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R M Shiffrin

Publications and source records attributed to R M Shiffrin.

At least 19 recordsLinked to original sources
PubMed2001

Altering object representations through category learning.

Previous research has shown that objects that are grouped together in the same category become more similar to each other and that objects that are grouped in different categories become increasingly dissimilar, as measured by similarity ratings and psychophysical discriminations. These findings are consistent with two theories of the influence of concept learning on similarity. By a Strategic Judgment Bias account, the categories associated with objects are explicitly used as cues for determining similarity, and objects that are categorized together are judged to be more similar because similarity is not only a function of the objects themselves, but also the objects' category labels. By a Changed Object Description account, category learning alters the description of the objects themselves, emphasizing properties that are relevant for categorization. A new method for distinguishing between these accounts is introduced which measures the difference between the similarity ratings of categorized objects to a neutral object. The results indicate both strategic biases based on category labels and genuine representational change, with the strategic bias affecting mostly objects belonging to different categories and the representational change affecting mostly objects belonging to the same category.

Adult↗
PubMed2001

Perception and preference in short-term word priming.

Responding optimally with unknown sources of evidence (ROUSE) is a theory of short-term priming applied to associative, orthographic-phonemic, and repetition priming. In our studies, perceptual identification is measured with two-alternative forced-choice testing. ROUSE assumes features activated by primes are confused with those activated by the target. A near-optimal decision discounts evidence arising from such shared features. Too little discounting explains the finding that primed words were preferred after passive viewing of primes. Too much discounting explains the findings of reverse preference after active processing of primes. These preference changes highlight the need to use paradigms (like the present ones) capable of separating preferential and perceptual components of priming. Evidence of enhanced perception was found only with associative priming and was very small in magnitude compared with preference effects.

Analysis of Variance↗
PubMed2001

A Bayesian model for implicit effects in perceptual identification.

Retrieving effectively from memory (REM; R. M. Shiffrin & M. Steyvers, 1997), an episodic model of memory, is extended to implicit memory phenomena, namely the perceptual identification studies reported in R. Ratcliff and G. McKoon (1997). In those studies, the influence of prior study was greatest when words were presented most briefly and when forced-choice targets and foils were most similar. R. Ratcliff and G. McKoon use these data to argue against models in which prior study changes a word's representation. A model in which prior study changes a word's representation by adding context information is fit to their data; at test, the model uses a Bayesian decision process to compare the perceptual and context features associated with the test flash to stored traces. The effects of prior study are due to matching extra context information and are larger when alternatives share many features, thereby reducing noise that attenuates these effects.

Bayes Theorem↗
PubMed2001

Retrieval processes in recognition and cued recall.

The present studies used response time (RT) and accuracy to explore the processes and relation of recognition and cued recall. The studies used free-response and signal-to-respond techniques and varied list length and presentation rate. In Experiment 1, the free-RT distributions for recognition had much lower mean and variance than those for cued recall. Similarly, signal-to-respond curves showed fast rates of accumulation of information in recognition and slow rates in recall. (Quantitative models of the results are presented in the companion article by D. E. Diller, P. A. Nobel, and R. M. Shiffrin, 2001). To rule out the possibility that the slower responses in cued recall were due to a fast retrieval process followed by a slow process of cleaning up the retrieved trace for output, additional signal-to-respond tasks provided the relevant alternatives at test. Yet, these conditions showed slow growth rates, similar to those seen in recall. The results support the hypothesis that retrieval processes differ for single-item recognition and cued recall, with retrieval in cued recall (and associative recognition) due to a sequential search.

Adult↗
PubMed2001

An ARC-REM model for accuracy and response time in recognition and recall.

This article presents a model for accuracy and response time (RT) in recognition and cued recall, fitted to free-response and signal-to-respond data from Experiment 1 of P. A. Nobel and R. M. Shiffrin (2001). The model posits that recognition operates through parallel activation in a single retrieval step and cued recall operates as a sequential search. Because the data for recognition showed that variations in list length and study time per list had a large effect on accuracy but a small or negligible effect on (a) free-response RT distributions and (b) retrieval dynamics in signal-to-respond, the timing of the recognition decision is based on an assessment of retrieval completion (ARC), rather than on a sufficiency of evidence in favor of 1 of the response options. By assuming within-trial forgetting, the model predicts both the dissociation of accuracy and RT and the finding that errors are slower than correct responses. For cued recall, this model was incorporated as the 1st step in a search consisting of cycles of sampling and recovery.

Attention↗
PubMed2000

Perceptual inertia: spatial attention and warning foreperiod?

Perceptual inertia refers to a potential explanation for the observation that during a short period after stimulus onset, the visual system is insensitive to discriminatory detail. The present study attempted to replicate this empirical result in a simple one-item letter-identification task. The results provided little if any support for the construct of perceptual inertia. In the five experiments reported, evidence consistent with perceptual inertia was only obtained in Experiment 5. However, the Experiment 5 results can at least equally parsimoniously be explained in terms of two standard explanatory factors: an effect of precuing of the target position (selective attention) and foreperiod duration (general preparation).

Analysis of Variance↗
PubMed1999

Priming in a free association task as a function of association directionality.

Two experiments investigated priming in free association, a conceptual implicit memory task. The stimuli consisted of bidirectionally associated word pairs (e.g., BEACH-SAND) and unidirectionally associated word pairs that have no association from the target response back to the stimulus cue (e.g., BONE-DOG). In the study phase, target words (e.g., SAND, DOG) were presented in an incidental learning task. In the test phase, participants generated an associate to the stimulus cues (e.g., BEACH, BONE). In both experiments, priming was obtained for targets (e.g., SAND) that had an association back to the cue, but not for targets (e.g., DOG) for which such a backward association was absent. These results are problematic for theoretical accounts that attribute priming in free association to the strengthening of target responses. It is argued that priming in free association depends on the strengthening of cue-target associations.

Adult↗
PubMed1995

Effects of category length and strength on familiarity in recognition.

In most recognition models a decision is based on a global measure often termed familiarity. However, a response criterion is free to vary across lists varying in length and strength, making familiarity changes immeasurable. We presented a single list with a mixture of exemplars from many categories, so that the criterion would be unlikely to vary with length or strength of the category of the test item. False alarms rose with category length but not category strength, suggesting that familiarity does not change much with changes in strength of other items but grows when additional items are studied. The results were well fit by an extension of the search of associative memory (SAM) model presented by R. M. Shiffrin, R. Ratcliff, and S. E. Clark (1990).

Adult↗
PubMed1994

Seven plus or minus two: a commentary on capacity limitations.

Miller's classic 1956 article is best known today for its discussion of capacity limitations in short-term memory, but the bulk of the article dealt with capacity limitations in absolute judgment tasks and the relation of such limitations to information theory. Many of the puzzles of absolute judgment first raised by Miller remain a puzzle today. The authors review some of the literature directed toward this issue and discuss a few models that attempt to elucidate the phenomena. Since 1956 there has been an enormous research effort aimed at understanding the mechanisms and limitations of short-term memory, resulting in considerable progress. The authors briefly discuss some of these advances. The authors conclude, as Miller did, by noting the probable lack of connection between the limitations observed in these 2 areas of inquiry.

Attention↗
PubMed1993

Short-term memory: a brief commentary.

Over the years, a metatheoretical view of short-term memory has developed. This view, closely related to the "modal" model from the 1960s, is supported by an increasing base of neurophysiological data, and a wide variety of empirical findings. It treats short-term memory as (1) the temporary, above threshold, activation of neural structures (related in not-too-well-specified ways to various recency effects); (2) a work space for carrying out virtually all cognitive operations involved in human cognition; and (3) the source of capacity limitations, accounting for certain memory limitations and most attentional limitations. The main problem with this view is the fact that it encompasses virtually everything that we are concerned with in human cognition--a successful model would almost be a general model of cognition, something the field has not yet approached. This situation is not grounds for despair. Progress is being made on many fronts, notwithstanding the fact that the most successful models are focused on specific task domains. Recent advances include an increasing awareness of the necessity for detailed models of short-term retrieval, a theme reflected in a number of articles in the present collection.

Arousal↗
PubMed1992

Cuing effects and associative information in recognition memory.

Item recognition requires discrimination of studied words from nonstudied words. Associative recognition requires subjects to discriminate studied word groups from recombinations of words from different groups. Cued recognition requires the same old-new discrimination as item recognition, but list items are presented as cues along with the test item. The results from three experiments show (1) little or no effect of cuing for low-frequency words, but (2) positive cuing effects for high-frequency words; (3) increasing levels of overall performance with increases in study time, but (4) unchanging effects of cuing with study time; and (5) stronger positive cuing effects for two cues than for one cue. Five models (Independent Cue Model, Matrix model, MINERVA 2, SAM, and TODAM) were fit to the data of Experiment 1. Each model has trouble with at least one aspect of the results. Theoretical implications and modifications are discussed at length.

Adult↗
PubMed1992

Automatization and training in visual search.

In several search tasks, the amount of practice on particular combinations of targets and distractors was equated in varied-mapping (VM) and consistent-mapping (CM) conditions. The results indicate the importance of distinguishing between memory and visual search tasks, and implicate a number of factors that play important roles in visual search and its learning. Visual search was studied in Experiment 1. VM and CM performance were almost equal, and slope reductions occurred during practice for both, suggesting the learning of efficient attentive search based on features, and no important role for automatic attention attraction. However, positive transfer effects occurred when previous CM targets were re-paired with previous CM distractors, even though these targets and distractors had not been trained together. Also, the introduction of a demanding simultaneous task produced advantages of CM over VM. These latter two results demonstrated the operation of automatic attention attraction. Visual search was further studied in Experiment 2, using novel characters for which feature overlap and similarity were controlled. The design and many of the findings paralleled Experiment 1. In addition, enormous search improvement was seen over 35 sessions of training, suggesting the operation of perceptual unitization for the novel characters. Experiment 3 showed a large, persistent advantage for CM over VM performance in memory search, even when practice on particular combinations of targets and distractors was equated in the two training conditions. A multifactor theory of automatization and attention is put forth to account for these findings and others in the literature.

Adult↗
PubMed1991

Interference and the representation of events in memory.

Most current models of memory predict that the presence of increasingly well-learned, or strong, items in memory will cause increasing interference. This phenomenon, the list-strength effect, occurs as predicted when memory is tested by free recall but not when a recognition test is used. Four experiments use end-of-session testing to demonstrate that redistribution of storage time or effort from strong to weak items on mixed lists does not occur and therefore cannot be masking interference by strong items. Delay between study and test is found to cause memory loss independent of the basic list-strength findings. It is concluded that the presence of strong items in memory does not interfere with recognition performance and that interference is due to failures of retrieval rather than to composition or other forms of destructive interaction during storage.

Analysis of Variance↗
PubMed1991

Word repetitions in sentence recognition.

When some items on a list are strengthened by extra study time or repetitions, recognition of other, unrelated, list items is not harmed (Ratcliff, Clark, & Shiffrin, 1990). Shiffrin, Ratcliff, and Clark (1990) accounted for this list-strength finding with a model assuming that different items are stored separately in memory, but that repetitions are accumulated together into a single stronger memory trace. Repeating words in the context of different sentences might cause separate storage of the repetitions of a given word, because either word or sentence traces are stored separately. Separate storage would, in effect, convert a list-strength manipulation into a list-length manipulation and thereby induce a positive list-strength effect. In Experiment 1, this result was produced for single-word recognition and for two types of sentence recognition. In Experiment 2, both words and sentences were repeated together, which should have caused repetitions to be stored in a single, stronger, trace. As expected, the list-strength effect was eliminated. A sentence trace model was fit to the data, supporting the account of Shiffrin et al. (1990) and supporting an account of word and sentence recognition in which activation is summed for representations of all list items. The results from the two studies are inconsistent with most current models of memory (as shown by the theoretical analyses of Shiffrin et al., 1990) and pose an additional challenge for theory.

Cognition↗
PubMed1990

List-strength effect: II. Theoretical mechanisms.

Ratcliff, Clark, and Shiffrin (1990) examined the list-strength effect: the effect of strengthening (or weakening) some list items upon memory for other list items. The list-strength effect was missing or negative in recognition, missing or positive in cued recall, and large and positive in free recall. We show that a large number of current models fail to predict these findings. A variant of the SAM model of Gillund and Shiffrin (1984), involving a differentiation hypothesis, can handle the data. A variant of MINERVA 2 (Hintzman, 1986, 1988) comes close but has some problems. Successful variants of a variety of composite and network models were not found (e.g., Ackley, Hinton, & Sejnowski, 1985; Anderson, 1972, 1973; Metcalfe Eich, 1982; Murdock, 1982; Pike, 1984). The results suggest constraints on the future development of such models.

Cues↗
PubMed1990

List-strength effect: I. Data and discussion.

Extra items added to a list cause memory for the other items to decrease (the list-length effect). In one of the present studies we show that strengthening (or weakening) some items on a list harms (helps) free recall of the remaining list items. This is termed the list-strength effect. However, in seven recognition studies the list-strength effect was either absent or negative. This held whether strengthening was accomplished by extra study time or extra repetitions. The seven studies used various means to control rehearsal strategies, thereby providing evidence against the possibility that the findings were due to redistribution of rehearsal or effort from stronger to weaker items within a list. Current models appear unable to predict these results. We suggest that different retrieval operations underlie recall and recognition, as in the SAM model of Gillund and Shiffrin (1984), which can be made to fit the results with certain relatively minor modifications.

Cues↗
PubMed1988

A model of automatic attention attraction when mapping is partially consistent.

A model is described to account for the data of Durso, Cooke, Breen, and Schvaneveldt (1987). On the basis of the relative frequency of an item's presentation as a target, the item develops an automatic tendency to attract attention. When stimuli are then displayed, each calls the attention system to a degree determined by its present strength. We assume that attention eventually drifts to the strongest stimulus (which is then given as a response), but in a time determined inversely by the difference in strength between the two strongest stimuli. A version of this model in which the strengths were freely estimated parameters predicted the various elements of the data with good accuracy. In other versions of the model, strength values were derived from assumptions concerning the learning of automatism. Two of these models, quite different in character, captured the major qualitative features of the data. Further empirical tests of the models are suggested.

Attention↗