Data-driven multiscale computational models of cortical and subcortical regions
S Ramaswamy - Current opinion in neurobiology, 2024 - Elsevier
Data-driven computational models of neurons, synapses, microcircuits, and mesocircuits
have become essential tools in modern brain research. The goal of these multiscale models …
have become essential tools in modern brain research. The goal of these multiscale models …
[HTML][HTML] The quest for multiscale brain modeling
E D'Angelo, V Jirsa - Trends in neurosciences, 2022 - cell.com
Addressing the multiscale organization of the brain, which is fundamental to the dynamic
repertoire of the organ, remains challenging. In principle, it should be possible to model …
repertoire of the organ, remains challenging. In principle, it should be possible to model …
Modeling and simulation of neocortical micro-and mesocircuitry. Part II: Physiology and experimentation
In recent years, large-scale computational models of the cortex have emerged as a powerful
way to study the multi-scale mechanisms of neural processing. However, due to …
way to study the multi-scale mechanisms of neural processing. However, due to …
Brain Modeling ToolKit: An open source software suite for multiscale modeling of brain circuits
Experimental studies in neuroscience are producing data at a rapidly increasing rate,
providing exciting opportunities and formidable challenges to existing theoretical and …
providing exciting opportunities and formidable challenges to existing theoretical and …
NetPyNE, a tool for data-driven multiscale modeling of brain circuits
Biophysical modeling of neuronal networks helps to integrate and interpret rapidly growing
and disparate experimental datasets at multiple scales. The NetPyNE tool (www. netpyne …
and disparate experimental datasets at multiple scales. The NetPyNE tool (www. netpyne …
Challenges in reproducibility, replicability, and comparability of computational models and tools for neuronal and glial networks, cells, and subcellular structures
T Manninen, J Aćimović, R Havela… - Frontiers in …, 2018 - frontiersin.org
The possibility to replicate and reproduce published research results is one of the biggest
challenges in all areas of science. In computational neuroscience, there are thousands of …
challenges in all areas of science. In computational neuroscience, there are thousands of …
Bringing anatomical information into neuronal network models
SJ van Albada, A Morales-Gregorio… - … modelling of the brain …, 2021 - Springer
For constructing neuronal network models computational neuroscientists have access to
wide-ranging anatomical data that nevertheless tend to cover only a fraction of the …
wide-ranging anatomical data that nevertheless tend to cover only a fraction of the …
[HTML][HTML] Open source brain: a collaborative resource for visualizing, analyzing, simulating, and developing standardized models of neurons and circuits
P Gleeson, M Cantarelli, B Marin, A Quintana… - Neuron, 2019 - cell.com
Computational models are powerful tools for exploring the properties of complex biological
systems. In neuroscience, data-driven models of neural circuits that span multiple scales are …
systems. In neuroscience, data-driven models of neural circuits that span multiple scales are …
Brain signal predictions from multi-scale networks using a linearized framework
Simulations of neural activity at different levels of detail are ubiquitous in modern
neurosciences, aiding the interpretation of experimental data and underlying neural …
neurosciences, aiding the interpretation of experimental data and underlying neural …
Computational models in the age of large datasets
Highlights•Computational models will prove increasingly useful for understanding large
datasets.•Substantial challenges exist for fitting detailed models to data.•Conceptual and …
datasets.•Substantial challenges exist for fitting detailed models to data.•Conceptual and …