1. Neural Network Simulation of Emsemble-coding model
of primate Superior Colliculus
By Hyojung Seo
Dept. of Psychology

2. Population Activity in SC and Saccadic Vector
Amplitude (20 deg)
Direction
(60 deg)
Decomposition
Vertical
(deg)
17.3 10
Horizontal
(deg)

3. Vector Average

4. Needed Considerations for Simulation
1. Spatio-Temporal Transformation
2. Feedback Loops
3. Decomposition of
Horizontal and Vertical Components

5. Architecture of Neural Network
INPUT:
5*5 Matrix of physical positions in SC
Rows: U axis
Columns: V axis 40 20
-20
-40 5 10 30
Horizontal (i)
Vertical (j)
SC Cell(i,j)
i=1,2,3,4,5
j=1,2,3,4,5

6. Activation Values of each cell
Architecture of Neural Network (Cont’d)
Results of Input Programming with MatLab 5 10 20 30 40
-40
-20
0.5 1
Activation Values of each cell

7. Architecture of Neural Network (Cont’d)
There are 3 Pairs of extraoculor muscles to each eye:
ONLY 2 pairs will be included in this study
Left Eye
Right Eye
Superior
rectus
(Upward)
Superior
rectus
(Upward)
(Right)
Medial
rectus
Lateral
rectus
(Left)
Lateral
rectus
(Right)
Medial
rectus
(Left)
Inferior
rectus
(Downward)
Inferior
rectus
(Downward)

8. Architecture of Neural Network (Cont’d)
OUTPUT:
Activity Levels of Motor Neurons,
innervating Right-Eye extraocular muscles
leftward
upward
downward
rightward
Activity Level= Vector_avg. /k
(k: Maximum amplitude)

9. Architecture of Neural Network (Cont’d)
leftward
upward
downward
rightward
MNs a b c d
h-IBNs
up-IBNs
down-EBNs
OPNs
h-EBNs
up-EBNs
h-LLBNs
v-LLBNs
Excitatory connections SC
Inhibitory connections