iblrig.base_choice_world.ActiveChoiceWorldSession

class iblrig.base_choice_world.ActiveChoiceWorldSession

The ActiveChoiceWorldSession is a base class for protocols where the mouse is actively making decisions by turning the wheel. It has the following characteristics

• it is trial based

• it is decision based

• left and right simulus are equiprobable: there is no biased block

• a trial can either be correct / error / no_go depending on the side of the stimulus and the response

• it has a quantifiable performance by computing the proportion of correct trials of passive stimulations protocols or habituation protocols.

The TrainingChoiceWorld, BiasedChoiceWorld are all subclasses of this class

TrialDataModel

alias of ActiveChoiceWorldTrialData

__init__(**kwargs)

show_trial_log(extra_info=None, log_level=20)

Parameters:

• extra_info (dict[str, Any] | None)

• log_level (int)

trial_completed(bpod_data)

Update the trials table with information about the behaviour coming from the bpod.

Constraints on the state machine data:

• mandatory states: [‘correct’, ‘error’, ‘no_go’, ‘reward’]

• optional states : [‘omit_correct’, ‘omit_error’, ‘omit_no_go’]

Parameters:

bpod_data (dict) – The Bpod data as returned by pybpod

Raises:

AssertionError – If the position is zero or if the number of detected outcomes is not exactly one.

Parameters:

bpod_data (dict)

Return type:

None