The nature of memory processes underlying recognition judgments in the process dissociation procedure

The hypothesis is tested that the memory processes involved in recognition judgments in the process dissociation procedure are the same as those involved in standard source-monitoring tasks. It is shown how source-monitoring response categories can be mapped onto process dissociation response categories. On the basis of this observation, an experiment was conducted in which it was possible to compare, using a multinomial modeling approach, the parameters representing memory processes in the process dissociation procedure with those involved in source monitoring. For the two different encoding conditions realized, the results are compatible with the hypothesis that the same processes are involved in source monitoring and in recognition judgments in the process dissociation procedure. Implications for the interpretation of the model’s parameters are discussed.     

An integrative review of process dissociation and related models in social cognition

This chapter reviews the use of formal dual process models in social psychology, with a focus on the process dissociation model and related multinomial models. The utility of the models is illustrated using studies of social and affective influences on memory, judgement and decision making, and social attitudes and stereotypes. We then compare and contrast the process dissociation model with other approaches, including implicit and explicit tests, signal detection theory, and multinomial models. Finally we show how several recently proposed multinomial models can be integrated into a single family of models, of which process dissociation is a specific instance. We describe how these process models can be used as both theoretical and measurement tools to answer questions about the role of automatic and controlled processes in social behaviour.     

A Multinomial Model to Assess Fluency and Recollection in a Sequence Learning Task

We suggest that well-formedness judgements in conjunction with L.L. Jacoby's (1991) process dissociation procedure and an appropriate measurement model can be used to obtain measures of implicit and explicit sequence knowledge. We introduce a new measurement model designed specifically for the sequence learning task. The model assumes that sequence identification is based on recollection, perceptual or motor fluency, systematicity detection, and guessing. The model and the application of the process dissociation procedure were empirically evaluatedusing auditory eventsequences. In Experiment 1, the parameterreflecting recollection was higher in an intentional than in an incidental learning condition. Experiment 2 showed that random sequences interspersed among the systematic sequences during the acquisition phase may change this pattern of results. A manipulation of processing fluency in Experiment 3 was reflected in the appropriate model parameter. In sum, the new measurement model and the application of the process dissociation procedure appear to be useful tools in sequence learning research.     

Comparing single‐ and dual‐process models of memory development

This experiment examined single‐process and dual‐process accounts of the development of visual recognition memory. The participants, 6–7‐year‐olds, 9–10‐year‐olds and adults, were presented with a list of pictures which they encoded under shallow or deep conditions. They then made recognition and confidence judgments about a list containing old and new items. We replicated the main trends reported by Ghetti and Angelini ( 2008 ) in that recognition hit rates increased from 6 to 9 years of age, with larger age changes following deep than shallow encoding. Formal versions of the dual‐process high threshold signal detection model and several single‐process models (equal variance signal detection, unequal variance signal detection, mixture signal detection) were fit to the developmental data. The unequal variance and mixture signal detection models gave a better account of the data than either of the other models. A state‐trace analysis found evidence for only one underlying memory process across the age range tested. These results suggest that single‐process memory models based on memory strength are a viable alternative to dual‐process models for explaining memory development.     

Further evidence on the similarity of memory processes in the process dissociation procedure and in source monitoring

Buchner, Erdfelder, Steffens, and Martensen (1997) proposed that the memory processes involved in recognition judgments in the process dissociation procedure are the same as those involved in standard source monitoring tasks. Two extensions of that research are presented here. First, following a line of reasoning recently brought forward by Jacoby (1998), the instructions in the earlier study could have triggered different processes from those triggered by his instructions. However, with instructions conforming as closely as possible to those reported by Jacoby (1991), Experiment 1 replicated the earlier recognition judgment finding almost perfectly. Second, the memory processes underlying fame judgments in the process dissociation procedure could also resemble those involved in source monitoring tasks. Indeed, the results of Experiment 2 are compatible with the hypothesis that the same processes are involved in fame judgments given a source monitoring or a process dissociation procedure.     

Signal detection theory with finite mixture distributions: theoretical developments with applications to recognition memory

An extension of signal detection theory (SDT) that incorporates mixtures of the underlying distributions is presented. The mixtures can be motivated by the idea that a presentation of a signal shifts the location of an underlying distribution only if the observer is attending to the signal; otherwise, the distribution is not shifted or is only partially shifted. Thus, trials with a signal presentation consist of a mixture of 2 (or more) latent classes of trials. Mixture SDT provides a general theoretical framework that offers a new perspective on a number of findings. For example, mixture SDT offers an alternative to the unequal variance signal detection model; it can also account for nonlinear normal receiver operating characteristic curves, as found in recent research.     

A Signal Detection Model for Multiple-Choice Exams

A model for multiple-choice exams is developed from a signal-detection perspective. A correct alternative in a multiple-choice exam can be viewed as being a signal embedded in noise (incorrect alternatives). Examinees are assumed to have perceptions of the plausibility of each alternative, and the decision process is to choose the most plausible alternative. It is also assumed that each examinee either knows or does not know each item. These assumptions together lead to a signal detection choice model for multiple-choice exams. The model can be viewed, statistically, as a mixture extension, with random mixing, of the traditional choice model, or similarly, as a grade-of-membership extension. A version of the model with extreme value distributions is developed, in which case the model simplifies to a mixture multinomial logit model with random mixing. The approach is shown to offer measures of item discrimination and difficulty, along with information about the relative plausibility of each of the alternatives. The model, parameters, and measures derived from the parameters are compared to those obtained with several commonly used item response theory models. An application of the model to an educational data set is presented.     

A hierarchical process-dissociation model

In fitting the process-dissociation model (L. L. Jacoby, 1991) to observed data, researchers aggregate outcomes across participant, items, or both. T. Curran and D. L. Hintzman (1995) demonstrated how biases from aggregation may lead to artifactual support for the model. The authors develop a hierarchical process-dissociation model that does not require aggregation for analysis. Most importantly, the Curran and Hintzman critique does not hold for this model. Model analysis provides for support of process dissociation--selective influence holds, and there is a dissociation in correlation patterns among participants and items. Items that are better recollected also elicit higher automatic activation. There is no correlation, however, across participants; that is, participants with higher recollection have no increased tendency toward automatic activation. The critique of aggregation is not limited to process dissociation. Aggregation distorts analysis in many nonlinear models, including signal detection, multinomial processing tree models, and strength models. Hierarchical modeling serves as a general solution for accurately fitting these psychological-processing models to data.     

The ROC Toolbox: A toolbox for analyzing receiver-operating characteristics derived from confidence ratings

Signal-detection theory, and the analysis of receiver-operating characteristics (ROCs), has played a critical role in the development of theories of episodic memory and perception. The purpose of the current paper is to present the ROC Toolbox. This toolbox is a set of functions written in the Matlab programming language that can be used to fit various common signal detection models to ROC data obtained from confidence rating experiments. The goals for developing the ROC Toolbox were to create a tool (1) that is easy to use and easy for researchers to implement with their own data, (2) that can flexibly define models based on varying study parameters, such as the number of response options (e.g., confidence ratings) and experimental conditions, and (3) that provides optimal routines (e.g., Maximum Likelihood estimation) to obtain parameter estimates and numerous goodness-of-fit measures.The ROC toolbox allows for various different confidence scales and currently includes the models commonly used in recognition memory and perception: (1) the unequal variance signal detection (UVSD) model, (2) the dual process signal detection (DPSD) model, and (3) the mixture signal detection (MSD) model. For each model fit to a given data set the ROC toolbox plots summary information about the best fitting model parameters and various goodness-of-fit measures. Here, we present an overview of the ROC Toolbox, illustrate how it can be used to input and analyse real data, and finish with a brief discussion on features that can be added to the toolbox.     

How many response options? A study of remember-know testing procedures

The remember-know procedure can be conducted in one or two steps. The one-step procedure does not include a recognition response (old-new) prior to the remember-know response. It is observed consistently that the one-step procedure leads to a more liberal placement of the response criterion, but it is unclear whether recognition accuracy is affected by the number of procedural steps. However, previous studies used bias-dependent measures of accuracy (A′ and d′). We manipulated the number of steps and confirmed the finding that the response criterion is more liberal with the one-step procedure. More importantly, we employed a signal detection theory bias-free accuracy measure (d_a) to show that varying the number of steps does not affect recognition accuracy, and we demonstrated that this pattern of results does not change when the dual process signal detection model (Yonelinas, 1997) is applied.     

再认记忆中的概率学习效应:加工分离框架

采用加工分离程序(PDP)与多项加工树模型,对比检验PDP与背景鉴别模型的构思效度;操纵加工水平与项目比例,考察再认记忆中的内隐学习效应。结果表明:(1)包含和排除测验都表现出加工水平效应,包含测验具有视听通道效应。(2)在单一操作中分离出意识回忆和自动加工两种过程。(3)在语义编码条件下出现了概率学习效应,自动加工可能具有情境依存性。未发现支持背景鉴别模型的结果。     

An application of signal detection theory with finite mixture distributions to source discrimination

A mixture extension of signal detection theory is applied to source discrimination. The basic idea of the approach is that only a portion of the sources (say A or B) of items to be discriminated is encoded or attended to during the study period. As a result, in addition to 2 underlying probability distributions associated with the 2 sources, there is a 3rd distribution that represents items for which sources were not attended to. Thus, over trials, the observed response results from a mixture of an attended (A or B) distribution and a nonattended distribution. The situation differs in an interesting way from detection in that, for detection, there is mixing only on signal trials and not on noise trials, whereas for discrimination, there is mixing on both A and B trials. Predictions of the mixture model are examined for data from several recent studies and in a new experiment.     

Multimodal signal detection: Independent decisions vs. integration

The pooling of information from simultaneous, spatially congruent auditory and visual stimuli is examined in a signal detection task. The paradigm used permits discrimination among a number of models of the decision mechanisms involved in processing multiple component stimuli. Parameter-free predictions are presented for the weighted integration model and for three versions of the independent decisions model. The data support an independent decisions model of the bimodal detection process in which attention is shared equally between modalities.     

Dissociating familiarity from recollection using rote rehearsal

Recollection-based recognition memory judgments benefit greatly from effortful elaborative encoding, whereas familiarity-based judgments are much less sensitive to such manipulations. In this study, we have examined whether rote rehearsal under divided attention might produce the opposite dissociation, benefiting familiarity more than recollection. Subjects rehearsed word pairs during the "distractor" phase of a working memory span task, and were then given a surprise memory test for the distractor items at the end of the experiment. Experiment 1 demonstrated that increasing rehearsal elevated the recognition rate for intact and rearranged pairs, but neither associative recognition accuracy nor implicit fragment completion benefited from rehearsal. The results suggest that rote rehearsal leads to a greater increase in familiarity than in recollection, and that the increase in observed familiarity cannot be attributed to effects of repetition priming. In Experiment 2, we tested item recognition with the remember/know procedure, and the results supported the conclusions of Experiment 1. Moreover, a signal detection model of remember/know performance systematically overpredicted rehearsal increases in remember rates, and this worsened when high-rehearsal items were assumed to be more variable in strength. The results suggest that rote rehearsal can dissociate familiarity from recollection at the time of encoding and that item recognition cannot be fully accommodated within a one-dimensional signal detection model.     

Modeling response signal and response time data

The diffusion model (Ratcliff, 1978) and the leaky competing accumulator model (LCA, Usher & McClelland, 2001) were tested against two-choice data collected from the same subjects with the standard response time procedure and the response signal procedure. In the response signal procedure, a stimulus is presented and then, at one of a number of experimenter-determined times, a signal to respond is presented. The models were fit to the data from the two procedures simultaneously under the assumption that responses in the response signal procedure were based on a mixture of decision processes that had already terminated at response boundaries before the signal and decision processes that had not yet terminated. In the latter case, decisions were based on partial information in one variant of each model or on guessing in a second variant. Both variants of the diffusion model fit the data well and both fit better than either variant of the LCA model, although the differences in numerical goodness-of-fit measures were not large enough to allow decisive selection between the models.     

Using the PLUM procedure of SPSS to fit unequal variance and generalized signal detection models

The recent addition of a procedure in SPSS for the analysis of ordinal regression models offers a simple means for researchers to fit the unequal variance normal signal detection model and other extended signal detection models. The present article shows how to implement the analysis and how to interpret the SPSS output. Examples of fitting the unequal variance normal model and other generalized signal detection models are given. The approach offers a convenient means for applying signal detection theory to a variety of research.     

Context effects in recognition memory: the role of familiarity and recollection

A variant of the process dissociation procedure was coupled with a manipulation of response signal lag to assess whether manipulations of context affect one or both of the familiarity and search processes described by the dual process model of recognition. Participants studied a list of word pairs (context+target) followed by a recognition test with target words presented in the same or different context, and in the same or different form as study (singular/plural). Participants were asked to recognize any target word regardless of changes to form (inclusion), or to only recognise words that were presented in the same form (exclusion). The standard context reinstatement effect was evident even at the short response lags. Analyses of the estimates of the contributions of familiarity and search processes suggest that the context effect demonstrated here can be attributed in part to the influence of familiarity on recognition, whereas the effect on recollection was less clear.     

Dual processes in recognition: Does a focus on measurement operations provide a sufficient foundation?

Current theoretical thinking about dual processes in recognition relies heavily on the measurement operations embodied within the process dissociation procedure. We critically evaluate the ability of this procedure to support this theoretical enterprise. We show that there are alternative processes that would produce a rough invariance in familiarity (a key prediction of the dual-processing approach) and that the process dissociation procedure does not have the power to differentiate between these alternative possibilities. We also show that attempts to relate parameters estimated by the process dissociation procedure to subjective reports (remember-know judgments) cannot differentiate between alternative dual-processing models and that there are problems with some of the historical evidence and with obtaining converging evidence. Our conclusion is that more specific theories incorporating ideas about representation and process are required.     

Effects of race on responses and response latencies in the weapon identification task: a test of six models

The authors consider six models of underlying process in the weapon identification task: The first two are response-time extensions of signal detection models; the last four, of the process dissociation model. Predictions for accuracy data, correct response latencies, and false response latencies are used to discriminate between models. In the present study, racial bias in responses and correct response latency was replicated. New findings were that the direction of bias was reversed in error latency and that errors were faster than correct responses. These findings rule out four models, in particular, the idea that race biases early perception and interpretation of targets. Implications for reducing errors in the weapon identification task and possibilities of discriminating between the remaining two models are discussed.     

Do changes in the subjective experience of recognition over time suggest independent processes?

Two experiments examined the nature of recognition memory by asking how subjective reports of remembering change over time. In Experiment 1, participants were asked to report their experience of remembering using the well‐known remember–know–guess procedure. Estimates of recollection declined over a 14‐day period, but estimates of familiarity remained constant, suggesting that the processes are independent. In Experiment 2, participants were asked to report their confidence in their recognition decisions. Subjective reports of confidence were analysed via receiver operating characteristics and also indicated different rates of decline for recollection and familiarity. Superficially, the data appear to support a dual‐process account of recognition, but close inspection shows the data to be consistent with a simple signal detection model. The conclusion is that although the phenomenal experience of remembering changes over time this is most likely to be predicated on a single process.