Recognition memory for source and occurrence: The importance of recollection

Previous recognition memory studies indicate that when both recollection and familiarity are expected to contribute to recognition performance (e.g., discriminating studied items from nonstudied items) the dual-process and the unequal-variance signal detection models provide comparable accounts of performance. When familiarity is not expected to be useful (e.g., when items from two equally familiar sources are discriminated between), the dual-process model provides a significantly better account of performance. In the present study, source recognition was tested under conditions in which familiarity could have been used to perform a list-discrimination task; participants were required to discriminate between strong studied items, weak studied items, and new items. The dual-process model provided a better account of performance than did the unequal-variance model. Moreover, the results indicated that the unequal-variance assumption in a single-process signal detection model was not a valid substitution for recollection and that recollection was used to make recognition judgments even when assessments of familiarity were useful.     

Moving beyond pure signal-detection models: comment on Wixted (2007)

The dual-process signal-detection (DPSD) model assumes that recognition memory is based on recollection of qualitative information or on a signal-detection-based familiarity process. The model has proven useful for understanding results from a wide range of memory research, including behavioral, neuropsychological, electrophysiological, and neuroimaging studies. However, a number of concerns have been raised about the model over the years, and it has been suggested that an unequal-variance signal-detection (UVSD) model that incorporates separate recollection and familiarity processes (J. T. Wixted, 2007) may provide an equally good, or even better, account of the data. In this article, the authors show that the results of studies that differentiate these models support the predictions of the DPSD model and indicate that recognition does not reflect the summing of 2 signal-detection processes, as the new UVSD model assumes. In addition, the assumptions of the DPSD model are clarified in order to address some of the common misconceptions about the model. Although important challenges remain, hybrid models such as this provide a more useful framework within which to understand human memory than do pure signal-detection models.     

A dual-process specification of causal conditional reasoning

There are two accounts describing causal conditional reasoning: the probabilistic and the mental models account. According to the probabilistic account, the tendency to accept a conclusion is related to the probability by which cause and effect covary. According to the mental models account, the tendency to accept a conclusion relates to the availability of counterexamples. These two accounts are brought together in a dual-process theory: It is argued that the probabilistic reasoning process can be considered as a heuristic process whereas the mental models account can be seen as its analytic counterpart. Experiment 1 showed that the two processes differ on a temporal dimension: The variation in fast responses was best predicted by the variation in likelihood information, while the variation in slow responses was best predicted by variation in counterexample information. Experiments 2 and 3 validate the override principle: The likelihood conclusion can be overwritten when specific counterexamples are retrieved in time. In Experiment 2 both accounts were compared based on their difference in input. In Experiment 3 we used a verbal protocol analysis to validate the dual-process idea at the output level. The data of the three experiments provide converging support for framing the two reasoning accounts in a dual-process theory.     

Feature sampling in categorization and recognition of objects

This article presents an overview of some recent work on the time course of perceptual categorization and recognition memory. First, The EGCM-RT, which is a feature-sampling model of the time course of categorization, is described. It is shown that the model explains a wide range of categorization data. Second, an overview is given of a feature-sampling model of the time course of recognition that is derived from the EGCM-RT. This model explains results that have been interpreted in the past as evidence for dual-process models of recognition, and it provides a single-process alternative to dual-process accounts.     

Reasoning with conditionals: a test of formal models of four theories

The four dominant theories of reasoning from conditionals are translated into formal models: The theory of mental models (Johnson-Laird, P. N., & Byrne, R. M. J. (2002). Conditionals: a theory of meaning, pragmatics, and inference. Psychological Review, 109, 646-678), the suppositional theory (Evans, J. S. B. T., & Over, D. E. (2004). If. Oxford: Oxford University Press), a dual-process variant of the model theory (Verschueren, N., Schaeken, W., & d'Ydewalle, G. (2005). A dual-process specification of causal conditional reasoning. Thinking &Reasoning, 11, 278-293), and the probabilistic theory (Oaksford, M., Chater, N., & Larkin, J. (2000). Probabilities and polarity biases in conditional inference. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 883-899). The first three theories are formalized as multinomial models. The models are applied to the frequencies of patterns of acceptance or rejection across the four basic inferences modus ponens, acceptance of the consequent, denial of the antecedent, and modus tollens. Model fits are assessed for two large data sets, one representing reasoning with abstract, basic conditionals, the other reflecting reasoning with pseudo-realistic causal and non-causal conditionals. The best account of the data was provided by a modified version of the mental-model theory, augmented by directionality, and by the dual-process model.     

Signal-Detection, Threshold, and Dual-Process Models of Recognition Memory: ROCs and Conscious Recollection

Threshold- and signal-detection-based models have dominated theorizing about recognition memory. Building upon these theoretical frameworks, we have argued for a dual-process model in which conscious recollection (a threshold process) and familiarity (a signal-detection process) contribute to memory performance. In the current paper we assessed several memory models by examining the effects of levels of processing and the number of presentations on recognition memory receiver operating characteristics (ROCs). In general, when the ROCs were plotted in probability space they exhibited an inverted U shape; however, when they were plotted inzspace they exhibited a U shape. An examination of the ROCs showed that the dual-process model could account for the observed ROCs, but that models based solely on either threshold or signal-detection processes failed to provide a sufficient account of the data. Furthermore, an examination of subjects' introspective reports using the remember/know procedure showed that subjects were aware of recollection and familiarity and were able to consistently report on their occurrence. The remember/know data were used to accurately predict the shapes of the ROCs, and estimates of recollection and familiarity derived from the ROC data mirrored the subjective reports of these processes.     

Models of positive and negative symptoms in schizophrenia: an empirical evaluation of latent structures

The present investigation empirically evaluated three competing models of the relations between positive and negative symptoms in schizophrenia, namely the severity-liability model (Gottesman, McGuffin, & Farmer, 1987), Andreasen's unidimensional bipolar model (Andreasen & Olsen, 1982), and Crow's independent dual-process model (Crow, 1980a, 1980b). Using positive and negative symptom ratings based on 220 schizophrenic subjects, the results of a LISREL VI (Joreskog & Sorbom, 1984) confirmatory factor analysis revealed that Crow's model of positive and negative symptoms provided the best fit to the observed data among the three models. The severity-liability model provided a modest fit to observed data, and Andreasen's model fit the data poorly. Results are interpreted as supporting the validity of the positive and negative symptom distinction in schizophrenia and as providing substantive empirical support for Crow's independent dual-process model. The methodological advantages of confirmatory factor analysis in the specification and evaluation of theoretical models in experimental and developmental psychopathology are discussed.     

The dimensionality of the remember-know task: a state-trace analysis

This article addresses the issue of whether the remember-know (RK) task is best explained by a single-process or a dual-process model. All single-process models propose that remember and know responses reflect different levels of a single strength-of-evidence dimension. Thus, across conditions in which response criteria are held constant, these models predict that the RK task is unidimensional. Many dual-process models propose that remember and know responses reflect two qualitatively distinct processes underlying recognition memory, often characterized as recollection and familiarity. These models predict that the RK task is bidimensional. Using data from 37 studies, the author conducted a state-trace analysis to determine the dimensionality of the RK task. In those studies, non-memory-related differences between conditions were eliminated via decision criteria constrained to be constant across all levels of the independent variables. The results reveal little or no evidence of bidimensionality and lend additional support to the unequal-variance signal detection model. Other arguments supporting a bidimensional interpretation are examined, and the author concludes there is insufficient evidence for the RK task to be used to identify qualitatively different memory components.     

Decision-making models of remember-know judgments: comment on Rotello, Macmillan, and Reeder (2004)

The sum-difference theory of remembering and knowing (STREAK) provides a sophisticated account of many interactions in the remember-know (R-K) area (C. M. Rotello, N. A. Macmillan, & J. A. Reeder, 2004). It assumes 2 orthogonal strength dimensions and oblique criterion planes. Another dual-process model (J. T. Wixted & V. Stretch, 2004) with one decision axis has also been applied to R-K judgments with considerable success and provides new insights into the processes involved. An analysis of the 4 major R-K interactions can also be explained by a simpler one-dimensional signal detection theory (J. C. Dunn, 2004a). However these models do not make contact with standard work on recognition memory, so their scope is limited. To bridge this gap, a global-matching model (a theory of distributed associative memory [TODAM]) for R-K judgments is proposed. This model can produce good fits to the data, and there are established experimental manipulations with which to test it. It provides further support for the idea that R judgments are based on associative information, whereas K judgments are based on item information.     

Diffusion models of the flanker task: discrete versus gradual attentional selection

The present study tested diffusion models of processing in the flanker task, in which participants identify a target that is flanked by items that indicate the same (congruent) or opposite response (incongruent). Single- and dual-process flanker models were implemented in a diffusion-model framework and tested against data from experiments that manipulated response bias, speed/accuracy tradeoffs, attentional focus, and stimulus configuration. There was strong mimcry among the models, and each captured the main trends in the data for the standard conditions. However, when more complex conditions were used, a single-process spotlight model captured qualitative and quantitative patterns that the dual-process models could not. Since the single-process model provided the best balance of fit quality and parsimony, the results indicate that processing in the simple versions of the flanker task is better described by gradual rather than discrete narrowing of attention.     

Diffusion models of the flanker task: Discrete versus gradual attentional selection

The present study tested diffusion models of processing in the flanker task, in which participants identify a target that is flanked by items that indicate the same (congruent) or opposite response (incongruent). Single- and dual-process flanker models were implemented in a diffusion-model framework and tested against data from experiments that manipulated response bias, speed/accuracy tradeoffs, attentional focus, and stimulus configuration. There was strong mimcry among the models, and each captured the main trends in the data for the standard conditions. However, when more complex conditions were used, a single-process spotlight model captured qualitative and quantitative patterns that the dual-process models could not. Since the single-process model provided the best balance of fit quality and parsimony, the results indicate that processing in the simple versions of the flanker task is better described by gradual rather than discrete narrowing of attention.     

A multitrait-multimethod validation of the Implicit Association Test: implicit and explicit attitudes are related but distinct constructs

Recent theoretical and methodological innovations suggest a distinction between implicit and explicit evaluations. We applied Campbell and Fiske's (1959) classic multitrait-multimethod design precepts to test the construct validity of implicit attitudes as measured by the Implicit Association Test (IAT). Participants (N = 287) were measured on both self-report and IAT for up to seven attitude domains. Through a sequence of latent-variable structural models, systematic method variance was distinguished from attitude variance, and a correlated two-factors-per-attitude model (implicit and explicit factors) was superior to a single-factor-per-attitude specification. That is, despite sometimes strong relations between implicit and explicit attitude factors, collapsing their indicators into a single attitude factor resulted in relatively inferior model fit. We conclude that these implicit and explicit measures assess related but distinct attitude constructs. This provides a basis for, but does not distinguish between, dual-process and dual-representation theories that account for the distinctions between constructs.     

Models of recognition: A review of arguments in favor of a dual-process account

The majority of computationally specified models of recognition memory have been based on a single-process interpretation, claiming that familiarity is the only influence on recognition. There is increasing evidence that recognition is, in fact, based on two processes: recollection and familiarity. This article reviews the current state of the evidence for dual-process models, including the usefulness of the remember/know paradigm, and interprets the relevant results in terms of the source of activation confusion (SAC) model of memory. We argue that the evidence from each of the areas we discuss, when combined, presents a strong case that inclusion of a recollection process is necessary. Given this conclusion, we also argue that the dual-process claim that the recollection process is always available is, in fact, more parsimonious than the single-process claim that the recollection process is used only in certain paradigms. The value of a well-specified process model such as the SAC model is discussed with regard to other types of dual-process models.     

Does opposition logic provide evidence for conscious and unconscious processes in artificial grammar learning?

The question of whether studies of human learning provide evidence for distinct conscious and unconscious influences remains as controversial today as ever. Much of this controversy arises from the use of the logic of dissociation. The controversy has prompted the use of an alternative approach that places conscious and unconscious influences on memory retrieval in opposition. Here we ask whether evidence acquired via the logic of opposition requires a dual-process account or whether it can be accommodated within a single similarity-based account. We report simulations using a simple neural network model of two artificial grammar learning experiments reported by that dissociated conscious and unconscious influences on classification. The simulations demonstrate that opposition logic is insufficient to distinguish between single- and multiple-system models.     

The<Emphasis Type="Italic">remember</Emphasis> response: Subject to bias,graded, and not a process-pure indicator of recollection

Recognition memory judgments have long been assumed to depend on the contributions of two underlying processes: recollection and familiarity. We measured recollection with receiver-operating characteristic (ROC) data and remember-know judgments. Under standard remember-know instructions, the two estimates of recollection diverged. When subjects were told they might need to justify theirremember responses to the experimenter, the two estimates were more likely to agree. The data support the conclusion thatremember responses are generally based on a continuous underlying process but that specific task instructions can produce data that appear consistent with a high-threshold recollective process. Models based on signal detection theory provide a better account of these data than does the dual-process model (Yonelinas, 1994) or process-pure interpretations.     

Nonword reading: Comparing dual-route cascaded and connectionist dual-process models with human data

Two prominent dual-route computational models of reading aloud are the dual-route cascaded (DRC) model, and the connectionist dual-process plus (CDP+) model. While sharing similarly designed lexical routes, the two models differ greatly in their respective nonlexical route architecture, such that they often differ on nonword pronunciation. Neither model has been appropriately tested for nonword reading pronunciation accuracy to date. We argue that empirical data on the nonword reading pronunciation of people is the ideal benchmark for testing. Data were gathered from 45 Australian-English-speaking psychology undergraduates reading aloud 412 nonwords. To provide contrast between the models, the nonwords were chosen specifically because DRC and CDP+ disagree on their pronunciation. Both models failed to accurately match the experiment data, and both have deficiencies in nonword reading performance. However, the CDP+ model performed significantly worse than the DRC model. CDP++, the recent successor to CDP+, had improved performance over CDP+, but was also significantly worse than DRC. In addition to highlighting performance shortcomings in each model, the variety of nonword responses given by participants points to a need for models that can account for this variety. (PsycINFO Database Record (c) 2012 APA, all rights reserved).     

A dual-process approach to health risk decision making: The prototype willingness model

Although dual-process models in cognitive, personality, and social psychology have stimulated a large body of research about analytic and heuristic modes of decision making, these models have seldom been applied to the study of adolescent risk behaviors. In addition, the developmental course of these two kinds of information processing, and their relation to the development of self-regulation are not well understood at this time. The current paper reviews what leading dual-process models have to say about the development of analytic and heuristic decision making, and their implications for adolescent risk behavior. In addition, it reviews research on the prototype willingness model of adolescent decision making—a dual-process model designed specifically to address non-intentional, but volitional adolescent risk behavior. It also discusses the implications of dual-process models for intervention research.     

Predicting individual false alarm rates and signal detection theory: A role for remembering

The relationships between hit, remember, and false alarm rates were examined across individual subjects in three remember-know experiments in order to determine whether signal detection theory would be consistent with the observed data. The experimental data differed from signal detection predictions in two critical ways. First, remember reports were unrelated, or slightly negatively related, to the commission of false alarms. Second, both response types (remembers and false alarms) were uniquely related to hit rates, which demonstrated that the hit rate cannot be viewed as the result of a single underlying strength process. These results are consistent with the dual-process signal detection model of Yonelinas (1994), in which performance is determined by two independent processes--retrieval of categorical context information (remembering) and discriminations based on continuous item strength. Remember and false alarm rates selectively tap these processes, whereas the hit rate is jointly determined. Monte Carlo simulations in which the dual-process model was used successfully reproduced the pattern in the experimental data, whereas simulations in which a signal detection model, with separate "old" and "remember" criteria, was used, did not. The results demonstrate the utility of examining individual differences in response types when one is evaluating memory models.     

Evaluating models of recognition memory using first- and second-choice responses

Swets, Tanner Jr., and Birdsall (1961) proposed a 4-alternative forced-choice task with two choices (4AFC-2R) for distinguishing between the Equal-Variance Signal Detection model and the One-High Threshold model. This task was recently implemented in the field of recognition memory (Parks & Yonelinas, 2009), a field in which several candidate models have been proposed. One advantage of the 4AFC-2R task is that it permits parameter estimation and goodness of fit testing, something which so far was only possible through the use of Receiver Operating Characteristic (ROC) functions for the more complex candidate models. The present article provides a thorough characterization and comparison of the main recognition memory models in the context of this task. Results are illustrated by a reanalysis of Parks and Yonelinas’ original data, revealing a preference for hybrid approaches to recognition memory, more specifically for the dual-process model (Yonelinas, 1997), whereas pure signal detection models performed poorly. The present analysis provides an assessment of the merits and limitations of this task, highlighting future research applications.