ArticlePLoS computational biology2024
A multi-scale study of thalamic state-dependent responsiveness.
Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- From Atoms to Neuronal Spikes: A Multiscale Simulation Framework.Journal of chemical theory and computation · 2026Review
- From Atoms to Neuronal Spikes: A Multi-Scale Simulation Framework.bioRxiv : the preprint server for biology · 2025Article
- Region-specific mean field models enhance simulations of local and global brain dynamics.NPJ systems biology and applications · 2025Article
- Cerebellar control over inter-regional excitatory/inhibitory dynamics discriminates execution from observation of an action.Cerebellum (London, England) · 2025Article
- A computational approach to evaluate how molecular mechanisms impact large-scale brain activity.Nature computational science · 2025Article
- Multiscale modeling of neuronal dynamics in hippocampus CA1.Frontiers in computational neuroscience · 2024Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The thalamus is the brain's central relay station, orchestrating sensory processing and cognitive functions. However, how thalamic function depends on internal and external states, is not well understood. A comprehensive understanding would necessitate the integration of single cell dynamics with their collective behavior at population level. For this we propose a biologically realistic mean-field model of the thalamus, describing thalamocortical relay neurons (TC) and thalamic reticular neurons (RE). We perform a multi-scale study of thalamic responsiveness and its dependence on cell and brain states. Building upon existing single-cell experiments we show that: (1) Awake and sleep-like states can be defined via the absence/presence of the neuromodulator acetylcholine (ACh), which indirectly controls bursting in TC and RE. (2) Thalamic response to sensory stimuli is linear in awake state and becomes nonlinear in sleep state, while cortical input generates nonlinear response in both awake and sleep state. (3) Stimulus response is controlled by cortical input, which suppresses responsiveness in awake state while it 'wakes-up' the thalamus in sleep state promoting a linear response. (4) Synaptic noise induces a global linear responsiveness, diminishing the difference in response between thalamic states. Finally, the model replicates spindle oscillations within a sleep-like state, exhibiting a qualitative change in activity and responsiveness. The development of this thalamic mean-field model provides a new tool for incorporating detailed thalamic dynamics in large scale brain simulations.
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Registered trials
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