stim.amp, stim.dur, stim.delay = Is, Is_dur, Is_onset apical_stim.amp, apical_stim.dur, apical_stim.delay = Ia, Ia_dur, Ia_onset tuft_stim.amp, tuft_stim.dur, tuft_stim.delay = It, It_dur, It_onset epsp.imax, epsp.tau0, epsp.tau1, epsp.onset = Id_max, Id_rise, Id_decay, Id_onset pulses.delay, pulses.dur, pulses.per, pulses.num, pulses.amp = pulses_onset, pulses_dur, pulses_period, pulses_num, pulses_amp h.tstop = simdur - dt h.run() h.load_file('init_models_with_ca/init_model2.hoc') # Set up stimulus stim = h.IClamp(h.soma(0.5)) epsp = h.epsp(h.tuft(0.5)) pulses = h.Ipulse2(h.soma(0.5)) apical_stim = h.IClamp(h.apical(.5)) tuft_stim = h.IClamp(h.tuft(.5)) # Set up recording vectors soma_v_vec = h.Vector() soma_v_vec.record(h.soma(0.5)._ref_v) apical_v_vec = h.Vector() apical_v_vec.record(h.apical(0.5)._ref_v) tuft_v_vec = h.Vector() tuft_v_vec.record(h.tuft(0.5)._ref_v) stim_vec = h.Vector() stim_vec.record(stim._ref_i) epsp_vec = h.Vector() epsp_vec.record(epsp._ref_i) pulse_vec = h.Vector() pulse_vec.record(pulses._ref_i)
h.load_file('init_models_with_ca/init_model2.hoc') default_sca = h.tuft.gbar_sca # Set up stimulus stim = h.Ipulse2(h.soma(.5)) stim.amp = 2 stim.dur = 3 stim.delay = 500 stim.per = 10 stim.num = 3 # Set up recording vectors soma_v_vec = h.Vector() soma_v_vec.record(h.soma(.5)._ref_v) apical_end_v_vec = h.Vector() apical_end_v_vec.record(h.apical(1)._ref_v) tuft_v_vec = h.Vector() tuft_v_vec.record(h.tuft(.5)._ref_v) stim_vec = h.Vector() stim_vec.record(stim._ref_i) t_vec = h.Vector() t_vec.record(h._ref_t) # Simulation parameters dt = 0.025 h.tstop = 1000 - dt l = np.array([200, 300, 400, 500, 600]) fig, axes = plt.subplots(3, l.size, sharey='row',
from neuron import h import matplotlib.pyplot as plt import numpy as np h.load_file('init_models_with_ca/init_model2.hoc') h.delete_section(sec=h.axon) h.delete_section(sec=h.iseg) h.delete_section(sec=h.hillock) # Set up stimulus stim = h.SEClamp(h.apical(1)) stim.amp1 = -70 stim.amp2 = -40 stim.amp3 = -70 stim.dur1 = 500 stim.dur3 = 100 # Set up recording vectors apical_end_v_vec = h.Vector() apical_end_v_vec.record(h.apical(1)._ref_v) tuft_v_vec = h.Vector() tuft_v_vec.record(h.tuft(.5)._ref_v) t_vec = h.Vector() t_vec.record(h._ref_t) # Simulation parameters dt = 0.025 h.tstop = 1000 - dt h.tuft.gbar_sca = 0
locations = [0, 0.1, 0.3, 0.5, 0.7, 0.9, 1] probes = [0] * len(locations) # Set up stimulus stim = h.Ipulse2(h.soma(.5)) stim.amp = 2 stim.dur = 3 stim.delay = 500 stim.per = 10 stim.num = 1 # Set up recording vectors for i in range(len(probes)): probes[i] = h.Vector() probes[i].record(h.apical(locations[i])._ref_v) t_vec = h.Vector() t_vec.record(h._ref_t) dt = 0.025 h.tstop = 1000 - dt lengths = np.array([200, 300, 400, 500, 600]) fig, axes = plt.subplots(1, 2, sharex='all', squeeze=False, figsize=(16, 8)) for i in range(lengths.size): h.apical.L = lengths[i] h('recalculate_passive_properties()') h('recalculate_channel_densities()')
h('recalculate_geometry()') h.tuft.gbar_sca = 0 return () h.load_file('init_models_with_ca/init_model2.hoc') h.delete_section(sec=h.axon) h.delete_section(sec=h.iseg) h.delete_section(sec=h.hillock) # Set up stimulus default_amp = -40 default_dur = 10 stim = h.SEClamp(h.apical(1)) stim.amp1 = -70 stim.amp2 = default_amp stim.amp3 = -70 stim.dur1 = 500 stim.dur2 = default_dur stim.dur3 = 100 # Set up recording vectors tuft_v_vec = h.Vector() tuft_v_vec.record(h.tuft(.5)._ref_v) t_vec = h.Vector() t_vec.record(h._ref_t) # Simulation parameters dt = 0.025