Associative Learning, from Conceptualization to Implementation

Two main commitments appear in Rey's Unified Radical Associationism: 1) using Hebbian learning as a unified computational framework in psychological science, 2) using associations as a unique construct to account for mental activities. Hebbian learning has been shown to account for complex behavioral repertoires in experimental paradigms coming from different psychological traditions. Here we review the processing mechanisms underlying such a complex repertoire, we suggest two additional points to extend the associationist hypothesis, and we point to the need to understand how implemented associative learning mechanisms are balanced and modulated. We believe these points are key for future research to support or question both commitments in Rey's Unified Radical Associationism.