Content revision 4e771eaf0390cc87b6c7c6fd8469f3508f6ceeec7119472e6c1ccf17e2e1e5d2

## Functional Encoding and Representational Binding in Componential Transfer

Research
Source ID research:encoding
Original https://www.henryw.me/#/research#encoding

Why can a learner demonstrate a rule during training yet fail to use it on a new item? We built a computational account in which transfer depends on how useful components are encoded and bound together. Functional encoding determines which components enter the representation used to generate a response. Representational binding determines whether those components remain available as reusable parts or become fused with the whole stimulus. Varying these properties lets us generate patterns of learning and transfer within one model. Across artificial orthography, Chinese character learning and artificial grammar, tests that preserve a trained component primarily reveal its encoding, while recombination tests reveal how the components are bound.

A continuous binding parameter accounts for patterns previously attributed to two separate systems, connecting those patterns to how knowledge is organised.