Large-scale model of mammalian thalamocortical systems

By Eugene M. Izhikevich, Gerald M. Edelman. Proceedings of the National Academy of Sciences of the United States of America, 2008

1,081 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/b72123d8e2f70920d60a624082e090a4beb56251

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cellular and Molecular Neuroscience

1. Olaf Sporns
2. Gustavo Deco
3. S. Furber
4. Morten L. Kringelbach
5. Viktor Jirsa
6. J. Krichmar
7. Filip Ponulak
8. Andrzej J. Kasinski

In Cognitive Neuroscience

1. Olaf Sporns
2. Gustavo Deco
3. Morten L. Kringelbach
4. Viktor Jirsa
5. Joana Cabral
6. E. Bullmore
7. Anthony Randal McIntosh
8. Karl J. Friston

In Radiology, Nuclear Medicine and Imaging

1. Olaf Sporns
2. Gustavo Deco
3. Viktor Jirsa
4. Morten L. Kringelbach
5. E. Bullmore
6. Joana Cabral
7. Anthony Randal McIntosh
8. Patric Hagmann

Citations in the corpus

• Overview of the SpiNNaker System Architecture (2013, neutral): “on the mammalian thalamo-cortical system [13], [14].”
• ROBUST TIMING AND MOTOR PATTERNS BY TAMING CHAOS IN RECURRENT NEURAL NETWORKS (2012, background): “…puzzle in neuroscience: theoretical and experimental studies suggest that the brain exhibits chaotic regimes (Banerjee et al., 2008; Brunel, 2000; Izhikevich and Edelman, 2008; London et al., 2010; Skarda and Freeman, 1987; van Vreeswijk and Sompolinsky, 1996); yet experimental evidence, and…”
• The use and abuse of large-scale brain models. (2014, positive): “One of the first brain-scale models ever developed was the 100 million neuron thalamocortical model developed by Izhikevich and Edelman [8].”
• The cat is out of the bag: cortical simulations with 109 neurons, 1013 synapses (2009, background): “Recently, [18] built a cortical model with 1 million multicompartmental spiking neurons and half a billion synapses using global diffusion tensor imaging-based white matter connectivity and thalamocortical microcircuitry.”
• Artificial General Intelligence: Concept, State of the Art, and Future Prospects (2009, background): “(Izhikevich and Edelman, 2008).”
• Functional connectivity dynamically evolves on multiple time-scales over a static structural connectome: Models and mechanisms (2017, background): “At the brink of multi-stability Starting with the most detailed generative model, Deco and Jirsa (2012) opted to represent each brain area by a network of interconnected excitatory and inhibitory spiking neurons (Brunel and Wang, 2001, Izhikevich and Edelman, 2008).”
• Cognitive Developmental Robotics: A Survey (2009, background): “Recently, Izhikevich and Edelman [38] simulated a detailed large-scale thalamocortical model based on experimental measures in several mammalian species.”
• Predicting human resting-state functional connectivity from structural connectivity (2009, background): “It is also important that future models include the thalamus (50, 51) as well as the basal ganglia, which likely mediate diverse cortico-cortical interactions.”
• A Large-Scale Model of the Functioning Brain (2012, neutral): “Serial working memory A3 [3 2 4 3 5] ? A3 [4 2 5 3 4 2] ? 3 2 4 3 5 4 2 5 – 4 2 Counting A4 [3] [2] ? A4 [0] [7] ? 5 7 Question answering A5 [4 3 8 6] [K] [4] ? A5 [4 3 8 6] [P] [4] ? 1 6 Rapid variable creation A6 [3312] [12 ][3392] [92] [3362] [62] [3342] ? A6 [342] [2 ][345] [5] [347] [7] [340] ?”
• Anticorrelations in resting state networks without global signal regression (2011, neutral): “Third, computational simulations of monkey and human brains suggest existence of spontaneous anticorrelated networks (Deco et al., 2009; Honey et al., 2007; Izhikevich and Edelman, 2008).”
• Supplementary Materials for A Large-Scale Model of the Functioning Brain (2012, neutral): “Serial working memory A3 [3 2 4 3 5] ? A3 [4 2 5 3 4 2] ? 3 2 4 3 5 4 2 5 – 4 2 Counting A4 [3] [2] ? A4 [0] [7] ? 5 7 Question answering A5 [4 3 8 6] [K] [4] ? A5 [4 3 8 6] [P] [4] ? 1 6 Rapid variable creation A6 [3312] [12 ][3392] [92] [3362] [62] [3342] ? A6 [342] [2 ][345] [5] [347] [7] [340] ?”
• The Metastable Brain (2014, neutral): “The coupling is never null, since there is no island in the brain (see also Figure 5 in Izhikevich and Edelman, 2008 for a related account).”
• Emerging concepts for the dynamical organization of resting-state activity in the brain (2010, positive): “A more microscopic approach was taken by Izhikevich and Edelman 41 who used diffusion tensor imaging (DTI)-based connectivity for their large-scale network modelling and implemented single neuron models (rather than neural population models).”
• An efficient automated parameter tuning framework for spiking neural networks (2014, background): “Moreover, it has been difficult to construct SNNs large enough to describe the complex functionality and dynamics found in real nervous systems (Izhikevich and Edelman, 2008; Krichmar et al., 2011; Eliasmith et al., 2012).”
• Ongoing Cortical Activity at Rest: Criticality, Multistability, and Ghost Attractors (2012, background): “, 2007) or truncation of time delays via signal transmission and rescaling of the connectivity (Izhikevich and Edelman, 2008)].”