Signal Detection and Threshold Models of Source Memory

2011 ◽  
Vol 58 (4) ◽  
pp. 293-311 ◽  
Author(s):  
Julia Schütz ◽  
Arndt Bröder
Keyword(s):  
Signal Detection ◽  
Source Memory ◽  
Source Monitoring ◽  
High Threshold ◽  
Threshold Models ◽  
Estimation Of Parameters ◽  
Operating Characteristics ◽  
Detection Model ◽  
Measurement Tools ◽  
Different Response

Recently, several authors claimed that the curvilinear shape of rating-based source memory receiver operating characteristics (ROCs) refutes threshold models. However, rating-based ROCs are not diagnostic to disprove threshold models. Furthermore, source memory ROC-analyses ignore influences of other processes like old-new-detection and old-new-response-tendencies, so direct estimation of parameters is preferable. Five source monitoring experiments with different response bias manipulations and materials were conducted. We fitted the Two High Threshold Multinomial Model of Source Monitoring by Bayen, Murnane, and Erdfelder (1996) and the Multivariate Signal Detection Model for Selection by DeCarlo (2003) . We also included rating-based ROCs. The results suggest that both models are at least equally valid as measurement tools which capture bias processes in the corresponding parameters, and they can perhaps be integrated theoretically.

scholarly journals Evidence for the Contribution of A Threshold Retrieval Process to Semantic Memory

2017 ◽  
Vol 70 (10) ◽  
pp. 2026-2047 ◽  
Author(s):  
Maria Kempnich ◽  
Josephine A. Urquhart ◽  
Akira R. O'Connor ◽  
Chris J.A. Moulin
Keyword(s):  
Signal Detection ◽  
Semantic Memory ◽  
Target Identification ◽  
Dual Process ◽  
Semantic Retrieval ◽  
Retrieval Process ◽  
Operating Characteristics ◽  
Semantic Task ◽  
Unequal Variance ◽  
Detection Model

It is widely held that episodic retrieval can recruit two processes: a threshold context retrieval process (recollection) and a continuous signal strength process (familiarity). Conversely the processes recruited during semantic retrieval are less well specified. We developed a semantic task analogous to single-item episodic recognition to interrogate semantic recognition receiver-operating characteristics (ROCs) for a marker of a threshold retrieval process. We fitted observed ROC points to three signal detection models: two models typically used in episodic recognition (unequal variance and dual-process signal detection models) and a novel dual-process recollect-to-reject (DP-RR) signal detection model that allows a threshold recollection process to aid both target identification and lure rejection. Given the nature of most semantic questions, we anticipated the DP-RR model would best fit the semantic task data. Experiment 1 (506 participants) provided evidence for a threshold retrieval process in semantic memory, with overall best fits to the DP-RR model. Experiment 2 (316 participants) found within-subjects estimates of episodic and semantic threshold retrieval to be uncorrelated. Our findings add weight to the proposal that semantic and episodic memory are served by similar dual-process retrieval systems, though the relationship between the two threshold processes needs to be more fully elucidated.

An analysis of signal detection and threshold models of source memory.

2000 ◽  
Vol 26 (6) ◽  
pp. 1499-1517 ◽  
Author(s):  
Scott D. Slotnick ◽  
Stanley A. Klein ◽  
Chad S. Dodson ◽  
Arthur P. Shimamura
Keyword(s):  
Signal Detection ◽  
Source Memory ◽  
Threshold Models

Measuring Source Memory

2007 ◽  
Vol 215 (1) ◽  
pp. 52-60 ◽  
Author(s):  
Arndt Bröder ◽  
Thorsten Meiser
Keyword(s):  
Cognitive Processes ◽  
Source Memory ◽  
Source Monitoring ◽  
Memory Item ◽  
Item Memory ◽  
Research Practice ◽  
Multinomial Models ◽  
Monitoring Process ◽  
Measurement Tools ◽  
Review Model

Abstract. The investigation of source monitoring (SM) as a special faculty of episodic memory has gained much attention in recent years. However, several measures of source memory have been used in research practice that show empirical and theoretical shortcomings: First, they often confound various cognitive processes like source memory, item memory and response bias, and second, they do not do justice to the multitude of processes involved in SM according to the framework of Johnson, Hashtroudi, and Lindsay (1993) . We therefore review model-based measurement approaches, focusing on multinomial models, and we distinguish between theorizing about source memory and the pragmatics of source memory measurement as two partly separate goals of research. Whereas signal detection models seem to be more adequate theories of the underlying source monitoring process, multinomial models have some pragmatic advantages that nevertheless recommend them as viable measurement tools.

Modeling Guessing

2009 ◽  
Vol 217 (3) ◽  
pp. 125-135 ◽  
Author(s):  
Francis S. Bellezza
Keyword(s):  
Signal Detection ◽  
Source Monitoring ◽  
Dual Process ◽  
Process Dissociation ◽  
New Approach ◽  
Detection Model ◽  
Multinomial Processing Tree ◽  
Monitoring Model ◽  
Tree Modeling ◽  
Different Levels

Multinomial processing-tree modeling has had a major impact on process-dissociation theory. Buchner, Erdfelder, and Vaterrodt-Plünnecke (1995) added guessing parameters to the original model of Jacoby (1991) and created a class of process-dissociation models. Furthermore, Erfelder and Buchner (1998) formulated criterion values of the dual-process signal-detection model ( Yonelinas, 1994 ) as multinomial parameters. Buchner, Erdfelder, Steffens, and Martensen (1997) suggested a new approach by proposing a multinomial source-monitoring model for process-dissociation data. Two experiments described here demonstrated that dual-process signal-detection theory must assume different levels of familiarity in inclusion and exclusion tests. Similarly, in some cases the source-monitoring model must assume different levels of recognition guessing in the two tests. Reasons are given for preferring the source-monitoring model.

Further Evidence for Discrete-State Mediation in Recognition Memory

2015 ◽  
Vol 62 (1) ◽  
pp. 40-53 ◽  
Author(s):  
David Kellen ◽  
Henrik Singmann ◽  
Jan Vogt ◽  
Karl Christoph Klauer
Keyword(s):  
Recognition Memory ◽  
Response Times ◽  
Threshold Model ◽  
Choice Task ◽  
High Threshold ◽  
Operating Characteristics ◽  
Discrete State ◽  
Detection Model ◽  
Forced Choice Task ◽  
Model Mimicry

The two high threshold model (2HTM) of recognition memory makes strong predictions regarding differences between receiver operating characteristics (ROC) functions across strength manipulations. Province and Rouder (2012) tested these predictions and showed that the 2HTM provided a better account of the data than a continuous signal detection model using an extended two-alternative forced-choice task. The present study replicates and extends Province and Rouder’s findings at the level of confidence-rating responses as well as their associated response times. Model-mimicry simulations are also reported, ascertaining that the models can be well discriminated in this experimental design. Supplemental files for this article are available at osf.io/zadt6/

Multidimensional source monitoring: Prior retrieval of one source attribute improves source memory for a second

2010 ◽  
Author(s):  
Michael R. Dewitt ◽  
Justin B. Knight ◽  
B. Hunter Ball ◽  
Jason L. Hicks
Keyword(s):  
Source Memory ◽  
Source Monitoring
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