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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
Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Saccades 2
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delay
FEF
PP
FOn
PPct r
ms
Peter Dominey & Michael Arbib:
Cerebral Cortex, 2:153-175
switch
Filling in the Schemas: Neural
Network Models Based on
Monkey Neurophysiology
qv
sm
vm
FEF
vs
PP
MD
VisCx
sm
CAUDATE
Vis Cx
SC
CD
TH
LGN
vm
SNr
SNR
vs
SG
sm
delay
Develop hypotheses on Neural
Networks that yield an equivalent
functionality:
mapping schemas (functions) to the
cooperative cooperation of sets of
brain regions (structures)
FEFvs
FEFms
SC
vs
ms
qv
FOn
wta
eye movement
FEFvs
FEFms
Brainstem
Saccade
Generator
Retina
VisInput
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
Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Saccades 2
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Experimental Findings
FEF  PP
- FEF, PPC  SC
- SC  saccade generator (SG)
- FEF  BG (CD and SNr)  SC
- connection
(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
Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Saccades 2
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Basic Model Element: Layer
2D array of neurons
delay
FEF
PPct r
ms
topographic correspondence from layer to
layer
switch
PP
FOn
qv
sm
vm
vs
VisCx
sm
CD
external world: 27x27
array
TH
LGN
vm
SNR
vs
sm
model retina: 9x9
layer; so, each model
neuron represents a
small population of
biological neurons
delay
FEFvs
FEFms
SC
vs
ms
qv
FOn
Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Saccades 2
wta
eye movement
FEFvs
FEFms
Brains tem
Saccade
Generator
Retina
VisInput
5
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)
Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Saccades 2
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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
Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Saccades 2
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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!
Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Saccades 2
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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
Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Saccades 2
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Double Saccade Experiment
+
time
Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Saccades 2
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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
Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Saccades 2
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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)
Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Saccades 2
FOn = fixation is on
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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
Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Saccades 2
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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
Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Saccades 2
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The Full Dominey Model
DCEP
trig
SC
PN
RI
dimension
Retina,
VisCx
Delay
(d1)
Mechanism A
FEF
velocity
EBN
LLBN,
MLBN
TN
MN
7a/LIP/PP
Brain Stem – Saccade Burst Generator
DCEP-Damped Change in Eye Position
7a/LIP-Oculomotor Region of Posterior Parietal Cortex
Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Saccades 2
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Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Saccades 2
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Laurent Itti: CS564 - Brain Theory and Artificial Intelligence. Saccades 2
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