32 research outputs found

    Mechanisms of Memory Updating: State Dependency vs. Reconsolidation

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    Reactivating a memory trace has been argued to put it in a fragile state where it must undergo a stabilization process known as reconsolidation. During this process, memories are thought to be susceptible to interference and can be updated with new information. In the spatial context paradigm, memory updating has been shown to occur when new information is presented in the same spatial context as old information, an effect attributed to a reconsolidation process. However, the integration concept holds that memory change can only occur when reactivation and test states are the same, similar to a state-dependent effect. Thus, in human episodic memory, memory updating should only be found when state is the same across the study, reactivation, and test sessions. We investigated whether memory updating can be attributed to state dependency in two experiments using mood as a state. We found evidence of memory updating only when mood was the same across all sessions of the experiments, lending support to the integration concept and posing a challenge to a reconsolidation explanation

    The Effects of working memory on high and low working memory capacity

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    Acute stress is a factor that impairs working memory (McHugh et al.,2010). Emotional stimuli have been used in long-term memory studies. The emotional content of information is important in long-term memory studies that have focused on stress, but it is unknown if the valence of the stimuli matter for working memory tasks. Little research is know to use emotional pictures of N-back stimuli. Our goal is to determine whether these factors may significantly disrupt the working memory process of efficiently completing complex tasks

    The North American tree-ring fire-scar network

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    Fire regimes in North American forests are diverse and modern fire records are often too short to capture important patterns, trends, feedbacks, and drivers of variability. Tree-ring fire scars provide valuable perspectives on fire regimes, including centuries-long records of fire year, season, frequency, severity, and size. Here, we introduce the newly compiled North American tree-ring fire-scar network (NAFSN), which contains 2562 sites, >37,000 fire-scarred trees, and covers large parts of North America. We investigate the NAFSN in terms of geography, sample depth, vegetation, topography, climate, and human land use. Fire scars are found in most ecoregions, from boreal forests in northern Alaska and Canada to subtropical forests in southern Florida and Mexico. The network includes 91 tree species, but is dominated by gymnosperms in the genus Pinus. Fire scars are found from sea level to >4000-m elevation and across a range of topographic settings that vary by ecoregion. Multiple regions are densely sampled (e.g., >1000 fire-scarred trees), enabling new spatial analyses such as reconstructions of area burned. To demonstrate the potential of the network, we compared the climate space of the NAFSN to those of modern fires and forests; the NAFSN spans a climate space largely representative of the forested areas in North America, with notable gaps in warmer tropical climates. Modern fires are burning in similar climate spaces as historical fires, but disproportionately in warmer regions compared to the historical record, possibly related to under-sampling of warm subtropical forests or supporting observations of changing fire regimes. The historical influence of Indigenous and non-Indigenous human land use on fire regimes varies in space and time. A 20th century fire deficit associated with human activities is evident in many regions, yet fire regimes characterized by frequent surface fires are still active in some areas (e.g., Mexico and the southeastern United States). These analyses provide a foundation and framework for future studies using the hundreds of thousands of annually- to sub-annually-resolved tree-ring records of fire spanning centuries, which will further advance our understanding of the interactions among fire, climate, topography, vegetation, and humans across North America

    The Importance of Unitization for Familiarity-Based Learning

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    Evidence of State-Dependent Learning in a Reconsolidation Paradigm

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    Generalizing Reconsolidation: Spatial Context and Prediction Error

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    Activating a previously consolidated memory trace brings it back into a labile state where it must then undergo a re-stabilization process known as reconsolidation. During this process memories are susceptible to interference and may be updated with new information. In the studies showing this effect in human episodic memory, the reconsolidation process has been triggered primarily by using spatial context or prediction error manipulations to reactivate an established memory. However, these studies have produced conflicting results, showing both that spatial context is necessary and sufficient to trigger reconsolidation and that prediction error is necessary and sufficient to trigger the process. We examined this conflict in two experiments, one investigating the role of context cues and another investigating the role of prediction error. In Experiment 1, spatial context triggered a reconsolidation process and prediction error was irrelevant. In Experiment 2, prediction error triggered reconsolidation, and spatial context cues were irrelevant. These findings replicate prior research but add to the puzzle concerning the roles of these two means of triggering reconsolidation

    The Importance of Unitization for Familiarity-Based Learning

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    It is often assumed that recollection is necessary to support memory for novel associations, whereas familiarity supports memory for single items. However, the levels of unitization framework assumes that familiarity can support associative memory under conditions in which the components of an association are unitized (i.e., treated as a single coherent item). In the current study we tested two critical assumptions of this framework. First, does unitization reflect a specialized form of learning or is it simply a form of semantic or elaborative encoding, and, second, can the beneficial effects of unitization on familiarity be observed for across-domain associations or are they limited to creating new associations between items that are from the same stimulus domains? Unitization was found to increase associative recognition but not item recognition. It affected familiarity more than recollection, increased associative but not item priming, and was dissociable from levels of processing effects. Moreover, unitization effects were found to be particularly effective in supporting face-word and fractal-sound pairs. The current results indicate that unitization reflects a specialized form of learning that supports associative familiarity of within- and across-domain associations
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