NEST Simulator

713 found.

Wang F, Kulkarni S, Theilman B, Rothganger F, Schuman C, Lim SH and Aimone JB (2024) Scaling neural simulations in STACS. IOP Publishing Neuromorphic Computing and Engineering. 4:024002 doi
Stanojevic A, Woźniak S, Bellec G, Cherubini G, Pantazi A and Gerstner W (2023) An exact mapping from ReLU networks to spiking neural networks. Elsevier BV Neural Networks. 168:74–88 doi
Kuniyoshi Y, Kuriyama R, Omura S, Gutierrez CE, Sun Z, Feldotto B, Albanese U, Knoll AC., Yamada T, Hirayama T, Morin FO., Igarashi J, Doya K and Yamazaki T (2023) Embodied bidirectional simulation of a spiking cortico-basal ganglia-cerebellar-thalamic brain model and a mouse musculoskeletal body model distributed across computers including the supercomputer Fugaku. Frontiers Media SA Frontiers in Neurorobotics. 17 doi
Fang W, Chen Y, Ding J, Yu Z, Masquelier T, Chen D, Huang L, Zhou H, Li G and Tian Y (2023) SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence. American Association for the Advancement of Science (AAAS) Science Advances. 9 doi
Pham MD, D'Angiulli A, Dehnavi MM and Chhabra R (2023) From Brain Models to Robotic Embodied Cognition: How Does Biological Plausibility Inform Neuromorphic Systems?. MDPI AG Brain Sciences. 13:1316 doi
Knowles TC., Summerton AG., Whiting JG. H. and Pearson MJ. (2023) Ring Attractors as the Basis of a Biomimetic Navigation System. MDPI AG Biomimetics. 8:399 doi
Trinh AT, Girardi-Schappo M, Béïque JC, Longtin A and Maler L (2023) Adaptive spike threshold dynamics associated with sparse spiking of hilar mossy cells are captured by a simple model. Wiley The Journal of Physiology. 601:4397–4422 doi
Qu P, Lin H, Pang M, Liu X, Zheng W and Zhang Y (2023) ENLARGE: An Efficient SNN Simulation Framework on GPU Clusters. Institute of Electrical and Electronics Engineers (IEEE) IEEE Transactions on Parallel and Distributed Systems. 34:2529–2540 doi
Gruel A, Hareb D, Grimaldi A, Martinet J, Perrinet L, Linares-Barranco B and Serrano-Gotarredona T (2023) Stakes of neuromorphic foveation: a promising future for embedded event cameras. Springer Science and Business Media LLC Biological Cybernetics. 117:389–406 doi
Bouhadjar Y, Siegel S, Tetzlaff T, Diesmann M, Waser R and Wouters DJ (2023) Sequence learning in a spiking neuronal network with memristive synapses. IOP Publishing Neuromorphic Computing and Engineering. 3:034014 doi
Sønstebø JL., Brunborg H and Lepperød ME (2023) Spikeometric: Linear Non-Linear Cascade Spiking Neural Networks with Pytorch Geometric. The Open Journal Journal of Open Source Software. 8:5451 doi
Golosio B, Villamar J, Tiddia G, Pastorelli E, Stapmanns J, Fanti V, Paolucci PS, Morrison A and Senk J (2023) Runtime Construction of Large-Scale Spiking Neuronal Network Models on GPU Devices. MDPI AG Applied Sciences. 13:9598 doi
Angelidis E (2023) A perspective on large-scale simulation as an enabler for novel biorobotics applications. Frontiers Media SA Frontiers in Robotics and AI. 10 doi
Cabrera-Álvarez J, Sánchez-Claros J, Carrasco-Gómez M, del Cerro-León A, Gómez-Ariza CJ., Maestú F, Mirasso CR. and Susi G (2023) Understanding the effects of cortical gyrification in tACS: insights from experiments and computational models. Frontiers Media SA Frontiers in Neuroscience. 17 doi
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 doi
Wang Z, Yu N and Essaf F (2023) A soma-synapses neuron model and FPGA implementation. Wiley Concurrency and Computation: Practice and Experience doi
Wu Z, Shen Y, Zhang J, Liang H, Zhao R, Li H, Xiong J, Zhang X and Chua Y (2023) BIDL: a brain-inspired deep learning framework for spatiotemporal processing. Frontiers Media SA Frontiers in Neuroscience. 17 doi
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 doi
Zajzon B, Duarte R and Morrison A (2023) Toward reproducible models of sequence learning: replication and analysis of a modular spiking network with reward-based learning. Frontiers Media SA Frontiers in Integrative Neuroscience. 17 doi
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 doi
Frenkel C, Bol D and Indiveri G (2023) Bottom-Up and Top-Down Approaches for the Design of Neuromorphic Processing Systems: Tradeoffs and Synergies Between Natural and Artificial Intelligence. Institute of Electrical and Electronics Engineers (IEEE) Proceedings of the IEEE. 111:623–652 doi
Giacopelli G, Migliore M and Tegolo D (2023) NeuronAlg: An Innovative Neuronal Computational Model for Immunofluorescence Image Segmentation. MDPI AG Sensors. 23:4598 doi
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 doi
Bouhadjar Y, Wouters DJ., Diesmann M and Tetzlaff T (2023) Coherent noise enables probabilistic sequence replay in spiking neuronal networks. Public Library of Science (PLoS) PLOS Computational Biology. 19:e1010989 doi
Siegel S, Bouhadjar Y, Tetzlaff T, Waser R, Dittmann R and Wouters DJ (2023) System model of neuromorphic sequence learning on a memristive crossbar array. IOP Publishing Neuromorphic Computing and Engineering. 3:024002 doi
Schmid D, Oess T and Neumann H (2023) Listen to the Brain-Auditory Sound Source Localization in Neuromorphic Computing Architectures. MDPI AG Sensors. 23:4451 doi
Cerina M, Piastra MC and Frega M (2023) The potential of in vitro neuronal networks cultured on micro electrode arrays for biomedical research. IOP Publishing Progress in Biomedical Engineering. 5:032002 doi
Ghazinouri B, Nejad MM and Cheng S (2023) Navigation and the efficiency of spatial coding: insights from closed-loop simulations. Springer Science and Business Media LLC Brain Structure and Function doi
Kauth K, Stadtmann T, Sobhani V and Gemmeke T (2023) neuroAIx-Framework: design of future neuroscience simulation systems exhibiting execution of the cortical microcircuit model 20x faster than biological real-time. Frontiers Media SA Frontiers in Computational Neuroscience. 17 doi
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 doi
Chlasta K, Sochaczewski P, Wójcik GM. and Krejtz I (2023) Neural simulation pipeline: Enabling container-based simulations on-premise and in public clouds. Frontiers Media SA Frontiers in Neuroinformatics. 17 doi
Yang Y, Hosseini MJM, Kruger W and Nawrocki RA. (2023) Modular Modeling of Analog Organic Neuromorphic Circuits: Toward Prototyping of Hardware-Level Spiking Neural Networks. Institute of Electrical and Electronics Engineers (IEEE) IEEE Transactions on Circuits and Systems I: Regular Papers. 70:1161–1174 doi
Gandolfi D, Mapelli J, Solinas SM. G., Triebkorn P, D’Angelo E, Jirsa V and Migliore M (2023) Full-scale scaffold model of the human hippocampus CA1 area. Springer Science and Business Media LLC Nature Computational Science. 3:264–276 doi
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 doi
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 doi
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 doi
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 doi
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 doi
Zhang H and Vargas DV (2023) A Survey on Reservoir Computing and its Interdisciplinary Applications Beyond Traditional Machine Learning. Institute of Electrical and Electronics Engineers (IEEE) IEEE Access. 11:81033–81070 doi
Shirsavar SR, Vahabie AH and Dehaqani MRA. (2023) Models developed for spiking neural networks. Elsevier BV MethodsX. 10:102157 doi
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 doi
Wei W and Wang X (2022) Ion-specific effects in confined nanochannels and neural network. Wiley Aggregate. 4:e302 doi
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 doi
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 doi
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 doi
D'Angelo E and Jirsa V (2022) The quest for multiscale brain modeling. Elsevier BV Trends in Neurosciences. 45:777–790 doi
Griffiths JD., Shen K and Gleeson P (2022) Editorial: Neuroinformatics of large-scale brain modelling. Frontiers Media SA Frontiers in Neuroinformatics. 16:1043732 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
Yamazaki K, Vo-Ho VK, Bulsara D and Le N (2022) Spiking Neural Networks and Their Applications: A Review. Brain Sciences. 12:863 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
Peres L and Rhodes O (2022) Parallelization of Neural Processing on Neuromorphic Hardware. Frontiers in Neuroscience. 16:867027 doi
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 doi
Ostrau C, Klarhorst C, Thies M and Rückert U (2022) Benchmarking Neuromorphic Hardware and Its Energy Expenditure. Frontiers in Neuroscience. 16:873935 doi
Osborne H and de Kamps M (2022) A numerical population density technique for N-dimensional neuron models. Frontiers in Neuroinformatics. 16:883796 doi
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 doi
Maith O, Dinkelbach HÜ, Baladron J, Vitay J and Hamker FH. (2022) BOLD Monitoring in the Neural Simulator ANNarchy. Frontiers in Neuroinformatics. 16:790966 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
Kon M and Francis G (2022) Cortical circuits for top-down control of perceptual grouping. Neural Networks. 151:190-210 doi
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 doi
Huang C, Zeldenrust F and Celikel T (2022) Cortical Representation of Touch in Silico. Neuroinformatics:1-27 doi
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 doi
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 doi
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 doi
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 doi
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 doi
Feldotto B, Morin FO. and Knoll A (2022) The Neurorobotics Platform Robot Designer: Modeling Morphologies for Embodied Learning Experiments. Frontiers in Neurorobotics. 16:856727 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
Schuman CD., Plank JS., Parsa M, Kulkarni SR., Skuda N and Mitchell J. P (2021) A Software Framework for Comparing Training Approaches for Spiking Neuromorphic Systems. , 2021 International Joint Conference on Neural Networks (IJCNN). IEEE doi
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 doi
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 doi
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 doi
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 doi
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 doi
Schuman CD., Kay B, Date P, Kannan R, Sao P and Potok TE. (2021) Sparse Binary Matrix-Vector Multiplication on Neuromorphic Computers. , 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). IEEE doi
Elbez H, Benhaoua MK, Devienne P and Boulet P (2021) VS2N : Interactive Dynamic Visualization and Analysis Tool for Spiking Neural Networks. , 2021 International Conference on Content-Based Multimedia Indexing (CBMI). IEEE doi
Podobas A, Svedin M, Chien SW. D., Peng IB., Ravichandran NB, Herman P, Lansner A and Markidis S (2021) StreamBrain. , Proceedings of the 11th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies. ACM doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
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 doi
Yin Y (2021) RANDOM NEURAL NETWORK METHODS AND DEEP LEARNING. Cambridge University Press (CUP) Probability in the Engineering and Informational Sciences:1–31 doi
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 doi
Wardak A and Gong P (2021) Fractional diffusion theory of balanced heterogeneous neural networks. American Physical Society (APS) Physical Review Research. 3:013083 doi
Albada SJ. van, Pronold J, Meegen Avan and Diesmann M (2021) Usage and Scaling of an Open-Source Spiking Multi-Area Model of Monkey Cortex. Springer International Publishing:47–59 doi
Yin Y (2021) RANDOM NEURAL NETWORK METHODS AND DEEP LEARNING. Probability in the Engineering and Informational Sciences. 35:6-36 doi
Yamazaki T, Igarashi J and Yamaura H (2021) Human-scale brain simulation via supercomputer: a case study on the cerebellum. Neuroscience. 462:235-246 doi
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. 10:e60936 doi
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