Modeling sleep and wakefulness in the thalamocortical system.
By Sean L. Hill, Giulio Tononi. Journal of Neurophysiology, 2005
399 citations recorded by the source corpus.
Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience
View Paper: https://www.semanticscholar.org/paper/b671b168b98c96ac42dc10cf0a3329c1e5e36611
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
- Giulio Tononi
- Giri Panamoottil Krishnan
- Maxim Bazhenov
- Umberto Olcese
- S. Esser
- Igor Timofeev
- Sylvain Chauvette
- Timothy Tadros
In Cognitive Neuroscience
- Maxim Bazhenov
- Giri Panamoottil Krishnan
- Giulio Tononi
- Timothy Tadros
- Ramyaa Ramyaa
- Umberto Olcese
- S. Esser
- Igor Timofeev
Citations in the corpus
- Synaptic Mechanisms of Memory Consolidation during Sleep Slow Oscillations (2016, background): “Finally, another model of slow oscillation proposed that “depolarization-activated potassium currents and synaptic depression terminate the Up state” without specifying the origin of the depolarization-activated potassium current (Hill and Tononi, 2005).”
- Cellular and neurochemical basis of sleep stages in the thalamocortical network (2016, background): “DOI: 10.7554/eLife.18607 17 of 29 Bazhenov et al., 2002; Compte et al., 2003; Hill and Tononi, 2005; Bonjean et al., 2011).”
- Sleep and synaptic renormalization: a computational study. (2010, methodology): “…present work is based on a large-scale model previously shown to accurately reproduce several 677 aspects of the population and single-unit dynamics of corticothalamic circuits during wakefulness and 678 slow wave sleep (Hill & Tononi 2005; Esser et al. 2005; Esser et al. 2007; Esser et al. 2009).”
- A cortical circuit for gain control by behavioral state (2014, background): “Changes in the balance between intrinsic excitatory and inhibitory conductances have long been linked to the change of brain state (Bazhenov et al., 2002; Hill and Tononi, 2005), and one salient feature of awake cortical responses is powerful inhibition (Haider et al.”
- Biologically inspired sleep algorithm for artificial neural networks (2019, methodology): “In this new study, we implemented the main mechanisms behind the sleep neuronal activity to benefit ANNs performance based on the relevant biophysical modeling work [15, 16, 17].”
- Precise Long-Range Synchronization of Activity and Silence in Neocortical Neurons during Slow-Wave Sleep (2006, background): “Fi- nally, some recent hypotheses ascribe termination of activity and onset of silent states to the intrinsic cellular properties and currents or synaptic depression (Bazhenov et al., 2002; Compte et al., 2003; Hill and Tononi, 2004; Milojkovic et al., 2005).”