def test_gatekeeper(self, total_duration=14.0, stimulus_period=(2.0, 12.0), gate_period=(5.0, 8.0), delay=0.01):
startTime = time()
timeNow = 0.0
n1 = Neuron((0.0, 0.0, 0.0), timeNow)
n2 = Neuron((0.0, 0.0, 1.0), timeNow)
g1 = Neuron((-1.0, -1.0, 1.0), timeNow) # gatekeeper
n1.synapseWith(n2, None, g1) # auto-initialize synaptic strength
# Set up plotting
figure(figsize = (12, 9))
hold(True) # [graph]
ax = subplot(311) # [graph]
xlim(0.0, total_duration) # [graph]
ylim(action_potential_trough.mu - 0.01, action_potential_peak + 0.01) # [graph]
setup_neuron_plot("Presynaptic neuron", None, None)
ax.get_xaxis().set_ticklabels([])
ax = subplot(312) # [graph]
xlim(0.0, total_duration) # [graph]
ylim(action_potential_trough.mu - 0.01, action_potential_peak + 0.01) # [graph]
setup_neuron_plot("Postsynaptic neuron", None, "Membrane potential (V)")
ax.get_xaxis().set_ticklabels([])
subplot(313) # [graph]
xlim(0.0, total_duration) # [graph]
ylim(action_potential_trough.mu - 0.01, action_potential_peak + 0.01) # [graph]
setup_neuron_plot("Gatekeeper neuron", "Time (s)", None)
subplots_adjust(hspace = 0.33)
while timeNow <= total_duration:
timeNow = time() - startTime
if stimulus_period[0] <= timeNow <= stimulus_period[1]:
n1.accumulate(np.random.normal(0.004, 0.0005)) # TODO accumulate value based on deltaTime (since last accumulate)
if gate_period[0] <= timeNow <= gate_period[1]:
g1.accumulate(np.random.normal(0.0035, 0.0005))
n1.update(timeNow)
#print n1.id, n1.timeCurrent, n1.potential # [log: potential]
n2.update(timeNow)
#print n2.id, n2.timeCurrent, n2.potential # [log: potential]
g1.update(timeNow)
subplot(311) # [graph]
n1.plot() # [graph]
subplot(312) # [graph]
n2.plot() # [graph]
subplot(313) # [graph]
g1.plot() # [graph]
pause(delay) # [graph]
#sleep(delay)
if holdPlots:
show() # [graph]
def test_inhibitor(self, total_duration=14.0, stimulus_period=(2.0, 12.0), inhibition_period=(5.0, 8.0), delay=0.01):
startTime = time()
timeNow = 0.0
n1 = Neuron((0.0, 0.0, 0.0), timeNow)
n2 = Neuron((0.0, 0.0, 1.0), timeNow)
i1 = Neuron((-1.0, -1.0, 1.0), timeNow) # inhibitor
n1.synapseWith(n2) # no synaptic gating
i1.synapseWith(n2, -np.random.normal(synaptic_strength.mu, synaptic_strength.sigma)) # inhibitory synapse
# Set up plotting
figure(figsize = (12, 9))
hold(True) # [graph]
subplot(311) # [graph]
xlim(0.0, total_duration) # [graph]
ylim(action_potential_trough.mu - 0.01, action_potential_peak + 0.01) # [graph]
setup_neuron_plot("Neuron " + str(n1.id))
subplot(312) # [graph]
xlim(0.0, total_duration) # [graph]
ylim(action_potential_trough.mu - 0.01, action_potential_peak + 0.01) # [graph]
setup_neuron_plot("Neuron " + str(n2.id))
subplot(313) # [graph]
xlim(0.0, total_duration) # [graph]
ylim(action_potential_trough.mu - 0.01, action_potential_peak + 0.01) # [graph]
setup_neuron_plot("Neuron " + str(i1.id) + " (inhibitor)")
subplots_adjust(hspace = 0.33)
while timeNow <= total_duration:
timeNow = time() - startTime
if stimulus_period[0] <= timeNow <= stimulus_period[1]:
n1.accumulate(np.random.normal(0.004, 0.0005)) # TODO accumulate value based on deltaTime (since last accumulate)
if inhibition_period[0] <= timeNow <= inhibition_period[1]:
i1.accumulate(np.random.normal(0.0035, 0.0005))
n1.update(timeNow)
#print n1.id, n1.timeCurrent, n1.potential # [log: potential]
n2.update(timeNow)
#print n2.id, n2.timeCurrent, n2.potential # [log: potential]
i1.update(timeNow)
subplot(311) # [graph]
n1.plot() # [graph]
subplot(312) # [graph]
n2.plot() # [graph]
subplot(313) # [graph]
i1.plot() # [graph]
pause(delay) # [graph]
#sleep(delay)
if holdPlots:
show() # [graph]
def test_pair(self, pre_duration=2.0, stimulus_duration=10.0, post_duration=2.0, delay=0.01):
total_duration = pre_duration + stimulus_duration + post_duration
stimulus_begin = pre_duration
stimulus_end = pre_duration + stimulus_duration
startTime = time()
timeNow = 0.0
n1 = Neuron((0.0, 0.0, 0.0), timeNow)
n2 = Neuron((0.0, 0.0, 1.0), timeNow)
n1.synapseWith(n2)
# Set up plotting
figure(figsize = (12, 9))
hold(True) # [graph]
subplot(211) # [graph]
xlim(0.0, total_duration) # [graph]
ylim(action_potential_trough.mu - 0.01, action_potential_peak + 0.02) # [graph]
setup_neuron_plot("Presynaptic neuron", None, "Membrane potential (V)")
subplot(212) # [graph]
xlim(0.0, total_duration) # [graph]
ylim(action_potential_trough.mu - 0.01, action_potential_peak + 0.02) # [graph]
setup_neuron_plot("Postsynaptic neuron", "Time (s)", "Membrane potential (V)")
subplots_adjust(hspace = 0.33)
while timeNow <= total_duration:
timeNow = time() - startTime
if stimulus_begin <= timeNow <= stimulus_end:
n1.accumulate(np.random.normal(0.0035, 0.0005)) # TODO accumulate value based on deltaTime (since last accumulate)
n1.update(timeNow)
#print n1.id, n1.timeCurrent, n1.potential # [log: potential]
n2.update(timeNow)
#print n2.id, n2.timeCurrent, n2.potential # [log: potential]
subplot(211) # [graph]
n1.plot() # [graph]
subplot(212) # [graph]
n2.plot() # [graph]
pause(delay) # [graph]
#sleep(delay)
if holdPlots:
show() # [graph]