Biomedical Engineering Reference
In-Depth Information
Hightest Sensitivity Neurons
Intermediate Sensitivity Neurons
60
60
40
40
20
20
0
0
-20
-20
0
10
20
30
40
50
60
0
10
20
30
40
50
60
Lowest Sensitivity Neurons
Movements of Test Trajec
tory
1
60
All Neurons
0.8
40
0.6
10 Highest Sensitivity
84 Intermediate Sensitivity
10 Lowest Sensitivity
20
0.4
0
0.2
-20
0
0
10
20
30
40
50
60
0
20
40
60
80
100
Time (100ms)
3D Error Radius (mm)
FIgURE 4.7:
Testing outputs for RMLP models trained with subsets of neurons. (a-c)
x
,
y
, and
z
tra-
jectories (bold) for one movement (light) from three RMLPs trained with the highest, intermediate, and
lowest sensitivity neurons. (d) Cumulative error metric decreases as sensitive neurons are dropped.
This result verifies that the method of RMLP model-based sensitivity analysis for BMIs is able to
produce a graded list of neurons involved in the reconstructing a hand trajectory.
We now need to address why the neurons with the highest sensitivity are important for the
production of the output movement. The answer is quite simple and can be obtained by plotting the
binned firing counts for highest and lowest sensitivity neurons in the vicinity of a reaching move-
ment (Figure
4.8
). In the top subplot of each column, we have included the first reaching movement
as in the above simulations. For the highest sensitivity neurons, we can see some strong correlations
between the neuronal firing and the rest/food, food/mouth, and mouth/rest movements. Neurons
4, 5, 7, 19, and 26 (PP) display increased firing during the rest/food movement, and are zero other-
wise. Neurons 93 and 104 (M1) show a firing increase during the food/mouth movement. Neuron
45 (M1) does not correlate with the movement directly but seems to fire right before the movement,
indicating that it may be involved in movement initiation. Neuron 84 (M1) fires only single pulses
during the transitions of the movement. In the firing patterns of these neurons, we see the effect of
the decay of the time-varying sensitivity at time
t
, which can be influenced by samples 2 sec in the
past.
