Porres, Christian P.; Meyer, Elisabeth M. M.; Grothe, Benedikt; Felmy, Felix
NMDA Currents Modulate the Synaptic Input–Output Functions of Neurons in the Dorsal Nucleus of the Lateral Lemniscus in Mongolian Gerbils.
In: The journal of neuroscience, Vol. 31, Nr. 12: S. 4511-4523
Neurons in the dorsal nucleus of the lateral lemniscus (DNLL) receive excitatory and inhibitory inputs from the superior olivary complex (SOC) and convey GABAergic inhibition to the contralateral DNLL and the inferior colliculi. Unlike the fast glycinergic inhibition in the SOC, this GABAergic inhibition outlasts auditory stimulation by tens of milliseconds. Two mechanisms have been postulated to explain this persistent inhibition. One, an “integration-based” mechanism, suggests that postsynaptic excitatory integration in DNLL neurons generates prolonged activity, and the other favors the synaptic time course of the DNLL output itself. The feasibility of the integration-based mechanism was tested in vitro in DNLL neurons of Mongolian gerbils by quantifying the cellular excitability and synaptic input–output functions (IO-Fs). All neurons were sustained firing and generated a near monotonic IO-F on current injections. From synaptic stimulations, we estimate that activation of approximately five fibers, each on average liberating ∼18 vesicles, is sufficient to trigger a single postsynaptic action potential. A strong single pulse of afferent fiber stimulation triggered multiple postsynaptic action potentials. The steepness of the synaptic IO-F was dependent on the synaptic NMDA component. The synaptic NMDA receptor current defines the slope of the synaptic IO-F by enhancing the temporal and spatial EPSP summation. Blocking this NMDA-dependent amplification during postsynaptic integration of train stimulations resulted into a ∼20% reduction of the decay time course of the GABAergic inhibition. Thus, our data show that the NMDA-dependent amplification of the postsynaptic activity contributes to the GABAergic persistent inhibition generated by DNLL neurons.