A recurrent
neural network that produces predictive spatial updating
using retinal error and eye velocity efference copy signals
*G. P. KEITH1,2, G. BLOHM2, J. D. CRAWFORD1,2,3
1Psychology, York University,
Toronto, ON, CANADA, 2Centre for Vision Research, Centre
for Vision Research, Toronto, ON, CANADA, 3Biology and Kinesiology, York
University, Toronto, ON, CANADA.
It is currently believed that
remembered visual target locations are
stored in eye-centered coordinates and updated across eye movements.
Neuronal behavior associated with this updating has been observed in
brain areas associated with saccade generation, in the form of
transient receptive field remapping prior to and during the saccade.
The dynamics of this remapping, however, remain a question; for
example, whether these receptive fields spread or jump (Wurtz &
Sommer 2005). We trained three 3-layer recurrent neural networks with
discrete time-steps to examine how representations of target position
evolve during saccade-related updating. Target position during
fixations was represented in the output layer as a hill of activation
in a 2-D topographic array of units. Network inputs were initial target
position, dynamic eye position, and the signal(s) used to drive the
updating which, for the three networks were 1) the initial 'cortical'
representation of the saccade target, 2) the dynamic 'brainstem'
velocity signal of the saccade, and 3) both. In the first network,
predictive updating was observed in which the hill of activity jumped
directly from initial to remapped target position in a single
time-step. In the second network, a gradual shift in the output hill of
activation from initial to remapped target position over the duration
of the saccade was observed, the hill's amplitude being suppressed
during this movement. In the third network, the evolution of the output
activation combined that of a jumping and a moving hill. The latency of
the remapping for different trials in this network, as measured by the
onset of activity at the updated target location, showed a temporal
spectrum that spanned the time immediately before and during the
saccade, similar to what has been observed neurophysiologically in the
frontal eye fields (Umeno and Goldberg 1997). Our model thus shows that
the manner in which updating is carried out in a particular brain
region depends on the signals used to perform the updating. The use of
both initial saccade retinal error and velocity signals to drive
updating explains the temporal spectrum of predictive remapping
observed in the brain.