PulseDecisionMaking#
- class braintools.cogtask.PulseDecisionMaking(t_fixation=Quantity(500., 'ms'), t_cue=Quantity(100., 'ms'), t_delay=Quantity(240., 'ms'), num_pulses=7, t_response=Quantity(150., 'ms'), num_choices=2, pulse_values=(-0.08, -0.04, -0.02, -0.01, 0.01, 0.02, 0.04, 0.08), **kwargs)[source]#
Pulse-Based Decision Making task.
Agent accumulates evidence from discrete pulses. Each pulse provides a small amount of evidence for one direction.
Structure: Fixation >> (Cue >> Delay) * N >> Response
- Parameters:
t_fixation (
Quantity) – Fixation duration (default: 500ms).t_cue (
Quantity) – Duration of each cue pulse (default: 100ms).t_delay (
Quantity) – Delay between pulses (default: 240ms).num_pulses (
int) – Number of evidence pulses (default: 7).t_response (
Quantity) – Response duration (default: 150ms).num_choices (
int) – Number of choices (default: 2).pulse_values (
Sequence[float]) – Possible evidence values (positive = choice 1, negative = choice 0) (default: (-0.08, -0.04, -0.02, -0.01, 0.01, 0.02, 0.04, 0.08)).seed (int, optional) – Random seed.
Examples
>>> task = PulseDecisionMaking() >>> X, Y, info = task.sample_trial(0)
- define_features()[source]#
Define input and output features.
Override in subclass for class-based task definition.
- Return type:
- Returns:
input_features (Feature or FeatureSet) – Input feature definitions.
output_features (Feature or FeatureSet) – Output feature definitions.