Metalearning is a neuroscientific term proposed by Kenji Doya,[1] as a theory for how neurotransmitters facilitate distributed learning mechanisms in the Basal Ganglia.
[2] The theory emerged from efforts to unify the dynamic selection process for these three learning algorithms to a regulatory mechanism reducible to individual neurotransmitters.
In this way, dopamine is involved in a learning algorithm in which Actor, Environment and Critic are bound in a dynamic interplay that ultimately seeks to maximise the sum of future rewards by producing an optimal action selection policy.
At lower levels of Norepinephrine, plastic changes are proposed to occur much more slowly, potentially being protective against unhelpful learning conditions or allowing for information changes to embody a much broader temporal resolution.
The investigation of Metalearning as a neuroscientific concept has potential benefits to both the understanding and treatment of Psychiatric Disease, as well as bridging the gaps between Neural Networks, Computer Science and Machine Learning.