timescales.sim.sim_spikes_prob

timescales.sim.sim_spikes_prob(n_seconds, fs, kernel, isi=None, mu=None, refract=None, var_noise=None)

Simulate spiking probability.

Parameters

n_secondsfloat

Length of the signal, in seconds.

fsfloat

Sampling rate, in hz.

kernel1d or 2d array

Synaptic kernel to convolve with Poisson.

n_neuronsint, optional, default: 100

Number of neurons to simulate.

isi1d array, optional, default: None

Interspike intervals to randomly sample from.

mufloat, optional, default: None

Mean of the isi exponential distribuion. Only used if isi is None.

refractint, optional, default: None

Minimum distances between spikes (i.e. refactory period).

var_noisefloat, optional, default: 0.

Variance of gaussian noise to be added to spike probabilities. Larger values, approaching 1, will produce smaller spectral exponents.

Returns

probs2d array, optional

Probablility of spiking at each sample.