Recognition memory and the hippocampus: A test of the hippocampal contribution to recollection and familiarity

Jeneson, Annette; Kirwan, C. Brock; Hopkins, Ramona O.; Wixted, John T.; Squire, Larry R.

doi:10.1101/lm.1546110

Cited by 37 publications

(46 citation statements)

References 42 publications

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“…In that study, the slope of the ROC was greater than 1, even when overall memory performance was very good (e.g., dЈ Ͼ 2). Jeneson et al (2010) suggested that the lure distribution may have equal or greater variance than the target distribution under these conditions because the lures are associated with both recall-to-reject (when the incorrect detail is recollected, adding to high-confidence correct rejections when recollection is strong) and recall-to-accept (when the incorrect detail is not noticed but other thoughts about the item are recollected, adding to high-confidence false alarms when recollection is strong). This would have the effect of increasing the variance of the lure distribution relative to the target distribution, for which only a recall-to-accept process would apply.…”

Section: Resultsmentioning

confidence: 99%

Strong memories are hard to scale.

Mickes

Hwe²,

Wais³

et al. 2011

Journal of Experimental Psychology: General

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People are generally skilled at using a confidence scale to rate the strength of their memories over a wide range. Specifically, low-confidence recognition decisions are often associated with close-to-chance accuracy, whereas high-confidence recognition decisions can be associated with close-to-perfect accuracy. However, using a 20-point rating scale, the authors found that the ability to scale memory strength had its limitations in that a high proportion of list items received the highest rating of 20. Efforts to induce participants to differentiate between these strong memories using emphatic instructions and alternative scales were not successful. Remember/know judgments indicated that these strong and hard-to-scale memories were often based on familiarity (not just recollection). Providing error feedback on a plurals discrimination task finally produced a high-confidence criterion shift. The authors suggest that the ability to scale strong (and almost perfectly accurate) memories may be limited because of the absence of differential error feedback for very strong memories in the past (the kind of differential error feedback that may account for the memory-scaling expertise that participants otherwise exhibit).Keywords: recognition memory, confidence and accuracy, signal-detection theory, feedbackMemories vary in strength, and people are generally quite adept at using a numerical confidence scale to indicate how strong different memories are. This ability is most apparent in studies of recognition memory, in which accuracy is typically strongly related to confidence (Ratcliff & Murdock, 1976). Mickes, Wixted, and Wais (2007) showed that the strong relationship between confidence and accuracy extends over a wider range than had been previously investigated. In that study, participants completed a standard recognition memory test during which targets and lures were presented one at a time, and participants were asked to rate each item using a 20-point scale. A rating of 1 indicated 100% certainty that the item was new, and a rating of 20 indicated 100% certainty that the item was old. Intermediate ratings indicated varying degrees of lesser certainty, with ratings of 10 and 11 indicating complete uncertainty that the item was new (10) or old (11). As shown in Figure 1, participants were very accurate when confidence was high (i.e., for ratings of 1 or 20), and accuracy declined in continuous fashion to chance levels as confidence decreased to complete uncertainty (toward the middle of the scale). Thus, as a general rule, participants are able to use a confidence scale to provide valid ratings of the strength of their memories. The fact that participants exhibit this expertise without being trained by the experimenter is a key consideration for the memory scaling issue that is the main focus of this article. Figure 2a illustrates one interpretation of these results in terms of the standard unequal-variance signal-detection model. According to this account, items vary in memory strength, with the mean and varianc...

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Section: Resultsmentioning

confidence: 99%

Strong memories are hard to scale.

Mickes

Hwe²,

Wais³

et al. 2011

Journal of Experimental Psychology: General

Self Cite

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“…Whereas many studies report a disproportionate effect of hippocampal damage on recollection and associative memory relative to familiarity (Huppert and Piercy 1978;VarghaKhadem et al 1997;Holdstock et al 2002;Yonelinas et al 2002;Giovanello et al 2003;Mayes et al 2004;Aggleton et al 2005), other reports find that hippocampal damage impacts familiarity and recollection to a similar extent (Manns and Squire 1999;Stark et al 2002;Manns et al 2003;Cipolotti et al 2006;Wais et al 2006;Jeneson et al 2010;Kirwan et al 2010;Song et al 2011). Interestingly, a patient with significant perirhinal damage that spared the hippocampus showed impaired familiarity and preserved recollection (Bowles et al 2007).…”

Section: Hippocampus and Mtlmentioning

confidence: 99%

Memory Retrieval in Mice and Men

Ben-Yakov

Dudai

Mayford

2015

Cold Spring Harb Perspect Biol

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Retrieval, the use of learned information, was until recently mostly terra incognita in the neurobiology of memory, owing to shortage of research methods with the spatiotemporal resolution required to identify and dissect fast reactivation or reconstruction of complex memories in the mammalian brain. The development of novel paradigms, model systems, and new tools in molecular genetics, electrophysiology, optogenetics, in situ microscopy, and functional imaging, have contributed markedly in recent years to our ability to investigate brain mechanisms of retrieval. We review selected developments in the study of explicit retrieval in the rodent and human brain. The picture that emerges is that retrieval involves coordinated fast interplay of sparse and distributed corticohippocampal and neocortical networks that may permit permutational binding of representational elements to yield specific representations. These representations are driven largely by the activity patterns shaped during encoding, but are malleable, subject to the influence of time and interaction of the existing memory with novel information.

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“…Functional MTL accounts have prominently focused on psychologically distinct processes underlying recognition memory, i.e., recollection and familiarity: PRC is thought to support familiarity and a PHC-HC network is thought to support recollection (Eichenbaum et al, 2007;Yonelinas et al, 2010). However, Squire and colleagues propose a more unified account of MTL memory processes Wixted and Squire, 2011), in which HC as well as PRC may support both processes, and, in HC patient studies, report memory and learning deficits across processes (Jeneson et al, 2010) and stimulus content (Shrager et al, 2007;Kim et al, 2011). In a recent neuroanatomy-based approach (Wixted and Squire, 2011), they suggested that MTL subregions may process different attributes of memory (see also Squire et al, 2007).…”

Section: Implications For Functional Mtl Modelsmentioning

confidence: 99%

Direct Evidence for Domain-Sensitive Functional Subregions in Human Entorhinal Cortex

Schultz

Sommer²,

Peters³

2012

J. Neurosci.

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The medial temporal lobes (MTL) are known to play a crucial role in memory processes. Anatomical findings from animal studies suggest partially segregated MTL pathways converge in the hippocampus, with a posterior stream including parahippocampal and medial lateral entorhinal cortex and an anterior stream including perirhinal and lateral entorhinal cortex. These streams may operate on spatial and nonspatial information, respectively. In humans, such a functional dissociation has been suggested between parahippocampal and perirhinal cortex. Data from rodents and nonhuman primates suggest a similar dissociation between medial and lateral entorhinal cortex, which are reciprocally connected to parahippocampal and perirhinal cortex, but evidence for functional subregions within entorhinal cortex in humans is lacking. We addressed this issue using high-resolution fMRI with improved spatial normalization. Volunteers (n ϭ 28) performed a working memory paradigm involving the retrieval of spatial (scenes) and nonspatial (faces) information after distraction. A clear dissociation between MTL subcircuits emerged. A perirhinal-lateral entorhinal pathway was more involved in the retrieval of faces after distraction, whereas a parahippocampal-medial entorhinal pathway was more involved in the retrieval of scenes after distraction. A cluster in posterior hippocampus showed a deactivation for the retrieval of faces after distraction. Our data thus provide direct evidence for a functional specialization within human entorhinal cortex and thereby strongly support MTL models that emphasize the importance of partially segregated parallel processing streams.

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Recognition memory and the hippocampus: A test of the hippocampal contribution to recollection and familiarity

Cited by 37 publications

References 42 publications

Strong memories are hard to scale.

Strong memories are hard to scale.

Memory Retrieval in Mice and Men

Direct Evidence for Domain-Sensitive Functional Subregions in Human Entorhinal Cortex

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