Moritz Helias

发表

Structural Plasticity Controlled by Calcium Based Correlation Detection

Moritz Helias, Stefan Rotter, Marc-Oliver Gewaltig, 2008, Frontiers Comput. Neurosci..

A model for correlation detection based on Ca2+ concentration in spines

Moritz Helias, Stefan Rotter, Markus Diesmann, 2007, BMC Neuroscience.

Efficient Communication in Distributed Simulations of Spiking Neuronal Networks With Gap Junctions

Moritz Helias, Susanne Kunkel, Jakob Jordan, 2020, Frontiers in Neuroinformatics.

Neuroinformatics Original Research Article Pynest: a Convenient Interface to the Nest Simulator

Moritz Helias, Marc-Oliver Gewaltig, Markus Diesmann, 2022 .

Neurons hear their echo

Moritz Helias, Markus Diesmann, Tom Tetzlaff, 2010, BMC Neuroscience.

Correlations in spiking neuronal networks with distance dependent connections

Moritz Helias, Stefan Rotter, Ad Aertsen, 2009, Journal of Computational Neuroscience.

Functional methods for disordered neural networks

Moritz Helias, Sven Goedeke, Jannis Schuecker, 2016 .

Taming the model zoo: a unified view on correlations in recurrent networks

Moritz Helias, Markus Diesmann, Tom Tetzlaff, 2012, BMC Neuroscience.

Perfect Detection of Spikes in the Linear Sub-threshold Dynamics of Point Neurons

Edoardo Di Napoli, Moritz Helias, Markus Diesmann, 2018, Front. Neuroinform..

NEST 2.8.0

Alexander Peyser, Wolfram Schenck, Moritz Helias, 2015 .

Spectral properties of excitable systems subject to colored noise

Moritz Helias, Markus Diesmann, Jannis Schuecker, 2014 .

Comparison of methods to calculate exact spike times in integrate-and-fire neurons with exponential currents

Moritz Helias, Markus Diesmann, Abigail Morrison, 2008, BMC Neuroscience.

Equilibrium and response properties of the integrate-and-fi re neuron in discrete time

Moritz Helias, Stefan Rotter, Markus Diesmann, 2022 .

Supercomputers Ready for Use as Discovery Machines for Neuroscience

Tomoki Fukai, Shin Ishii, Moritz Helias, 2012, Front. Neuroinform..

Capacity of the covariance perceptron pdf

Matthieu Gilson, Moritz Helias, David Dahmen, 2019, ArXiv.

Noise Suppression and Surplus Synchrony by Coincidence Detection

Sonja Grün, Moritz Helias, Markus Diesmann, 2012, PLoS Comput. Biol..

The transfer function of the LIF model: from white to filtered noise

Moritz Helias, Markus Diesmann, Jannis Schuecker, 2014, BMC Neuroscience.

Influence of different types of downscaling on a cortical microcircuit model

Moritz Helias, Markus Diesmann, Sven Schrader, 2013, BMC Neuroscience.

Instantaneous Non-Linear Processing by Pulse-Coupled Threshold Units

Moritz Helias, Stefan Rotter, Markus Diesmann, 2010, PLoS Comput. Biol..

NEST 2.10.0

Alexander Peyser, Moritz Helias, Mikael Djurfeldt, 2015 .

Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers

Mitsuhisa Sato, Moritz Helias, Markus Diesmann, 2018, Front. Neuroinform..

Event-based update of synapses in voltage-based learning rules

Moritz Helias, Markus Diesmann, Matthias Bolten, 2020 .

Cortical correlations support optimal sequence memory

Moritz Helias, Sven Goedeke, Jannis Schuecker, 2017 .

The dynamics of error processing in the human brain as reflected by high-gamma activity in noninvasive and intracranial EEG

Wolfram Burgard, Tonio Ball, Pavel Krsek, 2017, NeuroImage.

The Correlation Structure of Local Neuronal Networks Intrinsically Results from Recurrent Dynamics

Moritz Helias, Markus Diesmann, Tom Tetzlaff, 2013, PLoS Comput. Biol..

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator

Moritz Helias, Markus Diesmann, Matthias Bolten, 2016, Front. Neuroinform..

Second type of criticality in the brain uncovers rich multiple-neuron dynamics

Sonja Grün, Moritz Helias, Markus Diesmann, 2016, Proceedings of the National Academy of Sciences.

Run-Time Interoperability Between Neuronal Network Simulators Based on the MUSIC Framework

Örjan Ekeberg, Moritz Helias, Markus Diesmann, 2010, Neuroinformatics.

Towards a unified theory of correlations in recurrent neural networks

Moritz Helias, Markus Diesmann, Tom Tetzlaff, 2011, BMC Neuroscience.

Decorrelation of low-frequency neural activity by inhibitory feedback

Moritz Helias, Markus Diesmann, Tom Tetzlaff, 2010, BMC Neuroscience.

Correlation transmission of spiking neurons is boosted by synchronous input

Sonja Grün, Moritz Helias, Markus Diesmann, 2011, BMC Neuroscience.

Bistability, non-ergodicity, and inhibition in pairwise maximum-entropy models

Sonja Grün, Moritz Helias, Vahid Rostami, 2016, PLoS Comput. Biol..

The covariance perceptron: A new paradigm for classification and processing of time series in recurrent neuronal networks

Matthieu Gilson, Andrea Insabato, Moritz Helias, 2020, PLoS computational biology.

Strong and localized recurrence controls dimensionality of neural activity across brain areas

Eric Shea-Brown, Moritz Helias, David Dahmen, 2020, bioRxiv.

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 1

Simona Cocco, Rémi Monasson, Robert Chen, 2017, BMC Neuroscience.

Effective neuronal refractoriness dominates the statistics of superimposed spike trains

Moritz Helias, Stefan Rotter, Moritz Deger, 2011, BMC Neuroscience.

Decorrelation of Neural-Network Activity by Inhibitory Feedback

Moritz Helias, Markus Diesmann, Gaute T. Einevoll, 2012, PLoS Comput. Biol..

Transition to chaos and short-term memory in driven random neural networks

Moritz Helias, Jannis Schücker, Sven Goedeke, 2016, IEEE CNS 2016.

Transition to chaos in random neural networks in the presence of noise

Moritz Helias, Sven Goedeke, Jannis Schücker, 2016 .

A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations

Moritz Helias, Markus Diesmann, Jun Igarashi, 2015, Front. Neuroinform..

Conditions for wave trains in spiking neural networks

Moritz Helias, Markus Diesmann, Tom Tetzlaff, 2018, Physical Review Research.

Statistical properties of superimposed stationary spike trains

Moritz Helias, Stefan Rotter, Moritz Deger, 2011, Journal of Computational Neuroscience.

The Poisson process with dead time captures important statistical features of neural activity

Moritz Helias, Stefan Rotter, Moritz Deger, 2009, BMC Neuroscience.

Spiking network simulation code for petascale computers

Tomoki Fukai, Shin Ishii, Moritz Helias, 2014, Front. Neuroinform..

20 years of NEST: a mature brain simulator

Moritz Helias, Marc-Oliver Gewaltig, Markus Diesmann, 2013 .

Including Gap Junctions into Distributed Neuronal Network Simulations

Brian J. N. Wylie, Moritz Helias, Markus Diesmann, 2015, BrainComp.

How pattern formation in ring networks of excitatory and inhibitory spiking neurons depends on the input current regime

Moritz Helias, Markus Diesmann, Gaute T. Einevoll, 2013, Front. Comput. Neurosci..

Spike-Timing Dependence of Structural Plasticity Explains Cooperative Synapse Formation in the Neocortex

Moritz Helias, Stefan Rotter, Markus Diesmann, 2012, PLoS Comput. Biol..

Transient Chaotic Dimensionality Expansion by Recurrent Networks

Moritz Helias, Tobias Kuhn, David Dahmen, 2020, 2002.11006.

ASSET: Analysis of Sequences of Synchronous Events in Massively Parallel Spike Trains

Sonja Grün, Moritz Helias, Michael Denker, 2016, PLoS Comput. Biol..

Data from: Fundamental activity constraints lead to specific interpretations of the connectome

Moritz Helias, Markus Diesmann, Sacha J. van Albada, 2019 .

Modeling the calcium spike as a threshold triggered fixed waveform for synchronous inputs in the fluctuation regime

Yansong Chua, Moritz Helias, Abigail Morrison, 2015, Front. Comput. Neurosci..

Two types of criticality in the brain

Moritz Helias, Markus Diesmann, David Dahmen, 2017 .

Locking of correlated neural activity to ongoing oscillations

Moritz Helias, Tobias Kühn, M. Helias, 2016, PLoS Comput. Biol..

Perfect Detection of Spikes in the Linear Sub-threshold Dynamics of Point Neurons

Edoardo Di Napoli, Moritz Helias, Markus Diesmann, 2017, Front. Neuroinform..

Recurrence and external sources differentially shape network correlations

Moritz Helias, Markus Diesmann, Tom Tetzlaff, 2013, BMC Neuroscience.

The non-linear response of the integrate-and-fire neuron to finite synaptic potentials

Moritz Helias, Stefan Rotter, Markus Diesmann, 2009, Neuroscience Research.

The covariance perceptron: A new paradigm for classification and processing of time series in recurrent neuronal networks

Matthieu Gilson, Moritz Helias, Andrea Insabato, 2019, bioRxiv.

Corrigendum: Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers

Mitsuhisa Sato, Moritz Helias, Markus Diesmann, 2018, Front. Neuroinform..

Fundamental Activity Constraints Lead to Specific Interpretations of the Connectome

Moritz Helias, Markus Diesmann, Maximilian Schmidt, 2015, PLoS Comput. Biol..

Python scripts for analysis and plotting

Moritz Helias, Markus Diesmann, Junji Ito, 2015 .

From laptops to supercomputers: a single highly scalable code base for spiking neuronal network simulations

Tomoki Fukai, Shin Ishii, Moritz Helias, 2013, BMC Neuroscience.

Computational Neuroscience: Mathematical and Statistical Perspectives.

Sonja Grün, Tomoki Fukai, Eric Shea-Brown, 2018, Annual review of statistics and its application.

Optimal Sequence Memory in Driven Random Networks

Moritz Helias, Jannis Schuecker, Sven Goedeke, 2016, Physical Review X.

Finite Post Synaptic Potentials Cause a Fast Neuronal Response

Moritz Helias, Stefan Rotter, Markus Diesmann, 2010, Front. Neurosci..

Detection of threshold crossings in the leaky integrate-and-fire neuron model with $\alpha$-shaped post-synaptic currents in time-driven simulations

Moritz Helias, Markus Diesmann, Jeyashree Krishnan, 2014 .

Identifying Anatomical Origins of Coexisting Oscillations in the Cortical Microcircuit

Moritz Helias, Markus Diesmann, Hannah Bos, 2015, PLoS Comput. Biol..

Fail-safe detection of threshold crossings of linear integrate-and-fire neuron models in time-driven simulations

Moritz Helias, Markus Diesmann, Abigail Morrison, 2011, BMC Neuroscience.

Neuroinformatics Original Research Article a General and Efficient Method for Incorporating Precise Spike times in Globally Time-driven Simulations

Moritz Helias, Markus Diesmann, Abigail Morrison, 2010 .

Supercomputer simulations of spiking neuronal networks

Moritz Helias, Markus Diesmann, Abigail Morrison, 2014 .

Unfolding recurrence by Green's functions for optimized reservoir computing

Matthieu Gilson, Moritz Helias, Holger Rauhut, 2020, NeurIPS.

NEST 5g: a simulation kernel for the exascale

Moritz Helias, Markus Diesmann, Abigail Morrison, 2016 .

Moritz Helias, David Dahmen, Hannah Bos, 2015, 1512.01073.

Inferring random network parameters from continuous-time trajectories

Moritz Helias, Tobias Kühn, Alexander van Meegen, 2020 .

Scalability of Asynchronous Networks Is Limited by One-to-One Mapping between Effective Connectivity and Correlations

Moritz Helias, Markus Diesmann, Sacha Jennifer van Albada, 2014, PLoS Comput. Biol..

A unified view on weakly correlated recurrent networks

Moritz Helias, Markus Diesmann, Tom Tetzlaff, 2013, Front. Comput. Neurosci..

Limits to the scalability of cortical network models

Moritz Helias, Markus Diesmann, Sacha J van Albada, 2015, BMC Neuroscience.

Event-Based Update of Synapses in Voltage-Based Learning Rules

Moritz Helias, Markus Diesmann, Matthias Bolten, 2021, Frontiers in Neuroinformatics.

Unified Field Theory for Deep and Recurrent Neural Networks

Moritz Helias, David Dahmen, Alexander van Meegen, 2021 .

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Moritz Helias, Stefan Rotter, Markus Diesmann, 2010 .

of Statistics and Its Application Computational Neuroscience : Mathematical and Statistical Perspectives

Emery N. Brown, Sonja Grün, Tomoki Fukai, 2018 .

Statistical Field Theory for Neural Networks

Moritz Helias, David Dahmen, M. Helias, 2019, Lecture Notes in Physics.

Echoes in correlated neural systems

Moritz Helias, Markus Diesmann, Tom Tetzlaff, 2012, 1207.0298.

Self-consistent formulations for stochastic nonlinear neuronal dynamics.

Moritz Helias, Thomas Luu, Carsten Honerkamp, 2018, Physical review. E.

Modulated escape from a metastable state driven by colored noise.

Moritz Helias, Markus Diesmann, Jannis Schuecker, 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 2

Minoru Asada, Anders M. Dale, Anna Devor, 2017, BMC Neuroscience.

Nonequilibrium dynamics of stochastic point processes with refractoriness.

Moritz Helias, Stefan Rotter, Moritz Deger, 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

Long-range coordination patterns in cortex change with behavioral context

Sonja Grün, Moritz Helias, Markus Diesmann, 2020, bioRxiv.

Invariance of covariances arises out of noise

Moritz Helias, Markus Diesmann, Tom Tetzlaff, 2013 .

The correlation structure of local cortical networks intrinsically results from recurrent dynamics

Moritz Helias, Markus Diesmann, Tom Tetzlaff, 2013 .

Noise dynamically suppresses chaos in neural networks

Moritz Helias, Sven Goedeke, Jannis Schuecker, 2016 .

Distributions of covariances as a window into the operational regime of neuronal networks

Moritz Helias, Markus Diesmann, David Dahmen, 2016 .

The perfect integrator driven by Poisson input and its approximation in the diffusion limit

Moritz Helias, Stefan Rotter, Markus Diesmann, 2010 .