ArticleFrontiers in computational neuroscience2012
Shortest Loops are Pacemakers in Random Networks of Electrically Coupled Axons.
Article in Frontiers in computational neuroscience, 2012. 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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9 citing papers in PubMed, 23 citations in OpenAlex.
- Toward a theory of coactivation patterns in excitable neural networks.PLoS computational biology · 2018Article
- Connectivity and complex systems: learning from a multi-disciplinary perspective.Applied network science · 2018Review
- Topological determinants of self-sustained activity in a simple model of excitable dynamics on graphs.Scientific reports · 2017Article
- Article
- In situ three-dimensional reconstruction of mouse heart sympathetic innervation by two-photon excitation fluorescence imaging.Journal of neuroscience methods · 2014Article
- Gap junction networks can generate both ripple-like and fast ripple-like oscillations.The European journal of neuroscience · 2014Article
- Synaptic gating at axonal branches, and sharp-wave ripples with replay: a simulation study.The European journal of neuroscience · 2013Article
- Inhibition enhances memory capacity: optimal feedback, transient replay and oscillations.Journal of computational neuroscience · 2013Article
- Building blocks of self-sustained activity in a simple deterministic model of excitable neural networks.Frontiers in computational neuroscience · 2012Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
High-frequency oscillations (HFOs) are an important part of brain activity in health and disease. However, their origins remain obscure and controversial. One possible mechanism depends on the presence of sparsely distributed gap junctions that electrically couple the axons of principal cells. A plexus of electrically coupled axons is modeled as a random network with bi-directional connections between its nodes. Under certain conditions the network can demonstrate one of two types of oscillatory activity. Type I oscillations (100-200 Hz) are predicted to be caused by spontaneously spiking axons in a network with strong (high conductance) gap junctions. Type II oscillations (200-300 Hz) require no spontaneous spiking and relatively weak (low-conductance) gap junctions, across which spike propagation failures occur. The type II oscillations are reentrant and self-sustained. Here we examine what determines the frequency of type II oscillations. Using simulations we show that the distribution of loop lengths is the key factor for determining frequency in type II network oscillations. We first analyze spike failure between two electrically coupled cells using a model of anatomically reconstructed CA1 pyramidal neuron. Then network oscillations are studied by a cellular automaton model with random network connectivity, in which we control loop statistics. We show that oscillation periods can be predicted from the network's loop statistics. The shortest loop, around which a spike can travel, is the most likely pacemaker candidate. The principle of one loop as a pacemaker is remarkable, because random networks contain a large number of loops juxtaposed and superimposed, and their number rapidly grows with network size. This principle allows us to predict the frequency of oscillations from network connectivity and visa versa. We finally propose that type I oscillations may correspond to ripples, while type II oscillations correspond to so-called fast ripples.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.