ArticleFrontiers in computational neuroscience2015
Synaptic dynamics and neuronal network connectivity are reflected in the distribution of times in Up states.
Article in Frontiers in computational neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Mesoscopic description of hippocampal replay and metastability in spiking neural networks with short-term plasticity.PLoS computational biology · 2022Article
- Emergence and fragmentation of the alpha-band driven by neuronal network dynamics.PLoS computational biology · 2021Article
- Understanding ethanol's acute effects on medial prefrontal cortex neural activity using state-space approaches.Neuropharmacology · 2021Review
- Differential Excitability of PV and SST Neurons Results in Distinct Functional Roles in Inhibition Stabilization of Up States.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
- Ethanol Alters Variability, But Not Rate, of Firing in Medial Prefrontal Cortex Neurons of Awake-Behaving Rats.Alcoholism, clinical and experimental research · 2020Article
- Dynamics of spontaneous activity in random networks with multiple neuron subtypes and synaptic noise : Spontaneous activity in networks with synaptic noise.Journal of computational neuroscience · 2018Article
- Bistability and up/down state alternations in inhibition-dominated randomly connected networks of LIF neurons.Scientific reports · 2017Article
- Article
- Entrainment in up and down states of neural populations: non-smooth and stochastic models.Journal of mathematical biology · 2016Article
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Authors and funding
6 authors.
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Abstract
The dynamics of neuronal networks connected by synaptic dynamics can sustain long periods of depolarization that can last for hundreds of milliseconds such as Up states recorded during sleep or anesthesia. Yet the underlying mechanism driving these periods remain unclear. We show here within a mean-field model that the residence time of the neuronal membrane potential in cortical Up states does not follow a Poissonian law, but presents several peaks. Furthermore, the present modeling approach allows extracting some information about the neuronal network connectivity from the time distribution histogram. Based on a synaptic-depression model, we find that these peaks, that can be observed in histograms of patch-clamp recordings are not artifacts of electrophysiological measurements, but rather are an inherent property of the network dynamics. Analysis of the equations reveals a stable focus located close to the unstable limit cycle, delimiting a region that defines the Up state. The model further shows that the peaks observed in the Up state time distribution are due to winding around the focus before escaping from the basin of attraction. Finally, we use in vivo recordings of intracellular membrane potential and we recover from the peak distribution, some information about the network connectivity. We conclude that it is possible to recover the network connectivity from the distribution of times that the neuronal membrane voltage spends in Up states.
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