Methods for reducing interference in the Complementary Learning Systems model: oscillating inhibition and autonomous memory rehearsal

Human relational memory requires time and sleep

Relational memory, the flexible ability to generalize across existing stores of information, is a fundamental property of human cognition. Little is known, however, about how and when this inferential knowledge emerges. Here, we test the hypothesis that human relational memory develops during offline time periods. Fifty-six participants initially learned five "premise pairs" (A>B, B>C, C>D, D>E, and E>F). Unknown to subjects, the pairs contained an embedded hierarchy (A>B>C>D>E>F). Following an offline delay of either 20 min, 12 hr (wake or sleep), or 24 hr, knowledge of the hierarchy was tested by examining inferential judgments for novel "inference pairs" (B>D, C>E, and B>E). Despite all groups achieving near-identical premise pair retention after the offline delay (all groups, >85%; the building blocks of the hierarchy), a striking dissociation was evident in the ability to make relational inference judgments: the 20-min group showed no evidence of inferential ability (52%), whereas the 12- and 24-hr groups displayed highly significant relational memory developments (inference ability of both groups, >75%; P < 0.001). Moreover, if the 12-hr period contained sleep, an additional boost to relational memory was seen for the most distant inferential judgment (the B>E pair; sleep = 93%, wake = 69%, P = 0.03). Interestingly, despite this increase in performance, the sleep benefit was not associated with an increase in subjective confidence for these judgments. Together, these findings demonstrate that human relational memory develops during offline time delays. Furthermore, sleep appears to preferentially facilitate this process by enhancing hierarchical memory binding, thereby allowing superior performance for the more distant inferential judgments, a benefit that may operate below the level of conscious awareness.

Lexico-semantic structure and the word-frequency effect in recognition memory

The word-frequency effect (WFE) in recognition memory refers to the finding that more rare words are better recognized than more common words. We demonstrate that a familiarity-discrimination model operating on data from a semantic word-association space yields a robust WFE in data on both hit rates and false-alarm rates. Our modeling results suggest that word frequency is encoded in the semantic structure of language, and that this encoding contributes to the WFE observed in item-recognition experiments.

The role of sleep in declarative memory consolidation: passive, permissive, active or none?

Those inclined to relish in scientific controversy will not be disappointed by the literature on the effects of sleep on memory. Opinions abound. Yet refinements in the experimental study of these complex processes of sleep and memory are bringing this fascinating relationship into sharper focus. A longstanding position contends that sleep passively protects memories by temporarily sheltering them from interference, thus providing precious little benefit for memory. But recent evidence is unmasking a more substantial and long-lasting benefit of sleep for declarative memories. Although the precise causal mechanisms within sleep that result in memory consolidation remain elusive, recent evidence leads us to conclude that unique neurobiological processes within sleep actively enhance declarative memories.

Interfering with theories of sleep and memory: sleep, declarative memory, and associative interference

Mounting behavioral evidence in humans supports the claim that sleep leads to improvements in recently acquired, nondeclarative memories. Examples include motor-sequence learning; visual-discrimination learning; and perceptual learning of a synthetic language. In contrast, there are limited human data supporting a benefit of sleep for declarative (hippocampus-mediated) memory in humans (for review, see). This is particularly surprising given that animal models (e.g.,) and neuroimaging studies (e.g.,) predict that sleep facilitates hippocampus-based memory consolidation. We hypothesized that we could unmask the benefits of sleep by challenging the declarative memory system with competing information (interference). This is the first study to demonstrate that sleep protects declarative memories from subsequent associative interference, and it has important implications for understanding the neurobiology of memory consolidation.

An analysis of the mean theta phase of population activity in a model of hippocampal region CA1

In a recent study, Manns et al. (2007) showed that CA1 population spiking activity differs in mean phase between conditions of exposure to stimuli of varying levels of familiarity. Here, we provide an analysis of a computational model of the hippocampus from Hasselmo et al. (2002) to examine how an animal's history of exposures to stimuli affects CA1 population activity. We show how the model can reproduce the major findings from the study by Manns et al. Specifically, we show that differences in direction and magnitude of the mean phase of population activity between two stimuli in the model depend on the order of presentation of the stimuli and the duration of exposure during each presentation. The analyses also reveal that the model's learning rule results in stability and normalization of synaptic weights and show how dysfunction of neuromodulatory systems might lead to epileptic or amnestic type conditions.

Declarative Memory: Sleep Protects New Memories from Interference

Interference is one of the most fundamental phenomena in memory research: acquiring new memories causes forgetting of other, related memories. A new study shows that sleep, interposed between learning episodes, can mitigate the extent to which new (post-sleep) learning interferes with recall of previously acquired knowledge.