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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 ()):
  ---------------------------------------------------------------------
  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?