539 found.- Wang Z, Yu N and Essaf F (2023) A soma-synapses neuron model and FPGA implementation. Wiley Concurrency and Computation: Practice and Experience
- Zeng Y, Zhao D, Zhao F, Shen G, Dong Y, Lu E, Zhang Q, Sun Y, Liang Q, Zhao Y, Zhao Z, Fang H, Wang Y, Li Y, Liu X, Du C, Kong Q, Ruan Z and Bi W (2023) BrainCog: A spiking neural network based, brain-inspired cognitive intelligence engine for brain-inspired AI and brain simulation. Elsevier BV Patterns:100789
- Date P, Kulkarni S, Young A, Schuman C, Potok T and Vetter J (2023) Encoding integers and rationals on neuromorphic computers using virtual neuron. Springer Science and Business Media LLC Scientific Reports. 13
- Arthur BJ., Kim CM., Chen S, Preibisch S and Darshan R (2023) A scalable implementation of the recursive least-squares algorithm for training spiking neural networks. Frontiers Media SA Frontiers in Neuroinformatics. 17
- Rosa-Gallardo DJ., Torre JCde la, Quintana FM., Dominguez-Morales JP. and Perez-Peña F (2023) NESIM-RT: A real-time distributed spiking neural network simulator. Elsevier BV SoftwareX. 22:101349
- Giacopelli G, Migliore M and Tegolo D (2023) NeuronAlg: An Innovative Neuronal Computational Model for Immunofluorescence Image Segmentation. MDPI AG Sensors. 23:4598
- Birgiolas J, Haynes V, Gleeson P, Gerkin RC., Dietrich SW. and Crook S (2023) NeuroML-DB: Sharing and characterizing data-driven neuroscience models described in NeuroML. Public Library of Science (PLoS) PLOS Computational Biology. 19:e1010941
- Schmitt FJ, Rostami V and Nawrot MP (2023) Efficient parameter calibration and real-time simulation of large-scale spiking neural networks with GeNN and NEST. Frontiers Media SA Frontiers in Neuroinformatics. 17:941696
- Nilsson M, Schelén O, Lindgren A, Bodin U, Paniagua C, Delsing J and Sandin F (2023) Integration of neuromorphic AI in event-driven distributed digitized systems: Concepts and research directions. Frontiers Media SA Frontiers in Neuroscience. 17:1074439
- Zajzon B, Dahmen D, Morrison A and Duarte R (2023) Signal denoising through topographic modularity of neural circuits. eLife Sciences Publications, Ltd eLife. 12:e77009
- Haufler D, Ito S, Koch C and Arkhipov A (2023) Simulations of cortical networks using spatially extended conductance-based neuronal models. Wiley The Journal of Physiology
- Sten S, Podéus H, Sundqvist N, Elinder F, Engström M and Cedersund G (2023) A quantitative model for human neurovascular coupling with translated mechanisms from animals. Public Library of Science PLOS Computational Biology. 19:1-42
- Cobb EA. W., Petroccione MA. and Scimemi A (2023) NRN-EZ: an application to streamline biophysical modeling of synaptic integration using NEURON. Scientific Reports. 13:464
- Wei W and Wang X (2022) Ion-specific effects in confined nanochannels and neural network. Wiley Aggregate. 4:e302
- Lehmann HM., Hille J, Grassmann C, Knoll A and Issakov V (2022) Analog Spiking Neural Network Based Phase Detector. Institute of Electrical and Electronics Engineers (IEEE) IEEE Transactions on Circuits and Systems I: Regular Papers. 69:4837–4846
- Nieus T, Borgonovo D, Diwakar S, Aletti G and Naldi G (2022) A multi-class logistic regression algorithm to reliably infer network connectivity from cell membrane potentials. Frontiers Media SA Frontiers in Applied Mathematics and Statistics. 8:1023310
- Si H and Sun X (2022) Inter-areal transmission of multiple neural signals through frequency-division-multiplexing communication. Springer Science and Business Media LLC Cognitive Neurodynamics
- Griffiths JD., Shen K and Gleeson P (2022) Editorial: Neuroinformatics of large-scale brain modelling. Frontiers Media SA Frontiers in Neuroinformatics. 16:1043732
- Oberländer J, Bouhadjar Y and Morrison A (2022) Learning and replaying spatiotemporal sequences: A replication study. Frontiers Media SA Frontiers in Integrative Neuroscience. 16:974177
- D'Angelo E and Jirsa V (2022) The quest for multiscale brain modeling. Elsevier BV Trends in Neurosciences. 45:777–790
- Senk J, Kriener B, Djurfeldt M, Voges N, Jiang HJ, Schüttler L, Gramelsberger G, Diesmann M, Plesser HE. and Albada SJ. van (2022) Connectivity concepts in neuronal network modeling. Public Library of Science (PLoS) PLOS Computational Biology. 18:e1010086
- Bologna LL, Smiriglia R, Lupascu CA, Appukuttan S, Davison AP., Ivaska G, Courcol JD and Migliore M (2022) The EBRAINS Hodgkin-Huxley Neuron Builder: An online resource for building data-driven neuron models. Frontiers Media SA Frontiers in Neuroinformatics. 16:991609
- Gutierrez CE, Skibbe H, Musset H and Doya K (2022) A Spiking Neural Network Builder for Systematic Data-to-Model Workflow. Frontiers Media SA Frontiers in Neuroinformatics. 16:855765
- Yu Q, Li S, Tang H, Wang L, Dang J and Tan KC (2022) Toward Efficient Processing and Learning With Spikes: New Approaches for Multispike Learning. IEEE Transactions on Cybernetics. 52:1364-1376
- Yegenoglu A, Subramoney A, Hater T, Jimenez-Romero C, Klijn W, Martín AP, van der Vlag M, Herty M, Morrison A and Diaz-Pier S (2022) Exploring Parameter and Hyper-Parameter Spaces of Neuroscience Models on High Performance Computers With Learning to Learn. Frontiers in Computational Neuroscience. 16:885207
- Yang X, Lei Y, Wang M, Cai J, Wang M, Huan Z and Lin X (2022) Evaluation of the Effect of the Dynamic Behavior and Topology Co-Learning of Neurons and Synapses on the Small-Sample Learning Ability of Spiking Neural Network. Brain Sciences. 12:139
- Yamazaki K, Vo-Ho VK, Bulsara D and Le N (2022) Spiking Neural Networks and Their Applications: A Review. Brain Sciences. 12:863
- Turner JP, Knight JC, Subramanian A and Nowotny T (2022) mlGeNN: accelerating SNN inference using GPU-enabled neural networks. Neuromorphic Computing and Engineering. 2:024002
- Trensch G and Morrison A (2022) A System-on-Chip Based Hybrid Neuromorphic Compute Node Architecture for Reproducible Hyper-Real-Time Simulations of Spiking Neural Networks. Frontiers in Neuroinformatics. 16:884033
- Trapani A, Sheiban FJ, Bertone E, Chiosso S, Colombo L, D'Andrea M, De Santis F, Fati F, Fossati V, Gonzalez V and Pedrocchi A (2022) Reproducing a decision-making network in a virtual visual discrimination task. Frontiers in Integrative Neuroscience. 16:930326
- Tiddia G, Golosio B, Albers J, Senk J, Simula F, Pronold J, Fanti V, Pastorelli E, Paolucci PS and van Albada SJ. (2022) Fast Simulation of a Multi-Area Spiking Network Model of Macaque Cortex on an MPI-GPU Cluster. Frontiers in Neuroinformatics. 16:883333
- Shrestha A, Fang H, Mei Z, Rider DP, Wu Q and Qiu Q (2022) A Survey on Neuromorphic Computing: Models and Hardware. IEEE Circuits and Systems Magazine. 22:6-35
- Schuman CD., Kulkarni SR., Parsa M, Mitchell J. P, Date P and Kay B (2022) Opportunities for neuromorphic computing algorithms and applications. Nature Computational Science. 2:10-19
- Schirner M, Domide L, Perdikis D, Triebkorn P, Stefanovski L, Pai R, Prodan P, Valean B, Palmer J, Langford C, Blickensdörfer A, van der Vlag M, Diaz-Pier S, Peyser A, Klijn W, Pleiter D, Nahm A, Schmid O, Woodman M, Zehl L, Fousek J, Petkoski S, Kusch L, Hashemi M, Marinazzo D, Mangin JF, Flöel A, Akintoye S, Stahl BC, Cepic M, Johnson E, Deco G, McIntosh AR, Hilgetag CC, Morgan M, Schuller B, Upton A, McMurtrie C, Dickscheid T, Bjaalie JG, Amunts K, Mersmann J, Jirsa V and Ritter P (2022) Brain simulation as a cloud service: The Virtual Brain on EBRAINS. NeuroImage. 251:118973
- Ramezanian-Panahi M, Abrevaya G, Gagnon-Audet JC, Voleti V, Rish I and Dumas G (2022) Generative Models of Brain Dynamics. Frontiers in Artificial Intelligence. 5:807406
- Qu P, Yang L, Zheng W and Zhang Y (2022) A review of basic software for brain-inspired computing. CCF Transactions on High Performance Computing. 4:34-42
- Pronold J, Jordan J, Wylie BJ. N., Kitayama I, Diesmann M and Kunkel S (2022) Routing Brain Traffic Through the Von Neumann Bottleneck: Parallel Sorting and Refactoring. Frontiers in Neuroinformatics. 15:785068
- Pronold J., Jordan J., Wylie B.J.N., Kitayama I., Diesmann M. and Kunkel S. (2022) Routing brain traffic through the von Neumann bottleneck: Efficient cache usage in spiking neural network simulation code on general purpose computers. Parallel Computing. 113:102952
- Petschenig H, Bisio M, Maschietto M, Leparulo A, Legenstein R and Vassanelli S (2022) Classification of Whisker Deflections From Evoked Responses in the Somatosensory Barrel Cortex With Spiking Neural Networks. Frontiers in Neuroscience. 16:838054
- Peres L and Rhodes O (2022) Parallelization of Neural Processing on Neuromorphic Hardware. Frontiers in Neuroscience. 16:867027
- Panagiotou S, Sidiropoulos H, Soudris D, Negrello M and Strydis C (2022) EDEN: A High-Performance, General-Purpose, NeuroML-Based Neural Simulator. Frontiers in Neuroinformatics. 16:724336
- Ostrau C, Klarhorst C, Thies M and Rückert U (2022) Benchmarking Neuromorphic Hardware and Its Energy Expenditure. Frontiers in Neuroscience. 16:873935
- Osborne H and de Kamps M (2022) A numerical population density technique for N-dimensional neuron models. Frontiers in Neuroinformatics. 16:883796
- Müller E, Arnold E, Breitwieser O, Czierlinski M, Emmel A, Kaiser J, Mauch C, Schmitt S, Spilger P, Stock R, Stradmann Y, Weis J, Baumbach A, Billaudelle S, Cramer B, Ebert F, Göltz J, Ilmberger J, Karasenko V, Kleider M, Leibfried A, Pehle C and Schemmel J (2022) A Scalable Approach to Modeling on Accelerated Neuromorphic Hardware. Frontiers in Neuroscience. 16:884128
- Maith O, Dinkelbach HÜ, Baladron J, Vitay J and Hamker FH. (2022) BOLD Monitoring in the Neural Simulator ANNarchy. Frontiers in Neuroinformatics. 16:790966
- Lopes PH., Oliveira BC, de S. Souza AA and Blanco W (2022) Mitigating Computer Limitations in Replicating Numerical Simulations of a Neural Network Model With Hodgkin-Huxley-Type Neurons. Frontiers in Neuroinformatics. 16:874234
- Li G and Yap PT (2022) From descriptive connectome to mechanistic connectome: Generative modeling in functional magnetic resonance imaging analysis. Frontiers in Human Neuroscience. 16:940842
- Leone G, Raffo L and Meloni P (2022) A Bandwidth-Efficient Emulator of Biologically-Relevant Spiking Neural Networks on FPGA. IEEE Access. 10:76780-76793
- Lee JH, Tsunada J, Vijayan S and Cohen YE. (2022) Cortical circuit-based lossless neural integrator for perceptual decision-making: A computational modeling study. Frontiers in Computational Neuroscience. 16:979830
- Layer M, Senk J, Essink S, van Meegen A, Bos H and Helias M (2022) NNMT: Mean-Field Based Analysis Tools for Neuronal Network Models. Frontiers in Neuroinformatics. 16:835657
- Ladd A, Kim KG, Balewski J, Bouchard K and Ben-Shalom R (2022) Scaling and Benchmarking an Evolutionary Algorithm for Constructing Biophysical Neuronal Models. Frontiers in Neuroinformatics. 16:882552
- Kurth AC, Senk J, Terhorst D, Finnerty J and Diesmann M (2022) Sub-realtime simulation of a neuronal network of natural density. Neuromorphic Computing and Engineering. 2:021001
- Kon M and Francis G (2022) Cortical circuits for top-down control of perceptual grouping. Neural Networks. 151:190-210
- Javanshir A, Nguyen TT, Mahmud M. A. P and Kouzani AZ. (2022) Advancements in Algorithms and Neuromorphic Hardware for Spiking Neural Networks. Neural Computation. 34:1289-1328
- Huang C, Zeldenrust F and Celikel T (2022) Cortical Representation of Touch in Silico. Neuroinformatics:1-27
- Heittmann A, Psychou G, Trensch G, Cox CE., Wilcke WW., Diesmann M and Noll TG. (2022) Simulating the Cortical Microcircuit Significantly Faster Than Real Time on the IBM INC-3000 Neural Supercomputer. Frontiers in Neuroscience. 15:728460
- Hagen E, Magnusson SH., Ness TV., Halnes G, Babu PN., Linssen C, Morrison A and Einevoll GT. (2022) Brain signal predictions from multi-scale networks using a linearized framework. PLoS Computational Biology. 18:e1010353
- Geminiani A, Mockevičius A, D’Angelo E and Casellato C (2022) Cerebellum Involvement in Dystonia During Associative Motor Learning: Insights From a Data-Driven Spiking Network Model. Frontiers in Systems Neuroscience. 16:919761
- Feldotto B, Eppler JM, Jimenez-Romero C, Bignamini C, Gutierrez CE, Albanese U, Retamino E, Vorobev V, Zolfaghari V, Upton A, Sun Z, Yamaura H, Heidarinejad M, Klijn W, Morrison A, Cruz F, McMurtrie C, Knoll AC., Igarashi J, Yamazaki T, Doya K and Morin FO. (2022) Deploying and Optimizing Embodied Simulations of Large-Scale Spiking Neural Networks on HPC Infrastructure. Frontiers in Neuroinformatics. 16:884180
- Feldotto B, Soare C, Knoll A, Sriya P, Astill S, de Kamps M and Chakrabarty S (2022) Evaluating Muscle Synergies With EMG Data and Physics Simulation in the Neurorobotics Platform. Frontiers in Neurorobotics. 16:856797
- De Schepper R, Geminiani A, Masoli S, Rizza MF, Antonietti A, Casellato C and D’Angelo E (2022) Model simulations unveil the structure-function-dynamics relationship of the cerebellar cortical microcircuit. Communications Biology. 5:1240
- Chrysanthidis N, Fiebig F, Lansner A and Herman P (2022) Traces of Semantization, from Episodic to Semantic Memory in a Spiking Cortical Network Model. eNeuro. 9:eneuro.0062-22.2022
- Chakravarty K, Roy S, Sinha A, Nambu A, Chiken S, Kotaleski JH and Kumar A (2022) Transient Response of Basal Ganglia Network in Healthy and Low-Dopamine State. eNeuro. 9:eneuro.0376-21.2022
- Bouhadjar Y, Diesmann M, Wouters DJ and Tetzlaff T (2022) Sequence learning, prediction, and replay in networks of spiking neurons.. PLoS computational biology. 18:e1010233
- Awile O, Kumbhar P, Cornu N, Dura-Bernal S, King JG, Lupton O, Magkanaris I, McDougal RA., Newton AJ. H., Pereira F, Săvulescu A, Carnevale NT., Lytton WW., Hines ML. and Schürmann F (2022) Modernizing the NEURON Simulator for Sustainability, Portability, and Performance. Frontiers in Neuroinformatics. 16:884046
- Antonietti A, Geminiani A, Negri E, D'Angelo E, Casellato C and Pedrocchi A (2022) Brain-Inspired Spiking Neural Network Controller for a Neurorobotic Whisker System. Frontiers in Neurorobotics. 16:817948
- Albers J, Pronold J, Kurth AC, Vennemo SB, Mood KH, Patronis A, Terhorst D, Jordan J, Kunkel S, Tetzlaff T, Diesmann M and Senk J (2022) A Modular Workflow for Performance Benchmarking of Neuronal Network Simulations. Frontiers in Neuroinformatics. 16:837549
- Aitsam M, Davies S and Nuovo AD (2022) Neuromorphic Computing for Interactive Robotics: A Systematic Review. Institute of Electrical and Electronics Engineers (IEEE) IEEE Access. 10:122261–122279
- Ronchini M, Zamani M, Huynh HA, Rezaeiyan Y, Panuccio G, Farkhani H and Moradi F (2021) A CMOS-based neuromorphic device for seizure detection from LFP signals. IOP Publishing Journal of Physics D: Applied Physics. 55:014001
- Santos-Mayo A, Moratti S, Echegaray Jde and Susi G (2021) A Model of the Early Visual System Based on Parallel Spike-Sequence Detection, Showing Orientation Selectivity. MDPI AG Biology. 10:801
- Dominguez-Morales JP., Buccelli S, Gutierrez-Galan D, Colombi I, Jimenez-Fernandez A and Chiappalone M (2021) Real-time detection of bursts in neuronal cultures using a neuromorphic auditory sensor and spiking neural networks. Elsevier BV Neurocomputing. 449:422–434
- Angelidis E, Buchholz E, Arreguit J, Rougé A, Stewart T, Arnim Avon, Knoll A and Ijspeert A (2021) A spiking central pattern generator for the control of a simulated lamprey robot running on SpiNNaker and Loihi neuromorphic boards. IOP Publishing Neuromorphic Computing and Engineering. 1:014005
- Bologna LL., Smiriglia R, Curreri D and Migliore M (2021) The EBRAINS NeuroFeatureExtract: An Online Resource for the Extraction of Neural Activity Features From Electrophysiological Data. Frontiers Media SA Frontiers in Neuroinformatics. 15:713899
- Osborne H, Lai YM, Lepperød ME, Sichau D, Deutz L and Kamps Mde (2021) MIIND : A Model-Agnostic Simulator of Neural Populations. Frontiers Media SA Frontiers in Neuroinformatics. 15:614881
- Zweifel NO., Bush NE., Abraham I, Murphey TD. and Hartmann MJ. Z. (2021) A dynamical model for generating synthetic data to quantify active tactile sensing behavior in the rat. Proceedings of the National Academy of Sciences Proceedings of the National Academy of Sciences. 118:e2011905118
- Romaro C, Najman FA, Lytton WW., Roque AC. and Dura-Bernal S (2021) NetPyNE Implementation and Scaling of the Potjans-Diesmann Cortical Microcircuit Model. MIT Press - Journals Neural Computation. 33:1993–2032
- Susi G, Garcés P, Paracone E, Cristini A, Salerno M, Maestú F and Pereda E (2021) FNS allows efficient event-driven spiking neural network simulations based on a neuron model supporting spike latency. Springer Science and Business Media LLC Scientific Reports. 11:12160
- Shimoura RO, Pena RF. O., Lima V, Kamiji NL., Girardi-Schappo M and Roque AC. (2021) Building a model of the brain: from detailed connectivity maps to network organization. Springer Science and Business Media LLC The European Physical Journal Special Topics. 230:2887–2909
- Stapmanns J, Hahne J, Helias M, Bolten M, Diesmann M and Dahmen D (2021) Event-Based Update of Synapses in Voltage-Based Learning Rules. Frontiers Media SA Frontiers in Neuroinformatics. 15:609147
- Moon J, Wu Y, Zhu X and Lu WD. (2021) Neural connectivity inference with spike-timing dependent plasticity network. Springer Science and Business Media LLC Science China Information Sciences. 64:160405
- Dazza M, Métens S, Monceau P and Bottani S (2021) A novel methodology to describe neuronal networks activity reveals spatiotemporal recruitment dynamics of synchronous bursting states. Springer Science and Business Media LLC Journal of Computational Neuroscience. 49:375–394
- Schmuker M, Kupper R, Aertsen A, Wachtler T and Gewaltig MO (2021) Feed-forward and noise-tolerant detection of feature homogeneity in spiking networks with a latency code. Springer Science and Business Media LLC Biological Cybernetics. 115:161–176
- Weidel P, Duarte R and Morrison A (2021) Unsupervised Learning and Clustered Connectivity Enhance Reinforcement Learning in Spiking Neural Networks. Frontiers Media SA Frontiers in Computational Neuroscience. 15:543872
- Knight JC. and Nowotny T (2021) Larger GPU-accelerated brain simulations with procedural connectivity. Springer Science and Business Media LLC Nature Computational Science. 1:136–142
- Kasi SK, Das S and Biswas S (2021) Energy-efficient event pattern recognition in wireless sensor networks using multilayer spiking neural networks. Springer Science and Business Media LLC Wireless Networks. 27:2039–2054
- Wybo WA, Jordan J, Ellenberger B, Mengual UM, Nevian T and Senn W (2021) Data-driven reduction of dendritic morphologies with preserved dendro-somatic responses. eLife Sciences Publications, Ltd eLife. 10:e60936
- Yin Y (2021) RANDOM NEURAL NETWORK METHODS AND DEEP LEARNING. Cambridge University Press (CUP) Probability in the Engineering and Informational Sciences:1–31
- Wardak A and Gong P (2021) Fractional diffusion theory of balanced heterogeneous neural networks. American Physical Society (APS) Physical Review Research. 3:013083
- Yin Y (2021) RANDOM NEURAL NETWORK METHODS AND DEEP LEARNING. Probability in the Engineering and Informational Sciences. 35:6-36
- Yamazaki T, Igarashi J and Yamaura H (2021) Human-scale brain simulation via supercomputer: a case study on the cerebellum. Neuroscience. 462:235-246
- Tsang IJ, Corradi F, Sifalakis M, Van Leekwijck W and Latré S (2021) Radar-Based Hand Gesture Recognition Using Spiking Neural Networks. Electronics. 10:1405
- Trimarco E, Mirino P and Caligiore D (2021) Cortico-Cerebellar Hyper-Connections and Reduced Purkinje Cells Behind Abnormal Eyeblink Conditioning in a Computational Model of Autism Spectrum Disorder. Frontiers in Systems Neuroscience. 15:666649
- Steffen L, Koch R, Ulbrich S, Nitzsche S, Roennau A and Dillmann R (2021) Benchmarking Highly Parallel Hardware for Spiking Neural Networks in Robotics. Frontiers in Neuroscience. 15:667011
- Spreizer S, Senk J, Rotter S, Diesmann M and Weyers B (2021) NEST Desktop, an Educational Application for Neuroscience. eNeuro. 8:eneuro.0274-21.2021
- Scheffer LK. and Meinertzhagen IA. (2021) A connectome is not enough – what is still needed to understand the brain of Drosophila?. Journal of Experimental Biology. 224
- Nguyen QAP, Andelfinger P, Tan WJ, Cai W and Knoll A (2021) Transitioning Spiking Neural Network Simulators to Heterogeneous Hardware. ACM Transactions on Modeling and Computer Simulation. 31:1-26
- Meamardoost S, Bhattacharya M, Hwang EJ, Komiyama T, Mewes C, Wang L, Zhang Y and Gunawan R (2021) FARCI: Fast and Robust Connectome Inference. Brain Sciences. 11:1556
- Lazar AA, Liu T, Turkcan MK and Zhou Y (2021) Accelerating with FlyBrainLab the discovery of the functional logic of the Drosophila brain in the connectomic era. eLife. 10:e62362
- Kuriyama R, Casellato C, D'Angelo E and Yamazaki T (2021) Real-Time Simulation of a Cerebellar Scaffold Model on Graphics Processing Units. Frontiers in Cellular Neuroscience. 15:623552
- Kulkarni SR., Parsa M, Mitchell J. P and Schuman CD. (2021) Benchmarking the performance of neuromorphic and spiking neural network simulators. Neurocomputing. 447:145-160
- Jordan J, Schmidt M, Senn W and Petrovici MA (2021) Evolving interpretable plasticity for spiking networks. eLife. 10:e66273
- He H, Wang Q, Yang X, Lei Y, Cai J and Deng N (2021) A memory neural system built based on spiking neural network. Neurocomputing. 442:146-160
- Dasbach S, Tetzlaff T, Diesmann M and Senk J (2021) Dynamical Characteristics of Recurrent Neuronal Networks Are Robust Against Low Synaptic Weight Resolution. Frontiers in Neuroscience. 15:757790
- Cakan C, Jajcay N and Obermayer K (2021) neurolib: A Simulation Framework for Whole-Brain Neural Mass Modeling. Cognitive Computation:1-21
- Antolik J, Sabatier Q, Galle C, Frégnac Y and Benosman R (2021) Assessment of optogenetically-driven strategies for prosthetic restoration of cortical vision in large-scale neural simulation of V1. Scientific Reports. 11:10783
- Dai K, Gratiy SL., Billeh YN., Xu R, Cai B, Cain N, Rimehaug AE., Stasik AJ., Einevoll GT., Mihalas S, Koch C and Arkhipov A (2020) Brain Modeling ToolKit: An open source software suite for multiscale modeling of brain circuits. Public Library of Science (PLOS) PLOS Computational Biology. 16:e1008386
- Jordan J, Helias M, Diesmann M and Kunkel S (2020) Efficient Communication in Distributed Simulations of Spiking Neuronal Networks With Gap Junctions. Frontiers Media SA Frontiers in Neuroinformatics. 14:12
- Senk J, Korvasova K, Schuecker J, Hagen E, Tetzlaff T, Diesmann M and Helias M (2020) Conditions for wave trains in spiking neural networks. American Physical Society (APS) Physical Review Research. 2:023174
- Martı́nez-Cancino R, Delorme A, Truong D, Artoni F, Kreutz-Delgado K, Sivagnanam S, Yoshimoto K, Majumdar A and Makeig S (2020) The Open EEGLAB Portal Interface:High-Performance Computing with EEGLAB. Elsevier BV NeuroImage:116778
- Yamaura H, Igarashi J and Yamazaki T (2020) Simulation of a Human-Scale Cerebellar Network Model on the K Computer. Frontiers Media SA Frontiers in Neuroinformatics. 14:16
- Aljalbout E, Walter F, Röhrbein F and Knoll A (2020) Task-Independent Spiking Central Pattern Generator: A Learning-Based Approach. Springer Science and Business Media LLC Neural Processing Letters. 51:2751–2764
- Fiebig F, Herman P and Lansner A (2020) An Indexing Theory for Working Memory Based on Fast Hebbian Plasticity. Society for Neuroscience eneuro. 7:ENEURO.0374–19.2020
- Billeh YN., Cai B, Gratiy SL., Dai K, Iyer R, Gouwens NW., Abbasi-Asl R, Jia X, Siegle JH., Olsen SR., Koch C, Mihalas S and Arkhipov A (2020) Systematic Integration of Structural and Functional Data into Multi-scale Models of Mouse Primary Visual Cortex. Elsevier BV Neuron. 106:388–403.e18
- Yang X, Lin J, Zheng W, Zhao J, Ji M, Lei Y and Chai Z (2020) Research on learning mechanism designing for equilibrated bipolar spiking neural networks. Springer Science and Business Media LLC Artificial Intelligence Review. 53:5189–5215
- Dai K, Hernando J, Billeh YN., Gratiy SL., Planas J, Davison AP., Dura-Bernal S, Gleeson P, Devresse A, Dichter BK., Gevaert M, King JG., Geit WA. H. V, Povolotsky AV., Muller E, Courcol JD and Arkhipov A (2020) The SONATA data format for efficient description of large-scale network models. Public Library of Science (PLoS) PLOS Computational Biology. 16:e1007696
- Huyck CR. (2020) A neural cognitive architecture. Elsevier BV Cognitive Systems Research. 59:171–178
- LaTorre A, Kwong MT, Garcı́a-Grajales JA., Shi R, Jérusalem A and Peña JḾa (2020) Model calibration using a parallel differential evolution algorithm in computational neuroscience: Simulation of stretch induced nerve deficit. Elsevier BV Journal of Computational Science. 39:101053
- Balaji A, Catthoor F, Das A, Wu Y, Huynh K, Dell-Anna FG., Indiveri G, Krichmar JL., Dutt ND. and Schaafsma S (2020) Mapping Spiking Neural Networks to Neuromorphic Hardware. Institute of Electrical and Electronics Engineers (IEEE) IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 28:76–86
- Vlag MA. van der, Smaragdos G, Al-Ars Z and Strydis C (2020) Exploring Complex Brain-Simulation Workloads on Multi-GPU Deployments. Association for Computing Machinery (ACM) ACM Transactions on Architecture and Code Optimization. 16:1–25
- Senden M, Peters J, Röhrbein F, Deco G and Goebel R (2020) Editorial: The Embodied Brain: Computational Mechanisms of Integrated Sensorimotor Interactions With a Dynamic Environment. Frontiers in Computational Neuroscience. 14:53
- Rostro-Gonzalez H, Lauterio-Cruz JP and Pottiez O (2020) Modelling Neural Dynamics with Optics: A New Approach to Simulate Spiking Neurons through an Asynchronous Laser. Electronics. 9:1853
- Romano V, Reddington AL., Cazzanelli S, Mazza R, Ma Y, Strydis C, Negrello M, Bosman LW.J. and De Zeeuw CI. (2020) Functional Convergence of Autonomic and Sensorimotor Processing in the Lateral Cerebellum. Cell Reports. 32:107867
- Rhodes O, Peres L, Rowley AG. D., Gait A, Plana LA., Brenninkmeijer C and Furber SB. (2020) Real-time cortical simulation on neuromorphic hardware.. Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences. 378:20190160
- Rezaei H, Aertsen A, Kumar A and Valizadeh A (2020) Facilitating the propagation of spiking activity in feedforward networks by including feedback. PLoS Computational Biology. 16:e1008033
- Qu P, Zhang Y, Fei X and Zheng W (2020) High Performance Simulation of Spiking Neural Network on GPGPUs. IEEE Transactions on Parallel and Distributed Systems. 31:2510-2523
- Müller MG, Papadimitriou CH, Maass W and Legenstein R (2020) A model for structured information representation in neural networks of the brain. eNeuro. 7:eneuro.0533-19.2020
- Mosbacher Y, Khoyratee F, Goldin M, Kanner S, Malakai Y, Silva M, Grassia F, Simon YB, Cortes J, Barzilai A, Levi T and Bonifazi P (2020) Toward neuroprosthetic real-time communication from in silico to biological neuronal network via patterned optogenetic stimulation. Scientific Reports. 10:7512
- Michaelis C, Lehr AB. and Tetzlaff C (2020) Robust Trajectory Generation for Robotic Control on the Neuromorphic Research Chip Loihi. Frontiers in Neurorobotics. 14:589532
- Mascaro ALA, Falotico E, Petkoski S, Pasquini M, Vannucci L, Tort-Colet N, Conti E, Resta F, Spalletti C, Ramalingasetty ST, von Arnim A, Formento E, Angelidis E, Blixhavn CH., Leergaard TB., Caleo M, Destexhe A, Ijspeert A, Micera S, Laschi C, Jirsa V, Gewaltig MO and Pavone FS. (2020) Experimental and Computational Study on Motor Control and Recovery After Stroke: Toward a Constructive Loop Between Experimental and Virtual Embodied Neuroscience. Frontiers in Systems Neuroscience. 14:31
- Lee JH (2020) Biologically plausible mechanisms underlying motor response correction during reward-based decision-making. Neurocomputing. 412:416-425
- Kohler M, Stratmann P, Röhrbein F, Knoll A, Albu-Schäffer A and Jörntell H (2020) Biological data questions the support of the self inhibition required for pattern generation in the half center model. PLoS ONE. 15:e0238586
- Kim CM, Egert U and Kumar A (2020) Dynamics of multiple interacting excitatory and inhibitory populations with delays. Physical Review E. 102:022308
- Huyck CR and Vergani AA (2020) Hot coffee: associative memory with bump attractor cell assemblies of spiking neurons. Journal of Computational Neuroscience. 48:299-316
- Hazan H, Saunders DJ., Sanghavi DT., Siegelmann H and Kozma R (2020) Lattice map spiking neural networks (LM-SNNs) for clustering and classifying image data. Annals of Mathematics and Artificial Intelligence. 88:1237-1260
- George R, Chiappalone M, Giugliano M, Levi T, Vassanelli S, Partzsch J and Mayr C (2020) Plasticity and Adaptation in Neuromorphic Biohybrid Systems. iScience. 23:101589
- DeWolf T, Jaworski P and Eliasmith C (2020) Nengo and Low-Power AI Hardware for Robust, Embedded Neurorobotics. Frontiers in Neurorobotics. 14:568359
- Dai K, Gratiy SL., Billeh YN., Xu R, Cai B, Cain N, Rimehaug AE., Stasik AJ., Einevoll GT., Mihalas S, Koch C and Arkhipov A (2020) Brain Modeling ToolKit: An open source software suite for multiscale modeling of brain circuits. PLOS Computational Biology. 16:e1008386
- Crook SM., Davison AP., McDougal RA. and Plesser HE (2020) Editorial: Reproducibility and Rigour in Computational Neuroscience. Frontiers in Neuroinformatics. 14:23
- Caligiore D and Mirino P (2020) How the Cerebellum and Prefrontal Cortex Cooperate During Trace Eyeblinking Conditioning.. International Journal of Neural Systems. 30:2050041
- Abdoli B and Safari S (2020) A reconfigurable real‐time neuromorphic hardware for spiking winner‐take‐all network. International Journal of Circuit Theory and Applications. 48:2141–2152
- Rhodes O, Peres L, Rowley AG. D., Gait A, Plana LA., Brenninkmeijer C and Furber SB. (2019) Real-time cortical simulation on neuromorphic hardware. The Royal Society Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 378:20190160
- Zajzon B, Mahmoudian S, Morrison A and Duarte R (2019) Passing the Message: Representation Transfer in Modular Balanced Networks. Frontiers Media SA Frontiers in Computational Neuroscience. 13:79
- Jordan J, Petrovici MA., Breitwieser O, Schemmel J, Meier K, Diesmann M and Tetzlaff T (2019) Deterministic networks for probabilistic computing. Springer Science and Business Media LLC Scientific Reports. 9:18303
- Vandesompele A, Urbain G, wyffels F and Dambre J (2019) Populations of spiking neurons for reservoir computing: Closed loop control of a compliant quadruped. Elsevier BV Cognitive Systems Research. 58:317–323
- Gast R, Rose D, Salomon C, Möller HE., Weiskopf N and Knösche TR. (2019) PyRates - A Python framework for rate-based neural simulations. Public Library of Science (PLoS) PLOS ONE. 14:e0225900
- Dold D, Bytschok I, Kungl AF., Baumbach A, Breitwieser O, Senn W, Schemmel J, Meier K and Petrovici MA. (2019) Stochasticity from function - Why the Bayesian brain may need no noise. Elsevier BV Neural Networks. 119:200–213
- LaTorre A, Kwong MT, García-Grajales JA., Shi R, Jérusalem A and Peña JM (2019) Model calibration using a parallel differential evolution algorithm in computational neuroscience: simulation of stretch induced nerve deficit. Elsevier BV Journal of Computational Science:101053
- Igarashi J, Yamaura H and Yamazaki T (2019) Large-Scale Simulation of a Layered Cortical Sheet of Spiking Network Model Using a Tile Partitioning Method. Frontiers Media SA Frontiers in Neuroinformatics. 13:71
- Crone JC., Vindiola MM., Yu AB., Boothe DL., Beeman D, Oie KS. and Franaszczuk PJ. (2019) Enabling Large-Scale Simulations With the GENESIS Neuronal Simulator. Frontiers Media SA Frontiers in Neuroinformatics. 13:69
- Saunders DJ., Patel D, Hazan H, Siegelmann HT. and Kozma R (2019) Locally connected spiking neural networks for unsupervised feature learning. Elsevier BV Neural Networks. 119:332–340
- Zielasko D, Zhao X, Demiralp AC, Kuhlen TW. and Weyers B (2019) Voxel-based edge bundling through direction-aware kernel smoothing. Elsevier BV Computers & Graphics. 83:87–96
- Kaiser J, Hoff M, Konle A, Tieck J. CV, Kappel D, Reichard D, Subramoney A, Legenstein R, Roennau A, Maass W and Dillmann R (2019) Embodied Synaptic Plasticity With Online Reinforcement Learning. Frontiers Media SA Frontiers in Neurorobotics. 13:81
- Kobayashi R, Kurita S, Kurth A, Kitano K, Mizuseki K, Diesmann M, Richmond BJ. and Shinomoto S (2019) Reconstructing neuronal circuitry from parallel spike trains. Springer Science and Business Media LLC Nature Communications. 10:4468
- Hazan H, Saunders DJ., Sanghavi DT., Siegelmann H and Kozma R (2019) Lattice map spiking neural networks (LM-SNNs) for clustering and classifying image data. Springer Science and Business Media LLC Annals of Mathematics and Artificial Intelligence. 88:1237–1260
- Kumbhar P, Hines M, Fouriaux J, Ovcharenko A, King J, Delalondre F and Schürmann F (2019) CoreNEURON : An Optimized Compute Engine for the NEURON Simulator. Frontiers Media SA Frontiers in Neuroinformatics. 13:63
- Chrysanthidis N, Fiebig F and Lansner A (2019) Introducing double bouquet cells into a modular cortical associative memory model. Springer Science and Business Media LLC Journal of Computational Neuroscience. 47:223–230
- Gleeson P, Cantarelli M, Marin B, Quintana A, Earnshaw M, Sadeh S, Piasini E, Birgiolas J, Cannon RC., Cayco-Gajic N. A, Crook S, Davison AP., Dura-Bernal S, Ecker A, Hines ML., Idili G, Lanore F, Larson SD., Lytton WW., Majumdar A, McDougal RA., Sivagnanam S, Solinas S, Stanislovas R, Albada SJ. van, Geit Wvan and Silver R. A (2019) Open Source Brain: A Collaborative Resource for Visualizing, Analyzing, Simulating, and Developing Standardized Models of Neurons and Circuits. Elsevier BV Neuron. 103:395–411.e5
- Lagzi F, Atay FM. and Rotter S (2019) Bifurcation analysis of the dynamics of interacting subnetworks of a spiking network. Springer Science and Business Media LLC Scientific Reports. 9:11397
- Stimberg M, Brette R and Goodman DF (2019) Brian 2, an intuitive and efficient neural simulator. eLife Sciences Publications, Ltd eLife. 8:e47314
- Jordan J, Weidel P and Morrison A (2019) A Closed-Loop Toolchain for Neural Network Simulations of Learning Autonomous Agents. Frontiers Media SA Frontiers in Computational Neuroscience. 13:46
- Chen S, He Z, Han X, He X, Li R, Zhu H, Zhao D, Dai C, Zhang Y, Lu Z, Chi X and Niu B (2019) How Big Data and High-performance Computing Drive Brain Science. Elsevier BV Genomics, Proteomics & Bioinformatics. 17:381–392
- Mozafari M, Ganjtabesh M, Nowzari-Dalini A and Masquelier T (2019) SpykeTorch: Efficient Simulation of Convolutional Spiking Neural Networks With at Most One Spike per Neuron. Frontiers Media SA Frontiers in Neuroscience. 13:625
- Magalhaes BR. C., Sterling T, Hines M and Schürmann F (2019) Asynchronous Branch-Parallel Simulation of Detailed Neuron Models. Frontiers Media SA Frontiers in Neuroinformatics. 13:54
- Merkt B, Schüßler F and Rotter S (2019) Propagation of orientation selectivity in a spiking network model of layered primary visual cortex. Public Library of Science (PLOS) PLOS Computational Biology. 15:e1007080
- Dahmen D, Grün S, Diesmann M and Helias M (2019) Second type of criticality in the brain uncovers rich multiple-neuron dynamics. Proceedings of the National Academy of Sciences Proceedings of the National Academy of Sciences. 116:13051–13060
- Stepniewski M., Breit M., Hoffer M. and Queisser G. (2019) NeuroBox: computational mathematics in multiscale neuroscience. Springer Science and Business Media LLC Computing and Visualization in Science. 20:111–124
- Yu Q, Li H and Tan KC (2019) Spike Timing or Rate? Neurons Learn to Make Decisions for Both Through Threshold-Driven Plasticity. Institute of Electrical and Electronics Engineers (IEEE) IEEE Transactions on Cybernetics. 49:2178–2189
- Andalibi V, Hokkanen H and Vanni S (2019) Controlling Complexity of Cerebral Cortex Simulations - I: CxSystem, a Flexible Cortical Simulation Framework. MIT Press - Journals Neural Computation. 31:1048–1065
- Bohnstingl T, Scherr F, Pehle C, Meier K and Maass W (2019) Neuromorphic Hardware Learns to Learn. Frontiers Media SA Frontiers in Neuroscience. 13:483
- Bornet A, Kaiser J, Kroner A, Falotico E, Ambrosano A, Cantero K, Herzog MH. and Francis G (2019) Running Large-Scale Simulations on the Neurorobotics Platform to Understand Vision - The Case of Visual Crowding. Frontiers Media SA Frontiers in Neurorobotics. 13:33
- Caligiore D, Mannella F and Baldassarre G (2019) Different Dopaminergic Dysfunctions Underlying Parkinsonian Akinesia and Tremor. Frontiers Media SA Frontiers in Neuroscience. 13:550
- Jokar E, Abolfathi H and Ahmadi A (2019) A Novel Nonlinear Function Evaluation Approach for Efficient FPGA Mapping of Neuron and Synaptic Plasticity Models. Institute of Electrical and Electronics Engineers (IEEE) IEEE Transactions on Biomedical Circuits and Systems. 13:454–469
- Fernandez-Musoles C, Coca D and Richmond P (2019) Communication Sparsity in Distributed Spiking Neural Network Simulations to Improve Scalability. Frontiers Media SA Frontiers in Neuroinformatics. 13:19
- Rasmussen D (2019) NengoDL: Combining Deep Learning and Neuromorphic Modelling Methods. Springer Nature Neuroinformatics. 17:611–628
- Khoyratee F, Grassia F, Saïghi S and Levi T (2019) Optimized Real-Time Biomimetic Neural Network on FPGA for Bio-hybridization. Frontiers Media SA Frontiers in Neuroscience. 13:377
- Narasimhamurthy S, Danilov N, Wu S, Umanesan G, Markidis S, Rivas-Gomez S, Peng IB, Laure E, Pleiter D and Witt Sde (2019) SAGE: Percipient Storage for Exascale Data Centric Computing. Elsevier BV Parallel Computing. 83:22–33
- Haessig G, Berthelon X, Ieng SH and Benosman R (2019) A Spiking Neural Network Model of Depth from Defocus for Event-based Neuromorphic Vision. Springer Nature Scientific Reports. 9:3744
- Popovych OV., Manos T, Hoffstaedter F and Eickhoff SB. (2019) What Can Computational Models Contribute to Neuroimaging Data Analytics?. Frontiers Media SA Frontiers in Systems Neuroscience. 12:68
- Antonietti A, Martina D, Casellato C, D'Angelo E and Pedrocchi A (2019) Control of a Humanoid NAO Robot by an Adaptive Bioinspired Cerebellar Module in 3D Motion Tasks. Hindawi Limited Computational Intelligence and Neuroscience. 2019:1–15
- Syeda F., Kumbhare D., Baron M. S. and Hadimani R. L. (2019) Modeling of Transcranial Magnetic Stimulation Versus Pallidal Deep Brain Stimulation for Parkinson's Disease. Institute of Electrical and Electronics Engineers (IEEE) IEEE Transactions on Magnetics:1–5
- Knight JC. and Nowotny T (2018) GPUs Outperform Current HPC and Neuromorphic Solutions in Terms of Speed and Energy When Simulating a Highly-Connected Cortical Model. Frontiers Media SA Frontiers in Neuroscience. 12:941
- van Meegen A and Lindner B (2018) Self-Consistent Correlations of Randomly Coupled Rotators in the Asynchronous State. American Physical Society Phys. Rev. Lett.. 121:258302
- Hazan H, Saunders DJ., Khan H, Patel D, Sanghavi DT., Siegelmann HT. and Kozma R (2018) BindsNET: A Machine Learning-Oriented Spiking Neural Networks Library in Python. Frontiers Media SA Frontiers in Neuroinformatics. 12:3389
- Gutzen R, Papen Mvon, Trensch G, Quaglio P, Grün S and Denker M (2018) Reproducible Neural Network Simulations: Statistical Methods for Model Validation on the Level of Network Activity Data. Frontiers Media SA Frontiers in Neuroinformatics. 12:90
- Trensch G, Gutzen R, Blundell I, Denker M and Morrison A (2018) Rigorous Neural Network Simulations: A Model Substantiation Methodology for Increasing the Correctness of Simulation Results in the Absence of Experimental Validation Data. Frontiers Media SA Frontiers in Neuroinformatics. 12:3389
- Huyck C and Mitchell I (2018) CABots and Other Neural Agents. Frontiers Media SA Frontiers in Neurorobotics. 12:79
- Rhodes O, Bogdan PA., Brenninkmeijer C, Davidson S, Fellows D, Gait A, Lester DR., Mikaitis M, Plana LA., Rowley AG. D., Stokes AB. and Furber SB. (2018) sPyNNaker: A Software Package for Running PyNNSimulations on SpiNNaker. Frontiers Media SA Frontiers in Neuroscience. 12:816
- Blundell I, Plotnikov D, Eppler JM. and Morrison A (2018) Automatically Selecting a Suitable Integration Scheme for Systems of Differential Equations in Neuron Models. Frontiers Media SA Frontiers in Neuroinformatics. 12:50
- Nayak L, Dasgupta A, Das R, Ghosh K and De RK (2018) Computational neuroscience and neuroinformatics: Recent progress and resources. Springer Nature America, Inc Journal of Biosciences. 43:1037–1054
- Leukhin A, Talanov M, Vallverdú J and Gafarov F (2018) Bio-plausible simulation of three monoamine systems to replicate emotional phenomena in a machine. Elsevier BV Biologically Inspired Cognitive Architectures. 26:166–173
- Rinke S, Butz-Ostendorf M, Hermanns MA, Naveau M and Wolf F (2018) A scalable algorithm for simulating the structural plasticity of the brain. Elsevier BV Journal of Parallel and Distributed Computing. 120:251–266
- Gajewska-Dendek E, Wróbel A, Bekisz M and Suffczynski P (2018) Lateral Inhibition Organizes Beta Attentional Modulation in the Primary Visual Cortex. World Scientific Pub Co Pte Lt International Journal of Neural Systems:1850047
- Scheffer LK. (2018) Analysis Tools for Large Connectomes. Frontiers Media SA Frontiers in Neural Circuits. 12:85
- Miska NJ, Richter LM, Cary BA, Gjorgjieva J and Turrigiano GG (2018) Sensory experience inversely regulates feedforward and feedback excitation-inhibition ratio in rodent visual cortex. eLife Sciences Publications, Ltd eLife. 7:e38846
- Akbarzadeh-Sherbaf K, Abdoli B, Safari S and Vahabie AH (2018) A Scalable FPGA Architecture for Randomly Connected Networks of Hodgkin-Huxley Neurons. Frontiers Media SA Frontiers in Neuroscience. 12:698
- Schmidt M, Bakker R, Shen K, Bezgin G, Diesmann M and Albada SJvan (2018) A multi-scale layer-resolved spiking network model of resting-state dynamics in macaque visual cortical areas. Public Library of Science PLoS PLOS Computational Biology. 14:e1006359
- Cantarelli M, Marin B, Quintana A, Earnshaw M, Court R, Gleeson P, Dura-Bernal S, Silver R. A and Idili G (2018) Geppetto: a reusable modular open platform for exploring neuroscience data and models. The Royal Society Philosophical Transactions of the Royal Society B: Biological Sciences. 373:20170380
- Tennøe S, Halnes G and Einevoll GT. (2018) Uncertainpy: A Python Toolbox for Uncertainty Quantification and Sensitivity Analysis in Computational Neuroscience. Frontiers Media SA Frontiers in Neuroinformatics. 12:49
- Bahuguna J, Weidel P and Morrison A (2018) Exploring the role of striatal D1 and D2 medium spiny neurons in action selection using a virtual robotic framework. Wiley European Journal of Neuroscience. 49:737–753
- Heiberg T, Kriener B, Tetzlaff T, Einevoll GT. and Plesser HE. (2018) Firing-rate models for neurons with a broad repertoire of spiking behaviors. Springer Nature America, Inc Journal of Computational Neuroscience. 45:103–132
- Sanz-Leon P, Robinson PA., Knock SA., Drysdale PM., Abeysuriya RG., Fung FK., Rennie CJ. and Zhao X (2018) NFTsim: Theory and Simulation of Multiscale Neural Field Dynamics. Public Library of Science (PLoS) PLOS Computational Biology. 14:e1006387
- Pauli R, Weidel P, Kunkel S and Morrison A (2018) Reproducing Polychronization: A Guide to Maximizing the Reproducibility of Spiking Network Models. Frontiers Media SA Frontiers in Neuroinformatics. 12:46
- Casadiego J, Maoutsa D and Timme M (2018) Inferring Network Connectivity from Event Timing Patterns. American Physical Society (APS) Physical Review Letters. 121:054101
- Nair M, Kannimoola JM, Jayaraman B, Nair B and Diwakar S (2018) Temporal constrained objects for modelling neuronal dynamics. PeerJ PeerJ Computer Science. 4:e159
- Setareh H, Deger M and Gerstner W (2018) Excitable neuronal assemblies with adaptation as a building block of brain circuits for velocity-controlled signal propagation. Public Library of Science (PLoS) PLOS Computational Biology. 14:e1006216
- Maksimov A, Diesmann M and Albada SJ. van (2018) Criteria on Balance, Stability, and Excitability in Cortical Networks for Constraining Computational Models. Frontiers Media SA Frontiers in Computational Neuroscience. 12:44
- Mostafa H and Cauwenberghs G (2018) A Learning Framework for Winner-Take-All Networks with Stochastic Synapses. MIT Press - Journals Neural Computation. 30:1542–1572
- Nowke C, Diaz-Pier S, Weyers B, Hentschel B, Morrison A, Kuhlen TW. and Peyser A (2018) Toward Rigorous Parameterization of Underconstrained Neural Network Models Through Interactive Visualization and Steering of Connectivity Generation. Frontiers Media SA Frontiers in Neuroinformatics. 12:32
- Mulugeta L, Drach A, Erdemir A, Hunt C. A., Horner M, Ku JP., Jr. JG. M, Vadigepalli R and Lytton WW. (2018) Credibility, Replicability, and Reproducibility in Simulation for Biomedicine and Clinical Applications in Neuroscience. Frontiers Media SA Frontiers in Neuroinformatics. 12:18
- Wang RM., Thakur CS. and Schaik Avan (2018) An FPGA-Based Massively Parallel Neuromorphic Cortex Simulator. Frontiers Media SA Frontiers in Neuroscience. 12:213
- Antolík J and Davison AP. (2018) Arkheia: Data Management and Communication for Open Computational Neuroscience. Frontiers Media SA Frontiers in Neuroinformatics. 12:6
- Sherfey JS., Soplata AE., Ardid S, Roberts EA., Stanley DA., Pittman-Polletta BR. and Kopell NJ. (2018) DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation. Frontiers Media SA Frontiers in Neuroinformatics. 12:10
- Gallinaro JV. and Rotter S (2018) Associative properties of structural plasticity based on firing rate homeostasis in recurrent neuronal networks. Scientific Reports. 8:3754
- Martinez-Canada P, Mobarhan MH, Halnes G, Fyhn M, Morillas C, Pelayo F and Einevoll GT. (2018) Biophysical network modeling of the dLGN circuit: Effects of cortical feedback on spatial response properties of relay cells. Public Library of Science (PLOS) PLOS Computational Biology. 14:e1005930
- Talanov M, Gafarov F, Vallverdú J, Ostapenko S, Gazizov M, Toschev A, Leukhin A and Distefano S (2018) Simulation of serotonin mechanisms in NEUCOGAR cognitive architecture. Elsevier BV Procedia Computer Science. 123:473–478
- Krishnan J, Porta Mana P, Helias M, Diesmann M and Di Napoli E (2018) Perfect Detection of Spikes in the Linear Sub-threshold Dynamics of Point Neurons. Frontiers in Neuroinformatics. 11:75
- Kappel D, Legenstein R, Habenschuss S, Hsieh M and Maass W (2018) A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning. Society for Neuroscience eneuro. 5:ENEURO.0301–17.2018
- Fardet T, Bottani S, Métens S and Monceau P (2018) Effects of inhibitory neurons on the quorum percolation model and dynamical extension with the Brette–Gerstner model. Physica A: Statistical Mechanics and its Applications. 499:98 - 109
- van Albada SJ., Rowley AG., Senk J, Hopkins M, Schmidt M, Stokes AB., Lester DR., Diesmann M and Furber SB. (2018) Performance Comparison of the Digital Neuromorphic Hardware SpiNNaker and the Neural Network Simulation Software NEST for a Full-Scale Cortical Microcircuit Model. Frontiers in Neuroscience. 12:291
- Geminiani A, Casellato C, Locatelli F, Prestori F, Pedrocchi A and D'Angelo E (2018) Complex Dynamics in Simplified Neuronal Models: Reproducing Golgi Cell Electroresponsiveness. Frontiers in Neuroinformatics. 12:88
- Senk J, Carde C, Hagen E, Kuhlen TW., Diesmann M and Weyers B (2018) VIOLA - A Multi-Purpose and Web-Based Visualization Tool for Neuronal-Network Simulation Output. Frontiers in Neuroinformatics. 12:75
- Blundell I, Brette R, Cleland TA., Close TG., Coca D, Davison AP., Diaz-Pier S, Fernandez Musoles C, Gleeson P, Goodman DF. M., Hines M, Hopkins MW., Kumbhar P, Lester DR., Marin B, Morrison A, Müller E, Nowotny T, Peyser A, Plotnikov D, Richmond P, Rowley A, Rumpe B, Stimberg M, Stokes AB., Tomkins A, Trensch G, Woodman M and Eppler JM (2018) Code Generation in Computational Neuroscience: A Review of Tools and Techniques. Frontiers in Neuroinformatics. 12:68
- Jordan J, Ippen T, Helias M, Kitayama I, Sato M, Igarashi J, Diesmann M and Kunkel S (2018) Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers. Frontiers in Neuroinformatics. 12:2
- Lee JH (2017) Disrupted cholinergic modulation can underlie abnormal gamma rhythms in schizophrenia and auditory hallucination. Journal of Computational Neuroscience. 43:173–187
- Lee JH, Koch C and Mihalas S (2017) A Computational Analysis of the Function of Three Inhibitory Cell Types in Contextual Visual Processing. Frontiers Media S.A. Frontiers in Computational Neuroscience. 11:28
- Einarsson H, Gauy MM, Lengler J and Steger A (2017) A Model of Fast Hebbian Spike Latency Normalization. Frontiers Media S.A. Frontiers in Computational Neuroscience. 11:33–
- Pani D, Meloni P, Tuveri G, Palumbo F, Massobrio P and Raffo L (2017) An FPGA Platform for Real-Time Simulation of Spiking Neuronal Networks. Frontiers Media S.A. Frontiers in Neuroscience. 11:90–
- Naveros F, Garrido JA, Carrillo RR, Ros E and Luque NR (2017) Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks. Frontiers Media S.A. Frontiers in Neuroinformatics. 11:7–
- Schenck W, El Sayed S, Foszczynski M, Homberg W and Pleiter D (2017) Evaluation and Performance Modeling of a Burst Buffer Solution. ACM SIGOPS Oper. Syst. Rev.. 50:12–26
- Hinkel G, Groenda H, Krach S, Vannucci L, Denninger O, Cauli N, Ulbrich S, Roennau A, Falotico E, Gewaltig MO, Knoll A and Dillmann R (2017) A Framework for Coupled Simulations of Robots and Spiking Neuronal Networks. Journal of Intelligent Robotic Systems. 85:71–91
- Gerhard F, Deger M and Truccolo W (2017) On the stability and dynamics of stochastic spiking neuron models: Nonlinear Hawkes process and point process GLMs. Public Library of Science PLOS Computational Biology. 13:1-31
- Belic JJ., Kumar A and Hellgren Kotaleski J (2017) Interplay between periodic stimulation and GABAergic inhibition in striatal network oscillations. Public Library of Science PLOS ONE. 12:1-17
- Rostami V, Porta Mana P, Gruen S and Helias M (2017) Bistability, non-ergodicity, and inhibition in pairwise maximum-entropy models. Public Library of Science PLOS Computational Biology. 13:1-44
- Schuecker J, Schmidt M, van Albada SJ., Diesmann M and Helias M (2017) Fundamental Activity Constraints Lead to Specific Interpretations of the Connectome. Public Library of Science PLOS Computational Biology. 13:1-25
- Schwalger T, Deger M and Gerstner W (2017) Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size. Public Library of Science PLOS Computational Biology. 13:1-63
- Kühn T and Helias M (2017) Locking of correlated neural activity to ongoing oscillations. Public Library of Science PLOS Computational Biology. 13:1-32
- Tikidji-Hamburyan RA., Narayana V, Bozkus Z and El-Ghazawi TA. (2017) 10.3389/fninf.2017.00046. Frontiers in Neuroinformatics. 11:46
- Spreizer S, Angelhuber M, Bahuguna J, Aertsen A and Kumar A (2017) Activity Dynamics and Signal Representation in a Striatal Network Model with Distance-Dependent Connectivity. Society for Neuroscience eNeuro. 4:ENEURO.0348–16.2017
- Sadeh S, Silver R. A, Mrsic-Flogel TD. and Muir DR (2017) Assessing the Role of Inhibition in Stabilizing Neocortical Networks Requires Large-Scale Perturbation of the Inhibitory Population. Society for Neuroscience Journal of Neuroscience. 37:12050–12067
- Mirzaei A, Kumar A, Leventhal D, Mallet N, Aertsen A, Berke J and Schmidt R (2017) Sensorimotor Processing in the Basal Ganglia Leads to Transient Beta Oscillations during Behavior. Society for Neuroscience Journal of Neuroscience. 37:11220–11232
- Lensjo KK, Lepperod ME, Dick G, Hafting T and Fyhn M (2017) Removal of Perineuronal Nets Unlocks Juvenile Plasticity Through Network Mechanisms of Decreased Inhibition and Increased Gamma Activity. Society for Neuroscience Journal of Neuroscience. 37:1269–1283
- Lee JH and Mihalas S (2017) Visual processing mode switching regulated by VIP cells. Scientific Reports. 7:1843
- Ippen T, Eppler JM., Plesser HE and Diesmann M (2017) Constructing neuronal network models in massively parallel environments. Front. Neuroinform.. 11:30
- Fiebig F and Lansner A (2017) A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation. Society for Neuroscience Journal of Neuroscience. 37:83–96
- Falotico E, Vannucci L, Ambrosano A, Albanese U, Ulbrich S, Vasquez Tieck JC, Hinkel G, Kaiser J, Peric I, Denninger O, Cauli N, Kirtay M, Roennau A, Klinker G, Von Arnim A, Guyot L, Peppicelli D, Martínez-Cañada P, Ros E, Maier P, Weber S, Huber M, Plecher D, Röhrbein F, Deser S, Roitberg A, van der Smagt P, Dillman R, Levi P, Laschi C, Knoll AC. and Gewaltig MO (2017) Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform. Frontiers in Neurorobotics. 11:2
- Aasebo IE. J., Lepperod ME., Stavrinou M, Nokkevangen S, Einevoll G, Hafting T and Fyhn M (2017) Temporal Processing in the Visual Cortex of the Awake and Anesthetized Rat. Society for Neuroscience eNeuro. 4
- Deniz T and Rotter S (2017) Joint statistics of strongly correlated neurons via dimensionality reduction. Journal of Physics A: Mathematical and Theoretical. 50:254002
- Vannucci L, Falotico E and Laschi C (2017) Proprioceptive Feedback through a Neuromorphic Muscle Spindle Model. Frontiers in Neuroscience. 11:341
- Kunkel S and Schenck W (2017) The NEST Dry-Run Mode: Efficient Dynamic Analysis of Neuronal Network Simulation Code. Frontiers in Neuroinformatics. 11:40
- Hahne J, Dahmen D, Schuecker J, Frommer A, Bolten M, Helias M and Diesmann M (2017) Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator. Frontiers in Neuroinformatics. 11:34
- Stöckel A, Jenzen C, Thies M and Rückert U (2017) Binary Associative Memories as a Benchmark for Spiking Neuromorphic Hardware. Frontiers in Computational Neuroscience. 11:71
- Lytton WW., Seidenstein AH., Dura-Bernal S, McDougal RA., Schãärmann F and Hines ML. (2016) Simulation Neurotechnologies for Advancing Brain Research: Parallelizing Large Networks in NEURON. MIT Press Neural Computation. 28:2063–2090
- Dahmen D, Bos H and Helias M (2016) Correlated Fluctuations in Strongly Coupled Binary Networks Beyond Equilibrium. American Physical Society Phys. Rev. X. 6:031024
- Sun H, Sourina O and Huang GB (2016) Learning Polychronous Neuronal Groups Using Joint Weight-Delay Spike-Timing-Dependent Plasticity. MIT Press Neural Computation. 28:2181–2212
- Sreenivasa M., Ayusawa K. and Nakamura Y. (2016) Modeling and Identification of a Realistic Spiking Neural Network and Musculoskeletal Model of the Human Arm, and an Application to the Stretch Reflex. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 24:591-602
- Sahasranamam A, Vlachos I, Aertsen A and Kumar A (2016) Dynamical state of the network determines the efficacy of single neuron properties in shaping the network activity. The Author(s) Scientific Reports. 6:26029–
- Pfeil T, Jordan J, Tetzlaff T, Grübl A, Schemmel J, Diesmann M and Meier K (2016) Effect of Heterogeneity on Decorrelation Mechanisms in Spiking Neural Networks: A Neuromorphic-Hardware Study. American Physical Society Phys. Rev. X. 6:021023
- Cheung K, Schultz SR. and Luk W (2016) NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors. Frontiers in Neuroscience. 9:516
- Wang Z, Guo L and Adjouadi M (2016) Wavelet decomposition and phase encoding of temporal signals using spiking neurons. NEUROCOMPUTING. 173:1203–1210
- Segev A, Curtis D, Jung S and Chae S (2016) Invisible Brain: Knowledge in Research Works and Neuron Activity. Public Library of Science PLoS ONE. 11:1-21
- Bos H, Diesmann M and Helias M (2016) Identifying Anatomical Origins of Coexisting Oscillations in the Cortical Microcircuit. Public Library of Science PLOS Computational Biology. 12:1-34
- Tully PJ., Lindén H, Hennig MH. and Lansner A (2016) Spike-Based Bayesian-Hebbian Learning of Temporal Sequences. Public Library of Science PLOS Computational Biology. 12:1-35
- Jovanovic S and Rotter S (2016) Interplay between Graph Topology and Correlations of Third Order in Spiking Neuronal Networks. Public Library of Science PLoS Comput Biol. 12:1-28
- Heiberg T, Hagen E, Halnes G and Einevoll GT. (2016) Biophysical Network Modelling of the dLGN Circuit: Different Effects of Triadic and Axonal Inhibition on Visual Responses of Relay Cells. Public Library of Science PLoS Comput Biol. 12:1-38
- Cain N, Iyer R, Koch C and Mihalas S (2016) The Computational Properties of a Simplified Cortical Column Model. Public Library of Science PLOS Computational Biology. 12:1-18
- Sboev A., Vlasov D., Serenko A., Rybka R. and Moloshnikov I. (2016) On the applicability of STDP-based learning mechanisms to spiking neuron network models. AIP Advances. 6:111305
- Westoe J and May PJ.C. (2016) Capturing contextual effects in spectro-temporal receptive fields. Hearing Research. 339:195 - 210
- Trengove C, Diesmann M and Leeuwen Cvan (2016) Dynamic effective connectivity in cortically embedded systems of recurrently coupled synfire chains. Journal of Computational Neuroscience. 40:1–26
- Talanov M, Vallverda J, Hu B, Moore P, Toschev A, Shatunova D, Maganova A, Sedlenko D and Leukhin A (2016) Emotional simulations and depression diagnostics. Biologically Inspired Cognitive Architectures. 18:41 - 50
- Schmitt O, Eipert P, Kettlitz R, Leßmann F and Wree A (2016) The connectome of the basal ganglia. Brain Structure and Function. 221:753–814
- Sboev A, Vlasov D, Serenko A, Rybka R and Moloshnikov I (2016) A comparison of learning abilities of spiking networks with different spike timing-dependent plasticity forms. Journal of Physics: Conference Series. 681:012013
- Ray S, Chintaluri C, Bhalla US. and Wójcik DK. (2016) NSDF: Neuroscience Simulation Data Format. Neuroinformatics. 14:147–167
- Liu Q, Pineda-GarcÃa G, Stromatias E, Serrano-Gotarredona T and Furber SB. (2016) Benchmarking Spike-Based Visual Recognition: A Dataset and Evaluation. Frontiers in Neuroscience. 10:496
- Lindahl M and Hellgren Kotaleski J (2016) Untangling Basal Ganglia Network Dynamics and Function: Role of Dopamine Depletion and Inhibition Investigated in a Spiking Network Model. Society for Neuroscience eNeuro. 3
- Weidel P, Djurfeldt M, Duarte RC. and Morrison A (2016) Closed Loop Interactions between Spiking Neural Network and Robotic Simulators Based on MUSIC and ROS. Frontiers in Neuroinformatics. 10:31
- Sukhinin DI., Engel AK., Manger P and Hilgetag CC. (2016) Building the Ferretome. Frontiers in Neuroinformatics. 10:16
- Chua Y and Morrison A (2016) Effects of Calcium Spikes in the Layer 5 Pyramidal Neuron on Coincidence Detection and Activity Propagation. Frontiers in Computational Neuroscience. 10:76
- Cattani A, Solinas S and Canuto C (2016) A Hybrid Model for the Computationally-Efficient Simulation of the Cerebellar Granular Layer. Frontiers in Computational Neuroscience. 10:30
- Berthet P, Lindahl M, Tully PJ., Hellgren-Kotaleski J and Lansner A (2016) Functional Relevance of Different Basal Ganglia Pathways Investigated in a Spiking Model with Reward Dependent Plasticity. Frontiers in Neural Circuits. 10:53
- Diaz-Pier S, Naveau M«l, Butz-Ostendorf M and Morrison A (2016) Automatic Generation of Connectivity for Large-Scale Neuronal Network Models through Structural Plasticity. Frontiers in Neuroanatomy. 10:57
- Knight JC., Tully PJ., Kaplan BA., Lansner A and Furber SB. (2016) Large-Scale Simulations of Plastic Neural Networks on Neuromorphic Hardware. Frontiers in Neuroanatomy. 10:37
- Majumdar A, Sivagnanam S, Carnevale NT, Yoshimoto K, Gleeson P, Quintana A and Silver RA (2016) Neuroscience Gateway ? Cyberinfrastructure Providing Supercomputing Resources for Large Scale Computational Neuroscience Research. Frontiers in Neuroinformatics
- Schuecker J, Diesmann M and Helias M (2015) Modulated escape from a metastable state driven by colored noise. American Physical Society Phys. Rev. E. 92:052119
- van Albada SJ, Helias M and Diesmann M (2015) Scalability of Asynchronous Networks Is Limited by One-to-One Mapping between Effective Connectivity and Correlations. Public Library of Science PLoS Comput Biol. 11:e1004490
- Zaytsev YV., Morrison A and Deger M (2015) Reconstruction of recurrent synaptic connectivity of thousands of neurons from simulated spiking activity. Journal of Computational Neuroscience. 39:77–103
- Tomsett RJ., Ainsworth M, Thiele A, Sanayei M, Chen X, Gieselmann MA., Whittington MA., Cunningham MO. and Kaiser M (2015) Virtual Electrode Recording Tool for EXtracellular potentials (VERTEX): comparing multi-electrode recordings from simulated and biological mammalian cortical tissue. Brain Structure and Function. 220:2333–2353
- Naveros F., Luque N.R., Garrido J.A., Carrillo R.R., Anguita M. and Ros E. (2015) A Spiking Neural Simulator Integrating Event-Driven and Time-Driven Computation Schemes Using Parallel CPU-GPU Co-Processing: A Case Study. Neural Networks and Learning Systems, IEEE Transactions on. 26:1567–1574
- Farkhooi F and van Vreeswijk C (2015) Renewal Approach to the Analysis of the Asynchronous State for Coupled Noisy Oscillators. PHYSICAL REVIEW LETTERS. 115:038103
- Vanni S, Sharifian F, Heikkinen H and Vigário R (2015) Modeling fMRI signals can provide insights into neural processing in the cerebral cortex. American Physiological Society Journal of Neurophysiology. 114:768–780
- Bahuguna J, Aertsen A and Kumar A (2015) Existence and Control of Go/No-Go Decision Transition Threshold in the Striatum. Public Library of Science PLoS Comput Biol. 11:e1004233
- Dr. Ing. Weyers B, Nowke C, Hänel C, Zielasko D, Hentschel B and Kuhlen T (2015) The Human Brain Project – Chances and Challenges for Cognitive Systems. DuEPublico
- Arnoldt H, Chang S, Jahnke S, Urmersbach B, Taschenberger H and Timme M (2015) When Less Is More: Non-monotonic Spike Sequence Processing in Neurons. Public Library of Science PLoS Comput Biol. 11:e1004002
- Sadeh S and Rotter S (2015) Orientation Selectivity in Inhibition-Dominated Networks of Spiking Neurons: Effect of Single Neuron Properties and Network Dynamics. Public Library of Science PLoS Comput Biol. 11:e1004045
- Pozzorini C, Mensi S, Hagens O, Naud R, Koch C and Gerstner W (2015) Automated High-Throughput Characterization of Single Neurons by Means of Simplified Spiking Models. Public Library of Science PLOS Computational Biology. 11:1-29
- Lagzi F and Rotter S (2015) Dynamics of Competition between Subnetworks of Spiking Neuronal Networks in the Balanced State. Public Library of Science PLOS ONE. 10:1-28
- Vallverdu J, Talanov M, Distefano S, Mazzara M, Tchitchigin A and Nurgaliev I (2015) A cognitive architecture for the implementation of emotions in computing systems. Biologically Inspired Cognitive Architectures:-
- Solanka L, van Rossum MC and Nolan MF (2015) Noise promotes independent control of gamma oscillations and grid firing within recurrent attractor networks. eLife Sciences Publications Limited eLife. 4:e06444
- Ray S, Chintaluri C, Bhalla US. and Wójcik DK. (2015) NSDF: Neuroscience Simulation Data Format. Neuroinformatics:1–21
- Muller E, Bednar JA, Diesmann M, Gewaltig MO, Hines M and Davison AP (2015) Python in Neuroscience. Frontiers in Neuroinformatics. 9:11
- Kukin K. and Sboev A. (2015) Comparison of learning methods for spiking neural networks. Pleiades Publishing Optical Memory and Neural Networks. 24:123–129
- Jahnke S, Timme M and Memmesheimer RM (2015) A Unified Dynamic Model for Learning, Replay, and Sharp-Wave/Ripples. Society for Neuroscience Journal of Neuroscience. 35:16236–16258
- Huyck C, Evans C and Mitchell I (2015) A comparison of simple agents implemented in simulated neurons. Biologically Inspired Cognitive Architectures:-
- Hagen E, Ness TV., Khosrowshahi A, Sørensen C, Fyhn M, Hafting T, Franke F and Einevoll GT. (2015) ViSAPy: A Python tool for biophysics-based generation of virtual spiking activity for evaluation of spike-sorting algorithms. Journal of Neuroscience Methods:-
- Colliaux D, Yger P and Kaneko K (2015) Impact of sub and supra-threshold adaptation currents in networks of spiking neurons. Journal of Computational Neuroscience. 39:255–270
- Bujan AF., Aertsen A and Kumar A (2015) Role of Input Correlations in Shaping the Variability and Noise Correlations of Evoked Activity in the Neocortex. The Journal of Neuroscience. 35:8611–8625
- van Albada S, Helias M and Diesmann M (2015) Limits to the scalability of cortical network models. BMC Neuroscience. 16:O1
- Nowke C, Zielasko D, Weyers B, Hentschel B, Peyser A and Kuhlen T (2015) Integrating Visualizations into Modeling NEST Simulations. Frontiers in Neuroinformatics. 9:29
- Hahne J, Helias M, Kunkel S, Igarashi J, Bolten M, Frommer A and Diesmann M (2015) A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations. Frontiers in Neuroinformatics. 9:22
- Vitay J, Dinkelbach HÜ and Hamker FH (2015) ANNarchy: a code generation approach to neural simulations on parallel hardware. Frontiers in Neuroinformatics. 9:19
- Chua Y, Helias M and Morrison A (2015) Modeling the calcium spike as a threshold triggered fixed waveform for synchronous inputs in the fluctuation regime. Frontiers in Computational Neuroscience. 9:91
- Probst D, Petrovici MA, Bytschok I, Bill J, Pecevski D, Schemmel J and Meier K (2015) Probabilistic Inference in Discrete Spaces Can Be Implemented into Networks of LIF Neurons. Frontiers in Computational Neuroscience. 9:13
- Jahnke S, Memmesheimer RM and Timme M (2014) Oscillation-Induced Signal Transmission and Gating in Neural Circuits. Public Library of Science PLoS Comput Biol. 10:e1003940
- Deger M, Schwalger T, Naud R and Gerstner W (2014) Fluctuations and information filtering in coupled populations of spiking neurons with adaptation. American Physical Society Phys. Rev. E. 90:062704
- Potjans TC and Diesmann M (2014) The Cell-Type Specific Cortical Microcircuit: Relating Structure and Activity in a Full-Scale Spiking Network Model.. Cereb Cortex. 3:785–806
- Petrovici MA., Vogginger B, Müller P, Breitwieser O, Lundqvist M, Muller L, Ehrlich M, Destexhe A, Lansner A, Schüffny R, Schemmel J and Meier K (2014) Characterization and Compensation of Network-Level Anomalies in Mixed-Signal Neuromorphic Modeling Platforms. Public Library of Science PLoS ONE. 9:e108590
- Hahn G, Bujan AF., Frégnac Y, Aertsen A and Kumar A (2014) Communication through Resonance in Spiking Neuronal Networks. Public Library of Science PLoS Comput Biol. 10:e1003811
- Wu JQ., Peters GJ., Rittner P, Cleland TA. and Smith DM. (2014) The hippocampus, medial prefrontal cortex, and selective memory retrieval: Evidence from a rodent model of the retrieval-induced forgetting effect. Wiley Hippocampus. 24:1070–1080
- Helias M, Tetzlaff T and Diesmann M (2014) The correlation structure of local neuronal networks intrinsically results from recurrent dynamics. PLoS Computational Biology. 10:e1003428
- Kriener B, Enger H, Tetzlaff T, Plesser HE, Gewaltig MO and Einevoll GT (2014) Dynamics of self-sustained asynchronous-irregular activity in random networks of spiking neurons with strong synapses. Frontiers Media SA Frontiers in computational neuroscience. 8:136
- Zaytsev YV. and Morrison A (2014) CyNEST: a maintainable Cython-based interface for the NEST simulator. Frontiers in Neuroinformatics. 8:23
- Wazny M and Wojcik GM. (2014) Shifting spatial attention—Numerical model of Posner experiment. Neurocomputing. 135:139–144
- Sousa M and Aguiar P (2014) Building, simulating and visualizing large spiking neural networks with NeuralSyns. Neurocomputing. 123:280–372
- Segundo J.Guzman ASCSH (2014) Stimfit: quantifying electrophysiological data with Python. Front Neuroinform. 8:16
- Rothganger F, Warrender CE., Trumbo D and Aimone JB. (2014) N2A: a computational tool for modeling from neurons to algorithms. Front Neural Circuits. 8:1
- Philip J. Tully MH. H and Lansner A (2014) Synaptic and nonsynaptic plasticity approximating probabilistic inference. Frontiers in Synaptic Neuroscience. 6:8
- Minkovich K., Thibeault C.M., O'Brien M.J. and Nogin A. (2014) HRLSim: A High Performance Spiking Neural Network Simulator for GPGPU Clusters. Neural Networks and Learning Systems, IEEE Transactions on. 25:316–331
- Djurfeldt M, Davison AP. and Eppler JM. (2014) Efficient generation of connectivity in neuronal networks from simulator-independent descriptions. Front Neuroinform. 8:43
- Vella M., Cannon R., Crook S., Davison A., Ganapathy G., Robinson H. P. C., Silver A. and Gleeson P. (2014) libNeuroML and PyLEMS: using Python to combine procedural and declarative modeling approaches in computational neuroscience. Front Neuroinform. 8:38
- Stimberg M., Goodman D., Benichoux V. and Brette1 R. (2014) Equation-oriented specification of neural models for simulations. Front Neuroinform. 8:6
- Man Yi Yim AKAA and Rotter S (2014) Impact of correlated inputs to neurons: modeling observations from in vivo intracellular recordings. Journal of Computational Neuroscience. 37:293–304
- Muller L, Reynaud A, Chavane F and Destexhe A (2014) The stimulus-evoked population response in visual cortex of awake monkey is a propagating wave. Nature Communications. 5
- Le Mouel C, Harris K. and Yger P (2014) Supervised learning with decision margins in pools of spiking neurons. Springer US Journal of Computational Neuroscience. 37:333–344
- Kunkel S, Schmidt M, Eppler JM, Plesser HE, Masumoto G, Igarashi J, Ishii S, Fukai T, Morrison A, Diesmann M and Helias M (2014) Spiking network simulation code for petascale computers. Frontiers in Neuroinformatics. 8
- Kriener B, Helias M, Rotter S, Diesmann M and Einevoll GT. (2014) How pattern formation in ring networks of excitatory and inhibitory spiking neurons depends on the input current regime. Frontiers in Computational Neuroscience. 7:187
- Gewaltig MO and Cannon R (2014) Current Practice in Software Development for Computational Neuroscience and How to Improve It. PLOS Computational Biology. 10:e1003376
- Eliasmith C and Trujillo O (2014) The use and abuse of large-scale brain models. Current Opinion in Neurobiology. 25:1–6
- Chun-Wei Yuan LKBG and Leibold C (2014) Neuronal Adaptation Translates Stimulus Gaps into a Population Code. PLOS One. 9:e95705
- Chen W and Schutter ED (2014) Python-based geometry preparation and simulation visualization toolkits for STEPS. Frontiers in Neuroinformatics. 8:37
- Chapuis A and Tetzlaff T (2014) The variability of tidewater-glacier calving: origin of event-size and interval distributions. Journal of Glaciology. 60:622–634
- Beata Strack KM.JKJ.C (2014) Simulating vertical and horizontal inhibition with short-term dynamics in a multi-column multi-layer model of neocortex. International Journal of Neural Systems. 24:1440002
- Ebert M, Hauptmann C and Tass P (2014) Coordinated reset stimulation in a large-scale model of the STN-GPe circuit. Frontiers in Computational Neuroscience. 8:154
- Duarte RCF and Morrison A (2014) Dynamic stability of sequential stimulus representations in adapting neuronal networks. Frontiers in Computational Neuroscience. 8:124
- Pyka M, Klatt S and Cheng S (2014) Parametric Anatomical Modeling: A method for modeling the anatomical layout of neurons and their projections. Frontiers in Neuroanatomy. 8:91
- Iyer R, Menon V, Buice M, Koch C and Mihalas S (2013) The Influence of Synaptic Weight Distribution on Neuronal Population Dynamics. Public Library of Science (PLoS) PLoS Computational Biology. 9:e1003248
- Schultze-Kraft M, Diesmann M, Grün S and Helias M (2013) Noise suppression and surplus synchrony by coincidence detection. Public Library of Science PLoS Comput Biol. 9:e1002904
- Zaytsev YV. and Morrison A (2013) Increasing quality and managing complexity in neuroinformatics software development with continuous integration. Front. Neuroinform.. 6:31
- Yger P and Harris KD. (2013) The Convallis Rule for Unsupervised Learning in Cortical Networks. PLOS Comput Bio. 9:10
- Wagatsuma N, Potjans TC., Diesmann M, Sakai K and Fukai T (2013) Spatial and Feature-Based Attention in a Layered Cortical Microcircuit Model. PLoS ONE. 8:12
- Vlachos A, Helias M, Becker D, Diesmann M and Deller T (2013) NMDA-receptor inhibition increases spine stability of denervated mouse dentate granule cells and accelerates spine density recovery following entorhinal denervation in vitro. Neurobiology of Disease. 59:267–276
- Vlachos I, Zaytsev YV., Spreizer S, Aertsen A and Kumar A (2013) Neural system prediction and identification challenge. Front Neuroinform.. 7:43
- Tang Y, Zhang B, Wu J, Hu T, Zhou J and Liu F (2013) Parallel architecture and optimization for discrete-event simulation of spike neural networks. SP Science China Press Science China Technological Sciences. 56:509–517
- Stevens JLR., Elver M and Bednar JA. (2013) An automated and reproducible workflow for running and analyzing neural simulations using Lancet and IPython Notebook. Front Neuroinform. 7:44
- Schwartz MO (2013) Reproducing Biologically Realistic Regimes on a Highly-Accelerated Neuromorphic Hardware System.
- Schutter E (2013) Collaborative Modeling in Neuroscience: Time to Go Open Model?. Springer-Verlag Neuroinformatics. 11:135–136
- Leon PS, Knock SA., Woodman M. M, Domide L, Mersmann J, McIntosh AR. and Jirsa V (2013) The Virtual Brain: a simulator of primate brain network dynamics. Frontiers Media SA Frontiers in Neuroinformatics. 7:10
- Richmond P, Cope A, Gurney K and Allerton DJ. (2013) From Model Specification to Simulation of Biologically Constrained Networks of Spiking Neurons. Neuroinformatics. 12:307–323
- Pernice V, Deger M, Cardanobile S and Rotter S (2013) The relevance of network micro-structure for neural dynamics. Frontiers in Computational Neuroscience. 7:72
- Parekh R and Ascoli GA. (2013) Neuronal Morphology Goes Digital: A Research Hub for Cellular and System Neuroscience. Neuron. 77:1017–1038
- Mulas M and Massobrio P (2013) NeuVision: A novel simulation environment to model spontaneous and stimulus-evoked activity of large-scale neuronal networks. Neurocomputing. 122:441–457
- Moren J, Shibata T and Doya K (2013) The Mechanism of Saccade Motor Pattern Generation Investigated by a Large-Scale Spiking Neuron Model of the Superior Colliculus. PLOS One. 8:e57134
- Mohemmed A, Schliebs S, Matsuda S and Kasabov N (2013) Training spiking neural networks to associate spatio-temporal input–output spike patterns. Neurocomputing. 107:3–10
- Mattioni M and Novère NL (2013) Integration of Biochemical and Electrical Signaling-Multiscale Model of the Medium Spiny Neuron of the Striatum. PLOS One. 8:e66811
- Mäki-Marttunen T, Aćimović J, Ruohonen K and Linne ML (2013) Structure-Dynamics Relationships in Bursting Neuronal Networks Revealed Using a Prediction Framework. PLOS One. 8:e69373
- Lindahl M, Sarvestani IK, Ekeberg Ö and Kotaleski JH (2013) Signal enhancement in the output stage of the basal ganglia by synaptic short-term plasticity in the direct, indirect, and hyperdirect pathways. Front Comput Neurosci. 7:Article 76:1–19
- Lengler J, Jug F and Steger A (2013) Reliable Neuronal Systems: The Importance of Heterogeneity. PLOS One. 8:12:e80694
- Lee J, Tsunada J and Cohen YE. (2013) A Model of the Differential Representation of Signal Novelty in the Local Field Potentials and Spiking Activity of the Ventrolateral Prefrontal Cortex. Neural Comput. 25:157–185
- Kaplan BA., Lansner A, Masson GS. and Perrinet LU. (2013) Anisotropic connectivity implements motion-based prediction in a spiking neural network. Front Comput Neurosci. 7:112
- Jahnke S, Memmesheimer RM and Timme M (2013) Propagating synchrony in feed-forward networks. Front Comput Neurosci. 7:153
- J. H. Saito J.-F. ME. PJ. B. DFM. C. N (2013) Simulated Activation Patterns of Biological Neurons Cultured onto a Multi-Electrode Array Based on a Modified Izhikevich's Model. Fundamenta Informaticae. 124:111–132
- Hull MJ. and Willshaw DJ. (2013) morphforge: a toolbox for simulating small networks of biologically detailed neurons in Python. Front Neuroinform.. 7:47
- Holt AB. and Netoff TI. (2013) Computational modeling of epilepsy for an experimental neurologist. Experimental Neurology. 244:75–86
- Hernandez OE and Zurek EE (2013) Teaching and learning the Hodgkin-Huxley model based on software developed in NEURONs programming language hoc. BioMed Central BMC Medical Education. 13:1–9
- Helias M, Tetzlaff T and Diesmann M (2013) Echoes in correlated neural systems. New Journal of Physics. 15:023002
- Heiberg T, Kriener B, Tetzlaff T, Casti A, Einevoll GT. and Plesser HE. (2013) Firing-rate models capture essential response dynamics of LGN relay cells. Springer US Journal of Computational Neuroscience:1–17
- Grytskyy D, Tetzlaff T, Diesmann M and Helias M (2013) A unified view on weakly correlated recurrent networks. Frontiers in Computional Neuroscience. 7:131
- Ferreiroa R and Sánchez E (2013) Functional properties of a realistic model of dLGN. Neurocomputing. 114:36–44
- Farkhooi F, Froese A, Muller E, Menzel R and Nawrot MP. (2013) Cellular Adaptation Facilitates Sparse and Reliable Coding in Sensory Pathways. PLOS Comput Bio. 9:10: e1003251
- Cohen MX. and Gulbinaite R (2013) Five methodological challenges in cognitive electrophysiology. NeuroImage:-
- Bekolay T, Bergstra J, Hunsberger E, DeWolf T, Stewart TC., Rasmussen D, Choo X, Voelker AR and Eliasmith C (2013) Nengo: a Python tool for building large-scale functional brain models. Front Neuroinform.. 7:48
- Beeman D (2013) History of Neural Simulation Software. Springer Series in Computational Neuroscience. 9:33–71
- Baptista D'io and Morgado-Dias F (2013) A survey of artificial neural network training tools. Springer-Verlag Neural Computing and Applications. 10:1–7
- Antolik J and Davison AP. (2013) Integrated workflows for spiking neuronal network simulations. Front Neuroinform.. 7:34
- Jahnke S, Timme M and Memmesheimer RM (2012) Guiding Synchrony through Random Networks. American Physical Society Phys. Rev. X. 2:041016
- Okun M, Yger P, Marguet SL, Gerard-Mercier F, Benucci A, Katzner S, Busse L, Carandini M and Harris KD (2012) Population rate dynamics and multineuron firing patterns in sensory cortex.. J Neurosci. 32:17108–17119
- Phoka E, Wildie M, Schultz SR and Barahona M (2012) Sensory experience modifies spontaneous state dynamics in a large-scale barrel cortical model.. J Comput Neurosci. 33:323–339
- Deger M, Helias M, Rotter S and Diesmann M (2012) Spike-timing dependence of structural plasticity explains cooperative synapse formation in the neocortex.. PLoS Comput Biol. 8:e1002689
- Kriener B (2012) How synaptic weights determine stability of synchrony in networks of pulse-coupled excitatory and inhibitory oscillators.. Chaos. 22:033143
- Mohemmed A, Schliebs S, Matsuda S and Kasabov N (2012) SPAN: Spike pattern association neuron for learning spatio-temporal spike patterns.. Int J Neural Syst. 22:1250012
- Trengove C, Leeuwen Cvan and Diesmann M (2012) High-capacity embedding of synfire chains in a cortical network model.. J Comput Neurosci. 34:185–209
- Tetzlaff T, Helias M, Einevoll GT and Diesmann M (2012) Decorrelation of neural-network activity by inhibitory feedback.. PLoS Comput Biol. 8:e1002596
- Schmitt O and Eipert P (2012) neuroVIISAS: approaching multiscale simulation of the rat connectome.. Neuroinformatics. 10:243–267
- Djurfeldt M (2012) The connection-set algebra–a novel formalism for the representation of connectivity structure in neuronal network models.. Neuroinformatics. 10:287–304
- Deger M, Helias M, Boucsein C and Rotter S (2012) Statistical properties of superimposed stationary spike trains.. J Comput Neurosci. 32:443–463
- Avermann M, Tomm C, Mateo C, Gerstner W and Petersen CCH (2012) Microcircuits of excitatory and inhibitory neurons in layer 2/3 of mouse barrel cortex.. J Neurophysiol. 107:3116–3134
- Henker S, Partzsch J and Schüffny R (2012) Accuracy evaluation of numerical methods used in state-of-the-art simulators for spiking neural networks.. J Comput Neurosci. 32:309–326
- Pernice V, Staude B, Cardanobile S and Rotter S (2012) Recurrent interactions in spiking networks with arbitrary topology.. Phys Rev E Stat Nonlin Soft Matter Phys. 85:031916
- Rothkegel A and Lehnertz K (2012) Conedy: A scientific tool to investigate complex network dynamics. AIP Publishing Chaos: An Interdisciplinary Journal of Nonlinear Science. 22:013125
- Vlachos I, Aertsen A and Kumar A (2012) Beyond statistical significance: implications of network structure on neuronal activity.. PLoS Comput Biol. 8:e1002311
- Yuan CW and Leibold C (2012) Recurrent coupling improves discrimination of temporal spike patterns.. Front Comput Neurosci. 6:25
- Waddington A, Appleby PA, Kamps MD and Cohen N (2012) Triphasic spike-timing-dependent plasticity organizes networks to produce robust sequences of neural activity.. Front Comput Neurosci. 6:88
- Voges N. and Perrinet L. (2012) Complex dynamics in recurrent cortical networks based on spatially realistic connectivities. Front Comput Neurosci. 6:41
- Stetter O, Battaglia D, Soriano J and Geisel T (2012) Model-free reconstruction of excitatory neuronal connectivity from calcium imaging signals. PLoS Comput Biol. 8:e1002653
- Rougier NP. and Fix J (2012) DANA: distributed numerical and adaptive modelling framework.. Network. 23:237–253
- Ren Q, Kolwankar KM., Areejit Samal and Jost J (2012) Hopf bifurcation in the evolution of STDP-driven networks. Physical review. 86:13
- Rast A., Navaridas J, Jin X, Galluppi F, Plana LA., Miguel-Alonso J, Patterson C, Luján M and Furber S (2012) Managing Burstiness and Scalability in Event-Driven Models on theSpiNNaker Neuromimetic System. Springer US International Journal of Parallel Programming. 40:553–582
- Pfeil T, Potjans TC, Schrader S, Potjans W, Schemmel J, Diesmann M and Meier K (2012) Is a 4-bit synaptic weight resolution enough? - constraints on enabling spike-timing dependent plasticity in neuromorphic hardware.. Front Neurosci. 6:90
- Muller L and Destexhe A (2012) Propagating waves in thalamus, cortex and the thalamocortical system: Experiments and models. Journal of Physiology-Paris. 106:222–238
- Mattioni M, Cohen U and Novère NL (2012) Neuronvisio: A Graphical User Interface with 3D Capabilities for NEURON.. Front Neuroinform. 6:20
- Marc-Oliver Gewaltig RC (2012) Current practice in software development for computational neuroscience and how to improve it. Public Library of Science PLOS Computational Biology
- Kamps Mde (2012) Towards truly human-level intelligence in artificial applications. Cognitive Systems Research. 14:1–9
- Kamali, Sarvestani I, Kozlov A, Harischandra N, Grillner S and Ekeberg Ö (2012) A computational model of visually guided locomotion in lamprey. Springer-Verlag Biological Cybernetics. -:1–16
- Helias M, Kunkel S, Masumoto G, Igarashi J, Eppler JM, Ishii S, Fukai T, Morrison A and Diesmann M (2012) Supercomputers ready for use as discovery machines for neuroscience.. Front Neuroinform. 6:26
- Fidjeland A., Gamez D, Shanahan M. and Lazdins E (2012) Three Tools for the Real-Time Simulation of Embodied Spiking Neural Networks Using GPUs. Springer-Verlag Neuroinformatics:1–24
- Farkhooi F, Froese A, Muller E, Menzel R and Nawrot MP. (2012) Cellular Adaptation Accounts for the Sparse and Reliable Sensory Stimulus Representation. Quantitative Biology:Neurons and Cognition. -:arXiv:1210.7165 [q-bio.NC]
- Dinkelbach HÜ, Vitay J, Beuth F and Hamker FH (2012) Comparison of GPU- and CPU-implementations of mean-firing rate neural networks on parallel hardware.. Network. 23:212–236
- Crook SM, Bednar JA, Berger S, Cannon R, Davison AP, Djurfeldt M, Eppler J, Kriener B, Furber S, Graham B, Plesser HE, Schwabe L, Smith L, Steuber V and Albada Svan (2012) Creating, documenting and sharing network models.. Network. 23:131–149
- Clewley R (2012) Hybrid Models and Biological Model Reduction with PyDSTool. PLoS Comput Biol. 8:e1002628
- Bray LC. J, Anumandla SR., Thibeault CM., Hoang RV., Goodman PH., Dascalu SM., Bryant BD. and Jr. FC. H (2012) Real-time human–robot interaction underlying neurorobotic trust and intent recognition. Neural Networks. 32:130–137
- Benjaminsson S and Lansner A (2012) Nexa: a scalable neural simulator with integrated analysis.. Network. 23:254–271
- Baptista D'io and Morgado-Dias F (2012) A survey of artificial neural network training tools. Neural Computating and Applications. 23:609–615
- Lindén H, Tetzlaff T, Potjans TC, Pettersen KH, Grün S, Diesmann M and Einevoll GT (2011) Modeling the spatial reach of the LFP.. Neuron. 72:859–872
- Kannon T, Inagaki K, Kamiji NL, Makimura K and Usui S (2011) PLATO: data-oriented approach to collaborative large-scale brain system modeling.. Neural Netw. 24:918–926
- Igarashi J, Shouno O, Fukai T and Tsujino H (2011) Real-time simulation of a spiking neural network model of the basal ganglia circuitry using general purpose computing on graphics processing units.. Neural Netw. 24:950–960
- Rast A, Galluppi F, Davies S, Plana L, Patterson C, Sharp T, Lester D and Furber S (2011) Concurrent heterogeneous neural model simulation on real-time neuromimetic hardware.. Neural Netw. 24:961–978
- Kumar A, Cardanobile S, Rotter S and Aertsen A (2011) The Role of Inhibition in Generating and Controlling Parkinsons Disease Oscillations in the Basal Ganglia. Frontiers in Systems Neuroscience. 5:86
- Yamazaki T, Ikeno H, Okumura Y, Satoh S, Kamiyama Y, Hirata Y, Inagaki K, Ishihara A, Kannon T and Usui S (2011) Simulation Platform: a cloud-based online simulation environment.. Neural Netw. 24:693–698
- Brette R and Goodman DFM (2011) Vectorized algorithms for spiking neural network simulation.. Neural Comput. 23:1503–1535
- Perez T and Uchida A (2011) Reliability and synchronization in a delay-coupled neuronal network with synaptic plasticity. American Physical Society Phys. Rev. E. 83:061915
- Pernice V, Staude B, Cardanobile S and Rotter S (2011) How structure determines correlations in neuronal networks.. PLoS Comput Biol. 7:e1002059
- Brüderle D, Petrovici MA, Vogginger B, Ehrlich M, Pfeil T, Millner S, Grübl A, Wendt K, Müller E, Schwartz MO, Oliveira DHde, Jeltsch S, Fieres J, Schilling M, Müller P, Breitwieser O, Petkov V, Muller L, Davison AP, Krishnamurthy P, Kremkow J, Lundqvist M, Muller E, Partzsch J, Scholze S, Zühl L, Mayr C, Destexhe A, Diesmann M, Potjans TC, Lansner A, Schüffny R, Schemmel J and Meier K (2011) A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems.. Biol Cybern. 104:263–296
- Vlachos I, Herry C, Lüthi A, Aertsen A and Kumar A (2011) Context-dependent encoding of fear and extinction memories in a large-scale network model of the basal amygdala.. PLoS Comput Biol. 7:e1001104
- Yim M.Y., Aertsen A. and Kumar A. (2011) Significance of input correlations in striatal function.. PLoS Comput Biol. 7:e1002254
- Yger P, Boustani S, Destexhe A and Frégnac Y (2011) Topologically invariant macroscopic statistics in balanced networks of conductance-based integrate-and-fire neurons. Springer US Journal of Computational Neuroscience. 31:229–245
- Yamauchi S., Kim H. and Shinomoto S. (2011) Elemental spiking neuron model for reproducing diverse firing patterns and predicting precise firing times.. Front Comput Neurosci. 5:42
- Wagatsuma N, Potjans TC, Diesmann M and Fukai T (2011) Layer-Dependent Attentional Processing by Top-down Signals in a Visual Cortical Microcircuit Model.. Front Comput Neurosci. 5:31
- Touboul J (2011) On the Simulation of Nonlinear Bidimensional Spiking Neuron Models. Neural Comput. 23:1704–1742
- Simonov A.Y. and Kazantsev V.B. (2011) Model of the appearance of avalanche bioelectric discharges in neural networks of the brain. SP MAIK Nauka/Interperiodica JETP Letters. 93:470–475
- Schrader S, Diesmann M and Morrison A (2011) A compositionality machine realized by a hierarchic architecture of synfire chains.. Front Comput Neurosci. 4:154
- Scholze S, Schiefer S, Partzsch J, Hartmann S, Mayr CG, Höppner S, Eisenreich H, Henker S, Vogginger B and Schüffny R (2011) VLSI Implementation of a 2.8 Gevent/s Packet-Based AER Interface with Routing and Event Sorting Functionality.. Front Neurosci. 5:117
- Richmond P, Buesing L, Giugliano M and Vasilaki E (2011) Democratic Population Decisions Result in Robust Policy-Gradient Learning: A Parametric Study with GPU Simulations. PLOS One. 6:e18539
- Richert M, Nageswaran JM, Dutt N and Krichmar JL (2011) An efficient simulation environment for modeling large-scale cortical processing.. Front Neuroinform. 5:19
- Potjans W, Diesmann M. and Morrison A. (2011) An Imperfect Dopaminergic Error Signal Can Drive Temporal-Difference Learning.. Public Library of Science PLoS Computational Biology. 7:e1001133
- Bustos OEH and Bustos LH (2011) Efect of the Kv3.1 potassium conductance in the firing frequency and firing rate of an unmyelinated axon. Salud, Barranquilla. 27:2
- Mäki-Marttunen T, Acimovic J, Nykter M, Kesseli J, Ruohonen K, Yli-Harja O and Linne ML (2011) Information Diversity in Structure and Dynamics of Simulated Neuronal Networks. Front Comput Neurosci. 5:26
- Kunkel S, Potjans TC, Eppler JM, Plesser HE, Morrison A and Diesmann M (2011) Meeting the memory challenges of brain-scale network simulation.. Front Neuroinform. 5:35
- Kunkel S, Diesmann M and Morrison A (2011) Limits to the development of feed-forward structures in large recurrent neuronal networks. Frontiers in Computational Neuroscience. 4:-
- Kolwankar KM., Ren Q, Samal A and Jost J (2011) Learning and structure of neuronal networks. Springer-Verlag Pramana. 77:817–826
- Indiveri G, Linares-Barranco B, Hamilton TJ, van Schaik A, Etienne-Cummings R, Delbruck T, Liu SC, Dudek P, Häfliger P, Renaud S, Schemmel J, Cauwenberghs G, Arthur J, Hynna K, Folowosele F, Saighi S, Serrano-Gotarredona T, Wijekoon J, Wang Y and Boahen K (2011) Neuromorphic silicon neuron circuits. Frontiers in Neuroscience. 5:73
- Kamali Sarvestani I, Lindahl M, Hellgren-Kotaleski J and Ekeberg Ö (2011) The Arbitration–Extension Hypothesis: A Hierarchical Interpretation of the Functional Organization of the Basal Ganglia. Frontiers in Computational Neuroscience. 5:13
- Hugo Cornelis AD. CJM. B (2011) A Federated Design for a Neurobiological Simulation Engine: The CBI Federated Software Architecture. PLOS One. 7:e28956
- Hines M, Kumar S and Schürmann F (2011) Comparison of neuronal spike exchange methods on a Blue Gene/P supercomputer. Frontiers in Computational Neuroscience. 5:49
- Bustos OEH and Bustos LH (2011) Relationship between sodium and potassium conductances Hodgkin and Huxley style and their effect in propagation of the action potential at 40°C. Revista Científica Salud Uninorte; Salud Uninorte. Barranquilla. 27:223–225
- Helias M, Deger M, Rotter S and Diesmann M (2011) Finite post synaptic potentials cause a fast neuronal response. Frontiers in Neuroscience. 5:19
- Helias M, Grytskyy D, Tetzlaff T and Diesmann M (2011) Model-invariant features of correlations in recurrent networks. Frontiers in Computational Neuroscience. 10:3389
- Harischandra N, Knuesel J, Kozlov A, Bicanski A, Cabelguen JM, Ijspeert AJ and Ekeberg Ö (2011) Sensory feedback plays a significant role in generating walking gait and in gait transition in salamanders: A simulation study. Frontiers in Neurorobotics. 5:-
- Hanuschkin A., Herrmann J., Morrison A. and Diesmann M. (2011) Compositionality of arm movements can be realized by propagating synchrony. Springer Science + Business Media B.V Journal of computational neuroscience. 30:675–697
- Hanuschkin A, Diesmann M and Morrison A (2011) A reafferent and feed-forward model of song syntax generation in the Bengalese finch. Journal of Computational Neuroscience. 31:509–532
- Cornelis H, Rodriguez AL., Coop AD. and Bower JM. (2011) Python as a Federation Tool for GENESIS 3.0. PLOS One. 7:1
- Kremkow J, Aertsen A and Kumar A (2010) Gating of signal propagation in spiking neural networks by balanced and correlated excitation and inhibition.. The Journal of neuroscience : the official journal of the Society for Neuroscience. 30:15760–15768
- Goodman DFM (2010) Code generation: a strategy for neural network simulators.. Neuroinformatics. 8:183–196
- Akam T and Kullmann DM. (2010) Oscillations and filtering networks support flexible routing of information.. Neuron. 67:308–320
- Kremkow J, Perrinet LU, Masson GS and Aertsen A (2010) Functional consequences of correlated excitatory and inhibitory conductances in cortical networks.. J Comput Neurosci. 28:579–594
- Bernardet U and Verschure PF.M.J. (2010) IQR: a tool for the construction of multi-level simulations of brain and behaviour.. Neuroinformatics. 8:113–134
- Gleeson P, Crook S, Cannon RC, Hines ML, Billings GO, Farinella M, Morse TM, Davison AP, Ray S, Bhalla US, Barnes SR, Dimitrova YD and Silver R. A (2010) NeuroML: a language for describing data driven models of neurons and networks with a high degree of biological detail.. PLoS Comput Biol. 6:e1000815
- Djurfeldt M, Hjorth J, Eppler JM, Dudani N, Helias M, Potjans TC, Bhalla US, Diesmann M, Kotaleski JH and Ekeberg O (2010) Run-time interoperability between neuronal network simulators based on the MUSIC framework.. Neuroinformatics. 8:43–60
- Voges N and Perrinet L (2010) Phase space analysis of networks based on biologically realistic parameters.. J Physiol Paris. 104:51–60
- Ren Q, Kolwankar KM., Samal A and Jost J (2010) STDP-driven networks and the C. elegans neuronal network. Physica A: Statistical Mechanics and its Applications. 389:3900–3914
- Potjans W, Morrison A and Diesmann M (2010) Enabling functional neural circuit simulations with distributed computing of neuromodulated plasticity.. Front Comput Neurosci. 4:141
- Nordlie E, Tetzlaff T and Einevoll GT (2010) Rate Dynamics of Leaky Integrate-and-Fire Neurons with Strong Synapses.. Front Comput Neurosci. 4:149
- Nordlie E and Plesser HE (2010) Visualizing neuronal network connectivity with connectivity pattern tables.. Front Neuroinform. 3:39
- Mulas M, Massobrio P, Martinoia S and Chiappalone M (2010) A simulated neuro-robotic environment for bi-directional closed-loop experiments. SP Versita Paladyn. 1:179–186
- Manninen T, Hituri K, Kotaleski JH, Blackwell KT and Linne ML (2010) Postsynaptic signal transduction models for long-term potentiation and depression.. Front Comput Neurosci. 4:152
- Linaro D., Poggi T. and Storace M. (2010) Experimental bifurcation diagram of a circuit-implemented neuron model. Physics Letters A. 374:4589–4593
- Ince RA.A., Mazzoni A, Petersen RS. and Panzeri S (2010) Open Source Tools for the Information Theoretic Analysis of Neural Data. Frontiers in Neuroscience. 4:62
- Helias M, Deger M, Rotter S and Diesmann M (2010) Instantaneous non-linear processing by pulse-coupled threshold units.. PLoS Comput Biol. 6:-
- Helias M, Deger M, Diesmann M and Rotter S (2010) Equilibrium and Response Properties of the Integrate-and-Fire Neuron in Discrete Time.. Front Comput Neurosci. 3:29
- Hanuschkin A, Kunkel S, Helias M, Morrison A and Diesmann M (2010) A general and efficient method for incorporating precise spike times in globally time-driven simulations. Frontiers Research Foundation Frontiers in Neuroinformatics. 4:113
- Gollo LL., Mirasso C and Villa AE.P. (2010) Dynamic control for synchronization of separated cortical areas through thalamic relay. Neuroimage. 52:947–955
- Berger D, Borgelt C, Louis S, Morrison A and Grün S (2010) Efficient identification of assembly neurons within massively parallel spike trains.. Comput Intell Neurosci. Volume 2010:439648
- Marre O, Yger P, Davison AP and Frégnac Y (2009) Reliable recall of spontaneous activity patterns in cortical networks.. J Neurosci. 29:14596–14606
- Schrader S, Gewaltig MO, Körner U and Körner E (2009) Cortext: a columnar model of bottom-up and top-down processing in the neocortex.. Neural Netw. 22:1055–1070
- Kriener B, Helias M, Aertsen A and Rotter S (2009) Correlations in spiking neuronal networks with distance dependent connections.. J Comput Neurosci. 27:177–200
- Boustani SE, Marre O, Behuret S, Baudot P, Yger P, Bal T, Destexhe A and Fregnac Y (2009) Network-state modulation of power-law frequency-scaling in visual cortical neurons.. PLoS Comput Biol. 5:e1000519
- Goodman DFM and Brette R (2009) The brian simulator.. Front Neurosci. 3:192–197
- Nordlie E, Gewaltig MO and Plesser HE (2009) Towards reproducible descriptions of neuronal network models.. PLoS Comput Biol. 5:e1000456
- Plesser HE and Diesmann M (2009) Simplicity and efficiency of integrate-and-fire neuron models.. Neural Comput. 21:353–359
- Potjans W, Morrison A and Diesmann M (2009) A spiking neural network model of an actor-critic learning agent.. Neural Comput. 21:301–339
- Boustani SE and Destexhe A (2009) A Master Equation Formalism for Macroscopic Modeling of Asynchronous Irregular Activity States. Neural Comput. 21:46–100
- Pecevski D, Natschläger T and Schuch K (2009) PCSIM: A Parallel Simulation Environment for Neural Circuits Fully Integrated with Python.. Front Neuroinform. 3:11
- Kobayashi R, Tsubo Y and Shinomoto S (2009) Made-to-order spiking neuron model equipped with a multi-timescale adaptive threshold.. Front Comput Neurosci. 3:9
- Eppler J (2009) A Python interface to NEST. The Neuromorphic Engineer
- Einevoll GT. (2009) Sharing with Python. Front Neurosci.. 3:334–335
- Eichner H, Klug T and Borst A (2009) Neural simulations on multi-core architectures.. Front Neuroinform. 3:21
- Drewes R, Zou Q and Goodman PH. (2009) Brainlab: A Python Toolkit to Aid in the Design, Simulation, and Analysis of Spiking Neural Networks with the NeoCortical Simulator. Front Neuroinformatics.. 3:16
- Davison AP., Hines ML. and Muller E (2009) Trends in Programming Languages for Neuroscience Simulations. Front Neurosci.. 3:374–380
- Brüderle D, Müller E, Davison A, Muller E, Schemmel J and Meier K (2009) Establishing a novel modeling tool: a python-based interface for a neuromorphic hardware system.. Front Neuroinform. 3:17
- Bednar JA. (2009) Topographica: Building and Analyzing Map-Level Simulations from Python, C/C++, MATLAB, NEST, or NEURON Components. Frontiers in Neuroinformatics. 3:8
- Schrader S, Grün S, Diesmann M and Gerstein GL (2008) Detecting synfire chain activity using massively parallel spike train recording.. J Neurophysiol. 100:2165–2176
- Tetzlaff T, Rotter S, Stark E, Abeles M, Aertsen A and Diesmann M (2008) Dependence of neuronal correlations on filter characteristics and marginal spike train statistics.. Neural Comput. 20:2133–2184
- Kriener B, Tetzlaff T, Aertsen A, Diesmann M and Rotter S (2008) Correlations and population dynamics in cortical networks.. Neural Comput. 20:2185–2226
- Morrison A, Diesmann M and Gerstner W (2008) Phenomenological models of synaptic plasticity based on spike timing.. Biol Cybern. 98:459–478
- Kumar A, Rotter S and Aertsen A (2008) Conditions for propagating synchronous spiking and asynchronous firing rates in a cortical network model.. J Neurosci. 28:5268–5280
- Schutter ED (2008) Why are computational neuroscience and systems biology so separate?. PLoS Comput Biol. 4:e1000078
- Kumar A, Schrader S, Aertsen A and Rotter S (2008) The high-conductance state of cortical networks.. Neural Comput. 20:1–43
- Versace M, Ames H, Léveillé J, Fortenberry B and Gorchetchnikov A (2008) KInNeSS: a modular framework for computational neuroscience.. Neuroinformatics. 6:291–309
- Scorcioni R, Hamilton DJ. and Ascoli GA. (2008) Self-sustaining non-repetitive activity in a large scale neuronal-level model of the hippocampal circuit. Neural Networks. 21:1153–1163
- Meier R, Egert U, Aertsen A and Nawrot MP. (2008) FIND — A unified framework for neural data analysis. Neural Networks. 21:1085–1093
- Lefort S, Tomm C, Sarria J.C.F and Petersen CC.H. (2008) The Excitatory Neuronal Network of the C2 Barrel Column in Mouse Primary Somatosensory Cortex. Neuron. 10:1016
- Helias M, Rotter S, Gewaltig MO and Diesmann M (2008) Structural plasticity controlled by calcium based correlation detection. helias@bccn.uni-freiburg.de.. Front Comput Neurosci. 2:7
- Goodman D and Brette R (2008) Brian: a simulator for spiking neural networks in python.. Front Neuroinform. 2:5
- Goedeke S and Diesmann M (2008) The mechanism of synchronization in feed-forward neuronal networks. New Journal of Physics. 10:015007
- Eppler JM, Helias M, Muller E, Diesmann M and Gewaltig MO (2008) PyNEST: A Convenient Interface to the NEST Simulator.. Front Neuroinform. 2:12
- Djurfeldt M, Ekeberg O and Lansner A (2008) Large-scale modeling - a tool for conquering the complexity of the brain.. Front Neuroinform. 2:1
- Djurfeldt M., Lundqvist M., Johansson C., Rehn M., Ekeberg O. and Lansner A. (2008) Brain-scale simulation of the neocortex on the IBM Blue Gene L supercomputer. IBM Journal of Research and Development. 52:31–41
- Davison AP., Brüderle D, Eppler J, Kremkow J, Muller E, Pecevski D, Perrinet L and Yger P (2008) PyNN: A Common Interface for Neuronal Network Simulators.. Front. Neuroinform.. 2:11
- Bednar JA. (2008) Understanding Neural Maps with Topographica. Brains, Minds, and Media. 3
- Brette R, Rudolph M, Carnevale T, Hines M, Beeman D, Bower JM., Diesmann M, Morrison A, Goodman PH., Harris JFC, Zirpe M, Natschläger T, Pecevski D, Ermentrout B, Djurfeldt M, Lansner A, Rochel O, Vieville T, Muller E, Davison AP., El Boustani S and Destexhe A (2007) Simulation of networks of spiking neurons: a review of tools and strategies.. J. Comput. Neurosci.. 23:349–398
- Muller E, Buesing L, Schemmel J and Meier K (2007) Spike-frequency adapting neural ensembles: beyond mean adaptation and renewal theories.. Neural Comput. 19:2958–3010
- Morrison A, Straube S, Plesser HE and Diesmann M (2007) Exact subthreshold integration with continuous spike times in discrete-time neural network simulations. MIT Press One Rogers Street, Cambridge, MA 02142-1209, USA journals-info … Neural computation. 19:47–79
- Backofen R., Borrmannand H.-G., Deck W., Dedner A., Raedt L. D, Desch K., Diesmann M., Geier M., Greiner A., Hess W. R., Honerkamp J., Jankowski S., Krossing I., Liehr A. W., Karwath A., Klofkorn R., Pesche R., Potjans T., Rottger M. C., Schmidt-Thieme L., Schneider G., Voss B., Wiebelt B., Wienemann P. and Winterer V.-H. (2007) A Bottom-up approach to Grid-Computing at a University: the Black-Forest-Grid Initiative. Praxis der Informationsverarbeitung und Kommunikation. 29:81–87
- Meier R, Kumar A, Schulze-Bonhage A and Aertsen A (2007) Comparison of dynamical states of random networks with human EEG. Neurocomputing. 70:1843–1847
- Kremkow J, Kumar A, Rotter S and Aertsen A (2007) Emergence of population synchrony in a layered network of the cat visual cortex. Neurocomputing. 70:2069–2073
- Gürel T, Raedt LD and Rotter S (2007) Ranking neurons for mining structure-activity relations in biological neural networks: NeuronRank. Neurocomputing. 70:1897–1901
- Gleeson P, Steuber V and Silver R. A (2007) neuroConstruct: A Tool for Modeling Networks of Neurons in 3D Space. Neuron. 54:219–235
- Gewaltig MO and Diesmann M (2007) NEST:NEural Simulation Tool. Scholarpedia. 2:1430
- Cornelis H and Schutter ED (2007) Neurospaces:Towards automated model partitioning for parallel computers. Neurocomputing. 70:2117–2121
- Cannon RC., Gewaltig MO, Gleeson P, Bhalla US., Cornelis H, Hines ML., Howell FW., Muller E, Stiles JR., Wils S and De Schutter E (2007) Interoperability of Neuroscience Modeling Software: Current Status and Future Directions. Humana Press Inc Neuroinformatics. 5:127–138
- Mayor J and Gerstner W (2005) Signal buffering in random networks of spiking neurons: Microscopic versus macroscopic phenomena. American Physical Society Phys. Rev. E. 72:051906
- Morrison A, Mehring C, Geisel T, Aertsen A. D. and Diesmann M (2005) Advancing the boundaries of high-connectivity network simulation with distributed computing.. Neural Comput. 17:1776–1801
- Mayor J and Gerstner W (2005) Noise-enhanced computation in a model of a cortical column. Cognitive Neurosci. 16:1237–1240
- Kupper R, Gewaltig MO, Körner U and Körner E (2005) Spike-latency codes and the effect of saccades. Neurocomputing. 65–66:189–194
- Veredas F.J., Vico F.J. and Alonso J.M. (2004) A computational tool to simulate correlated activity in neural circuits. Journal of Neuroscience Methods. 136:23–32
- Eastridge BJ, Hamilton EC, O'Keefe GE, Rege RV, Valentine RJ, Jones DJ, Tesfay S and Thal ER (2003) Effect of sleep deprivation on the performance of simulated laparoscopic surgical skill.. Am J Surg. 186:169–174
- Mehring C, Hehl U, Kubo M, Diesmann M and Aertsen A (2003) Activity dynamics and propagation of synchronous spiking in locally connected random networks.. Biol Cybern. 88:395–408
- Aviel Y, Pavlov E., Abeles M and Horn D (2003) Synfire Chain in a Balanced Network. Neural Computation. 15:1321–1340
- Gewaltig MO, Richter A and Kupper R (2002) BLISS: towards the simulation of brain-like systems. Neurocomputing. 44-46:805–810
- Diesmann M and Gewaltig MO (2001) NEST: An Environment for Neural Systems Simulations. Forschung und wisschenschaftliches Rechnen, Beiträge zum Heinz-Billing-Preis. 58:43-70
- Diesmann M, Gewaltig MO and Aertsen A (1999) Stable propagation of synchronous spiking in cortical neural networks. Nature. 402:529–533
- Diesmann M., Gewaltig M.-O. and Aertsen A. (1995) SYNOD: an Environment for Neural Systems Simulations. Language Interface and Tutorial. Weizmann Institute of Science, technical report. GC-AA-/95-3
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