Control of a local neural network by feedforward and feedback inhibition

The signal transfer of a neuronal network is shaped by the local interactions between the
excitatory principal cells and the inhibitory interneurons. We investigated with a simple lumped
model how feedforward and feedback inhibition in.uence the steady-state network signal transfer. We analyze how the properties ofinhibition a1ect the input/output space ofthe network and compare the results with experimental data obtained in the hippocampal CA1 circuit. The speci4c non-linear transfer of the cell populations determine how feedforward and feedback inhibition modulate the gain and/or shift the network signal transfer. An important biological issue is whether the two forms of inhibition can be combined in the same interneurons. Combining both functions in the same interneurons requires highly non-linear addition of their inputs.