A unitary signal-detection model of implicit and explicit memory

doi:10.1016/j.tics.2008.06.005

Trends in Cognitive Sciences

Volume 12, Issue 10, October 2008, Pages 367-373

https://doi.org/10.1016/j.tics.2008.06.005 Get rights and content

Do dissociations imply independent systems? In the memory field, the view that there are independent implicit and explicit memory systems has been predominantly supported by dissociation evidence. Here, we argue that many of these dissociations do not necessarily imply distinct memory systems. We review recent work with a single-system computational model that extends signal-detection theory (SDT) to implicit memory. SDT has had a major influence on research in a variety of domains. The current work shows that it can be broadened even further in its range of application. Indeed, the single-system model that we present does surprisingly well in accounting for some key dissociations that have been taken as evidence for independent implicit and explicit memory systems.

Section snippets

Implicit and explicit memory

A popular view of memory is that there are functionally and neuroanatomically distinct explicit and implicit memory systems in the brain 1, 2. Explicit (declarative) memory is thought to be accessible to awareness, whereas the contents of implicit (non-declarative) memory are unconscious. The majority of evidence in favour of this ‘multiple-systems’ view has attempted to show that performance on particular tasks, thought to be driven by either implicit or explicit memory, can be dissociated

Functional dissociations

Consider the often reported dissociation that a manipulation affects recognition but has little or no effect on priming. In normal adults, examples of variables that produce this result are depth of processing manipulations (e.g. making a semantic versus non-semantic judgment about a word at encoding) 9, 10 or attentional manipulations (e.g. encoding words with or without a concurrent distractor task) [11]. A common interpretation of this dissociation is that explicit memory is selectively

Amnesia

Damage to the medial temporal lobe (MTL)/hippocampal regions results in amnesia and impairments in recognition, but leaves priming relatively unaffected (compared with controls). This striking dissociation is often considered to be the most compelling evidence for the multiple-systems view. From a multiple-systems perspective, it indicates that the MTL is the site of an explicit memory system that drives recognition but not priming (see also Box 3). Furthermore, Conroy et al. [17] recently

Within-item/group dissociations and stochastic independence

A common practice in priming and recognition research is to select a subset of items from the test phase that were not recognized, and to then show that a priming effect still exists for these items (e.g. Ref. [21]). It might then be concluded that the sources of memory that drive priming and recognition are independent because, if the same source of memory drives priming and recognition, why would priming occur for particular items in the absence of recognition? This result happens to fall

Conclusions

The endeavour to obtain dissociations between priming and recognition has yielded many interesting findings. However, as we 7, 8 and others 4, 5, 6 have shown, many dissociations can be explained without postulating independent memory systems or independent sources of memory. Formal models have been crucial in demonstrating this point, and we believe that they should be used to a greater extent to drive implicit and explicit memory research, as has been the case in theories of recognition (Box 1

Acknowledgements

Preparation for this article was supported by a UK Economic and Social Research Council (ESRC) grant, RES-063–27–0127, and by the Medical Research Council (WBSE U.1055.05.012.00001.01).

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The greater this signal for an item, the more likely it is to have a relatively fast identification RT and to be judged old with greater confidence. Other experimental work has confirmed specific predictions of this model, and the model can also explain the differential effect that some variables such as attention, amnesia, and aging have on recognition and priming (e.g. Berry, Henson, & Shanks, 2006; Berry et al., 2014; Berry et al., 2008a, 2008b; Berry, Shanks, Li, Rains, & Henson, 2010; Berry, Ward, & Shanks, 2017; Ward, Berry, & Shanks, 2013; see Shanks & Berry, 2012, for a review). Formal model comparisons have also shown that the single-system model tends to outperform a variety of multiple-systems models in which distinct memory signals drive performance in priming and recognition tasks (Berry et al., 2012).
We present new behavioral data and modeling that links priming, recognition, and source memory. In four experiments, we found that the magnitude of the priming effect, as measured with identification response time in a gradual clarification task, was (1) greater for studied items receiving correct source decisions than incorrect source decisions, and (2) increased as confidence in the source decision increased. Building on the framework for modeling recognition and priming proposed by Berry, Shanks, Speekenbrink, and Henson (2012), we developed a single-system model in which source memory decisions are driven by the same memory strength signal as recognition and priming. We formally compare the model against a multiple-systems model, in which the (implicit) memory signal driving priming is distinct to the (explicit) one driving recognition and source memory. The single-system model reproduces the qualitative patterns of the association between source memory and priming better than the multiple-systems model. Comparison of the quantitative fits was not as clear-cut, however: the single-system model tended to fit better in Experiments 1 and 2, but not in Experiments 3A and 3B, where the observed association between priming and recognition was weaker. Our investigation is an initial attempt at linking priming, recognition, and source memory in the same modelling framework, and provides a basis for further exploration and refinement.
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Although behavioral studies have consistently reported the spacing effect in learning, its cognitive and neural mechanisms are still not clearly elucidated. According to the storage/retrieval strength framework proposed by Bjork (1999; Bjork & Bjork, 1992), which was built on the study-phase retrieval hypothesis and the deficient processing hypothesis, the spacing effect is achieved by reducing memomtary retrieval strength during subsequent repetitions and thus enhancing storage strength. The present study tested this hypothesis with parallel fMRI and EEG. Participants were asked to study 180 words that were repeated three times, with half of the words having an inter-repetition-lag of 1–3 words (i.e., massed learning) and the other half an inter-repetition-lag of 25–35 words (i.e., spaced learning). An unexpected recognition test was administered 24 h after learning. Consistent with Bjork's hypothesis, the EEG data suggested that spaced learning was associated with weaker retrieval strength, as indicated by a reduced familiarity effect in frontal N400. Meanwhile, spaced learning effectively enhanced the encoding process and thus led to stronger storage strength, as indicated by greater fMRI responses during learning in brain regions whose activities were associated with subsequent memory. Interestingly, no direct association was found between repetition priming and episodic memory. These results furthered our understanding of the neural mechanisms underlying the spacing effect.
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Nevertheless, fMRI studies have also revealed that MTL activity can differentiate memory signals that are not consciously accessible to subject's explicit reports of recognition (Daselaar et al., 2006b; Hannula and Ranganath, 2009; Kirwan et al., 2009a; Manns and Squire, 2001), raising the possibility that the hippocampus may play a more critical role in implicit memory than the idiosyncratic role typically ascribed (e.g.: Corkin, 2002; for review see Hannula and Greene (2012)). In line with this, some models have proposed the hippocampus to be a common substrate for forms of both implicit and explicit memory processing (Berry et al., 2008a,b, 2012; Cermak, 1997; Moscovitch, 2008; Reber, 2013; Sheldon and Moscovitch, 2010; Taylor and Henson, 2012), but this has yet to be experimentally confirmed in human lesion studies. Studies of implicit memory in neuropsychological patients have been essential to current models of memory (Chun and Phelps, 1999; Corkin, 2002; Gabrieli et al., 1999; Hamann and Squire, 1997; Rosenbaum et al., 2014; Schacter and Church, 1995; Schacter and Graf, 1986), but have also been limited by a heavy reliance upon behavioral methods, and more broadly by challenges to isolating implicit memory effects independent from explicit memory activity (for discussion, see Voss et al. (2012)).
The hippocampus has traditionally been thought to be critical for conscious explicit memory but not necessary for unconscious implicit memory processing. In a recent study of a group of mild amnesia patients with evidence of MTL damage limited to the hippocampus, subjects were tested on a direct test of item recognition confidence while electroencephalogram (EEG) was acquired, and revealed intact measures of explicit memory from 400 to 600 ms (mid-frontal old–new effect, FN400). The current investigation re-analyzed this data to study event-related potentials (ERPs) of implicit memory, using a recently developed procedure that eliminated declarative memory differences. Prior ERP findings from this technique were first replicated in two independent matched control groups, which exhibited reliable implicit memory effects in posterior scalp regions from 400 to 600 ms, which were topographically dissociated from the explicit memory effects of familiarity. However, patients were found to be dramatically impaired in implicit memory effects relative to control subjects, as quantified by a reliable condition × group interaction. Several control analyses were conducted to consider alternative factors that could account for the results, including outliers, sample size, age, or contamination by explicit memory, and each of these factors was systematically ruled out. Results suggest that the hippocampus plays a fundamental role in aspects of memory processing that are beyond conscious awareness. The current findings therefore indicate that both memory systems of implicit and explicit memory may rely upon the same neural structures – but function in different physiological ways.
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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.
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One of the most fundamental topics in the study of memory is the dissociation between implicit and explicit memory (Graf & Schacter, 1985; Schacter & Tulving, 1994). Most studies have attempted to demonstrate one-to-one correspondence between performances of a certain task and a certain memory (Berry, Shanks, & Henson, 2008). In this view, the priming task is considered to be driven only by implicit memory and the recognition task only by explicit memory.
Previous studies have reported that longer stimulus presentation decreases the magnitude of priming. In the present study, we used meaningless kaleidoscope images, which were reported to minimize conceptual processing, to investigate the mechanism of the phenomenon. We assessed the impact of stimulus duration on perceptual priming (Experiment 1) and implicit recognition memory (Experiment 2). Both the magnitude of priming and the accuracy of implicit recognition were lower with the longer stimulus presentation (350 ms) compared with the shorter presentation (250 ms). This coincidence of temporal dynamics between priming and implicit recognition suggests similar underlying memory mechanisms. In both cases, the decrease of performance with longer presentation can be explained by either changes in perceptual processes or interference from explicit memory retrieval.

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Trends in Cognitive Sciences

OpinionA unitary signal-detection model of implicit and explicit memory

Section snippets

Implicit and explicit memory

Functional dissociations

Amnesia

Within-item/group dissociations and stochastic independence

Conclusions

Acknowledgements

Neurobiol. Learn. Mem.

J. Mem. Lang.

Cognit. Psychol.

Conscious. Cogn.

J. Mem. Lang.

Trends Cogn. Sci.

Trends Cogn. Sci.

Prog. Neurobiol.

Trends Cogn. Sci.

Trends Cogn. Sci.

Neuron

Trends Cogn. Sci.

Neuron

Cognitive neuroscience of human memory

Annu. Rev. Psychol.

Implicit memory in normal human subjects

Amnesia and the declarative/procedural distinction: a recurrent network model of classification, recognition, and repetition priming

J. Cogn. Neurosci.

Neuropsychological dissociations between priming and recognition: a single-system connectionist account

Psychol. Rev.

Categorization and recognition performance of a memory-impaired group: evidence for single-system models

J. Int. Neuropsychol. Soc.

A single-system account of the relationship between priming, recognition, and fluency

J. Exp. Psychol. Learn. Mem. Cogn.

On the relationship between autobiographical memory and perceptual learning

J. Exp. Psychol. Gen.

A revaluation of semantic versus nonsemantic processing in implicit memory

Mem. Cogn.

On the differential nature of implicit and explicit memory

Mem. Cogn.

A method for judging measures of stochastic dependence: further comments on the current controversy

J. Exp. Psychol. Learn. Mem. Cogn.

Discovering functionally independent mental processes: the principle of reversed association

Psychol. Rev.

Investigating dissociations among memory measures: support for a transfer-appropriate processing framework

J. Exp. Psychol. Learn. Mem. Cogn.

Opinion
A unitary signal-detection model of implicit and explicit memory