Interactive activation and competition models and semantic context: From behavioral to brain data

Interactive activation and competition models (IAMs) cannot only account for behavioral data from implicit memory tasks, but also for brain data. We start by a discussion of standards for developing and evaluating cognitive models, followed by example demonstrations. In doing so, we relate IAM representations to word length, sequence, frequency, repetition, and orthographic neighborhood effects in behavioral, electrophysiological, and neuroimaging studies along the ventral visual stream. We then examine to what extent lexical competition can account for anterior cingulate cortex (ACC) activation and the N2/N400 complex. The subsequent section presents the Associative Read-Out Model (AROM), which extends the scope of IAMs by introducing explicit memory and semantic representations. Thereby, it can account for false memories, and familiarity and recollection - explaining why memory signal variances are greater for studied than non-studied items. Since the AROM captures associative spreading across semantic long-term memory, it can also account for different temporal lobe functions, and allows for item-level predictions of the left inferior frontal gyrus' BOLD response. Finally, we use the AROM to examine whether semantic cohesiveness can account for effects previously ascribed to affective word features, i.e. emotional valence, and show that this is the case for positive, but not for negative valence.