A list of the latest publications from researchers involved with the Brain Simulation Platform.

Amsalem, O., Van Geit, W., Muller, E., Markram, H., & Segev, I. (2016). From Neuron Biophysics to Orientation Selectivity in Electrically Coupled Networks of Neocortical L2/3 Large Basket Cells. Cerebral Cortex, 26(8), 3655-3668. doi:10.1093/cercor/bhw166

Antonietti, A., Casellato, C., D'Angelo, E., & Pedrocchi, A. (2017). Model-Driven Analysis of Eyeblink Classical Conditioning Reveals the Underlying Structure of Cerebellar Plasticity and Neuronal Activity. IEEE Trans Neural Netw Learn Syst, 28(11), 2748-2762. doi:10.1109/TNNLS.2016.2598190

Balbi, P., Massobrio, P., & Hellgren Kotaleski, J. (2017). A single Markov-type kinetic model accounting for the macroscopic currents of all human voltage-gated sodium channel isoforms. PLoS Comput Biol, 13(9), e1005737. doi:10.1371/journal.pcbi.1005737

Berthet, P., Lindahl, M., Tully, P. J., Hellgren-Kotaleski, J., & Lansner, A. (2016). Functional Relevance of Different Basal Ganglia Pathways Investigated in a Spiking Model with Reward Dependent Plasticity. Front Neural Circuits, 10, 53. doi:10.3389/fncir.2016.00053

Bos, H., Diesmann, M., & Helias, M. (2016). Identifying Anatomical Origins of Coexisting Oscillations in the Cortical Microcircuit. PLoS Comput Biol, 12(10), e1005132. doi:10.1371/journal.pcbi.1005132

Brocke, E., Bhalla, U. S., Djurfeldt, M., Hellgren Kotaleski, J., & Hanke, M. (2016). Efficient Integration of Coupled Electrical-Chemical Systems in Multiscale Neuronal Simulations. Front Comput Neurosci, 10, 97. doi:10.3389/fncom.2016.00097

Brocke, E., Djurfeldt, M., Bhalla, U. S., Kotaleski, J. H., & Hanke, M. (2017). Multirate method for co-simulation of electrical-chemical systems in multiscale modeling. Journal of Computational Neuroscience, 42(3), 245-256. doi:10.1007/s10827-017-0639-7

Bruce, N. J., Ganotra, G. K., Kokh, D. B., Sadiq, S. K., & Wade, R. C. (2018). New approaches for computing ligand–receptor binding kinetics. Current Opinion in Structural Biology, 49, 1-10. doi:https://doi.org/10.1016/j.sbi.2017.10.001

Casasnovas, R., Limongelli, V., Tiwary, P., Carloni, P., & Parrinello, M. (2017). Unbinding Kinetics of a p38 MAP Kinase Type II Inhibitor from Metadynamics Simulations. Journal of the American Chemical Society, 139(13), 4780-4788. doi:10.1021/jacs.6b12950

Cellot, G., Maggi, L., Di Castro, M. A., Catalano, M., Migliore, R., Migliore, M., . . . Cherubini, E. (2016). Premature changes in neuronal excitability account for hippocampal network impairment and autistic-like behavior in neonatal BTBR T+tf/J mice. Sci Rep, 6, 31696. doi:10.1038/srep31696

D'Angelo, E., Antonietti, A., Casali, S., Casellato, C., Garrido, J. A., Luque, N. R., . . . Ros, E. (2016). Modeling the Cerebellar Microcircuit: New Strategies for a Long-Standing Issue. Front Cell Neurosci, 10, 176. doi:10.3389/fncel.2016.00176

Deitcher, Y., Eyal, G., Kanari, L., Verhoog, M. B., Atenekeng Kahou, G. A., Mansvelder, H. D., . . . Segev, I. (2017). Comprehensive Morpho-Electrotonic Analysis Shows 2 Distinct Classes of L2 and L3 Pyramidal Neurons in Human Temporal Cortex. Cerebral Cortex, 27(11), 5398-5414. doi:10.1093/cercor/bhx226

Doron, M., Chindemi, G., Muller, E., Markram, H., & Segev, I. (2017). Timed Synaptic Inhibition Shapes NMDA Spikes, Influencing Local Dendritic Processing and Global I/O Properties of Cortical Neurons. Cell Rep, 21(6), 1550-1561. doi:10.1016/j.celrep.2017.10.035

Dover, K., Marra, C., Solinas, S., Popovic, M., Subramaniyam, S., Zecevic, D., . . . Goldfarb, M. (2016). FHF-independent conduction of action potentials along the leak-resistant cerebellar granule cell axon. Nat Commun, 7, 12895. doi:10.1038/ncomms12895

Du, K., Wu, Y. W., Lindroos, R., Liu, Y., Rozsa, B., Katona, G., . . . Kotaleski, J. H. (2017). Cell-type-specific inhibition of the dendritic plateau potential in striatal spiny projection neurons. Proc Natl Acad Sci U S A, 114(36), E7612-E7621. doi:10.1073/pnas.1704893114

Eyal, G., Verhoog, M. B., Testa-Silva, G., Deitcher, Y., Lodder, J. C., Benavides-Piccione, R., . . . Segev, I. (2016). Unique membrane properties and enhanced signal processing in human neocortical neurons. Elife, 5. doi:10.7554/eLife.16553

Falotico, E., Vannucci, L., Ambrosano, A., Albanese, U., Ulbrich, S., Vasquez Tieck, J. C., . . . Gewaltig, M. O. (2017). Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform. Front Neurorobot, 11, 2. doi:10.3389/fnbot.2017.00002

Fernandez-Gonzalez, P., Benavides-Piccione, R., Leguey, I., Bielza, C., Larranaga, P., & DeFelipe, J. (2017). Dendritic-branching angles of pyramidal neurons of the human cerebral cortex. Brain Struct Funct, 222(4), 1847-1859. doi:10.1007/s00429-016-1311-0

Frezza, E., Martin, J., & Lavery, R. (2018). A molecular dynamics study of adenylyl cyclase: the impact of ATP and G-protein binding. PLOS ONE (accepted, 29 March 2018)

Gal, E., London, M., Globerson, A., Ramaswamy, S., Reimann, M. W., Muller, E., . . . Segev, I. (2017). Rich cell-type-specific network topology in neocortical microcircuitry. Nature Neuroscience, 20(7), 1004-1013. doi:10.1038/nn.4576

Gandolfi, D., Cerri, S., Mapelli, J., Polimeni, M., Tritto, S., Fuzzati-Armentero, M. T., . . . D'Angelo, E. (2017). Activation of the CREB/c-Fos Pathway during Long-Term Synaptic Plasticity in the Cerebellum Granular Layer. Front Cell Neurosci, 11, 184. doi:10.3389/fncel.2017.00184

Garrido, J. A., Luque, N. R., Tolu, S., & D'Angelo, E. (2016). Oscillation-Driven Spike-Timing Dependent Plasticity Allows Multiple Overlapping Pattern Recognition in Inhibitory Interneuron Networks. International Journal of Neural Systems, 26(5), 1650020. doi:10.1142/S0129065716500209

Geminiani, A., Casellato, C., Antonietti, A., D'Angelo, E., & Pedrocchi, A. (2017). A Multiple-Plasticity Spiking Neural Network Embedded in a Closed-Loop Control System to Model Cerebellar Pathologies. International Journal of Neural Systems, 1750017. doi:10.1142/S0129065717500174

Grillner, S., Ip, N., Koch, C., Koroshetz, W., Okano, H., Polachek, M., . . . Sejnowski, T. J. (2016). Worldwide initiatives to advance brain research. Nature Neuroscience, 19(9), 1118-1122. doi:10.1038/nn.4371

Grillner, S., & Robertson, B. (2016). The Basal Ganglia Over 500 Million Years. Current Biology, 26(20), R1088-R1100. doi:10.1016/j.cub.2016.06.041

Grillner, S., von Twickel, A., & Robertson, B. (2017). The blueprint of the vertebrate forebrain - With special reference to the habenulae. Seminars in Cell & Developmental Biology. doi:10.1016/j.semcdb.2017.10.023

Gulyas, A. I., Freund, T. F., & Kali, S. (2016). The Effects of Realistic Synaptic Distribution and 3D Geometry on Signal Integration and Extracellular Field Generation of Hippocampal Pyramidal Cells and Inhibitory Neurons. Front Neural Circuits, 10, 88. doi:10.3389/fncir.2016.00088

Hagen, E., Dahmen, D., Stavrinou, M. L., Linden, H., Tetzlaff, T., van Albada, S. J., . . . Einevoll, G. T. (2016). Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks. Cerebral Cortex, 26(12), 4461-4496. doi:10.1093/cercor/bhw237

Hahne, J., Helias, M., Kunkel, S., Igarashi, J., Kitayama, I., Wylie, B., . . . Diesmann, M. (2016). Including Gap Junctions into Distributed Neuronal Network Simulations, Cham.

Hinkel, G., Groenda, H., Krach, S., Vannucci, L., Denninger, O., Cauli, N., . . . Reussner, R. (2016). A Framework for Coupled Simulations of Robots and Spiking Neuronal Networks. Journal of Intelligent & Robotic Systems, 85(1), 71-91. doi:10.1007/s10846-016-0412-6

Ippen, T., Eppler, J. M., Plesser, H. E., & Diesmann, M. (2017). Constructing Neuronal Network Models in Massively Parallel Environments. Front Neuroinform, 11, 30. doi:10.3389/fninf.2017.00030

Jalalvand, E., Robertson, B., Tostivint, H., Wallen, P., & Grillner, S. (2016). The Spinal Cord Has an Intrinsic System for the Control of pH. Current Biology, 26(10), 1346-1351. doi:10.1016/j.cub.2016.03.048

Jalalvand, E., Robertson, B., Wallen, P., & Grillner, S. (2016). Ciliated neurons lining the central canal sense both fluid movement and pH through ASIC3. Nat Commun, 7, 10002. doi:10.1038/ncomms10002

Jordan, J., Ippen, T., Helias, M., Kitayama, I., Sato, M., Igarashi, J., . . . Kunkel, S. (2018). Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers. Front Neuroinform, 12, 2. doi:10.3389/fninf.2018.00002

Kohus, Z., Kali, S., Rovira-Esteban, L., Schlingloff, D., Papp, O., Freund, T. F., . . . Gulyas, A. I. (2016). Properties and dynamics of inhibitory synaptic communication within the CA3 microcircuits of pyramidal cells and interneurons expressing parvalbumin or cholecystokinin. J Physiol, 594(13), 3745-3774. doi:10.1113/JP272231

Li, J., Lyu, W., Rossetti, G., Konijnenberg, A., Natalello, A., Ippoliti, E., . . . Carloni, P. (2017). Proton Dynamics in Protein Mass Spectrometry. J Phys Chem Lett, 8(6), 1105-1112. doi:10.1021/acs.jpclett.7b00127

Lindroos, R., Dorst, M. C., Du, K., Filipovic, M., Keller, D., Ketzef, M., . . . Hellgren Kotaleski, J. (2018). Basal Ganglia Neuromodulation Over Multiple Temporal and Structural Scales-Simulations of Direct Pathway MSNs Investigate the Fast Onset of Dopaminergic Effects and Predict the Role of Kv4.2. Front Neural Circuits, 12, 3. doi:10.3389/fncir.2018.00003

Lupascu, C. A., Morabito, A., Merenda, E., Marinelli, S., Marchetti, C., Migliore, R., . . . Migliore, M. (2016). A General Procedure to Study Subcellular Models of Transsynaptic Signaling at Inhibitory Synapses. Front Neuroinform, 10, 23. doi:10.3389/fninf.2016.00023

Maksimov, A., van Albada, S. J., & Diesmann, M. (2016). [Re] Cellular and Network Mechanisms of Slow Oscillatory Activity (<1 Hz) and Wave Propagations in a Cortical Network Model. ReScience, 2(1), 1-18.

Masoli, S., & D'Angelo, E. (2017). Synaptic Activation of a Detailed Purkinje Cell Model Predicts Voltage-Dependent Control of Burst-Pause Responses in Active Dendrites. Front Cell Neurosci, 11, 278. doi:10.3389/fncel.2017.00278

Masoli, S., Rizza, M. F., Sgritta, M., Van Geit, W., Schurmann, F., & D'Angelo, E. (2017). Single Neuron Optimization as a Basis for Accurate Biophysical Modeling: The Case of Cerebellar Granule Cells. Front Cell Neurosci, 11, 71. doi:10.3389/fncel.2017.00071

Mercer, A., & Thomson, A. M. (2017). Cornu Ammonis Regions-Antecedents of Cortical Layers? Front Neuroanat, 11, 83. doi:10.3389/fnana.2017.00083

Nair, A. G., Bhalla, U. S., & Hellgren Kotaleski, J. (2016). Role of DARPP-32 and ARPP-21 in the Emergence of Temporal Constraints on Striatal Calcium and Dopamine Integration. PLoS Comput Biol, 12(9), e1005080. doi:10.1371/journal.pcbi.1005080

Nillegoda, N. B., Stank, A., Malinverni, D., Alberts, N., Szlachcic, A., Barducci, A., De Los Rois, P., Wade, R. C., & Bukau, B. (2017). Evolution of an intricate J-protein network driving protein disaggregation in eukaryotes. Elife, 6. doi:10.7554/eLife.24560

Palesi, F., De Rinaldis, A., Castellazzi, G., Calamante, F., Muhlert, N., Chard, D., . . . Gandini Wheeler-Kingshott, C. A. M. (2017). Contralateral cortico-ponto-cerebellar pathways reconstruction in humans in vivo: implications for reciprocal cerebro-cerebellar structural connectivity in motor and non-motor areas. Sci Rep, 7(1), 12841. doi:10.1038/s41598-017-13079-8

Parasuram, H., Nair, B., D'Angelo, E., Hines, M., Naldi, G., & Diwakar, S. (2016). Computational Modeling of Single Neuron Extracellular Electric Potentials and Network Local Field Potentials using LFPsim. Front Comput Neurosci, 10, 65. doi:10.3389/fncom.2016.00065

Parmar, K., Stadelmann, C., Rocca, M. A., Langdon, D., D'Angelo, E., D'Souza, M., . . . group, M. s. (2018). The role of the cerebellum in multiple sclerosis-150 years after Charcot. Neuroscience & Biobehavioral Reviews. doi:10.1016/j.neubiorev.2018.02.012

Perez-Fernandez, J., Kardamakis, A. A., Suzuki, D. G., Robertson, B., & Grillner, S. (2017). Direct Dopaminergic Projections from the SNc Modulate Visuomotor Transformation in the Lamprey Tectum. Neuron, 96(4), 910-924 e915. doi:10.1016/j.neuron.2017.09.051

Pfeil, T., Jordan, J., Tetzlaff, T., Grübl, A., Schemmel, J., Diesmann, M., & Meier, K. (2016). Effect of Heterogeneity on Decorrelation Mechanisms in Spiking Neural Networks: A Neuromorphic-Hardware Study. Physical Review X, 6(2). doi:10.1103/PhysRevX.6.021023

Plesser, H. E. (2017). Reproducibility vs. Replicability: A Brief History of a Confused Terminology. Front Neuroinform, 11, 76. doi:10.3389/fninf.2017.00076

Ranft, J., Almeida, L. G., Rodriguez, P. C., Triller, A., & Hakim, V. (2017). An aggregation-removal model for the formation and size determination of post-synaptic scaffold domains. PLoS Comput Biol, 13(4), e1005516. doi:10.1371/journal.pcbi.1005516

Rodriguez, P. C., Almeida, L. G., & Triller, A. (2017). Continuous rearrangement of the postsynaptic gephyrin scaffolding domain: a super-resolution quantified and energetic approach. bioRxiv. doi:10.1101/193698

Schmidt, M., Bakker, R., Hilgetag, C. C., Diesmann, M., & van Albada, S. J. (2017). Multi-scale account of the network structure of macaque visual cortex. Brain Struct Funct. doi:10.1007/s00429-017-1554-4

Schuecker, J., Schmidt, M., van Albada, S. J., Diesmann, M., & Helias, M. (2017). Fundamental Activity Constraints Lead to Specific Interpretations of the Connectome. PLoS Comput Biol, 13(2), e1005179. doi:10.1371/journal.pcbi.1005179

Sena, D. M., Jr., Cong, X., Giorgetti, A., Kless, A., & Carloni, P. (2017). Structural heterogeneity of the mu-opioid receptor's conformational ensemble in the apo state. Sci Rep, 8, 45761. doi:10.1038/srep45761

Senk, J., Yegenoglu, A., Amblet, O., Brukau, Y., Davison, A., Lester, D. R., . . . Grün, S. (2017). A Collaborative Simulation-Analysis Workflow for Computational Neuroscience Using HPC, Cham.

Sgritta, M., Locatelli, F., Soda, T., Prestori, F., & D'Angelo, E. U. (2017). Hebbian Spike-Timing Dependent Plasticity at the Cerebellar Input Stage. Journal of Neuroscience, 37(11), 2809-2823. doi:10.1523/JNEUROSCI.2079-16.2016

Suryanarayana, S. M., Robertson, B., Wallen, P., & Grillner, S. (2017). The Lamprey Pallium Provides a Blueprint of the Mammalian Layered Cortex. Current Biology, 27(21), 3264-3277 e3265. doi:10.1016/j.cub.2017.09.034

Tarenzi, T., Calandrini, V., Potestio, R., Giorgetti, A., & Carloni, P. (2017). Open Boundary Simulations of Proteins and Their Hydration Shells by Hamiltonian Adaptive Resolution Scheme. J Chem Theory Comput, 13(11), 5647-5657. doi:10.1021/acs.jctc.7b00508

Tong, R., Wade, R. C., & Bruce, N. J. (2016). Comparative electrostatic analysis of adenylyl cyclase for isoform dependent regulation properties. Proteins: Structure, Function, and Bioinformatics, 84(12), 1844-1858. doi:10.1002/prot.25167

Van Geit, W., Gevaert, M., Chindemi, G., Rossert, C., Courcol, J. D., Muller, E. B., . . . Markram, H. (2016). BluePyOpt: Leveraging Open Source Software and Cloud Infrastructure to Optimise Model Parameters in Neuroscience. Front Neuroinform, 10, 17. doi:10.3389/fninf.2016.00017

Vanherpe, L., Kanari, L., Atenekeng, G., Palacios, J., & Shillcock, J. (2016). Framework for efficient synthesis of spatially embedded morphologies. Phys Rev E, 94(2-1), 023315. doi:10.1103/PhysRevE.94.023315

Yapo, C., Nair, A. G., Clement, L., Castro, L. R., Hellgren Kotaleski, J., & Vincent, P. (2017). Detection of phasic dopamine by D1 and D2 striatal medium spiny neurons. J Physiol, 595(24), 7451-7475. doi:10.1113/JP274475

Zuccolo, E., Lim, D., Kheder, D. A., Perna, A., Catarsi, P., Botta, L., . . . Moccia, F. (2017). Acetylcholine induces intracellular Ca(2+) oscillations and nitric oxide release in mouse brain endothelial cells. Cell Calcium, 66, 33-47. doi:10.1016/j.ceca.2017.06.003