| human | Q5 |
| P973 | described at URL | https://mila.quebec/en/person/eilifmuller/ |
| P6178 | Dimensions author ID | 01135321707.01 |
| P1960 | Google Scholar author ID | r4-NZhwAAAAJ |
| P856 | official website | http://abl-lab.org/ |
| P496 | ORCID iD | 0000-0003-4309-8266 |
| P1153 | Scopus author ID | 22635721300 |
| P2002 | X username | NeuralEnsemble |
| P1416 | affiliation | Mila | Q67182995 |
| P108 | employer | Université de Montréal | Q392189 |
| P101 | field of work | neuroscience | Q207011 |
| P106 | occupation | researcher | Q1650915 |
| assistant professor | Q5669847 | ||
| P21 | sex or gender | male | Q6581097 |
| Q28596987 | 25th Annual Computational Neuroscience Meeting: CNS-2016 |
| Q45879038 | 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3. |
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| Q51551273 | Adaptation reduces variability of the neuronal population code. |
| Q36135746 | An algorithm to predict the connectome of neural microcircuits |
| Q57988812 | An integration layer for neural simulation: PyNN in the software forest |
| Q36067212 | BluePyOpt: Leveraging Open Source Software and Cloud Infrastructure to Optimise Model Parameters in Neuroscience |
| Q41908415 | Cell-type specific modulation of neocortical UP and DOWN states |
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| Q33475651 | Establishing a novel modeling tool: a python-based interface for a neuromorphic hardware system |
| Q91081414 | Estimating the Readily-Releasable Vesicle Pool Size at Synaptic Connections in the Neocortex |
| Q37126357 | From Neuron Biophysics to Orientation Selectivity in Electrically Coupled Networks of Neocortical L2/3 Large Basket Cells |
| Q108126728 | HippoUnit: A software tool for the automated testing and systematic comparison of detailed models of hippocampal neurons based on electrophysiological data |
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| Q33406510 | NEURON and Python |
| Q30653792 | Network-timing-dependent plasticity |
| Q57988172 | NeuralEnsemble.Org: Unifying neural simulators in Python to ease the model complexity bottleneck |
| Q46072860 | NineML: the network interchange for neuroscience modeling language |
| Q46524866 | Non-renewal Markov models for spike-frequency adapting neural ensembles. |
| Q21129072 | PyNEST: A Convenient Interface to the NEST Simulator |
| Q33405758 | PyNN: A Common Interface for Neuronal Network Simulators |
| Q46548479 | PyNN: towards a universal neural simulator API in Python |
| Q35404725 | Python in neuroscience |
| Q40320870 | Reconstruction and Simulation of Neocortical Microcircuitry. |
| Q38743899 | Rich cell-type-specific network topology in neocortical microcircuitry. |
| Q30485903 | Simulation of networks of spiking neurons: a review of tools and strategies |
| Q47837112 | Spike-frequency adapting neural ensembles: beyond mean adaptation and renewal theories |
| Q89857216 | The SONATA data format for efficient description of large-scale network models |
| Q36135754 | The neocortical microcircuit collaboration portal: a resource for rat somatosensory cortex |
| Q58730626 | The physiological variability of channel density in hippocampal CA1 pyramidal cells and interneurons explored using a unified data-driven modeling workflow |
| Q47979342 | Timed Synaptic Inhibition Shapes NMDA Spikes, Influencing Local Dendritic Processing and Global I/O Properties of Cortical Neurons |
| Q33536431 | Trends in programming languages for neuroscience simulations |
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