title: Primacy versus recency in a quantitative model: activity is the critical distinction.
abstract: Behavioral and neurobiological evidence shows that primacy and recency are subserved by memory systems for intermediate- and short-term memory, respectively. A widely accepted explanation of recency is that in short-term memory, new learning overwrites old learning. Primacy is not as well understood, but many hypotheses contend that initial items are better encoded into long-term memory because they have had more opportunity to be rehearsed. A simple, biologically motivated neural network model supports an alternative hypothesis of the distinct processing requirements for primacy and recency given single-trial learning without rehearsal. Simulations of the model exhibit either primacy or recency, but not both simultaneously. The incompatibility of primacy and recency clarifies possible reasons for two neurologically distinct systems. Inhibition, and its control of activity, determines those list items that are acquired and retained. Activity levels that are too low do not provide sufficient connections for learning to occur, while higher activity diminishes capacity. High recurrent inhibition, and progressively diminishing activity, allows acquisition and retention of early items, while later items are never acquired. Conversely, low recurrent inhibition, and the resulting high activity, allows continuous acquisition such that acquisition of later items eventually interferes with the retention of early items.
authors.affiliation: University of Virginia, Department of Neurosurgery, Charlottesville, Virginia 22908, USA.
authors.forename: A J
authors.initials: AJ
authors.lastname: Greene
authors.forename: C
authors.initials: C
authors.lastname: Prepscius
authors.forename: W B
authors.initials: WB
authors.lastname: Levy
mesh_terms: D000818:Animals; D001519:Behavior / Q000502:physiology; D003071:Cognition / Q000502:physiology; D006801:Humans; D007858:Learning / Q000502:physiology; D008568:Memory / Q000502:physiology*; D008570:Memory, Short-Term / Q000502:physiology; D008959:Models, Neurological; D009433:Neural Inhibition / Q000502:physiology; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology; D012153:Retention, Psychology / Q000502:physiology; D013569:Synapses / Q000502:physiology