We will consider two canonical models of population oscillators, one based on interacting sub-populations of excitatory and inhibitory neurons and the other based on an excitatory network with synaptic depression.
This classification would be used to speculate on the mechanisms underlying the effect of binaural background noise on ILD sensitivity based on the excitatory and inhibitory inputs to each response component, as are described in detail later.
Discriminant analysis based on the excitatory functional connectivity revealed that the neuronal populations of lower, middle and upper LII/III (sliding-window-derived groups) were clearly distinguishable (lower LII/III n = 14; middle LII/III n = 16; upper LII/III n = 14; p = 0.025, Wilk's lambda, 93 % correct classification).
When stimulated at 0.2 Hz, Marf mutants do not exhibit any obvious defect in transmitter release based on excitatory junction potential (EJP) recordings.
Neuronal nuclei, having low expression of the pan-neuronal marker Thy1 (Fig. 1d) and clustering separately from cellular data (Fig. 1e), could still be classified as S1 cortical excitatory neurons based on expression of the excitatory neuronal marker Slc17a7 and markers associated with upper layer cortical projection or granule neurons (Fig. 1d).
It should be noted, however, that "chemomicrostimulation" maps based on the use of excitatory amino acids in the rat do not support a role of neurons in these regions in generating deglutitive motor output (see next section).
The mechanism is based on a network of excitatory (E) and inhibitory (I) neurons with very simple assumptions: (1) Individual neurons have an expansive or supralinear input/output functions, e.g. a power law with power >1; (2) Feedback inhibition is sufficiently strong to drive the network to a stable fixed point for a given stable input.
Here we propose a different mechanism for deriving rivalry networks for the conventional and scrambled dot experiments, one based on features that lead to different types of excitatory couplings within learned patterns.
Motor system excitability is based on a complex interaction of excitatory and inhibitory processes [ 1].
Motor system excitability is based on a complex interaction of excitatory and inhibitory processes, which in turn are modulated by internal (e.g., volitional inhibition) and external (e.g., drugs) factors.
