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The control of movement can be studied
with the countermanding (stop signal) task
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error
Probability (noncancelled)
1.0
Inhibition function
0.5
0.0
50
100
150
200
250
Stop signal delay (ms)
100%
50%
116 ms
168 ms
216 ms
no stop signal
0%
300
200
Reaction time (ms)
400
RT distributions of
non-cancelled and no
stop signal trials
Race model can explain behavior
GO
STOP
GO process
STOP process
GO WINS!
non-cancelled trial
STOP WINS!
cancelled trial
Stop Signal Reaction Time (SSRT) – time needed to
cancel a previously planned movement
Frontal Eye Field
(as part of a network!)
Activation
Controls when gaze shifts
0.0
0.1
0.2
Time from stimulus (sec)
Hanes, D.P. and J.D. Schall (1996) Neural control of voluntary movement initiation. Science 274:427-430.
FEF
movement neurons
Stop Signal
SC
SSRT
100
No Stop Signal Trials
Stop Signal SSRT
200
No
difference.
100
Non-canceled Trials
0
200
Stop Signal
400
0
No Stop Signal Trials
SSRT
200
0
400
Stop Signal SSRT
200
Sig. difference
before SSRT.
100
100
0
fixation neurons
0
200
Stop Signal
400
SSRT
100
Canceled Trials
0
Canceled Trials
200
Stop Signal
400
SSRT
100
Sig. difference
before SSRT.
0
200
400
50
No Stop Signal Trials
0
0
200
400
Movement
Neuron
Fixation
Neuron
GO
process
STOP
process
Mapping the race model onto neural processes
1 - The race model of countermanding performance
assumes that the GO and the STOP processes have
independent finish times (Logan & Cowan, 1984).
2 – Saccades are produced by a network of interacting
neurons.
Paradox – How can a network of interacting neurons
produce behavior that looks like the outcome of race
between independent processes?
Mapping the race model onto neural processes
Explore properties of simple network of GO and STOP units.
GO
STOP
Constrain by the properties of countermanding behavior
and by the form of activation of neurons
L.Boucher, G.D.Logan, T.J.Palmeri, J.D.Schall. An interactive race model of countermanding saccades. Program No. 72.10. 2003 Abstract Viewer/Itinerary Planner.
ß STOP
1.0
GO process
STOP process
GO
STOP
0.5
ß GO
GO,s GO
STOP, s STOP
0.0
0
100
200
300
Time from stimulus (ms)
GO activation = (GO growth rate – STOP inhibition) + noise
daGO 
dt

GO 
 STOP  aSTOP  
dt

GO
STOP activation = (STOP growth rate – GO inhibition) + noise
daSTOP 
dt

 STOP 
 GO  aGO  
dt

 STOP
Independent Race Model
GO
STOP
Probability (noncancelled)
GO,s GO
1.0
STOP, s STOP
Observed
Model
0.5
0.0
50
100
150
200
Stop signal delay (ms)
250
Independent Race Model
GO
GO,s GO
STOP
STOP, s STOP
Non-cancelled and
no stop signal
Interactive Race Model
ß STOP
GO
STOP
ß GO
GO,s GO
STOP, s STOP
Probability (noncancelled)
1.0
Observed
Model
0.5
0.0
50
100
150
200
Stop signal delay (ms)
250
Interactive Race Model
ß STOP
GO
STOP
ß GO
 s
GO, GO

s
STOP, STOP
Non-cancelled
and no stop
signal
Cancelled and
no stop signal
Observed
Model Predictions