2014 Publications

41 HBP-funded scientific publications in 2014

Abdelmoula, W. M., Škrášková, K., Balluff, B., Carreira, R. J., Tolner, E. A., Lelieveldt, B. P., van der Maaten, L., Hans Morreau, H., van den Maagdenberg, A. M. J. M, Heeren, R. M. A., McDonnell, L. A. & Dijkstra, J. (2014). Automatic generic registration of mass spectrometry imaging data to histology using nonlinear stochastic embeddingAnalytical Chemistry86: 9204-9211.

Adhikari, P. R., Vavpetič, A., Kralj, J., Lavrač, N., & Hollmén, J. (2014, January). Explaining Mixture Models through Semantic Pattern Mining and Banded Matrix VisualizationDiscovery Science 8777: 1-12.

Anton-Sanchez, L., Bielza, C., Merchán-Pérez, A., Rodríguez, J. R., DeFelipe, J., & Larrañaga, P. (2014). Three-dimensional distribution of cortical synapses: a replicated point pattern-based analysisFrontiers in Neuroanatomy8: 1-15.

Antonelli, R., Pizzarelli, R., Pedroni, A., Fritschy, J. M., Del Sal, G., Cherubini, E., & Zacchi, P. (2014). Pin1-dependent signalling negatively affects GABAergic transmission by modulating neuroligin2/gephyrin interactionNature Communications5: 5066.

Asllani, M., Challenger, J. D., Pavone, F. S., Sacconi, L., & Fanelli, D. (2014). The theory of pattern formation on directed networksNature Communications5: 4517.

Bedard, C., & Destexhe, A. (2014). Generalized cable formalism to calculate the magnetic field of single neurons and neuronal populationsPhysical Review E, Statistical, Nonlinear, and Soft Matter Physics, 90: 042723. 

Bielza, C., & Larrañaga, P. (2014). Bayesian networks in neuroscience: a surveyFrontiers in Computational Neuroscience8: 131.

Bill, J., & Legenstein, R. (2014). A compound memristive synapse model for statistical learning through STDP in spiking neural networksFrontiers in Neuroscience8: 412.

Castellazzi, G., Palesi, F., Casali, S., Vitali, P., Sinforiani, E., Wheeler-Kingshott, C. A., & D'Angelo, E. (2014). A comprehensive assessment of resting state networks: bidirectional modification of functional integrity in cerebro-cerebellar networks in dementiaFrontiers in Neuroscience8: 223.

Chiovini, B., Turi, G. F., Katona, G., Kaszás, A., Pálfi, D., Maák, P., Gergely Szalay, G., Szabó, M. F., Szabó, G., Szadai Z., Káli, S. & Rózsa, B. (2014). Dendritic spikes induce ripples in parvalbumin interneurons during hippocampal sharp wavesNeuron82: 908-924.

Clarke, A. M., Herzog, M. H., & Francis, G. (2014). Visual crowding illustrates the inadequacy of local vs. global and feedforward vs. feedback distinctions in modeling visual perceptionFrontiers in Psychology5: 1193.

Corenthy, L., Garcia, M., Bayona, S., Santuy, A., San Martin, J., Benavides-Piccione, R., DeFelipe, J. & Pastor, L. (2014). Haptically Assisted Connection Procedure for the Reconstruction of Dendritic SpinesHaptics, IEEE Transactions on7: 486-498.

D'Angelo, E. (2014). The organization of plasticity in the cerebellar cortex: from synapses to controlProgress in Brain Research210: 31-58.

Frasconi, P., Silvestri, L., Soda, P., Cortini, R., Pavone, F. S., & Iannello, G. (2014). Large-scale automated identification of mouse brain cells in confocal light sheet microscopy imagesBioinformatics, 30: i587-i593.

Friedrich, P., Vella, M., Gulyás, A. I., Freund, T. F., & Káli, S. (2014). A flexible, interactive software tool for fitting the parameters of neuronal modelsFrontiers in Neuroinformatics8: 63.

Gandolfi, D., Pozzi, P., Tognolina, M., Chirico, G., Mapelli, J., & D'Angelo, E. (2014). The spatiotemporal organization of cerebellar network activity resolved by two-photon imaging of multiple single neuronsFrontiers in Cellular Neuroscience8: 92.

Giese, M. A. (2014). Skeleton model for the neurodynamics of visual action representationsArtificial Neural Networks and Machine Learning8681 :707-714.

Gudu, D., Hardt, M., & Streit, A. (2014). Evaluating the performance and scalability of the Ceph distributed storage system2014 IEEE International Conference onBig Data: 177-182.

Hernando, J. B., Duelo, C., & Martin, V. (2014). Visualization of Large-Scale Neural SimulationsBrain-Inspired Computing8603: 184-197.

Jonke, Z., Habenschuss, S., & Maass, W. (2014). A theoretical basis for efficient computations with noisy spiking neuronsarXiv preprint arXiv:1412.5862.

Kabdebon, C., Leroy, F., Simmonet, H., Perrot, M., Dubois, J., & Dehaene-Lambertz, G. (2014). Anatomical correlations of the international 10–20 sensor placement system in infantsNeuroImage99: 342-356.

King, J. R., & Dehaene, S. (2014). A model of subjective report and objective discrimination as categorical decisions in a vast representational space. Philosophical Transactions of the Royal Society B: Biological Sciences, 369(1641): 20130204.

Kunkel, S., Schmidt, M., Eppler, J. M., Plesser, H. E., Masumoto, G., Igarashi, J., Ishii, S., Fukai, T., Morrison, A., Diesmann, M. & Helias, M. (2014). Spiking network simulation code for petascale computersFrontiers in Neuroinformatics8: 78.

Legenstein, R., & Maass, W. (2014). Ensembles of spiking neurons with noise support optimal probabilistic inference in a dynamically changing environmentPLoS Computational Biology10(10): e1003859.

Maass, W. (2014). Noise as a resource for computation and learning in networks of spiking neuronsProceedings of the IEEE102(5): 860-880.

Mapelli, L., Solinas, S., & D'Angelo, E. (2014). Integration and regulation of glomerular inhibition in the cerebellar granular layer circuit. Frontiers in Cellular Neuroscience8: 55.

Mihaljević, B., Bielza, C., Benavides-Piccione, R., DeFelipe, J., & Larrañaga, P. (2014). Multi-dimensional classification of GABAergic interneurons with Bayesian network-modeled label uncertainty. Frontiers in Computational Neuroscience8: 150.

Monaco, J., Casellato, C., Koch, G., & D'Angelo, E. (2014). Cerebellar theta burst stimulation dissociates memory components in eyeblink classical conditioningEuropean Journal of Neuroscience40: 3363-3370.

Morales, J., Benavides-Piccione, R., Dar, M., Fernaud, I., Rodríguez, A., Anton-Sanchez, L., Bielza, C., Larrañaga, P., DeFelipe, J. & Yuste, R. (2014). Random Positions of Dendritic Spines in Human Cerebral CortexThe Journal of Neuroscience34: 10078-10084.

Nachbaur, D., Dumusc, R., Bilgili, A., Hernando, J., & Eilemann, S. (2015). Remote parallel rendering for high-resolution tiled display walls. Proceedings of IEEE Symposium on Large Data Analysis and Visualization. 

Naud, R., Bathellier, B., & Gerstner, W. (2014). Spike-timing prediction in cortical neurons with active dendritesFrontiers in Computational Neuroscience,8: 90.

Nieus, T. R., Mapelli, L., & D'Angelo, E. (2014). Regulation of output spike patterns by phasic inhibition in cerebellar granule cellsFrontiers in cellular neuroscience8: 246.

Pecevski, D., Kappel, D., & Jonke, Z. (2014). NEVESIM: event-driven neural simulation framework with a Python interface. Frontiers in Neuroinformatics8: 70.

Raya, L., Bayona, S., Pastor, L., & Garcia, M. (2014). A new user-adapted search haptic algorithm to navigate along filiform structuresIEEE Transactions on Haptics7(3): 273-284.

Robnik-Šikonja, M. (2014). Generator of unsupervised semi-artificial data. University of Lublijana, Faculty of Computer and Information Science.

Schlingloff, D., Káli, S., Freund, T. F., Hájos, N., & Gulyás, A. I. (2014). Mechanisms of sharp wave initiation and ripple generationThe Journal of Neuroscience34(34): 11385-11398.

Schuller, B., Benedyczak, K., & Rybicki, J. (2014). High-Performance Computing on the Web: Extending UNICORE with RESTful Interfaces. In The Sixth International Conference on Advances in Future Internet (No. FZJ-2014-06228). Jülich Supercomputing Center.

Subramaniyam, S., Solinas, S., Perin, P., Locatelli, F., Masetto, S., & D'Angelo, E. (2014). Computational modeling predicts the ionic mechanism of late-onset responses in unipolar brush cellsFrontiers in Cellular Neuroscience8: 237.

Testa-Silva, G., Verhoog, B., Linaro, D., de Kock, C.P., Baayen, J.C., Meredith, R.M., De Zeeuw, C.I., Giugliano, M., & Mansvelder, H.D. (2014). High bandwidth synaptic communication and frequency tracking in human neocortexPLoS Biology, 12: e1002007.

Van Der Maaten, L. (2014). Accelerating t-SNE using tree-based algorithmsThe Journal of Machine Learning Research15(1), 3221-3245.

Velychko, D., Endres, D., Taubert, N., & Giese, M. A. (2014). Coupling Gaussian Process Dynamical Models with Product-of-Experts Kernels. Artificial Neural Networks and Machine Learning–ICANN 20148681: 603-610.

 

Other relevant publications

Amunts, K., Lindner, A., & Zilles, K. (2014). The human brain project: neuroscience perspectives and German contributionse-Neuroforum5(2): 43-50.

Amunts, K., Zilles, K., & Lindner, A. (2014). The Human Brain Project: Neurowissenschaftliche Perspektiven und Beiträge aus Deutschland. Neuroforum2(14): 222-229.

Barry, C., & Burgess, N. (2014). Neural mechanisms of self-locationCurrent Biology24: R330-R339.

Bédard, C., & Destexhe, A. (2014). Mean-Field Formulation of Maxwell Equations to Model Electrically Inhomogeneous and Isotropic Media. Journal of Electromagnetic Analysis and Applications6: 296-302.

Ben-Yakov, A., Rubinson, M., & Dudai, Y. (2014). Shifting gears in hippocampus: temporal dissociation between familiarity and novel signatures in a single eventJournal of Neuroscience, 34: 12973-12981.

Bielza, C., Benavides-Piccione, R., López-Cruz, P., Larranaga, P., & DeFelipe, J. (2014). Branching angles of pyramidal cell dendrites follow common geometrical design principles in different cortical areasScientific Reports4: 5909.

Bush, D., & Burgess, N. (2014). A hybrid oscillatory interference/continuous attractor network model of grid cell firing. The Journal of Neuroscience34(14): 5065-5079.

Bush, D., Barry, C., & Burgess, N. (2014). What do grid cells contribute to place cell firing? Trends in Neurosciences37: 136-145.

Cabral, J., Kringelbach, M. L., & Deco, G. (2014). Exploring the network dynamics underlying brain activity during restProgress in Neurobiology114: 102-131.

Cabral, J., Luckhoo, H., Woolrich, M., Joensson, M., Mohseni, H., Baker, A., Kringelbach, M. L. & Deco, G. (2014). Exploring mechanisms of spontaneous functional connectivity in MEG: how delayed network interactions lead to structured amplitude envelopes of band-pass filtered oscillationsNeuroimage90, 423-435.

Caspers, J., Zilles, K., Amunts, K., Laird, A.R., Fox, P.T., & Eickhoff, S.B. (2014). Functional characterization and differential coactivation patterns of two cytoarchitectonic visual areas on the human posterior fusiform gyrusHuman Brain Mapping, 35: 2754-2767.

Caspers, J., Zilles, K., Beierle, C., Rottschy, C., & Eickhoff, S.B. (2014). A novel meta-analytic approach: mining frequent co-activation patterns in neuroimaging databasesNeuroimage, 90: 390-402.

Deco, G., & Kringelbach, M. L. (2014). Great expectations: using whole-brain computational connectomics for understanding neuropsychiatric disorders. Neuron84: 892-905.

Deco, G., Ponce-Alvarez, A., Hagmann, P., Romani, G. L., Mantini, D., & Corbetta, M. (2014). How Local Excitation–Inhibition Ratio Impacts the Whole Brain DynamicsThe Journal of Neuroscience34: 7886-7898.

Dehaene, S., Charles, L., King, J. R., & Marti, S. (2014). Toward a computational theory of conscious processingCurrent Opinion in Neurobiology, 25: 76-84.

Dohmatob, E. D., Gramfort, A., Thirion, B., & Varoquaux, G. (2014). Benchmarking solvers for TV-ℓ 1 least-squares and logistic regression in brain imaging2014 International Workshop on Pattern Recognition in Neuroimaging: 1-4.

Doolittle, E. L., Gingras, B., Endres, D. M., & Fitch, W. T. (2014). Overtone-based pitch selection in hermit thrush song: Unexpected convergence with scale construction in human musicProceedings of the National Academy of Sciences111: 16616-16621.

Dudai, Y., & Evers, K. (2014). To Simulate or Not to Simulate: What Are the Questions? Neuron84(2): 254-261.

Edelson, M. G., Dudai, Y., Dolan, R. J., & Sharot, T. (2014). Brain substrates of recovery from misleading influenceThe Journal of Neuroscience34: 7744-7753.

Frangeul, L., Porrero, C., Garcia-Amado, M., Maimone, B., Maniglier, M., Clascá, F., & Jabaoudon, D. (2014). Specific activation of the paralemniscal pathway during nociceptionEuropean Journal of Neuroscience, 39: 1455-1464.

Gabitov, E., Manor, D., & Karni, A. Done that: short-term repetition-related modulations of motor cortex activity as a stable signature for overnight motor memory consolidationJournal of Cognitive Neuroscience, 26: 2716-2734.

Galili, T., Mitelpunkt, A., Shachar, N., Marcus-Kalish, M., & Benjamini, Y. (2014). Categorize, Cluster, and Classify: A 3-C Strategy for Scientific Discovery in the Medical Informatics Platform of the Human Brain ProjectDiscovery Science8777: 73-86.

Galili, T., Mitelpunkt, A., Shachar, N., Marcus-Kalish, M., & Benjamini, Y. (2014, January). Erratum: Categorize, Cluster, and Classify: A 3-C Strategy for Scientific Discovery in the Medical Informatics Platform of the Human Brain ProjectDiscovery Science, 8777: E1-E1.

Gutierrez-Arenas, O., Eriksson, O., & Hellgren Kotaleski, J. (2014). Segregation and Crosstalk of D1 Receptor-Mediated Activation of ERK in Striatal Medium Spiny Neurons upon Acute Administration of PsychostimulantsPLoS Computational Biology10: e1003445.

Hänel, C., Pieperhoff, P., Hentschel, B., Amunts, K., & Kuhlen, T. (2014). Interactive 3D visualization of structural changes in the brain of a person with corticobasal syndromeFrontiers in Neuroinformatics8: 42.

Kandel, E. R., Dudai, Y., & Mayford, M. R. (2014). The molecular and systems biology of memoryCell157(1): 163-186.

Langner, R., Rottschy, C., Laird, A. R., Fox, P. T., & Eickhoff, S. B. (2014). Meta-analytic connectivity modeling revisited: Controlling for activation base ratesNeuroimage99: 559-570.

Lorio, S., Lutti, A., Kherif, F., Ruef, A., Dukart, J., Chowdhury, R., Frackowiak, R.S., Ashburner, J., Helms, G., Weiskopf, N., & Draganski, B. (2014). Disentangling in vivo the effects of iron content and atrophy on the ageing human brainNeuroimage, 103: 280-289.

Meli, G., Lecci, A., Manca, A., Krako, N., Albertini, V., Benussi, L., ... & Cattaneo, A. (2014). Conformational targeting of intracellular Aβ oligomers demonstrates their pathological oligomerization inside the endoplasmic reticulumNature Communications5: 3867.

Mihai, P. G., Otto, M., Platz, T., & Eickhoff, S. B. (2014). Sequential evolution of cortical activity and effective connectivity of swallowing using fMRIHuman Brain Mapping35: 5962-5973.

Nettekoven, C., Volz, L. J., Kutscha, M., Pool, E. M., Rehme, A. K., Eickhoff, S. B., ... & Grefkes, C. (2014). Dose-dependent effects of theta burst rTMS on cortical excitability and resting-state connectivity of the human motor system.The Journal of Neuroscience34: 6849-6859.

Papp, E. A., Leergaard, T. B., Calabrese, E., Johnson, G. A., & Bjaalie, J. G. (2014). Waxholm Space atlas of the Sprague Dawley rat brainNeuroimage, 97: 374-386.

Robertson, B., Kardamakis, A., Capantini, L., Pérez-Fernández, J., Suryanarayana, S.M., Wallén, P., Stephenson-Jones, M., & Grillner S. (2014). The lamprey blueprint of the mammalian nervous systemProgress in Brain Research, 212: 337-349.

Romos-Moreno, T., & Clascá, F. (2014). Quantitative mapping of the local and extrinsic sources of GABA and Reelin to the layer Ia neuropil in the adult rat neocortex.  Brain Structure and Function, 219: 1639-1657.

Salles, A, & Evers, K. (2014). La Vida Social del Cerebro. Derecho, Salud y Bioética.

Steratt, D.C., Sorokina, O., & Armstrong, D.J. (2014). Integration of rule-based models and compartmental models of neuronsThird International Workshop on Hybrid Systems Biology, Vienna, July 23-24, 2014.

Tauheed, F., Heinis, T., Schurmann, F., Markram, H., & Ailamaki, A. (2014). OCTOPUS: Efficient query execution on dynamic mesh datasets2014 IEEE 30th International Conference on Data Engineering (ICDE): 1000-1011.

Thirion, B., Varoquaux, G., Grisel, O., Poupon, C., & Pinel, P. (2014). Principal Component Regression predicts functional responses across individualsMedical Image Computing and Computer-Assisted Intervention 8674: 741-748.

Toharia, P., Morales, J., de Juan, O., Fernaud, I., Rodríguez, A., & DeFelipe, J. (2014). Musical Representation of Dendritic Spine Distribution: A New Exploratory ToolNeuroinformatics12: 341-353.

Vandoorne, K., Mechet, P., Van Vaerenbergh, T., Fiers, M., Morthier, G., Verstraeten, D., Schrauwen, B., Dambre, J. & Bienstman, P. (2014). Experimental demonstration of reservoir computing on a silicon photonics chipNature Communications5: 3541.

Weiner, K.S., Golarai, G., Caspers, J., Chuapoco, M.R., Mohlberg, H., Zilles, K., Amunts, K., & Grill-Spector, K. (2014). The mid-fusiform sulcus: a landmark identifying both cytoarchitectonic and functional divisions of human ventral temporal cortexNeuroimage, 84: 453-465.