Sacha J. van Albada

Orcid: 0000-0003-0682-4855

According to our database1, Sacha J. van Albada authored at least 15 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A method for the ethical analysis of brain-inspired AI.
Artif. Intell. Rev., June, 2024

2022
Connectivity concepts in neuronal network modeling.
PLoS Comput. Biol., September, 2022

Fast Simulation of a Multi-Area Spiking Network Model of Macaque Cortex on an MPI-GPU Cluster.
Frontiers Neuroinformatics, August, 2022

Cortical oscillations support sampling-based computations in spiking neural networks.
PLoS Comput. Biol., 2022

Phenomenological modeling of diverse and heterogeneous synaptic dynamics at natural density.
CoRR, 2022

2021
Editorial: Advances in Computational Neuroscience.
Frontiers Comput. Neurosci., 2021

2019
Usage and Scaling of an Open-Source Spiking Multi-Area Model of Monkey Cortex.
Proceedings of the Brain-Inspired Computing - 4th International Workshop, 2019

2018
A multi-scale layer-resolved spiking network model of resting-state dynamics in macaque visual cortical areas.
PLoS Comput. Biol., 2018

Criteria on Balance, Stability, and Excitability in Cortical Networks for Constraining Computational Models.
Frontiers Comput. Neurosci., 2018

2017
Fundamental Activity Constraints Lead to Specific Interpretations of the Connectome.
PLoS Comput. Biol., 2017

2016
A Collaborative Simulation-Analysis Workflow for Computational Neuroscience Using HPC.
Proceedings of the High-Performance Scientific Computing, 2016

2015
Scalability of Asynchronous Networks Is Limited by One-to-One Mapping between Effective Connectivity and Correlations.
PLoS Comput. Biol., 2015

2013
Cortical information flow in Parkinson's disease: a composite network/field model.
Frontiers Comput. Neurosci., 2013

Integrating Brain Structure and Dynamics on Supercomputers.
Proceedings of the Brain-Inspired Computing - International Workshop, 2013

VisNEST - Interactive analysis of neural activity data.
Proceedings of the IEEE Symposium on Biological Data Visualization, 2013


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