def test_get_multi_dipole_potential01(self):
morphology = os.path.join(LFPy.__path__[0], 'test',
'ball_and_sticks.hoc')
electrode_locs = np.array([[0., 0., 10000.]])
cell, electrode = cell_w_synapse_from_sections_w_electrode(
morphology, electrode_locs)
sigma = 0.3
t_point = 0
MD_inf = LFPy.InfiniteVolumeConductor(sigma)
pot_MD = MD_inf.get_multi_dipole_potential(cell, electrode_locs)
pot_cb = electrode.LFP
np.testing.assert_almost_equal(pot_MD, pot_cb)
np.testing.assert_allclose(pot_MD, pot_cb, rtol=1E-3)
def test_calc_potential(self):
'''test comparison between four-sphere model and model for
infinite homogeneous space
when sigma is constant and r4 goes to infinity'''
sigmas = [0.3, 0.3, 0.3 + 1e-16, 0.3]
radii = [10., 20 * 1e6, 30. * 1e6, 40. * 1e6]
rz = np.array([0., 0., 3.])
p = np.array([[0., 0., 100.], [50., 50., 0.]])
r_elec = np.array([[0., 0., 9.], [0., 0., 15.], [0., 0., 25.],
[0., 0., 40.], [0., 9., 0.], [0., 15., 0.],
[0., 25., 0.], [0., 40., 0.]])
four_s = LFPy.FourSphereVolumeConductor(radii, sigmas, r_elec)
pots_4s = four_s.calc_potential(p, rz)
inf_s = LFPy.InfiniteVolumeConductor(0.3)
pots_inf = inf_s.get_dipole_potential(p, r_elec - rz)
np.testing.assert_allclose(pots_4s, pots_inf, rtol=1e-6)
def make_data(morphology,
syninds,
dip_loc=None,
cell_model=None,
x_rot=0,
y_rot=0,
z_rot=0,
active=False):
sigma = 0.3 #extracellular conductivity
k = 1e6 # convert from mV to nV
# compute LFP close to neuron
# set up electrodes close to neuron
X, Z = np.meshgrid(np.linspace(-550, 550, 101),
np.linspace(-250, 850, 101))
Y = np.zeros(X.shape)
# simulate cell
(cell_parameters, synapse_parameters,
grid_electrode_parameters) = set_parameters(morphology,
X,
Y,
Z,
sigma=sigma,
cell_model=cell_model)
cell, synapse, grid_electrode_LFP = simulate(cell_parameters,
synapse_parameters,
grid_electrode_parameters,
syninds,
x_rot=x_rot,
y_rot=y_rot,
z_rot=z_rot,
active=active)
# multicompartment modeling of LFP close to cell
cb_LFP_close = grid_electrode_LFP * k
# multi-dipole modeling of LFP close to cell
multi_dips, multi_dip_locs = cell.get_multi_current_dipole_moments()
inf_vol = LFPy.InfiniteVolumeConductor(sigma)
gridpoints_close = np.array([X.flatten(), Y.flatten(), Z.flatten()]).T
multi_dip_LFP_close = inf_vol.get_multi_dipole_potential(
cell, gridpoints_close) * k
# single-dipole modeling of LFP close to cell
cdm = LFPy.CurrentDipoleMoment(cell)
single_dip = cdm.get_transformation_matrix() @ cell.imem
syninds = cell.synidx
if dip_loc is not None:
r_mid = dip_loc
else:
r_soma_syns = [
cell.get_intersegment_vector(idx0=0, idx1=i) for i in syninds
]
r_mid = np.average(r_soma_syns, axis=0)
r_mid = r_mid / 2. + cell.somapos
db_LFP_close = inf_vol.get_dipole_potential(single_dip,
gridpoints_close - r_mid) * k
# compute LFP far from neuron
# set up electrodes
X_f, Z_f = np.meshgrid(np.linspace(-15000, 15001, 101),
np.linspace(-15000, 15000, 101))
Y_f = np.zeros(X.shape)
grid_electrode_parameters = {
'x': X_f.flatten(),
'y': Y_f.flatten(),
'z': Z_f.flatten()
}
# simulate cell
cell, synapse, grid_electrode_far_LFP = simulate(cell_parameters,
synapse_parameters,
grid_electrode_parameters,
syninds,
x_rot=x_rot,
y_rot=y_rot,
z_rot=z_rot,
active=active)
# multicompartment modeling of LFP far from cell
cb_LFP_far = grid_electrode_far_LFP * k
# multi-dipole modeling of LFP far from cell
gridpoints_far = np.array([X_f.flatten(), Y_f.flatten(), Z_f.flatten()]).T
multi_dip_LFP_far = inf_vol.get_multi_dipole_potential(
cell, gridpoints_far) * k
# single-dipole modeling of LFP far from cell
db_LFP_far = inf_vol.get_dipole_potential(single_dip,
gridpoints_far - r_mid) * k
cdm = LFPy.CurrentDipoleMoment(cell)
single_dip = cdm.get_transformation_matrix() @ cell.imem
time_max = np.argmax(np.abs(np.linalg.norm(single_dip, axis=0)))
LFP_max = 100. #nV #np.round(np.max(np.abs(grid_electrode_LFP[:, time_max])))
return (cell, cb_LFP_close, cb_LFP_far, multi_dip_LFP_close,
multi_dip_LFP_far, db_LFP_close, db_LFP_far, LFP_max, time_max,
multi_dips, multi_dip_locs, single_dip, r_mid, X, Z, X_f, Z_f)