Which Computational Mechanisms Operate in the Hippocampus During Novelty Detection?

A fundamental property of adaptive behavior is the ability to rapidly distinguish what is novel from what is familiar in our environment. Empirical evidence and computational work have provided biologically plausible models of the neural substrate and mechanisms underlying the coding of stimulus novelty in the perirhinal cortex. In this article, we highlight the importance of a different category of novelty, namely associative novelty, which has received relatively little attention, despite its clear ecological importance. While previous studies in both animals and humans have documented hippocampal responses in relation to associative novelty, a key issue concerning the computations underlying these novelty signals has not been previously addressed. We argue that this question has importance not only for our understanding of novelty processing, but also for advancing our knowledge of the fundamental computational operations performed by the hippocampus. We suggest a different approach to this problem, and discuss recent evidence supporting the hypothesis that the hippocampus operates as a comparator during the processing of associative novelty, generating mismatch/novelty signals when prior predictions are violated by sensory reality. We also draw on conceptual similarities between associative novelty and contextual novelty to suggest that empirical findings from these two seemingly distant research fields accord with the operation of a comparator mechanism during novelty detection more generally. We therefore conclude that a comparator mechanism may underlie the role of the hippocampus not only in detecting occurrences that are unexpected given specific associatively retrieved predictions, but also events that violate more abstract properties of the experimental context.