hnn_core.Cell¶

class hnn_core.Cell(name, pos, sections, synapses, topology, sect_loc, gid=None)[source]¶

Create a cell object.

Parameters

namestr: The name of the cell.
postuple: The (x, y, z) coordinates.
sectionsdict of Section: Dictionary with keys as section name.
synapsesdict of dict: Keys are name of synaptic mechanism. Each synaptic mechanism has keys for parameters of the mechanism, e.g., ‘e’, ‘tau1’, ‘tau2’.
topologylist of list: The topology of cell sections. Each element is a list of 4 items in the format [parent_sec, parent_loc, child_sec, child_loc] where parent_sec and parent_loc are float between 0 and 1 specifying the location in the section to connect and parent_sec and child_sec are names of the connecting sections.
sect_locdict of list: Can have keys ‘proximal’ or ‘distal’ each containing names of section locations that are proximal or distal.
gidint or None (optional): Each cell in a network is uniquely identified by it’s “global ID”: GID. The GID is an integer from 0 to n_cells, or None if the cell is not yet attached to a network. Once the GID is set, it cannot be changed.

Examples

>>> section_soma = Section(
        L=39,
        diam=20,
        cm=0.85,
        Ra=200.,
        end_pts=[[0, 0, 0], [0, 39., 0]]
    )

Attributes

poslist of length 3: The position of the cell.
sectionsnested dict: The section parameters. The key is the name of the section and the value is a dictionary parametrizing the morphology of the section and the mechanisms inserted.
synapsesdict: The synapses that the cell can use for connections.
dipole_pplist of h.Dipole(): The Dipole objects (see dipole.mod).
vsecdict: Recording of section specific voltage. Must be enabled by running simulate_dipole(net, record_vsec=True) or simulate_dipole(net, record_vsoma=True)
isecdict: Contains recording of section specific currents indexed by synapse type (keys can be soma_gabaa, soma_gabab etc.). Must be enabled by running simulate_dipole(net, record_isec=True) or simulate_dipole(net, record_isoma=True)
tonic_biaseslist of h.IClamp: The current clamps inserted at each section of the cell for tonic biasing inputs.
gidint: GID of the cell in a network (or None if not yet assigned)
sect_locdict of list: Can have keys ‘proximal’ or ‘distal’ each containing names of section locations that are proximal or distal.

Methods

`build`([sec_name_apical])	Build cell in Neuron and insert dipole if applicable.
`copy`()	Return copy of instance.
`create_tonic_bias`(amplitude, t0, tstop[, loc])	Create tonic bias at the soma.
`modify_section`(sec_name[, L, diam, cm, Ra])	Change attributes of section specified by sec_name
`parconnect_from_src`(gid_presyn, nc_dict, ...)	Parallel receptor-centric connect FROM presyn TO this cell,
`plot_morphology`([ax, cell_types, show])	Plot the cell morphology.
`record`([record_vsec, record_isec])	Record current and voltage from all sections
`setup_source_netcon`(threshold)	Created for _PC.cell and specifies SOURCES of spikes.
`syn_create`(secloc, e, tau1, tau2)	Create an h.Exp2Syn synapse.

__repr__()[source]¶: Return repr(self).

build(sec_name_apical=None)[source]¶

Build cell in Neuron and insert dipole if applicable.

Parameters

sec_name_apicalstr | None: If not None, a dipole will be inserted in this cell in alignment with this section. The section should belong to the apical dendrite of a pyramidal neuron.

copy()[source]¶: Return copy of instance.

create_tonic_bias(amplitude, t0, tstop, loc=0.5)[source]¶

Create tonic bias at the soma.

Parameters

amplitudefloat: The amplitude of the input.
t0float: The start time of tonic input (in ms).
tstopfloat: The end time of tonic input (in ms).
locfloat (0 to 1): The location of the input in the soma section.

modify_section(sec_name, L=None, diam=None, cm=None, Ra=None)[source]¶

Change attributes of section specified by sec_name

Parameters

sec_namestr: Name of section to be modified. Must be a key of Cell.sections
Lfloat | int | None: length of a section in microns. Default None.
diamfloat | int | None: diameter of a section in microns.
cmfloat | int | None: membrane capacitance in micro-Farads.
Rafloat | int | None: axial resistivity in ohm-cm.

Notes

Leaving default of None produces no change.

parconnect_from_src(gid_presyn, nc_dict, postsyn, inplane_distance)[source]¶

Parallel receptor-centric connect FROM presyn TO this cell,: based on GID.

Parameters

gid_presynint: The cell ID of the presynaptic neuron
nc_dictdict: Dictionary with keys: pos_src, A_weight, A_delay, lamtha Defines the connection parameters
postsyninstance of h.Exp2Syn: The postsynaptic cell object.
inplane_distancefloat: The in plane-distance (in um) between pyramidal cell somas in the square grid.

Returns

ncinstance of h.NetCon: A network connection object.

plot_morphology(ax=None, cell_types=None, show=True)[source]¶

Plot the cell morphology.

Parameters

axinstance of Axes3D: Matplotlib 3D axis
showbool: If True, show the plot

Returns

axesinstance of Axes3D: The matplotlib 3D axis handle.

record(record_vsec=False, record_isec=False)[source]¶

Record current and voltage from all sections

Parameters

record_vsec‘all’ | ‘soma’ | False: Option to record voltages from all sections (‘all’), or just the soma (‘soma’). Default: False.
record_isec‘all’ | ‘soma’ | False: Option to record voltages from all sections (‘all’), or just the soma (‘soma’). Default: False.

setup_source_netcon(threshold)[source]¶

Created for _PC.cell and specifies SOURCES of spikes.

Parameters

thresholdfloat: The voltage threshold for action potential.

syn_create(secloc, e, tau1, tau2)[source]¶

Create an h.Exp2Syn synapse.

Parameters

seclocinstance of nrn.Segment: The section location. E.g., soma(0.5).
e: float: Reverse potential (in mV)
tau1: float: Rise time (in ms)
tau2: float: Decay time (in ms)

Returns

syninstance of h.Exp2Syn: A two state kinetic scheme synapse.