Associative and temporal learning: new directions

Associative and temporal learning are fundamental properties of behavior. Despite the temporal dynamics of behavior, traditional associative (trial based) approaches have often ignored (within trial) timing properties of behavior. Therefore, associative and temporal learning are considered different, parallel strategies, whose mechanisms and rules are domain-specific. The rift between the two fields is not surprising considering the difference in questions, measures, and approaches. Some questions explored in this mini-review are as follows: Are the behavioral phenomena appropriately described, measured or quantified? How do animals integrate associative and temporal information? What are the behavioral processes that bridge the associative and temporal fields? How are associative and temporal information instantiated and processed in the brain? A resolution involves finding a more adept way (e.g., computational or biological) to describe the associative and temporal phenomena, for example by transforming them in a more abstract dimension, such as information (e.g., entropy calculation) or frequency (e.g., neural firing). When seen from this neural-computation vantage point, the distinctions between associative and temporal learning vanish, and the question becomes: What are the mechanisms that coexist, cooperate and compete in a brain that processes associative and temporal information in real time? This article is part of a Special Issue entitled: Associative and Temporal Learning.