, Jangsup Moon, Yun Seo Choi, Juhee Kim, Sang Beom Jun, Seungjun Lee, Hyang Woon Lee
P114 Computational model to replicate seizure suppression effect by electrical stimulation
Sora Ahn, Sumin Jo, Eunji Jun, Suin Yu, Hyang Woon Lee, Sang Beom Jun, Seungjun Lee
P115 Identifying excitatory and inhibitory synapses in neuronal networks from spike trains using sorted local transfer entropy
Felix Goetze, Pik-Yin Lai
P116 Neural network model for obstacle avoidance based on neuromorphic computational model of boundary vector cell and head direction cell
Seonghyun Kim, Jeehyun Kwag
P117 Dynamic gating of spike pattern propagation by Hebbian and anti-Hebbian spike timing-dependent plasticity in excitatory feedforward network model
Hyun Jae Jang, Jeehyun Kwag
P118 Inferring characteristics of input correlations of cells exhibiting up-down state transitions in the rat striatum
Marko Filipović, Ramon Reig, Ad Aertsen, Gilad Silberberg, Arvind Kumar
P119 Graph properties of the functional connected brain under the influence of Alzheimer’s disease
Claudia Bachmann, Simone Buttler, Heidi Jacobs, Kim Dillen, Gereon R. Fink, Juraj Kukolja, Abigail Morrison
P120 Learning sparse representations in the olfactory bulb
Daniel Kepple, Hamza Giaffar, Dima Rinberg, Steven Shea, Alex Koulakov
P121 Functional classification of homologous basal-ganglia networks
Jyotika Bahuguna,Tom Tetzlaff, Abigail Morrison, Arvind Kumar, Jeanette Hellgren Kotaleski
P122 Short term memory based on multistability
Tim Kunze, Andre Peterson, Thomas Knösche
P123 A physiologically plausible, computationally efficient model and simulation software for mammalian motor units
Minjung Kim, Hojeong Kim
P125 Decoding laser-induced somatosensory information from EEG
Ji Sung Park, Ji Won Yeon, Sung-Phil Kim
P126 Phase synchronization of alpha activity for EEG-based personal authentication
Jae-Hwan Kang, Chungho Lee, Sung-Phil Kim
P129 Investigating phase-lags in sEEG data using spatially distributed time delays in a large-scale brain network model
Andreas Spiegler, Spase Petkoski, Matias J. Palva, Viktor K. Jirsa
P130 Epileptic seizures in the unfolding of a codimension-3 singularity
Maria L. Saggio, Silvan F. Siep, Andreas Spiegler, William C. Stacey, Christophe Bernard, Viktor K. Jirsa
P131 Incremental dimensional exploratory reasoning under multi-dimensional environment
Oh-hyeon Choung, Yong Jeong
P132 A low-cost model of eye movements and memory in personal visual cognition
Yong-il Lee, Jaeseung Jeong
P133 Complex network analysis of structural connectome of autism spectrum disorder patients
Su Hyun Kim, Mir Jeong, Jaeseung Jeong
P134 Cognitive motives and the neural correlates underlying human social information transmission, gossip
Jeungmin Lee, Jaehyung Kwon, Jerald D. Kralik, Jaeseung Jeong
P135 EEG hyperscanning detects neural oscillation for the social interaction during the economic decision-making
Jaehwan Jahng, Dong-Uk Hwang, Jaeseung Jeong
P136 Detecting purchase decision based on hyperfrontality of the EEG
Jae-Hyung Kwon, Sang-Min Park, Jaeseung Jeong
P137 Vulnerability-based critical neurons, synapses, and pathways in the Caenorhabditis elegans connectome
Seongkyun Kim, Hyoungkyu Kim, Jerald D. Kralik, Jaeseung Jeong
P138 Motif analysis reveals functionally asymmetrical neurons in C. elegans
Pyeong Soo Kim, Seongkyun Kim, Hyoungkyu Kim, Jaeseung Jeong
P139 Computational approach to preference-based serial decision dynamics: do temporal discounting and working memory affect it?
Sangsup Yoon, Jaehyung Kwon, Sewoong Lim, Jaeseung Jeong
P141 Social stress induced neural network reconfiguration affects decision making and learning in zebrafish
Choongseok Park, Thomas Miller, Katie Clements, Sungwoo Ahn, Eoon Hye Ji, Fadi A. Issa
P142 Descriptive, generative, and hybrid approaches for neural connectivity inference from neural activity data
JeongHun Baek, Shigeyuki Oba, Junichiro Yoshimoto, Kenji Doya, Shin Ishii
P145 Divergent-convergent synaptic connectivities accelerate coding in multilayered sensory systems
Thiago S. Mosqueiro, Martin F. Strube-Bloss, Brian Smith, Ramon Huerta
P146 Swinging networks
Michal Hadrava, Jaroslav Hlinka
P147 Inferring dynamically relevant motifs from oscillatory stimuli: challenges, pitfalls, and solutions
Hannah Bos, Moritz Helias
P148 Spatiotemporal mapping of brain network dynamics during cognitive tasks using magnetoencephalography and deep learning
Charles M. Welzig, Zachary J. Harper
P149 Multiscale complexity analysis for the segmentation of MRI images
Won Sup Kim, In-Seob Shin, Hyeon-Man Baek, Seung Kee Han
P150 A neuro-computational model of emotional attention
René Richter, Julien Vitay, Frederick Beuth, Fred H. Hamker
P151 Multi-site delayed feedback stimulation in parkinsonian networks
Kelly Toppin, Yixin Guo
P152 Bistability in Hodgkin–Huxley-type equations
Tatiana Kameneva, Hamish Meffin, Anthony N. Burkitt, David B. Grayden
P153 Phase changes in postsynaptic spiking due to synaptic connectivity and short term plasticity: mathematical analysis of frequency dependency
Mark D. McDonnell, Bruce P. Graham
P154 Quantifying resilience patterns in brain networks: the importance of directionality
Penelope J. Kale, Leonardo L. Gollo
P155 Dynamics of rate-model networks with separate excitatory and inhibitory populations
Merav Stern, L. F. Abbott
P156 A model for multi-stable dynamics in action recognition modulated by integration of silhouette and shading cues
Leonid A. Fedorov, Martin A. Giese
P157 Spiking model for the interaction between action recognition and action execution
Mohammad Hovaidi Ardestani, Martin Giese
P158 Surprise-modulated belief update: how to learn within changing environments?
Mohammad Javad Faraji, Kerstin Preuschoff, Wulfram Gerstner
P159 A fast, stochastic and adaptive model of auditory nerve responses to cochlear implant stimulation
Margriet J. van Gendt, Jeroen J. Briaire, Randy K. Kalkman, Johan H. M. Frijns
P160 Quantitative comparison of graph theoretical measures of simulated and empirical functional brain networks
Won Hee Lee, Sophia Frangou
P161 Determining discriminative properties of fMRI signals in schizophrenia using highly comparative time-series analysis
Ben D. Fulcher, Patricia H. P. Tran, Alex Fornito
P162 Emergence of narrowband LFP oscillations from completely asynchronous activity during seizures and high-frequency oscillations
Stephen V. Gliske, William C. Stacey, Eugene Lim, Katherine A. Holman, Christian G. Fink
P163 Neuronal diversity in structure and function: cross-validation of anatomical and physiological classification of retinal ganglion cells in the mouse
Jinseop S. Kim, Shang Mu, Kevin L. Briggman, H. Sebastian Seung, the EyeWirers
P164 Analysis and modelling of transient firing rate changes in area MT in response to rapid stimulus feature changes
Detlef Wegener, Lisa Bohnenkamp, Udo A. Ernst
P165 Step-wise model fitting accounting for high-resolution spatial measurements: construction of a layer V pyramidal cell model with reduced morphology
Tuomo Mäki-Marttunen, Geir Halnes, Anna Devor, Christoph Metzner, Anders M. Dale, Ole A. Andreassen, Gaute T. Einevoll
P166 Contributions of schizophrenia-associated genes to neuron firing and cardiac pacemaking: a polygenic modeling approach
Tuomo Mäki-Marttunen, Glenn T. Lines, Andy Edwards, Aslak Tveito, Anders M. Dale, Gaute T. Einevoll, Ole A. Andreassen
P167 Local field potentials in a 4 × 4 mm2 multi-layered network model
Espen Hagen, Johanna Senk, Sacha J. van Albada, Markus Diesmann
P168 A spiking network model explains multi-scale properties of cortical dynamics
Maximilian Schmidt, Rembrandt Bakker, Kelly Shen, Gleb Bezgin, Claus-Christian Hilgetag, Markus Diesmann, Sacha Jennifer van Albada
P169 Using joint weight-delay spike-timing dependent plasticity to find polychronous neuronal groups
Haoqi Sun, Olga Sourina, Guang-Bin Huang, Felix Klanner, Cornelia Denk
P170 Tensor decomposition reveals RSNs in simulated resting state fMRI
Katharina Glomb, Adrián Ponce-Alvarez, Matthieu Gilson, Petra Ritter, Gustavo Deco
P171 Getting in the groove: testing a new model-based method for comparing task-evoked vs resting-state activity in fMRI data on music listening
Matthieu Gilson, Maria AG Witek, Eric F. Clarke, Mads Hansen, Mikkel Wallentin, Gustavo Deco, Morten L. Kringelbach, Peter Vuust
P172 STochastic engine for pathway simulation (STEPS) on massively parallel processors
Guido Klingbeil, Erik De Schutter
P173 Toolkit support for complex parallel spatial stochastic reaction–diffusion simulation in STEPS
Weiliang Chen, Erik De Schutter
P174 Modeling the generation and propagation of Purkinje cell dendritic spikes caused by parallel fiber synaptic input
Yunliang Zang, Erik De Schutter
P175 Dendritic morphology determines how dendrites are organized into functional subunits
Sungho Hong, Akira Takashima, Erik De Schutter
P176 A model of Ca2+/calmodulin-dependent protein kinase II activity in long term depression at Purkinje cells
Criseida Zamora, Andrew R. Gallimore, Erik De Schutter
P177 Reward-modulated learning of population-encoded vectors for insect-like navigation in embodied agents
Dennis Goldschmidt, Poramate Manoonpong, Sakyasingha Dasgupta
P178 Data-driven neural models part II: connectivity patterns of human seizures
Philippa J. Karoly, Dean R. Freestone, Daniel Soundry, Levin Kuhlmann, Liam Paninski, Mark Cook
P179 Data-driven neural models part I: state and parameter estimation
Dean R. Freestone, Philippa J. Karoly, Daniel Soundry, Levin Kuhlmann, Mark Cook
P180 Spectral and spatial information processing in human auditory streaming
Jaejin Lee, Yonatan I. Fishman, Yale E. Cohen
P181 A tuning curve for the global effects of local perturbations in neural activity: Mapping the systems-level susceptibility of the brain
Leonardo L. Gollo, James A. Roberts, Luca Cocchi
P182 Diverse homeostatic responses to visual deprivation mediated by neural ensembles
Yann Sweeney, Claudia Clopath
P183 Opto-EEG: a novel method for investigating functional connectome in mouse brain based on optogenetics and high density electroencephalography
Soohyun Lee, Woo-Sung Jung, Jee Hyun Choi
P184 Biphasic responses of frontal gamma network to repetitive sleep deprivation during REM sleep
Bowon Kim, Youngsoo Kim, Eunjin Hwang, Jee Hyun Choi
P185 Brain-state correlate and cortical connectivity for frontal gamma oscillations in top-down fashion assessed by auditory steady-state response
Younginha Jung, Eunjin Hwang, Yoon-Kyu Song, Jee Hyun Choi
P186 Neural field model of localized orientation selective activation in V1
James Rankin, Frédéric Chavane
P187 An oscillatory network model of Head direction and Grid cells using locomotor inputs
Karthik Soman, Vignesh Muralidharan, V. Srinivasa Chakravarthy
P188 A computational model of hippocampus inspired by the functional architecture of basal ganglia
Karthik Soman, Vignesh Muralidharan, V. Srinivasa Chakravarthy
P189 A computational architecture to model the microanatomy of the striatum and its functional properties
Sabyasachi Shivkumar, Vignesh Muralidharan, V. Srinivasa Chakravarthy
P190 A scalable cortico-basal ganglia model to understand the neural dynamics of targeted reaching
Vignesh Muralidharan, Alekhya Mandali, B. Pragathi Priyadharsini, Hima Mehta, V. Srinivasa Chakravarthy
P191 Emergence of radial orientation selectivity from synaptic plasticity
Catherine E. Davey, David B. Grayden, Anthony N. Burkitt
P192 How do hidden units shape effective connections between neurons?
Braden A. W. Brinkman, Tyler Kekona, Fred Rieke, Eric Shea-Brown, Michael Buice
P193 Characterization of neural firing in the presence of astrocyte-synapse signaling
Maurizio De Pittà, Hugues Berry, Nicolas Brunel
P194 Metastability of spatiotemporal patterns in a large-scale network model of brain dynamics
James A. Roberts, Leonardo L. Gollo, Michael Breakspear
P195 Comparison of three methods to quantify detection and discrimination capacity estimated from neural population recordings
Gary Marsat, Jordan Drew, Phillip D. Chapman, Kevin C. Daly, Samual P. Bradley
P196 Quantifying the constraints for independent evoked and spontaneous NMDA receptor mediated synaptic transmission at individual synapses
Sat Byul Seo, Jianzhong Su, Ege T. Kavalali, Justin Blackwell
P199 Gamma oscillation via adaptive exponential integrate-and-fire neurons
LieJune Shiau, Laure Buhry, Kanishka Basnayake
P200 Visual face representations during memory retrieval compared to perception
Sue-Hyun Lee, Brandon A. Levy, Chris I. Baker
P201 Top-down modulation of sequential activity within packets modeled using avalanche dynamics
Timothée Leleu, Kazuyuki Aihara
Q28 An auto-encoder network realizes sparse features under the influence of desynchronized vascular dynamics
Ryan T. Philips, Karishma Chhabria, V. Srinivasa Chakravarthy
PMCID: PMC5001212  PMID: 27534393
23.  Polymer Amide as an Early Topology 
PLoS ONE  2014;9(7):e103036.
Hydrophobic polymer amide (HPA) could have been one of the first normal density materials to accrete in space. We present ab initio calculations of the energetics of amino acid polymerization via gas phase collisions. The initial hydrogen-bonded di-peptide is sufficiently stable to proceed in many cases via a transition state into a di-peptide with an associated bound water molecule of condensation. The energetics of polymerization are only favorable when the water remains bound. Further polymerization leads to a hydrophobic surface that is phase-separated from, but hydrogen bonded to, a small bulk water complex. The kinetics of the collision and subsequent polymerization are discussed for the low-density conditions of a molecular cloud. This polymer in the gas phase has the properties to make a topology, viz. hydrophobicity allowing phase separation from bulk water, capability to withstand large temperature ranges, versatility of form and charge separation. Its flexible tetrahedral carbon atoms that alternate with more rigid amide groups allow it to deform and reform in hazardous conditions and its density of hydrogen bonds provides adhesion that would support accretion to it of silicon and metal elements to form a stellar dust material.
PMCID: PMC4105422  PMID: 25048204
24.  ETS-NOCV description of σ-hole bonding 
Journal of Molecular Modeling  2012;19(7):2747-2758.
The ETS-NOCV analysis was applied to describe the σ-hole in a systematic way in a series of halogen compounds, CF3-X (X = I, Br, Cl, F), CH3I, and C(CH3)nH3-n-I (n = 1,2,3), as well as for the example germanium-based systems. GeXH3, X = F, Cl, H. Further, the ETS-NOCV analysis was used to characterize bonding with ammonia for these systems. The results show that the dominating contribution to the deformation density, Δρ1, exhibits the negative-value area with a minimum, corresponding to σ-hole. The “size” (spatial extension of negative value) and “depth” (minium value) of the σ-hole varies for different X in CF3-X, and is influenced by the carbon substituents (fluorine atoms, hydrogen atoms, methyl groups). The size and depth of σ-hole decreases in the order: I, Br, Cl, F in CF3-X. In CH3-I and C(CH3)nH3-n-I, compared to CF3-I, introduction of hydrogen atoms and their subsequent replacements by methyl groups lead to the systematic decrease in the σ-hole size and depth. The ETS-NOCV σ-hole picture is consistent with the existence the positive MEP area at the extension of σ-hole generating bond. Finally, the NOCV deformation density contours as well as by the ETS orbital-interaction energy indicate that the σ-hole-based bond with ammonia contains a degree of covalent contribution. In all analyzed systems, it was found that the electrostatic energy is approximately two times larger than the orbital-interaction term, confirming the indisputable role of the electrostatic stabilization in halogen bonding and σ-hole bonding.
FigureGraphical representation of the σ-hole on the halogen atom, based on the molecular electrostatic potential (upper row) and the NOCV deformation-density channel Δρ1 (lower row and the right-hand side plot)
PMCID: PMC3693432  PMID: 23053006
ETS-NOCV; Halogen bonding; Sigma hole bonding
25.  Molecular Designs for Controlling the Local Environments around Metal Ions 
Accounts of chemical research  2015;48(8):2407-2414.
The functions of metal complexes are directly linked to the local environment in which they are housed; modifications to the local environment (or secondary coordination sphere) are known to produce changes in key properties of the metal centers that can affect reactivity. Non-covalent interactions are the most common and influential forces that regulate the properties of secondary coordination spheres, which leads to complexities in structure that are often difficult to achieve in synthetic systems. Using key architectural features from the active sites of metalloproteins as inspiration, we have developed molecular systems that enforce intramolecular hydrogen bonds (H-bonds) around a metal center via incorporation of H-bond donors and acceptors into rigid ligand scaffolds. We have utilized these molecular species to probe mechanistic aspects of biological dioxygen activation and water oxidation.
This Account describes the stabilization and characterization of unusual M–oxo and heterobimetallic complexes. These types of species have been implicated in a range of oxidative processes in biology but are often difficult to study because of their inherent reactivity. Our H-bonding ligand systems allowed us to prepare an FeIII–oxo species directly from the activation of O2 that was subsequently oxidized to form a monomeric FeIV–oxo species with an S = 2 spin state, similar to those species proposed as key intermediates in non-heme monooxygenases. We also demonstrated that a single MnIII–oxo center that was prepared from water could be converted to a high spin MnV–oxo species via stepwise oxidation—a process that mimics the oxidative charging of the oxygen-evolving complex (OEC) of photosystem II.
Current mechanisms for photosynthetic O–O bond formation invoke a MnIV–oxyl species rather than the isoelectronic MnV–oxo system as the key oxidant based on computational studies. However, there is no experimental information to support the existence of an Mn–oxyl radical. We therefore probed the amount of spin density on the oxido ligand of our complexes using EPR spectroscopy in conjunction with oxygen-17 labeling. Our findings showed that there is a significant amount of spin on the oxido ligand, yet the M–oxo bonds are best described as highly covalent and there is no indication that an oxyl radical is formed. These results offer the intriguing possibility that high spin M–oxo complexes are involved in O–O bond formation in biology.
Ligand redesign to incorporate H-bond accepting units (sulfonamido groups) simultaneously provided a metal ion binding pocket, adjacent H-bond acceptors, and an auxiliary binding site for a second metal ion. These properties allowed us to isolate a series of heterobimetallic complexes of FeIII and MnIII in which a group II metal ion was coordinated within the secondary coordination sphere. Examination of the influence of the second metal ion on the electron transfer properties of the primary metal center revealed unexpected similarities between CaII and SrII ions—a result with relevance to the OEC. In addition, the presence of a second metal ion was found to prevent intramolecular oxidation of the ligand with an O-atom transfer reagent.
PMCID: PMC5097670  PMID: 26181849

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