1. Reading Assignments: Lecture 16. Saccades 2 The NSL Book
L. Itti: CS564 - Brain Theory and Artificial Intelligence University of Southern California
Lecture 16. Saccades 2
Reading Assignments:
The NSL Book
The Modular Design of the Oculomotor System in Monkeys
Peter Dominey, Michael Arbib, and Amanda Alexander
Supplementary Reading:
Crowley-Arbib Saccade Model
M. Crowley, E. Oztop, and S. Marmol

2. Filling in the Schemas: Neural Network Models Based on Monkey Neurophysiology Peter Dominey & Michael Arbib: Cerebral Cortex, 2: Develop hypotheses on Neural Networks that yield an equivalent functionality: mapping schemas (functions) to the cooperative cooperation of sets of brain regions (structures)

3. Last time, we saw that…
Double-saccade experiments suggest direction/amplitude coding rather than absolute target location
Lesion/stimulation studies suggest that the overall system still works when either SC or FEF is missing (but not both!)
FEF stimulation just after presentation of a visual target (SC lesioned) elicits a saccade towards the “fake” FEF target first

4. Experimental Findings
connection FEF  PP
FEF, PPC  SC
SC  saccade generator (SG)
FEF  BG (CD and SNr)  SC (role in disinhibition of SC for saccades)
Simple saccade: study topographic relations between sensory and motor areas
Memory saccade: study cortical and subcortical activity that sustains spatial memory
Double saccade: study dynamic remapping of target location with intervening eye movements

5. Basic Model Element: Layer
2D array of neurons
topographic correspon-
dence from layer to
layer
external world: 27x27
array
model retina: 9x9
layer; so, each model
neuron represents a
small population of
biological neurons

6. Visual Input At every iteration, eye position determines position
of 9x9 retinal window within
27x27 outside world
if eye velocity over 200deg/sec,
retinal input is reduced
(saccadic suppression)

7. Direct connection retinaSC
To superficial layer of SC (vs)
responsible for reflex saccades = short-latency saccades
to target which has not been recently fixated

8. visual pre-processing
LGN, V1, V2, V4 and MT areas
abstracted by a single layer
possible only because we have a
very coarse (9x9) retinal input
with no image noise!

9. quasi-visual cells in PP
Andersen et al. (1988) found
in PP cells that code for future
eye movements.
Quasi-visual because in
double-saccade task
found cells which fire at location
of second target respective
to first target, while there never
was a retinal stimulus there!
right movement field but wrong receptive field

10. Double Saccade Experiment+
time

11. remapping Hypothesis: occurs primarily in PP
(in reality, may occur in many regions at once,
with connections between regions serving for fine-tuning).
problem: eye velocity signals have not been found in PP.
but eye position signals have 
Dominey and Arbib’s computational hypothesis: remapping is done such as to compensate for difference between current eye position, and a damped/delayed eye position signal

12. frontal eye fields Bruce & Goldberg (1984): FEF contains:
visual cells (vm)
(receive input from PP)
movement cells (ms)
(fire just before saccade)
visuomovement cells (sm)
(memory: fire during delay
in memory saccade task)
postsaccadic cells
PPctr: active as long
as fixation cross present
(inhibits eye movements) FOn = fixation is on

13. superior colliculus Input from retina (reflex saccades)
Input from PPqv  SC qv layer
(yield saccades when FEF
lesioned)
Inputs from FEF
How can we choose?
WTA array: saccade to
currently strongest target

14. basal ganglia SNr provides tonic inhibition of SC and thalamus, unless
prevented to do so by FEF
(directly or via CD)
Goals:
prevent saccades while
a target is being fixated
memorise location of
future target in memory
saccade task
FEF can selectively control the targets for saccades, overriding collicular attempts to initiate saccades to distracting peripheral targets

15. The Full Dominey Model DCEP-Damped Change in Eye Position
7a/LIP-Oculomotor Region of Posterior Parietal Cortex