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We present the concept of a track trigger for the Belle II experiment, basedon a neural network approach, that is able to reconstruct the z (longitudinal)position of the event vertex within the latency of the first level trigger. Thetrigger will thus be able to suppress a large fraction of the dominatingbackground from events outside of the interaction region. The trigger uses thedrift time information of the hits from the Central Drift Chamber (CDC) ofBelle II within narrow cones in polar and azimuthal angle as well as intransverse momentum (sectors), and estimates the z-vertex without explicittrack reconstruction. The preprocessing for the track trigger is based on thetrack information provided by the standard CDC trigger. It takes input from the2D ($r - \varphi$) track finder, adds information from the stereo wires of theCDC, and finds the appropriate sectors in the CDC for each track in a givenevent. Within each sector, the z-vertex of the associated track is estimated bya specialized neural network, with a continuous output corresponding to thescaled z-vertex. The input values for the neural network are calculated fromthe wire hits of the CDC.

A neural network z-vertex trigger for Belle II