MotorTiming-v0

class neurogym.envs.readysetgo.MotorTiming(dt=80, rewards=None, timing=None, prod_margin=0.2)

Agents have to produce different time intervals using different effectors (actions).

Parameters:

prod_margin – controls the interval around the ground truth production time within which the agent receives proportional reward

Reference paper

Flexible timing by temporal scaling of cortical responses

Tags

timing, go-no-go, supervised

Supervised learning and analysis of this task

[Open in colab] [Jupyter notebook Source]

Reinforcement learning and analysis of this task

[Open in colab] [Jupyter notebook Source]

Sample run