A Stimulus-Response Neural Network Model Prepared by Top-Down Signals

The stimulus-response circuits in the brain need to have flexible and fast characteristics and these circuits should be activated during the preparatory period for movement. We propose a fundamental neural network model, which can trigger the movement in response to a specific sensory input using top-down signals. When the top-down signal is received in the 1st layer, this circuit waiting for the specific sensory input is in the ready state to move. In response to the specific sensory input, synchrony is emitted and quickly transmitted to the 2nd layer. Because of more convergent connections from 1st to 2nd layers, some synchronous spikes are stably transferred and others are suppressed by the 2nd top-down signal. Thus, appropriate pairing of top-down signals to 1st and 2nd layers enables the circuits to execute an arbitrary stimulus-response behavior.