Fast synaptic inhibition promotes synchronized gamma oscillations in hippocampal interneuron networks
Author(s) -
Marlene Bartos,
Imre Vida,
Michael Frotscher,
Axel H. Meyer,
Hannah Monyer,
Jörg R. P. Geiger,
Péter Jónás
Publication year - 2002
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.192233099
Subject(s) - interneuron , neuroscience , inhibitory postsynaptic potential , hippocampal formation , dentate gyrus , gabaergic , excitatory postsynaptic potential , postsynaptic potential , postsynaptic current , biology , parvalbumin , gamma aminobutyric acid , coupling (piping) , biophysics , receptor , biochemistry , materials science , metallurgy
Networks of GABAergic interneurons are of critical importance for the generation of gamma frequency oscillations in the brain. To examine the underlying synaptic mechanisms, we made paired recordings from "basket cells" (BCs) in different subfields of hippocampal slices, using transgenic mice that express enhanced green fluorescent protein (EGFP) under the control of the parvalbumin promoter. Unitary inhibitory postsynaptic currents (IPSCs) showed large amplitude and fast time course with mean amplitude-weighted decay time constants of 2.5, 1.2, and 1.8 ms in the dentate gyrus, and the cornu ammonis area 3 (CA3) and 1 (CA1), respectively (33-34 degrees C). The decay of unitary IPSCs at BC-BC synapses was significantly faster than that at BC-principal cell synapses, indicating target cell-specific differences in IPSC kinetics. In addition, electrical coupling was found in a subset of BC-BC pairs. To examine whether an interneuron network with fast inhibitory synapses can act as a gamma frequency oscillator, we developed an interneuron network model based on experimentally determined properties. In comparison to previous interneuron network models, our model was able to generate oscillatory activity with higher coherence over a broad range of frequencies (20-110 Hz). In this model, high coherence and flexibility in frequency control emerge from the combination of synaptic properties, network structure, and electrical coupling.
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