directionselectivityNcell_random
DIRECTIONSELECTIVITYNCELL_RANDOM
OUT = DIRECTIONSELECTIVITYNCELL_RANDOM
Randomly choose weights for a N-input single layer network and
calculate direction selectivity
One can also adjust the parameters using:
OUT = DIRECTIONSELECTIVITYNCELL_RANDOM(PARAM1NAME, PARAM1VALUE, ...)
The following parameters are adjustable (default value in ()):
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latency (0.200) | Latency between 1st and 2nd columns
lag (0.200) | Lag between stim hitting 1st and 2nd rows
Gmax_max (5e-9) | Maximum weights
Gmax_min (0) | Minimum weights
Gmax_weightlist ([]) | If provided, Gmax will be randomly chosen from this list
| Under this condition, Gmax_max and Gmax_min will be
| ignored.
classic_stdp (1) | 0/1 use classic stdp
synapseparams | synapse parameters
intfireparams | intfire parameters
dt (0.0001) | time resolution
trials (100) | number of trials
N (2) | Number of different positions
R (2) | Number of different latencies
isi (1) | Interstimulus interval (must be long enough)
randomness (0) | Randomness
plot_as_we_go (1) | 0/1 plot to a figure as we go?