bAP

class biophysics_fitting.hay.evaluation.bAP(soma_thresh=-30, stim_onset=295, stim_duration=5, bAP_thresh='+2mV', punish=250.0, punish_last_spike_after_deadline=True, punish_minspikenum=1, punish_returning_to_rest_tolerance=2.0, definitions=HAY_BAP_DEFINITIONS)

Evaluate the \(bAP\) stimulus protocol.

These metrics were introduced by Hay et al. [2], and illustrated in Bast et al. [3].

See also

biophysics_fitting.setup_stim.setup_bAP() for more information on the stimulus protocol.

Parameters:
soma_thresh : float

The threshold for APs in the somatic voltage trace. Defaults to \(-30\ mV\).

stim_onset : float

The onset of the stimulus (\(ms\)). Defaults to \(295\ ms\).

stim_duration : float

The duration of the stimulus (\(ms\)). Defaults to \(5\ ms\).

bAP_thresh : float

The threshold for the backpropagating action potential. Defaults to \(+2\ mV\).

punish : float

The punishment value in units of \(\sigma\). Used as a baseline if the voltage trace cannot be evaluated on a metric (e.g. if it does not contain an AP). Defaults to \(250 \sigma\).

punish_last_spike_after_deadline : bool

Whether to punish if the last spike is after the deadline. Defaults to True

punish_minspikenum : int

The minimum number of spikes required for this stimulus protocol. Defaults to \(1\).

punish_returning_to_rest_tolerance : float

The tolerance for returning to rest (\(mV\)). Defaults to \(2 mV\).

definitions : dict

The definitions for the evaluation metrics. See also: definitions.

Attributes:
soma_thresh

The threshold for APs in the somatic voltage trace. Defaults to \(-30\) mV.

Type:

float

stim_onset

The onset of the stimulus (ms). Defaults to \(295\) ms.

Type:

float

stim_duration

The duration of the stimulus (ms). Defaults to \(5\) ms.

Type:

float

bAP_thresh

The threshold for the backpropagating action potential. Defaults to \(+2\) mV.

Type:

float

punish

The punishment value in units of \(\sigma\). Used as a baseline if the voltage trace cannot be evaluated on a metric (e.g. if it does not contain an AP). Defaults to \(250 \sigma\).

Type:

float

punish_last_spike_after_deadline

Whether to punish if the last spike is after the deadline. Defaults to True

Type:

bool

punish_minspikenum

The minimum number of spikes required for this stimulus protocol.

Type:

int

punish_returning_to_rest_tolerance

The tolerance for returning to rest (\(mV\)). Defaults to \(2 mV\).

Type:

float

definitions

The empirical means and standard deviations for the evaluation metrics. Defaults to:

{
    'bAP_APheight': ('AP_height', 25.0, 5.0),
    'bAP_APwidth': ('AP_width', 2.0, 0.5),
    'bAP_att2': ('BPAPatt2', 45.0, 10.0),
    'bAP_att3': ('BPAPatt3', 36.0, 9.33),
    'bAP_spikecount': ('Spikecount', 1.0, 0.01)
}

Here, the format of each line is: ``acronym: [full name, mean, std]``
Type:

dict

Methods:

get(**voltage_traces)

Get the full evaluation of the voltage traces for bAP firing.

check(out, voltage_traces)

Check for problems in the voltage trace.

bAP_APheight(voltage_traces)

Get the height of the first action potential in the somatic voltage trace.

bAP_APwidth(voltage_traces)

Get the width of the first action potential in the somatic voltage trace.

bAP_spikecount(voltage_traces)

Get the number of spikes in the somatic voltage trace.

_bAP_att(voltage_traces, _n)

Get the backpropagating action potential attenuation.

bAP_att2(voltage_traces)

Get the backpropagating action potential attenuation between the soma and first dendritic pipette location.

bAP_att3(voltage_traces)

Get the backpropagating action potential attenuation between the soma and second dendritic pipette location.