Chapter 2. Prehension

128 THE PHASES OF PREHENSION
where a is a positive constant. The present position command is up-
dated as follows:
where G[Vi]+ = max(Vi,O). Motor priming is possible with this
model, because a new target may be specified, but no movement will
occur until the GO signal increases above zero. The difference vector
can still be computed.
Grossberg and Bullock showed how the VITEg model can
generate asymmetric velocity profiles across different movement
durations. This is elaborated in Figure 5.7. The GO signal controls
the speed of the movement. In Figure 57a, an asymmetrical velocity
profile is seen for a slow movement. As the movement speed
increases (Figures 5.7b and c), the velocity profiles become more
symmetrical. This is seen in Figure 5.7d, where these velocity profiles
are superimposed. Evidence in the neurophysiological data for the V
signal has been seen in the directional population vector of
Georgopoulos and colleagues (Georgopoulos et al., 1988; Kettner et
al., 1988; Schwartz et al., 1988). The VITE model is consistent with
higher peak velocity in target switching experiments. When there is an
internal model of target location and current hand position, error
corrections don't need to be made based on proprioception. The VITE
model can generate different offsets for muscles, as a function of the
GO signal, thus staggering the contraction onset times. Trajectories are
generalized in joint space. Motor commands to a muscle group are
read out at staggered times after the GO signal is received. While it
can reach the same goal from arbitrary initial states at variable rates,
the model cannot be easily applied to multi-joint movements and does
not address learning.
In summary, point to point simple arm movements have pre-
dictable spatial paths, although whether or not they are curved depends
on where in the workspace the movement occurs. For unrestrained
gGrossberg and Kuperstein (1986, 1989) have developed a feedback model (the
muscle linearization model MLN) that compares the feedforward internal model (P
in Figure 5.6) to sensory feedback. Mismatches between these generate error
signals which alter the gain of the motor command adaptively.