Prefrontal cortex basal ganglia working memory

Prefrontal cortex basal ganglia working memory (PBWM) is an algorithm that models working memory in the prefrontal cortex and the basal ganglia.[1]

It can be compared to long short-term memory (LSTM) in functionality, but is more biologically explainable.[1][2]

It uses the primary value learned value model to train prefrontal cortex working-memory updating system, based on the biology of the prefrontal cortex and basal ganglia.[3]

It is used as part of the Leabra framework and was implemented in Emergent in 2019.

  1. ^ a b O'Reilly, R.C & Frank, M.J. (2006). "Making Working Memory Work: A Computational Model of Learning in the Frontal Cortex and Basal Ganglia". Neural Computation. 18 (2): 283–328. doi:10.1162/089976606775093909. PMID 16378516. S2CID 8912485.
  2. ^ Jeevanandam, Nivash (2021-09-13). "Underrated But Fascinating ML Concepts #5 – CST, PBWM, SARSA, & Sammon Mapping". Analytics India Magazine. Retrieved 2021-12-04.
  3. ^ "Leabra PBWM". CCNLab.