The authors present a computational model that builds a holographic lexicon representing both word meaning and word order from unsupervised experience with natural language. The model uses simple convolution and superposition mechanisms (cf. B. B. Murdock, 1982) to learn distributed holographic representations for words. The structure of the resulting lexicon can account for empirical data from classic experiments studying semantic typicality, categorization, priming, and semantic constraint in sentence completions. Furthermore, order information can be retrieved from the holographic representations, allowing the model to account for limited word transitions without the need for built-in transition rules. The model demonstrates that a broad range of psychological data can be accounted for directly from the structure of lexical representations learned in this way, without the need for complexity to be built into either the processing mechanisms or the representations. The holographic representations are an appropriate knowledge representation to be used by higher order models of language comprehension, relieving the complexity required at the higher level.

this article may be addressed to either Michael Kahana or Robert Sekuler, Volen National Center for Complex Systems, MS 013, Brandeis University, Waltham, MA 02254-9110. E-mail may be sent to kahana @brandeis.edu or sekuler@brandeis.edu plex multidimensional stimulus spaces (Nosofsky, 1992; Maddox & Ashby, 1996; Ashby & Perrin, 1988), with decision rules that can predict performance in a variety of classification paradigms (Nosofsky & Palmeri, 1998; Nosofsky & Alfonso-Reese, 1999; Maddox & Ashby, 1996). Although models of classification and models of visual discrimination share many assumptions about stimulus representation and subjects' decision rules, models of classification have been primarily developed to explain subjects' classification of combinations of simple geometric forms, whereas models of discrimination have been developed to explain subjects ' discrimination of elemental visual stimuli, including sinusoidal luminance gratings. Because such stimuli can be combined to synthesize more complex images such as textures and natural scenes, they represent a natural test-bed for assessing theories' power and generalizability

A model of memory retrieval is described. The model embodies 4 main claims: (a) temporal memory— traces of items are represented in memory partly in terms of their temporal distance from the present; (b) scale-similarity—similar mechanisms govern retrieval from memory over many different timescales; (c) local distinctiveness—performance on a range of memory tasks is determined by interference from near psychological neighbors; and (d) interference-based forgetting—all memory loss is due to interference and not trace decay. The model is applied to data on free recall and serial recall. The account emphasizes qualitative similarity in the retrieval principles involved in memory performance at all timescales, contrary to models that emphasize distinctions between short-term and long-term memory.

The medial temporal lobe (MTL) has been studied extensively at all levels of analysis, yet its function remains unclear. Theory regarding the cognitive function of the MTL has centered along 3 themes. Different authors have emphasized the role of the MTL in episodic recall, spatial navigation, or relational memory. Starting with the temporal context model (M.W. Howard and M. J. Kahana, 2002), a distributed memory model that has been applied to benchmark data from episodic recall tasks, the authors propose that the entorhinal cortex supports a gradually changing representation of temporal context and the hippocampus proper enables retrieval of these contextual states. Simulation studies show this hypothesis explains the firing of place cells in the entorhinal cortex and the behavioral effects of hippocampal lesion in relational memory tasks. These results constitute a first step towards a unified computational theory of MTL function that integrates neurophysiological, neuropsychological and cognitive findings.

In the single-store model of memory, the enhanced recall for the last items in a free-recall task (i.e., the recency effect) is understood to reflect a general property of memory rather than a separate short-term store. This interpretation is supported by the finding of a long-term recency effect under conditions that eliminate the contribution from the short-term store. In this article, evidence is reviewed showing that recency effects in the short and long terms have different properties, and it is suggested that 2 memory components are needed to account for the recency effects: an episodic contextual system with changing context and an activation-based short-term memory buffer that drives the encoding of item–context associations. A neurocomputational model based on these 2 components is shown to account for previously observed dissociations and to make novel predictions, which are confirmed in a set of experiments.

The classic literature presents two opposing views of association: The independent association hypothesis sees associations as unidirectional links between stored items. The associative symmetry hypothesis sees associations as newly formed patterns combining elements of each stored item. Arguing for the symmetry hypothesis, S. Asch & S. Ebenholtz (1962) note that many experiments nd equivalent forward and backward recall of paired associates. Arguing for independent associations, G. Wolford (1971) cite ndings of asymmetric retrieval. A reexamination of the literature reveals that symmetric recall is often observed, but that certain conditions reliably elicit asymmetries. Although robust ndings of asymmetry appear fatal for mathematical memory models that assume symmetric associative mechanisms, careful analyses reveal that these models can account for both material-based and temporal asymmetries, just as models with separate forward and backward associative mechanisms c...

This paper considers the relation between item recognition and cued recall -- two standard measures of episodic memory. Going beyond measures of performance on each task, we examine the degree to which correlations between successful recognition and successful recall of a single studied episode reflect the commonality of memory processes underlying the two tasks. Specifically, we consider whether four computational memory models (local and global match versions of both matrix and convolution-correlation models) can account for the relatively invariant correlation (# 0.5) between successive recognition and recall tests. Whereas basic versions of each model cannot account for the correlation, versions that take into account variability in goodness-of-encoding and in response criteria, as well as output encoding, are able to account for the level of dependency between tasks. These elaborated models also succeeded in fitting data from two new experiments that manipulated the level of variability in goodness-of-encoding across conditions. This model-

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Alzheimer’s disease impairs episodic memory and subtly and progressively robs people of their ability to remember their recent experiences. In this paper, we describe two studies that lead to a better understanding of how caregivers use cues to support episodic memory impairment and what types of cues are best for supporting recollection. We also show how good memory cues differ between people with and without episodic memory impairment. We discuss how this improved understanding impacts the design of lifelogging technologies for automatically capturing and extracting the best memory cues to assist overburdened caregivers and people with episodic memory impairment in supporting recollection of episodic memory.

Associations in episodic memory are formed between items presented close together in time. The temporal context model (TCM) hypothesizes that this contiguity effect is a consequence of shared temporal contexts rather than temporal proximity per se. Using double function lists of paired associates, which include chains of pairs (e.g. A-B, B-C), we examined associations between items that were not presented close together in time but were presented in similar temporal contexts. For instance A and C do not appear together, but both occur in the context of B. Although within-pair associations (e.g. A-B) were asymmetric, across-pair associations (e.g. A-C) showed no evidence for asymmetry. We attempted to describe these transitive associations using two models. One was a heteroassociative model in which the A-C associations resulted from mediated chaining as a result of “stepping through ” the links in the chain. Although this heteroassociative model and TCM make identical predictions regarding simple contiguity effects, the heteroassociative model had great difficulty accounting for the form of transitive associations between items. TCM provided an excellent fit to the data. These data raise the surprising possiblity that episodic contiguity effects do not reflect direct associations between items but rather a process of binding, encoding and retrieval of a gradually-changing