Inferring connection proximity in electrically coupled networks (Cali et al. 2007)

In order to explore electrical coupling in the nervous system and its network-level organization, it is imperative to map the electrical synaptic microcircuits, in analogy with in vitro studies on monosynaptic and disynaptic chemical coupling. However, walking from cell to cell over large distances with a glass pipette is challenging, and microinjection of (fluorescent) dyes diffusing through gap-junctions remains so far the only method available to decipher such microcircuits even though technical limitations exist. Based on circuit theory, we derived analytical descriptions of the AC electrical coupling in networks of isopotential cells. We then proposed an operative electrophysiological protocol to distinguish between direct electrical connections and connections involving one or more intermediate cells. This method allows inferring the number of intermediate cells, generalizing the conventional coupling coefficient, which provides limited information. We provide here some analysis and simulation scripts that used to test our method through computer simulations, in vitro recordings, theoretical and numerical methods. Key words: Gap-Junctions; Electrical Coupling; Networks; ZAP current; Impedance.

Model Type: Neuron or other electrically excitable cell; Glia

Currents: I Na,t; I K; I Potassium

Model Concept(s): Methods

Simulation Environment: NEURON; MATLAB; PSpice; Sspice Symbolic SPICE

Implementer(s): Giugliano, Michele [mgiugliano at]


Calì C et al. (2008). Inferring connection proximity in networks of electrically coupled cells by subthreshold frequency response analysis. Journal of computational neuroscience. 24 [PubMed]

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