  We present the concept of a track trigger for the Belle II experiment, based
on 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. The
trigger will thus be able to suppress a large fraction of the dominating
background from events outside of the interaction region. The trigger uses the
drift time information of the hits from the Central Drift Chamber (CDC) of
Belle II within narrow cones in polar and azimuthal angle as well as in
transverse momentum (sectors), and estimates the z-vertex without explicit
track reconstruction. The preprocessing for the track trigger is based on the
track information provided by the standard CDC trigger. It takes input from the
2D ($r - \varphi$) track finder, adds information from the stereo wires of the
CDC, and finds the appropriate sectors in the CDC for each track in a given
event. Within each sector, the z-vertex of the associated track is estimated by
a specialized neural network, with a continuous output corresponding to the
scaled z-vertex. The input values for the neural network are calculated from
the wire hits of the CDC.
